“I hereby declare that I have read this thesis and in my opinion this thesis is
sufficient in terms of scope and quality for award of degree of
Master of Science (Hydrography)”.
Signature
:
Supervisor
:
……….…………………………………
Assoc. Prof. Dr. Mohd Razali bin Mahmud
…………….……………………………
Date
:
7 September 2006
………………….………………………
BAHAGIAN A – Pengesahan Kerjasama*
Adalah disahkan bahawa projek penyelidikan tesis ini telah dilaksanakan melalui
kerjasama antara _______________________ dengan _______________________
Disahkan oleh:
Tandatangan
:
Nama
:
Jawatan
(Cop rasmi)
:
Tarikh :
* Jika penyediaan tesis/projek melibatkan kerjasama.
BAHAGIAN B – Untuk Kegunaan Pejabat Sekolah Pengajian Siswazah
Tesis ini telah diperiksa dan diakui oleh:
Nama dan Alamat Pemeriksa Luar :
Nama dan Alamat Pemeriksa Dalam :
Nama Penyelia Lain (jika ada)
:
Disahkan oleh Penolong Pendaftar di SPS:
Tandatangan
:
Nama
:
Tarikh :
SUBM
AIRNEPIPE
ILNEU
O
RITNG ANDINSPE
IT
CN
O
W
IT
H GE
O
GR
APHIC
ALINF
O
R
M
AT
IO
N SY
ST
E
M
T
E
C
HNO
L
O
GY
CHAI BENG CHUNG
A thesis submitted in fulfillment of the requirement for the award of
Master of Science (Hydrography)
Faculty of Geoinformation Science and Engineering
Universiti Teknologi Malaysia
SEPTEMBER 2006
iii
DEDICATION
Again, to my lovely family….
iv
ACKNOWLEDGEMENTS
This report has been written with the support from several parties. First,
sincere thanks to Assoc. Prof. Dr. Mohd Razali bin Mahmud, the supervisor of this
study, for giving the opportunity to undertake this study. This study would never be
successful without his advice, guide as well as encouragements.
My gratefulness is also dedicated to the data suppliers, not only for their
kindness in supplying the required datasets in this study, but also for their significant
contribution by way of informal discussion. Special thanks to Mr. Idrus and Pn.
Zakiah from Petroliam National Berhad (PETRONAS), for their kind support to
release the pipe route survey datasets; Mr. Gert Riemersma, the Director of MAPIX
Technologies Ltd., for providing the inspection video as well as the relevant
program which enable the researcher to carry out this research; and Dr. Sofia Caires,
from Meteorological Service of Canada, for supplying the oceanographic datasets.
Last but not least, many thanks to all friends and colleagues of Hydrograhic
Research and Training Office (HRTO), who have helped in many ways with
valuable information as well as suggestions related to this study.
v
ABSTRACT
Major advances have been achieved in recent years in submarine pipeline
routing and inspection. Various tools and techniques are used to ensure the
maximum safety of the submarine pipelines. The resulting consequence of these
tools and techniques is the ever increasing data volumes, with the management and
subsequent analysis of the data becoming more and more of an issue. The objective
of this study is to implement the capabilities of Geographical Information System
(GIS) to assemble various submarine pipeline related datasets into a common,
compelling, efficient, user-friendly and interesting visualization system. In this
study, GIS is used as the Spatial Decision Support System (SDSS), to provide
appropriate information for efficient decision-making in submarine pipeline routing
and inspection activities. A review of the literature concerning submarine pipeline
routing and inspection technologies as well as GIS applications for both operations
has been made for a better understanding to the existing problem faced by the
industry. With the proper conceptual, logical and physical model design, an
integration system has been developed to assemble, manipulate and analyze various
submarine pipeline related datasets into a geodatabase. Sequentially, numerous Least
Cost Paths (LCPs) have been determined to identify the most preferred route from
SpringField platform to AutumnField platform, while considering the myriad of
complex spatial interactions according to the diversified routing criteria. The best
routing is then prudently analysed based on these LCPs with several geoprocessing
analysis. Meanwhile, this study has integrated Digital Video System (DVS) datasets
into ArcGIS-ArcMap environment to simultaneously record multiple channels of
inspection video into a geodatabase and replay them synchronously according to its
geographic features. Finally, some recommendations for future studies are made to
enhance the quality of this study as well as to minimize the risk of offshore
industries.
vi
ABSTRAK
Pembangunan dalam kerja perancangan dan pemeriksaan laluan saluran paip
dasar laut semakin pesat kebelakangan ini. Pelbagai teknik dan peralatan digunakan
bagi menjamin keselamatan yang maksimum bagi laluan saluran paip dasar laut
tersebut. Ini telah meningkatkan jumlah data dan menimbulkan isu ke atas
pengurusan analisis yang berturutan. Objektif utama bagi kajian ini ialah bagi
mengimplimentasi keupayaan Sistem Maklumat Geografi (GIS) untuk mengumpul
pelbagai data berkenaan saluran paip dasar laut ke dalam dataset yang bersesuaian,
efisyen, mesra pengguna dan mempunyai sistem visualisasi yang menarik. Dalam
kajian ini, GIS bertindak selaku Spatial Decision Support System (SDSS) yang
berfungsi untuk menyediakan maklumat bagi membantu membuat keputusan yang
lebih efisien dalam aktiviti perancangan dan pemeriksaan laluan saluran paip dasar
laut. Kajian literatur berkenaan aplikasi GIS dan teknologi dalam perancangan dan
pemeriksaan laluan saluran paip dasar laut dilakukan bagi mendapatkan pemahaman
yang lebih mendalam berkenaan masalah yang dihadapi dalam industri ini. Satu
sistem integrasi yang berdasarkan model konseptual, logikal
dan fizikal telah
dibangunkan bagi mengumpul, memanipulasi dan menganalisis pelbagai dataset
bekenaan saluran paip dasar laut di dalam satu geodatabase. Ini diikuti dengan
penentuan beberapa Least Cost Paths (LCPs) bagi mengenal pasti laluan yang
bersesuaian dari pelantar SpringField ke pelantar AutumnField dengan mengambil
kira kepelbagaian interaksi spatial yang kompleks berdasarkan beberapa kriteria
laluan.
Laluan
LCP
yang
terbaik
ditentukan
melalui
beberapa
analisis
geoprocessing. Dalam masa yang sama, pengintegrasian set data Digital Video
System (DVS) kedalam ArcGIS-ArcMap secara langsung merekodkan video
pemeriksaan yang berbilang saluran ke dalam satu geodatabase dan memainkannya
semula serentak berdasarkan rupa bentuk geografik. Akhir sekali, beberapa
cadangan kajian pada masa hadapan dibuat untuk mempertingkatkan kualiti kajian
ini serta meminimakan risiko bagi industri lepas pantai.
vii
TABLE OF CONTENTS
CHAPTER
1
TITLE
PAGE
TITLE PAGE
i
DECLARATION
ii
DEDICATION
iii
ACKNOWLEDGEMENTS
iv
ABSTRACT
v
ABSTRAK
vi
TABLE OF CONTENTS
vii
LIST OF TABLES
xi
LIST OF FIGURES
xiii
LIST OF NOTATION
xvi
LIST OF ACRONYMS
xix
LIST OF APPENDIXES
xxii
INTRODUCTION
1
1.1
Background
1
1.2
Problem Statement
5
1.3
Research Purpose
7
1.4
Research Objectives
7
1.5
Research Scopes
8
1.6
Overview of Research Methodology
12
1.7
The Benefit of this Study
13
1.8
Related Works
15
viii
1.9
2
Standard Revision of Submarine Pipeline
15
1.8.2
Computational Fluid Dynamics Solutions
17
1.8.3 Enhancement of Structural Stability
18
1.8.4
19
Spatial Decision Support System
Summary
21
SUBMARINE PIPELINE ROUTING DESIGN
22
2.1
Introduction
22
2.2
Submarine Pipeline Routing Evaluation
23
2.3
Hydrodynamic Forces
27
2.4
Vortex-Induced Oscillations
31
2.5
Pipeline-Soil Stability Analysis
33
2.5.1
Settlement and Flotation
33
2.5.2
Soil Strength Deterioration
34
2.5.3
Effect of Large Soil Movements
35
2.6
Effect of Seabed Irregularities
37
2.7
Scour and Erosion
41
2.8
GIS for Pipeline Routing Evaluation
44
2.8.1 Discrete Cost Map (DCM)
46
2.8.2 Accumulated Cost Map (ACM)
47
2.8.3 Optimal Route (OR)
48
2.8.4 Optimal Corridor (OC)
49
Summary
50
2.9
3
1.8.1
SUBMARINE PIPELINE INSPECTION
TECHNOLOGY
51
3.1
Introduction
51
3.2
The Need of Pipeline Inspection Survey
52
3.3
Internal Pipeline Inspection (IPI)
55
3.4
External Pipeline Inspection (EPI)
58
3.4.1
Multibeam Technology
58
3.4.2
Side Scan Sonar (SSS)
63
ix
3.4.3
Pipeline Protection Methods
68
2.10
GIS in Pipeline Inspection
70
2.10.1 IPI with GIS
70
2.10.2 EPI with GIS
73
Summary
74
RESEARCH METHODOLOGY
76
4.1
Introduction
76
4.2
Phase I – Preliminary Works
77
4.3
Phase II – System Design
78
4.3.1
Conceptual Design
80
4.3.2
Logical Design
83
4.3.3
Physical Design
84
4.4
5
65
2.9
2.11
4
Remotely Operated Vehicle (ROV)
Phase III – System Development
86
4.4.1
Format Conversion
87
4.4.2
Map Digitizing & Editing
88
4.4.3
Geodatabase Development
92
4.4.4
Programming
93
4.4.5
System Customization
94
4.5
Phase IV – System Evaluation
95
4.6
Phase V – Research Documentation
95
4.7
Summary
96
RESULT AND ANALYSIS
97
5.1
Introduction
97
5.2
GIS in Submarine Pipeline Routing
98
5.2.1
LCP Selection
99
5.2.1.1
DCM Analysis
100
5.2.1.2
ACM Analysis
107
5.2.1.3
Shortest Path Analysis
114
5.2.2
Hydrodynamic Analysis
117
x
6
5.2.3
LCP Finalization
123
5.2.4
Subsurface Modelling
132
5.3
GIS in Submarine Pipeline Inspection
134
5.4
Summary
140
CONCLUSION AND RECOMMENDATIONS
141
6.1
Conclusion
141
6.2
Recommendations
143
BIBLIOGRAPHY
148
APPENDIX
161
xi
LIST OF TABLES
TABLE NO.
TITLE
PAGE
1.1
Hardware and software
8
1.2
Available datasets
10
2.1
Types of submarine pipelines
23
2.2
Constraints involved in pipeline design
24
2.3
Special considerations for pipeline installation in
unstable areas
25
2.4
Linear (Airy) wave characteristics
30
3.1
Major needs of submarine pipeline inspection
53
3.2
Pipeline inspection and monitoring methods
55
3.3
Technologies used in intelligent PIGs
57
3.4
Protection method of submarine pipeline
68
4.1
Spatial E-R model symbology
81
4.2
Basic elements of logical data model
83
4.3
Map georeferencing accuracies
89
4.4
Comparison of spatial interpolation methods
90
5.1
Hazards constraint & its requirements
101
5.2
Discrete cost map classifications – Basic considerations
102
5.3
Discrete cost map classifications – Oceanographic
considerations
5.4
103
Discrete cost map classifications – Hydrodynamic
considerations
103
5.5
Weighting rate of LCP cost models
109
5.6
Length of LCP
114
5.7
Result of Exploratory Spatial Data Analysis (ESDA)
119
5.8
LCP evaluation – Boundary intersection
125
xii
5.9
LCP evaluation – Profile irregularities
126
5.10
LCP evaluation – Installation depth limits
127
5.11
LCP evaluation – Soil properties
128
5.12
LCP evaluation – Obstruction crossing
129
5.13
LCP evaluation – Coral crossing
129
5.14
LCP evaluation – Pockmark crossing
130
5.15
LCP Finalization
131
5.16
Telemetry contents in VideoDRS
137
5.17
Results of Pipeline Inspection
139
xiii
LIST OF FIGURES
FIGURE NO.
1.1
TITLE
PAGE
Submarine pipeline development in Gulf of Mexico
(1999-2003)
2
1.2
Petroleum transportation costs
2
1.3
'Bath tub” failure curve and extending pipelines' lives
3
1.4
Study area
9
1.5
Overview of research methodology
12
2.1
Flow diagram of pipeline routing and weight design
26
2.2
Hydrodynamic forces on pipe
27
2.3
Definitions of linear wave parameters
28
2.4
Flow diagram of hydrodynamic forces computation
29
2.5
Vortex-induced oscillations
31
2.6
Flow diagram of vortex-induced oscillations computation
32
2.7
Storm-induced bottom pressures
34
2.8
Flow diagram of maximum dimensionless stress computation
37
2.9
Pipe configurations due to low depression
38
2.10
Stresses due to low depressions
39
2.11
Pipe configuration due to elevated obstructions
40
2.12
Stresses due to elevated obstructions
41
2.13
Modes of grain transport
42
2.14
Current velocity for sediment transport
43
2.15
Concept of LCP analysis
44
2.16
Methodology of LCP analysis
45
2.17
Discrete Cost Map (DCM)
46
xiv
2.18
Accumulated Cost Map (ACM)
47
2.19
Optimal Route (OR)
48
2.20
Optimal Corridor (OC)
49
3.1
Pigs
56
3.2
Multibeam survey for EPI operation
59
3.3
EPI for exposed pipes
60
3.4
EPI of burial pipe
61
3.5
EPI of free-spanning pipe
61
3.6
Pipe DTM generated from echoes measurement
62
3.7
Typical SSS configurations and its result
64
3.8
ROV surveying
65
3.9
Common configuration of a ROV
66
3.10
Video Tracking Systems (VTS)
67
3.11
Some results of the pipeline edge extraction algorithm on
different real situations
67
3.12
Protection methods of submarine pipeline
69
3.13
Tracking pig with GIS
71
3.14
IPI application with MapObjects
72
3.17
GIS Applications for EPI
73
3.18
EPI with VideoDRS
74
4.1
Flow diagram of preliminary works
77
4.2
Flow diagram of system design
79
4.3
Conceptual Model
82
4.4
Implementation of physical design
84
4.5
ArcToolbox migration wizards
85
4.6
Flow diagram of system development
86
4.7
Methodology of format conversion
87
4.8
Methodology of map digitizing & editing
88
4.9
Oceanographic maps for January 1960
91
4.10
Methodology of geodatabase development
92
4.11
Programming flow
93
4.12
Flow diagram of system customization
94
5.1
LCP methodology
99
5.2
Procedures of source and cost datasets creation
100
xv
5.3
Methodology of discrete cost map creation
104
5.4
Basic considerations for DCM
105
5.5
Special consideration of reclassifications
106
5.6
Model of straight-line distance
107
5.7
Concept of cost maps accumulation
108
5.8
Accumulated cost maps (Model A – F)
111
5.9
Accumulated cost maps (Model G – L)
112
5.10
Concept of direction raster coding
113
5.11
Least cost path (Model A-F)
115
5.12
Least cost path (Model G - L)
116
5.13
Methodology of hydrodynamic analysis
117
5.14
Interfaces of wave calculator & hydrodynamic calculator
118
5.15
Wave characteristic maps- Part I
120
5.16
Wave characteristic maps- Part II
121
5.17
Hydrodynamic maps
122
5.18
LCP errors
123
5.19
Methodology of LCP evaluation
124
5.20
Methodology of subsurface modelling in RockWorks2004
132
5.21
Map of soil types
133
5.22
Screenshot of VideoRDS
136
5.23
Telemetry Display with VideoDRS
137
5.24
General flow of VideoDRS operation
138
xvi
LIST OF NOTATIONS
I
-
Grain size
T
-
Wave characteristics constant value, (2St)/T
4
-
Slope of seabed
K
-
Wave profile
U
-
Density of fluid, 2 slug/ft3 for sea water
G
-
Obstruction elevation
Us g
-
Weight density of steel (490/32.2)
[
-
Water particle displacement (Horizontal)
]
-
Water particle displacement (Vertical)
P
-
Coefficient of soil friction
E
-
Dimensionless tension
Vc
-
Characteristic stress
Vm
-
Maximum dimensionless stress
ax
-
Water particle accelerations (Horizontal)
az
-
Water particle accelerations (Vertical)
AT
-
Axial tension
C
-
Wave Celerity
Cs
-
Remolded cohesive shear strength
CD
-
Hydrodynamic drag coefficient
Cq
-
Group velocity
CL
-
Hydrodynamic lift coefficient
CM
-
Hydrodynamic inertia or mass coefficient
d
-
Water depth
du
-
horizontal water particle acceleration over pipe
D
-
Pipe outside diameter
xvii
Di
-
Pipe internal diameter
D/Wt
-
Pipe-diameter/wall thickness ratio
E
-
Elastic modulus
EI
-
Pipe stiffness
fn
-
Natural frequency of the pipe span
fs
-
Vortex-shedding frequency
FD
-
Combined drag force
Fi
-
Inertia force
FL
-
Combined lift force
Fr.
-
Friction resistance force between the pipe and the seabed
g
-
Constant value of gravity
H
-
Significant wave height
Ho
-
Deepwater wave height
L
-
Wave Length
Lc
-
Characteristic length
Lo
-
Deepwater wave length
Ls
-
Span Length
M
Combined mass of the pipe and added mass around the pipe
per unit length of pipe
Ma
-
Pipe unit mass
MD
-
Displaced mass
N
-
Normal force
p
-
Subsurface pressure
Re
-
Reynolds number
S
-
Strouhal number
SG
-
Specific gravity
SG1
-
Lower range of pipe specific gravity
SG2
-
Upper range of pipe specific gravity
SGC
-
Specific gravity (during construction)
SGo
-
Specified gravity (during operation)
SGfloat
-
Specified gravity (to float the pipeline)
SGsink
-
Specified gravity (to sink the pipeline)
t
-
Time (0 second is used for severe oceanographic condition)
T
-
Average wave period
xviii
u
-
Water particle velocity (Horizontal)
U
-
Flow velocity in boundary layer
Ue
-
Effective horizontal water-particle velocity over pipe height
Uo
-
Measured/calculated horizontal particle velocity at height yo,
v
-
Kinematics viscosity of the fluid about 1.0x105 ft2/sec for sea
water
V
-
Flow velocity
w
-
Water particle velocity (Vertical)
W
-
Submerged weight of the pipe and the weight of the contents
Wa
-
Pipe unit weight in air
WT
-
Pipe wall thickness
z
-
computational oceanographic height
xix
LIST OF ACRONYMS
2D
-
Two Dimensional
3D
-
Three Dimensional
ACM
-
Accumulative Cost Map
AIM
-
Asset Integrity Management
ANSI
-
American National Standard Code
API
-
American Petroleum Institute
ASCE
-
American Society of Civil Engineers
ASCII
-
Amsterdam Subversive Center for Information Interchange
ASE
-
Average Standard Error
ASME
-
American Standard for Mechanical Engineering
AUV
-
Autonomous Underwater Vehicle
BS
-
British Standard
CAD
-
Computer-Aided Design
CASE
-
Computer-Aided Software Engineering
CWD
-
Cost-Weighted Distance
CEOM
-
Centro Oceanologico Mediterraneo
CFD
-
Computational Fluid Dynamics
CIC
-
Cloud-In-Cell
COLOS
-
Conceptual of Learning Sciences
CP
-
Communication Plan
DBF
-
Dbase File
DBMS
-
Database Management System
DCM
-
Discrete Cost Map
DGPS
-
Differential Global Positioning System
DHSS
-
Dual Head Scanner Sonar
DNV
-
Det Norske Veritas
DTM
-
Digital Terrain Model
xx
DVS
-
Digital Video System
E-R
-
Entity-Relationship
EPI
-
External Pipeline Inspection
ESDA
-
Exploratory Spatial Data Analysis
ESRI
-
Environmental Science Research Institute
GA
-
Geostatistical Analyst
GB
-
Gigabyte
GEOPIG
-
Geometry Pig
GIS
-
Geographic Information System
GPS
-
Global Positioning System
GUI
-
Graphic User Interface
HCA
-
High Consequence Area
HRTO
-
Hydrographic Research and Training Office
IBP
Instituto Brasileiro de Petróleo e Gás / Brazilian Petroleum
and Gas Institute
IEEE
-
Institute of Electrical and Electronics Engineers
IHOCE
-
International Hydrographic & Oceanographic Conference &
Exhibition
ILI
-
In-Line Inspection
IMP
-
Integrity Management Plan
IPI
-
Internal Pipeline Inspection
LCP
-
Least Cost Path
LES
-
Large Eddy Simulations
LOOP
-
Louisiana Offshore Oil Port
LSD
-
Limit States Design
MB
-
Megabyte
MCP
-
Management of Change Plan
MSC
-
Meteorological Service of Canada
OC
-
Optimal Corridor
OCM
-
Optimal Corridor Map
OMAE
-
Offshore Mechanics and Arctic Engineering
OR
-
Optimal Route
OSIF
-
Offshore Soil Investigation Forum
PDF
-
Portable Document Format
xxi
PETRONAS -
Petroliam National Berhad
PKT
-
Packet format
PP
-
Performance Plan
PSI
-
Pounds per Square Inch
PTS
-
Petronas Technical Standard
PTTC
-
Petroleum Technology Transfer Council
PWG
-
Pipeline Working Group
QCP
-
Quality Control Plan
RAM
-
Random Access Memory
RANS
-
Reynolds Averaged Navier-Stokes
RMS
-
Root Mean Square
ROV
-
Remotely Operated Vehicle
SDSS
-
Spatial Decision Support System
SIGSA
-
Sistemas De Informacion Geographica, S.A.
SMYS
-
Specified Minimum Yield Strength
SPIM
-
Submarine Pipeline Integrity Management
SSS
-
Side Scan Sonar
SWL
-
Still Water Level
TIF
-
Tag Image File
TV
-
Television
TXT
-
Text File Format
ULCD
-
Ultrasonic Crack Detection
UML
-
Unified Modeling Language
USBL
-
Underwater Short Base Line
USGS
-
United State Geological Survey
VBA
-
Visual Basic for Application
VHS
-
Virtual High Storage
VTS
-
Video Tracking System
XLS
-
Microsoft Excel Workbook (Microsoft Excel 2002)
xxii
LIST OF APPENDICES
APPENDIX
TITLE
PAGE
A
3D Maps of Least Cost Path
161
B
Stratigraphic Maps
1
CHAPTER 1
INTRODUCTION
1.1
Background
In recent times, man’s inexorable demand of petroleum products has
intensified the search for oil and gas in regions of the world which hitherto were
unexplored. This has led to the development of petroleum resources in offshore
areas which are especially harsh due to deep water and/or the severity of prevailing
climatic conditions imposed by high winds, stormy seas and low temperatures as
described in Figure 1.1a. In many cases, submarine pipeline is the preferable
solution for oil and gas industry to transport the crude, either from offshore
platforms to onshore terminals as shown in Figure 1.1b.
The investigations that were carried out by Oynes (2004), Robertson, et al
(2004), and Kennedy (1984) proved that, oil and gas pipeline systems are
remarkable for its efficiency and low transportation cost as shown in Figure 1.2.
Networks of interlinking pipelines have also materialised in several offshore regions
to enhance the development of marginal fields and mitigate some of the risks arising
from the possible failure of singular pipelines (Mare, 1985). Evidence suggests that
the pace of recent developments will continue as onshore reserves of oil and gas
2
diminish, with the result that submarine pipelines will become extremely important
to the arteries in an increasingly energy-hungry world (Oynes, 2004; Robertson, et
al, 2004; and Mare, 1985).
(a)
Figure 1.1:
(b)
Submarine pipeline development in Gulf of Mexico (1999-2003):
(a) Deepwater exploratory and development wells drilled subdivided by water depth;
and (b) Deepwater pipeline mileage approved 1999-2003, subdivided by water depth
(source: Oynes, C., 2004)
Figure 1.2:
Petroleum transportation costs
Source: Kennedy, J. L., 1984
3
In general, the growth of deepwater exploration is particularly significant to
the pipeline market (Robertson, et al., 2004) due to (a) deepwater means longer
lengths of product because not only is the distance from the seabed to the surface
greater, but the project site also tends to be farther from shore, so export lines need
to be longer; and (b) the technical challenges presented by deepwater conditions
means that pipeline design, manufacture, installation and operation become more
troublesome and more expensive, making deepwater a high-risk, high value market.
At present, various techniques of submarine pipeline routing design have
been established as to ensure the maximum safety to the pipeline. In general,
submarine pipeline routing design requires careful examinations on hydrodynamic
stability analysis (installation and operating lifetime), soils liquefaction analysis
(safe range of pipe specific gravity), soil movements analysis (loads imposed on
pipeline), pipe buckling analysis, thermal load / flexibility analysis, pipe lay
analysis, route selection, profile extraction and so forth.
Figure 1.3:
'Bath tub” failure curve and extending pipelines' lives
Source: Penspen Integrity, Inc., 1998
4
Meanwhile, an investigation that was carried out by Jones and Hopkins
(2002) shows that engineering plant follow a 'bath tub' type failure probability curve
shown in Figure 1.3. This curve shows that during a structure's design life the
highest failure probability is when the structure is new, or when it is old. This curve
applies to automobiles, aircraft, etc., and pipeline engineers will agree with this
result; pipelines have high failure rates early in life (e.g., hydrostatic testing) and
later in life (due to corrosion) (Jones and Hopkins, 2002; Biagiotti and Guy, 2003).
An adequate parameters design and inspection of a pipeline will help to extend the
low probability portion of Figure 1.3 to 80 or even 100 years old.
Geographic Information System (GIS), is a computer-based system that is
capable of assembling, storing, manipulating, and displaying geographically
referenced information. GISs provide analytical capabilities that can greatly help in
submarine pipeline design and inspection purposes. The benefits of such analysis
will be appreciated by the pipeline engineers, who can now concentrate on analysing
his results as opposed to spending time compiling the results. This study deals
primarily with assembly of various datasets into a common, compelling, efficient,
user-friendly and interesting visualization GIS system for submarine pipeline routing
design and inspection purposes.
This chapter outlines the key notes of this study including research problems
statement, purpose, objectives, scope as well as the benefits of this study, The
following Chapter (see Chapter 2) provides an overview of hazardous conditions
and basic criteria of submarine pipeline routing design, such as hydrodynamic
forces, pipe-soil stability, etc. Chapter 3 illustrates the needs as well as the current
technologies of submarine pipeline inspection (e.g., SSS, ROV and so forth). The
methodology of this study is presented in Chapter 4. The capabilities of GIS
technology in submarine pipeline routing design are evaluated in Chapter 5, section
5.2 and Chapter 5, section 5.3 analyzed the implementation of GIS in submarine
pipeline inspection purposes. The conclusion and recommendations for future works
are presented in Chapter 6.
5
1.2
Problem Statement
Routing design of a submarine pipeline is a complicated business because of
all the parameters that must be prudently considered. Large numbers of effort have
been made to ensure the maximum safety and improve the longevity of the pipeline
operating lifetime (the summary of relevant researches are available in section 1.8).
For a successful submarine pipeline design operation, various techniques and tools
are used. As a result, diverse datasets are obtained, such as oceanographic data,
bathymetry data, magnetometer, soil sample, sub-bottom profiler and so forth.
Additionally, various datasets are obtained from submarine pipeline
inspection surveys (the detail description is available in Chapter 3). The Internal
Pipeline Inspection (IPI) data consists of attributes such as corrosion areas of the
internal pipeline wall, related to the distance from nearest pipe weld (given the
geographical locations of the pipe weld / field joints, absolute positions can then be
derived for the internal corrosion area). The External Pipeline Inspection (EPI) data
consists of attributes, such as debris on the seabed, whose geographical position is
known either via interpolation of Side Scan Sonar (SSS) imagery or Remotely
Operated Vehicle (ROV) positioning fixing (Riemersma, 2000).
Generally speaking, more data will produce better analysis results. However,
most of these datasets are deposited into files and databases where they sit in their
separate and unique formats. Hence, the information in these datasets often go unvisualized, un-interpreted and hence do not effectively contribute to the scientific
understanding or help pipeline engineers in submarine inspection or routing design
operation. Obviously, it is meaningless if the industry managed to survey or collect
the required datasets in high precision, but could not efficiently manipulate or
manage these datasets for maximum usage.
6
To overcome this problem, the conventional Database Management Systems
(DBMS) are not practical as most of these datasets are not geographically
referenced. Traditionally, the pipeline engineers will take time to analyse these
datasets for decision making from several separated systems where these datasets are
stored in. Evidently, this is inefficient to the industry and even worse is that analysis
results may not be accurate as the required information are not integrated.
As the solution for efficient decision-making, oil and gas industries are
recently seeking for the information system which is capable in:
x
Assembling, storing, manipulating, displaying and analysing the industrial
datasets. In this case, the system must be able to manipulate all the required
datasets for submarine pipeline routing and inspection activities.
x
Able (or at least able to be customised) to integrate with other hardware or
systems in order to be upgraded for onboard processing or fulfil the future
requirements.
x
Comprise various analytical functions that would meet the engineers’ needs
in their daily operation. In this case, the system must be able to identify the
High Consequence Areas (HCAs) to a submarine pipeline, and define the
most appropriate path for the pipeline to be installed.
x
Security protection to ensure the reliability of the system as well as the
confidentiality of the datasets.
7
1.3
Research Purpose
Seas and oceans contain a spaghetti-like labyrinth of submarine pipes and
cables that criss-cross the seafloor, providing fuel and communications throughout
the world. The condition and welfare of these pipelines remain the responsibility of
the pipeline’s asset owner. Usually, they will evaluate or design the pipeline route
away from all the harmful hazards and minimize the hydrodynamic forces to these
pipelines. Besides that, these pipelines are carefully inspected, in order to improve
its longevity as well as to minimize its impact to the environment.
For the convenience of the pipeline engineers, this study aims to implement
the GIS capabilities into submarine pipeline routing and inspection activities, that is
to assemble various datasets into a common, compelling, efficient, user-friendly and
interesting visualization system, with the aim of providing appropriate information
to pipeline engineers for efficient decision-making.
1.4
Research Objectives
The objectives of this study are:
x
To integrate the related datasets for submarine pipeline design and inspection
purposes into a geodatabase system.
x
To integrate the DVS (Digital Video System) dataset into ArcGIS-ArcMap
environment for efficient pipeline inspection analysis.
x
To customize a proper graphic interface for the conveniences of end user.
8
1.5
Research Scope
This study focuses mainly in the implementation of GIS technology as a
Spatial Decision Support System (SDSS) for submarine pipeline routing design and
inspection purposes. The basic criteria in submarine pipeline routing design and
inspection activities would be taken into account in this project. However, this study
is limited as follows:
x
Hardware, software and extension, the hardware and software that had
been used to achieve the objectives of this study are listed in Table 1.1. Thus,
this study has been proceeded based on the available functionality of these
hardware and software.
Hardware and software
Table 1.1:
Hardware
Operating System
Ź Intel Pentium III
Ź Window XP
Ź 128 Mb RAM
Software
ŹNETmc 3Head Player Tool
Ź ArcGIS-ArcInfo 8.3
Ź Abode Acrobat Professional 6.0
Ź Microsoft Excel 2003
Ź RockWorks 2004
Extension
Ź VideoDRS
Ź 3D Analyst
Ź Geostatistical Analyst
Ź Spatial Analyst
x
Types of pipeline, there are four general classifications of submarine
pipelines as outlined in Table 2.1 (see Chapter 2, section 2.2). But, this study
focuses only in the routing design of gathering lines (interfiled lines). The
criteria of routing design for other types of submarine pipeline (e.g.,
flowlines / intrafield lines and loading lines) are excluded from this study.
9
x
Study area, this study attempts to analyse a new proposed pipeline from
SpringField platform to AutumnField platform and to inspect the existing
pipeline between SummerField platform and WinterField platform (Figure
1.4), based on the available datasets provided by the data suppliers. In other
words, the routing design criteria, environmental constraints and available
datasets for other offshore platforms would be excluded from this study.
However, all the details (e.g., name of the platforms, pipelines) of this
selected area has been edited from this report due to the datasets
confidentiality (as stated in the agreement that attached in this report).
Boundary of available datasets
Figure 1.4:
x
Study area
Data, this study is limited to some datasets as listed in Table 1.2. Petroliam
National Berhad (PETRONAS) agreed to release 3 pipeline survey reports,
which consist the datasets of bathymetry survey, Side-Scan Sonar (SSS),
sub-bottom profiler and so forth. Besides that, MAPIX Technologies Ltd
supplies the DVS files and the relevant software. And, Dr. Sofia Caires from
the Meteorological Service of Canada (MSC) provides the requested monthly
oceanographic datasets from year 1960 to 2000. This study has been carried
out based on these datasets and other datasets are neglected from the study
due to the data inaccessibility.
Oceanographic
Dataset
ROV/DVS
Survey Datasets
5
Note:
6
4
MAPIX
Technologies
Ltd
MSC
Source
19602001
1999
1996
Benthos-type Gravity Corer
Year/ Acquisition
Period
1996
Atlas Deso 20 Dual Frequency Echo Sounder
System
1996
EG&G 260 Image Correcting SSS system,
complete with an EG&G 272TD dual frequency
(100 and 500 kHz)
1996
Geopulse Surface-Towed Profiling System
Available datasets
summary from pipeline survey report
personal interview with the relevant parties
Sub-Bottom
Profiler Dataset
Soil & Gravity
sampling
3
*
§
Bathymetry
Dataset
SSS Imageries
1
2
Data
Item
Table 1.2:
r 1cm with maximum
distance for two consecutive
locations not exceeding
5km*
r 10 cm §
0.2 m- 0.6m*
overall accumulative
accuracy is r 0.55 metres*
approx 5m in size and 15m
in position*
Accuracy
10
11
x
Routing design constraints, although there are several constraints (as outlined
in Chapter 2, section 2.2) that must be considered for a successful submarine
pipeline routing design, this study focuses mainly in the environmental
constraints involved in submarine pipeline routing. Other design constraints like
the methods of construction; operation and maintenance are excluded from this
study.
x
Assumption, due to the data inaccessibility, some assumptions have been made
in this study:
Ÿ
the size of purpose pipeline (from SpringField platform to AutumnField
platform) is assumed consistent with 1m diameter and 5cm thickness.
Ÿ
the average direction of wave is assumed normal or parallel to the
proposed pipeline axis.
Ÿ
the velocity and acceleration terms are typically evaluated at 1m above
the seabed based on standard wave theories as described in Table 2.4
(Mousselli, 1981). Hence, a boundary layer is then assumed from 1m
above the seabed to the seabed where the velocity terms vanish during the
hydrodynamic analysis in this study.
Ÿ
the G-Value, fill percent and soil density must be assigned with numeric
values for each soil types in RockWorks2004 to identify each soil types
in lithology models. However, these values are unsure in this study. Thus,
the recommended setting has been used to assign all the fill percent as
100%, all soil density as 1 and G-Value of '1' for the uppermost class of
soil and increment the integer by '1' for each next soil type (RockWare,
Inc., 2004).
12
1.6
Overview of Research methodology
Generally, the methodology of this study can be divided into five phases as
shown in Figure 1.5. The first part would cover the preliminary works such as
assessment of the research problem, research objectives, research scopes identification
as stated previously in sections 1.2, 1.3, 1.4 and 1.5. Besides that, the literature review of
the relevant studies would be carried out at the earliest stage of this study to ensure the
practicalities of this study (see section 1.8 or Chapter 2 & 3 for detail description).
Figure 1.5:
Overview of research methodology
13
The second step of this study accounts for system design (for more detail, see
Chapter4, section 4.3) which consists the conceptual design, logical design and physical
design of the system. The system development would be carried out with the selected
tools as soon as the design plans are completed in the third phase (see Chapter 4, section
4.4). The fourth part of this study focuses mainly on system evaluation and result, that
include the application of pipeline routing with spatial analysis (see Chapter 5,
section5.2); and simultaneously access multiple channels of pipeline inspection video in
ArcGIS-ArcMap (see Chapter 5, section5.3) according to its geographic features.
Eventually, the research documentations are compiled in the fifth phase for future
reference.
1.7
The Benefit of this Study
GIS is explicitly designed to assemble, manipulate and analyse geographically
referenced information, as the support system for decision-making. The following are
potential benefits that can be expected upon implementing GIS technology into
submarine pipeline routing and inspection purposes:
x
Measurable increases in productivity during the creation, maintenance, and
seeking/verifying of geographic-related information. A GIS automates routine,
repetitive tasks, leaving more time for pipeline engineer to focus on analysis and
problem solving.
14
x
Centralized database to provide a single source of pipeline related information.
Centralization will enable faster retrieval and selective modification of
information and provide more consistent operations, including standardization,
since all users will have access to the same current data.
x
Improved responsiveness to inquiries through increased information accuracy,
improved response time, and ability to quickly analyze larger volumes of data.
x
Capability to produce specialty maps at any desired scale to improve emergency
preparedness and accelerate work processes (e.g., processing of permits).
x
More effective analysis of geographic-related data that greatly enhance and
expedite management’s decision-making capabilities (e.g., assisted planning of
optimal routes)
15
1.8
Related Works
In order to improve the works of submarine pipeline routing design and
inspection, various researches had been carried out around the world, which can mainly
be categorized as below:
1.8.1 Standard Revisions of Submarine Pipeline
Several regulations or standards had been published and widely implemented to
ensure the maximum safety to submarine pipeline. For example, American Petroleum
Institute (API) Recommended Practice 111, 2nd Edition Nov.93 and British Standard
(BS) BS8010: Part 3 1993 Section 4 had been published refers specifically to submarine
pipeline routing selection. Det Norske Veritas (DNV) 1996, Page 18, Section 3 and
DNV Classification Notes – No. 30.4 refer specifically to soil investigation for pipelines.
Meanwhile, API RP5L emphasizes the material aspect than pipeline design guideline
against environmental loading (Mousselli, 1981; Mare, 1985; and Karal, 1987).
Over the years, these standards or regulations had been widely used as guidance
for design, materials, fabrication, installation and operation of submarine pipeline.
However, the pipeline industry has in recent years experienced a growing focus on cost
reduction, resulting in innovative design approaches and optimized construction
methods in increasingly deeper and rougher waters (Pradnyana, et al, 2000). Hence,
these regulations or standards may no longer be applicable and revision must be carried
out.
16
To do so, the Pipelines Working Group (PWG) of the Offshore Soil Investigation
Forum (OSIF) has been established. The forum is an informal grouping of oil company
geotechnical departments, geotechnical drilling vessel operators, geotechnical
contractors and consultants, that has been meeting annually since 1983, to exchange
experience and ideas; standardize the procedures, equipment; and continuously improve
all aspects of offshore soil investigations.
Besides that, Roberts (2004), reviews some of the major legislative and
regulatory changes concerning the integrity of transmission pipelines located in High
Consequence Areas (HCAs). Sylvestor (2004), review the elements of an Integrity
Management Program in American Standard for Mechanical Engineering (ASME)
B31.8S, which includes Integrity Management Plan (IMP), Performance Plan (PP),
Communication Plan (CP), Management of Change Plan (MCP), and Quality Control
Plan (QCP). Meanwhile, Penspen Integrity (1998), studied the possibility of the Limit
States Design (LSD) used to design a pipeline above 80% Specified Minimum Yield
Strength (SMYS).
From the existing pipeline design, Pradnyana, et al (2000) tried to do recalculation using DNV 1981, DNV 1996, DNV 1999, and DNV 1999 (revision).
Recalculation has been done by optimizing wall thickness (where internal pressure is
kept constant), and optimizing internal pressure (where wall thickness is constant).
According to Pradnyana, et al (2000), the results show that the pipeline wall thickness
can be reduced by using DNV 1996, DNV 1999 and DNV 1999 (revision), and the most
reduction in wall thickness was found when DNV 1999 (revision) is used. And the
ultimate internal pressure can be raised by using DNV 1996, DNV 1999 and DNV 1999
(revision).
17
1.8.2 Computational Fluid Dynamics (CFD) Solutions
In the most severe case, the scour hole and resultant forces on the structure may
cause failure. In other cases, pipelines, rubble-mound structures, or submerged mines
may be enveloped by the scour hole and eventually buried (Summer, et al., 2001). For
this reason, the hydraulic and ocean engineers had shown significant interest in
predicting the scour of sediment around bridge piers and submarine pipelines.
A number of investigations had been carried out to analyse the scour around the
vertical structures, such as steady current investigation by Laursen (1963); Lim & Cheng
(1998); and Melville & Chiew (1999); wave investigation (Summer, et al., 1992); wave
and current investigation (Summer and Freds‡e, 2001); field investigation include
Bayram and Larson (2000). Besides that, investigation of the scour for the horizontal
objects has primarily occurred in the last three decades (Kjeldsen, et al., 1973, and Mao
1986).
In the year 1988, the Cloud-In-Cell (CIC) model had been used by Summer et al,
(1988) to simulate laboratory observations of the cylinder wake. Followed by that, the
efforts to model the pipeline scour process have ranged from potential flow theory (Li
and Cheng, 1999) to more complicated turbulence closure models with the Reynolds
Averaged Navier-Stokes (RANS) equations (Van Beek and Wind, 1990).
More recently, Li and Cheng (2001) solved the RANS equations with a Large
Eddy Simulations (LES) turbulence scheme. Besides that, Br‡rs (1999) utilizes a nonhydrostatic finite element scheme to solve the RANS equations with a k-H turbulence
closure scheme. The morphologic evolution is accomplished with a finite difference
bedload transport model. However, the velocity variations downstream of the cylinder
18
were slightly under-predicted. The morphology module was evaluated with Mao’s
(1986) scour experiments. Overall agreement between the laboratory data and the model
for both the shape and depth of the scour hole is good, although the simulated
equilibrium depth was less than the final depth reached in the laboratory (Smith, 2004).
1.8.3 Enhancement of Structural Stability
As pipeline installations moved into deep water, the problems of pipeline
collapse caused by the increased hydrostatic pressure became significant. Pipe collapse
depends on many factors, including the pipe-diameter/wall thickness ratio (D/Wt),
stress-strain properties, initial ovalization (out of roundness), hydrostatic pressure, and
bending moment in the pipe (Mousselli, 1981).
To overcome these problems, new methods, tools and equipments are being
developed to enhance the structure of submarine pipeline. Dawans, et al, (1986) had
carefully evaluated the design and materials considerations for high pressure flexible
flowlines.
Meanwhile, various methods are introduced to protect the pipeline from
hazardous conditions (see Chapter 3, section 3.5), this include concrete coating (Bergan
& Mollestad, 1981; and Palmer, 1985); grouting (COLOS, 1983), sandbags, jack-ups,
gravel dumping (Melegari & Bressan, 1990) and etc (see Chapter 3, section 3.5 for
detail description of these protection methods).
19
Furthermore, several continuous or non-continuous techniques for internal
corrosion monitoring has been implemented, such as coupons, iron counts, ultrasonic
radiographic calliper, magnetic pigs, electrochemical noise, polarisation resistance and
so forth (see King & Geary, 1985, for a complete summary of internal corrosion
monitoring techniques).
Besides that, numbers of advance equipment and technology are developed and;
directly or indirectly contribute to the stability of submarine pipeline. For example, jet
barge, fluidizing equipment to trench a pipeline (Mousselli, 1981); and submarine
pipeline inspection with Side Scan Sonar (Cheah, 2003; Kamaruddin; 2003; Petillot, et
al, 2002 and Rainbow, et al, 1985), ROV/AUV (Thabeth, 2004; Kamaruddin; 2003;
Mahmud & Chai 2003a; Petillot, et al, 2002 ), pig (Elmer, 2004; Horton, 2004; Olson, et
al, 2004; Agthoven, 2003; and Beuker & Brown, 2003); FluoroTrack sensor (Thabeth,
2004); and some other Ultrasonic Crack Detection (ULCD) tools (Meade and Uzelac,
2004).
1.8.4 Spatial Decision Support System (SDSS)
Routing design of submarine pipeline is a complicated business because of all
the parameters that must be considered. To analyse the optimal route of submarine
pipeline, not only the pipeline scour process (see section 1.8.2) has to be simulated,
various criteria, regulations or standards must also be achieved (see section 1.8.1 and
Chapter 5, section 5.2). Furthermore, new methods, tools and equipments are being
developed to enhance the structure of submarine pipeline to oppose the severe
conditions in ocean environment (as described in section 1.8.). However, in certain
cases these are not flexible and cost-effective.
20
For these reasons, pipeline engineers seek for the solution which is capable to
consider all the routing constraints into a systems analysis. Since, most of these
constraints are geographically related, GIS has taken place as the Spatial Decision
Support System (SDSS) with its distinct spatial analytical capabilities. Various GIS
applications had been developed for routing design, such as defining a consensus
method for finding preferred routing (McCoy & Johnston, 2001); identifying the most
preferred route for power line (Berry, 1996); analyse the shortest and safest voyage
(Chai, 2002); finding an alternative access road to the new school site (McCoy and
Johnston, 2001); designate the optimal route for submarine cable routing (Joseph &
Hussong, 2005; and Osborne & Abbott, 2000); determine the alternative pipe routes
(Berry, et al, 2004; Wong, 2004; LoPresti & Miller, 2004, and Yusof & Baban, 2004).
Data integration is a critical process in an Integrity Management Plan (IMP). It
will still take several years to have a fully implemented pipeline integrity process. GIS
technology has already proven itself as a key-element to successfully manage the data
necessary for a pipeline integrity management program (Palmer, 2004; and Mahmud &
Chai, 2003b), such as wave modelling (Yaakob, 2003); internal inspection with PIGs
(Porter & Parsons, 2000; and Czyz, et al, 2000); sonar scanned images (Rasmussen,
1998) and external video tracking system (Rasmussen, 1998).
The focus of this study is on the fourth, that is to implement the true GIS
capabilities in submarine pipeline routing design and inspection purposes. To do so, it
requires (1) to gather various datasets regarding pipeline routing design & inspection;
(2) assembling, storing & manipulating these datasets in a geodatabase system; (3)
analyse the optimal pipeline route by taking into account the hazardous conditions (see
Chapter 2, section 2.8); (4) perform a georeference DVS for submarine pipeline
inspection in ArcGIS-ArcMap environment; and (5) customizing a common,
compelling, efficient, user-friendly interface for the convenience of end users.
21
1.9
Summary
Submarine pipelines play an important role in offshore hydrocarbon
transportation. In order to ensure the smoothness of offshore exploration activities and
the stability of marine biology, a large number of efforts have been made to study the
issues which are relevant to submarine pipelines, particularly in its routing design and
inspection techniques.
The objective of this study is to implement the GIS capabilities into submarine
pipeline routing and inspection activities. This study aims to assemble various datasets
into a common, compelling, efficient, user-friendly and interesting visualization system
to provide the appropriate information for efficient decision-making to pipeline
engineers.
22
CHAPTER 2
SUBMARINE PIPELINE ROUTING DESIGN
2.1
Introduction
The principal objective of submarine pipeline routing design is to maximize
the safety of the pipeline whilst incurring minimum life cycle costs. Ideally, the pipe
route should be selected to minimize forces of possible soil movement on the
pipeline and avoid any hazardous conditions which may occur along the pipeline
route. To do so, submarine pipeline routing design requires careful examination and
analysis of hydrodynamic stability, soils liquefaction, seabed irregularities, vortexinduced oscillations and so forth.
This Chapter provides an overview of the principles and constraints of
submarine pipeline routing design. Various environmental, natural and man-made
hazards to submarine pipeline are discussed in this Chapter. The common design
tasks are carefully illustrated and analyzed where its formulae are also presented in
this Chapter. Besides that, this Chapter attempts to elaborate the application of GIS
technology in submarine pipeline routing.
23
2.2
Submarine Pipeline Routing Evaluation
The ever-increasing demand for oil and gas has resulted in a substantial
increase of offshore projects for finding and producing hydrocarbons. One of the
most important links in the chain of operations that brings these hydrocarbons from
the reservoir to users around the world is a network of pipelines. Though pumping
stations and other facilities are scattered along pipeline routes, oil and gas produced
from offshore wells are brought to shore by pipeline, often through water several
hundred feet deep.
Table 2.1:
Types of submarine pipelines
Source: Mousselli, 1981
Types
Flowlines
or
Intrafield
Lines
Gathering
or
Interfield
Lines
Trunk
Lines
Loading
or
Unloading
Lines
Description
A flowline connects a well to a platform or subsea manifold. Usually
the line has a small diameter and may be bundled. Flow inside of it may
be at high pressure. It is used where reservoir pressure is sufficient to
flow the fluid through the line without boost (pump or compressor).
A gathering line connects from one (multiwell) platform to another
platform and is usually a small-to-medium-diameter line but can be
large diameter, too. It may be a bundled oil, gas, condensate, or twophase flow. The range of operating pressure is usually between 1,0001,400 psi. Flow in the lines is done by booster pumps or compressors
which are often installed on the platform. It may also transmit the
product from a drilling platform to a separate production platform.
A trunk line handles the combined flow from one or many platforms to
shore. The line is usually of large diameter and can either be oil or gas.
Booster pumps or compressors must be provided at intermediate
platforms for very long trunk lines. It is usually a common carrier,
carrying product owned by many producers.
These lines usually connect a production platform and a loading facility
or a subsea manifold and a loading facility. It can be small or large
diameter and carry liquid only. Connection may be from a shore facility
to an offshore loading or unloading terminal, as in the case of the
Louisiana Offshore Oil Port (LOOP).
Loading lines are usually short, ranging from 1 to 3 miles long,
although in the case of LOOP, the unloading line is about 21 miles
long. The loading facility may be temporary, such as an early
production facility, to provide limited product shipment until a
gathering or a trunk line can be completed. It can be used with a
permanent loading facility for small reservoirs and in remote areas.
24
Generally, there are four classifications of submarine pipelines, depending on
the line function. Certain pipe size and operating pressure may also be associated
with each line classification. These classifications are summarized in Table 2.1.
As these submarine pipelines were installed in increasingly deep water,
specialized technical and design problems had to be solved. A submarine pipeline
installed at any water depth must be designed such that it maintains its integrity
during construction and during its operating lifetime (Mousselli, 1981). During
construction, the pipeline is exposed to various bending stresses as it is laid from the
surface vessel to the seabed and due to lateral currents and various dynamic
conditions. After the pipe rests on the seabed, it is exposed to several potential risks
of damage due to wave and current conditions in the area, soil instability, anchors,
fishing trawls and other hazards.
Table 2.2:
Constraints involved in pipeline design
Source: Bea, 1985
CONSTRAINT
TYPE
Environmental
Constructional
Operational and
Maintenance
Design
DESCRIPTION
These require the definition of currents, mudslides, fault movements,
soil profiles and bathymetry, which could affect the stability and
integrity of the pipeline during its economic life.
These include the equipment needed for fabrication and installation, the
specification of the pipeline steels, welding and quality controls, and
pipeline bedding, backfill and armouring.
These must consider the need to tie-in points, flowrates, pressure and
temperature profiles and the corrosivity of the fluids to be transported,
methods of pipeline surveillance and monitoring, the need for
maintenance and possibly repair, means of controlling fluid escape and
emergency procedures.
These include the methods of analysis to be used, route guidelines,
regulatory requirements and codes, allowable stresses and factors-ofsafety. Economic considerations must include the costs of construction,
operation, surveillance, maintenance failure and repair. Furthermore,
the potential effects of the pipeline on other systems must be fully
explored for their economic, political, environmental and social effects,
especially when these are related to a pipeline failure.
25
In order to be successful in the pipeline engineering processes, pipeline
engineers must consider the constraints imposed on the pipeline design by the nature
of environment; the methods of construction, operation and maintenance; and the
changing state of pipeline technology. In view of these constraints (outlined in Table
2.2), the pipeline engineer has to gather data and information to define these
constraints at the outset. The design process then focuses on a logical balancing of
these constraints to yield an optimum design. Figure 2.1 shows the flow diagram of
the main design considerations for selecting the pipe route and its weight in
potentially unstable seabottoms.
To achieve the routing objectives, the hazardous conditions must first be
identified in the specific site as to minimize potential risks of damage to the pipeline,
then measures be taken to protect the pipeline from these hazards. An adequate
design of pipe parameters would be carried out after all the hazards, harmful
crossings and obstructions have been identified. The design parameters are carefully
determined so the pipe can withstand forces applied to it during construction, and
during the operating lifetime. Table 2.3 summarizes the special considerations for
submarine pipeline and riser installation in unstable areas.
Table 2.3:
Special considerations for pipeline installation in unstable areas
Source: Mousselli, 1981
Consideration
Tasks
Route Selection
™
Environmental design criteria & Hazard evaluation
Pipeline Design
™
Hydrodynamic & Buckling & liquefaction/stability analysis
™
Thermal load/flexibility analysis
™
Riser design & connection tie-in recommendations
™
Safety joint-valve recommendations
Specifications
™
Materials & installation
Evaluate Alternatives
™
Pipeline riser design
™
Installation methods & burial recommendations
™
Cost trade-offs & alternative bids
™
Design report
Permit Applications
26
Start
Oceanographic Data
Side Scan Sonar Imageries
Sub-bottom Profiler Data
Magnetometer Data
Soil Samples
Identify potential hazards, crossing & obstructions
Determine most
Severe conditions
during construction
for a specific
installation method
Determine most
severe conditions
during life of
pipeline
(e.g. 100 years)
Identify candidate pipeline route, if in mud slide area, route should be
selected to parallel direction of slide
Determine generalized soil conditions and stratigraphy along candidate routes
Perform soil stability analysis
Strength deterioration during storm conditions
Potential of large soil movements and induced forces
Establish lateral friction
coefficients of exposed pipe along route
Determine required pipe specific
gravity (when exposed) based on
hydrodynamic stability during
construction, SGc
Determine required pipe specific
gravity (exposed) based on
hydrodynamic stability during
Operation, SGo
No
Specify safe range of pipe specific
gravity in liquefied soil
SGfloat < SG < SGsink
Are soil movements potential
hazards along the pipe route?
Pipeline may be buried
Is burial required
due to other hazards?
Select safest pipe route and determine depth of
soil affected by storm loads, if any
Yes
No
Yes
Specific gravity requirements:
SG (during construction) > SGc
SGfloat < SG (pipe and content) < SGsink
Specific gravity requirements:
SG (during construction) > SGc
SGo < SG (pipe and content) < SGsink
End
Note: the description of all formula symbols are available in “List of Notation”
Figure 2.1:
Flow diagram of pipeline routing and weight design
27
2.3
Hydrodynamic Forces
The submarine pipeline can be subjected to the combined effect of steady currents,
oscillatory currents, and wave-induced forces while resting on the seabed. To
evaluate the stability of pipe due to these forces, a free-body diagram of these forces
acting on the pipe cross section is shown in Figure 2.2. These forces include (1)
submerged weight of the pipe and the weight of the contents, W; (2) combined drag
force, FD; (3) combined lift force, FL; (4) inertia force, Fi; and (5) friction resistance
force between the pipe and the seabed, Fr.
y
FL
U
Concrete coating
Steel Pipe
Fo
X
Fi
W
N
Fr
Figure 2.2:
Hydrodynamic forces on pipe
To evaluate the stability of pipe due to hydrodynamic forces, the studies of
submarine pipeline stability require reasonably accurate data concerning the
velocities of currents along the prospective pipeline route. However, these data are
seldom available in detail which is normally required (e.g., 100 years) (Nielsen, and
Gravesen, 1985). Thus, it becomes necessary to develop models of the specific wave
characteristics, which can then be used for hydrodynamic forces calculation. A
28
definition of various parameters for simple sinusoidal progressive wave is shown in
Figure 2.3. The formulae for calculating the different wave characteristics as a
function of wave height, period, wave phase angle and water depth are summarized
in Table 2.4 (Nielsen & Gravesen, 1985; and Mousselli, 1981).
Celerity
Direction of propagation
L
Crest
z
Still Water Level
a
K
x
H
a
Trough
d
Figure 2.3:
Definitions of linear wave parameters
To illustrate the hydrodynamic-force calculations presented in Figure 2.4,
consideration is made of linear, small-amplitude, oscillatory-wave theory. The
formulae for calculating the different wave characteristics as a function of wave
height, period, wave phase angle, and water depth are given in Table 2.4 (see
Mousselli, 1981, for complete description).
29
INPUT
wave height (Ho); wave period (T); water depth (d);
pipe diameter (D); seabed slope (Ԧ); and coefficient of soil friction
(ȝ)
COMPUTE 2
gT
d
where Lo
Lo
2S
DEFINE WAVE LENGTH & HEIGHT
From figure ….
d
1
%
L 25
1
d 1
% %
25 L 2
PARTICLE VELOCITY
PARTICLE VELOCITY
u
H
2
g
cos T
d
u
d
1
L
2
PARTICLE VELOCITY
H gT Cosh 2S z d / L cos T
2 L
Cosh 2Sd / L u
SH
T
e
2SZ
cos T
L
EFFECTIVE VELOCITY
U e2
0.778 (U 02 )( D / y o ) 0.286
REYNOLDS NUMBER
UeD
R
e
v
where v
2
DEFINE HYDRODYNAMIC FOEFFICIENTS
CD, CL & CM
DRAG FORCE
FD
LIFT FORCE
1
U CD D Ue2
2
FL
1
U C L D U e2
2
INERTIA FORCE
Fi
·
§
§ gSH · § cosh >2S z d / L @ ·
§ 2St · ¸
¸¸ sin ¨
U C M §¨ SD 2 / 4 ·¸ ¨¨ ¨
¸ ¨¨
¸¸
©
¹ ¨ © L ¹ © cosh 2Sd / L ¹
© T ¹¸
¹
©
SUBMERGED WEIGHT
W
FL 1
P
FD Fi Note: the description of all formula symbols are available in “List of Notations”
Figure 2.4:
Flow diagram of hydrodynamic forces analysis
g
cosT
d
Z
cosT
d
Note: the description of all formula symbols are available in “List of Notations”
H
Z
1 cosT
2
d
Ug (K z )
g
sinT
d
1
Subsurface Pressure, P
HT
4S
T
S 2
g
sin T
d
2 H
HS
T
HS
z
1
sin T
T
d
H
2
gd
Vertical, ]
Water Particle Displacements
Horizontal, [
Vertical, az
Water Particle Accelerations
Horizontal, ax
Vertical, w
Water Particle Velocity
Horizontal, u
Group Velocity, Cg
gd
Wave Length, L
T
gd
Ug
cosh 2Sd / L >
@ Ugz
@
cosh 2S Z d / L
>
@
H sinh 2S z d / L
cosT
2
sinh 2Sd / L >
@
H cosh 2S z d / L
sin T
2
sinh 2Sd / L >
@
gSH sinh 2S z d / L
cosT
L
cosh 2Sd / L >
@
gSH cosh 2S z d / L
sinT
L
cosh 2Sd / L >
@
H gT Sinh 2S z d ) / L sin T
2 L
Cosh 2Sd / L >
H gT Cosh 2S z d ) / L cosT
2 L
Cosh 2Sd / L 1 ª
º
4Sd / L
1
»¼
2 «
sinh
4
d
/
L
S
¬
C
H
cosT
2
or
2Sd
gT
tanh
2S
L
gT 2
2Sd
tanh
L
2S
2Sx 2St
H
cos
2
L
T
1 d 1
% %
25 L 2
Same As
   o
Transitional Water
d 1
%
L 25
Linear (Airy) wave characteristics
Shallow Water
Wave Celerity, C
Wave Profile, K
Relative Depth
Table 2.4:
e
cosT
H 2SZ
e
sinT
2 L
L
UgKe
2SZ
UgZ
L
H 2SZ
e
cosT
2 L
T
e
L
sinT
sinT
S 2 2SZ
T
e
L
cosT
S 2 2SZ
2 H
2H
T
e
L
SH 2Sz
T
SH 2Sz
1
C
2
2S
gT
2S
gT 2
Same As
m   
d 1
%
L 2
Deep Water
30
31
2.4
Vortex-Induced Oscillations
When water current flow across the pipeline, vortices (eddies) occur downstream
from the pipe. These vortices are caused by the flow turbulence and instability behind
the pipe. Vortex shedding causes a periodic change in the net hydrodynamic pressure on
the pipe, which may cause a pipe span to vibrate.
Frequency of the vortex shedding depends on pipe diameter and the flow
velocity. If the vortex frequency, also referred to as Strouhal frequency, is synchronized
with one of the natural frequencies of the pipeline span, then resonance occurs and the
pipe span vibrates. Pipe damages have been reported due to vortex-induced oscillations
in the pipeline. The pipeline oscillations may occur in the cross-flow direction and the
in-line direction of the flow. By far the more serious oscillations are those which occur
in the cross-flow direction. In-line oscillations are not generally considered to cause
serious oscillation problems in the pipe, although some exceptions to this have been
reported. Vortex-induced pipe oscillations are illustrated in Figure 2.5, while Figure 2.6
represented the flow-diagram of vortex-induced oscillations computation.
Flow direction
Pipe
Vortex
Cross-flow oscillation
In-line oscillations
Figure 2.5:
Vortex-induced oscillations
32
INPUT
pipe diameter (D); pipe thickness (WT); flow velocity (Fv); span length (Ls)
VORTEX-EXCITING FREQUENCY
fs
SV
D
COMPUTE
Di
D 2WT
and
I
S
64
D
4
Di 4
PIPE UNIT MASS
Ma
S
4
D
2
Di 2 *15.218
DISPLACED MASS
MD
S
4
D
2
Di 2 *1.988
PIPE-SPAN NATURAL FREQUENCY
fn
C
L2
EI
M
where
E
3 *107
C S /2
M
NO
Ma MD
f s d 0.7 f n
THE PIPE IS NOT SAFE
YES
THE PIPE IS SAFE
Note: the description of all formula symbols are available in “List of Notations”
Figure 2.6:
Flow diagram of vortex-induced oscillations computation
33
2.5
Pipeline-soil stability analysis
Vertical and horizontal pipeline stabilities need to be carefully examined when
the pipe is resting on the seabed or embedded in the soil. These stabilities must be
analyzed under static conditions as well as under cyclic pressure conditions caused by
passage of surface wave (Mousselli, 1981).
2.5.1
Settlement and Flotation
When a pipeline is partially or totally buried, it may float upward or settle
downward under storm conditions, depending on the pipe weight (including contents),
soil density, and undrained shear strength of the soil. Various experiments have been
made to measure soil flotation and resistance forces. According to Mousselli (1981), a
range of pipe specific gravities may be selected such that the pipe is stable. Typically,
the upper and lower limits of the pipe specific gravity required for equilibrium can be
calculated as follows:
SG1 < SG < SG2
Where:
SG
=
Allowable range of pipe specific gravity
SG1
=
SGSoil – 2Cs/UD lower limit of SG
SG2
=
SGSoil + 2Cs/UD lower limit of SG
34
2.5.2
Soil Strength Deterioration
Under cyclic loadings of the bottom sediments caused by passage of a storm
wave (see Figure 2.7), the significant cyclic strains may develop in clay generating large
pore pressures. As a result, the soil strength after this cyclic loading becomes less than
the static undrained shear strength. Hence, the remolded (reduced) shear strength in
determining the allowable range of pipe specific gravities required for pipe stability.
In general, determination of the potential soil-strength reduction when subjected
to storm-wave stresses on the seabed requires knowledge of the wave time history and
the strength characteristics of the soil. According to Mousselli (1981), previous studies
have indicated that the deterioration of soil strength when subjected to cyclic loading
depends on the generation of excess pore pressure. Generation of this pore pressure is
basically strain dependent; hence, soil failure can be defined in terms of the cyclic strain
amplitude.
Surface Wave
MSL
Differential Pressure
re at mudline
Mean Pressu
ouple
Pressure C
Shear
Resistance
Figure 2.7:
Idealized failure surface
Storm-induced bottom pressures
Edited from Mousselli, 1981
35
According to Mousselli (1981), the pore pressure may build up to a level equal to
the vertical effective stress in sand areas and then quickly causing sand liquefaction.
Thus, the failure potential for sand is commonly evaluated based on the ratio of the
cyclic excess pore pressure to the vertical effective stress. Oppositely, the accurate pore
pressure measurements require very slow rates of cyclic loadings, and most cyclic tests
on clay do not include any pore-pressure measurements because of the relatively low
permeability of clay. Thus, failure criteria for clay are commonly defined in terms of
cyclic-strain amplitude caused by cyclic-stress loadings.
A storm wave is composed of an infinite number of frequencies, and concepts
have been developed to express the effects of irregular cyclic loadings on soil in terms of
an equivalent number of uniform cycles of an average corresponding cyclic stress. After
determining the potential and extent of soil-strength deterioration, pipe specific gravities
may be selected such that the pipe remains stable in the weak soil. As general criteria,
pipe in unstable soils should be designed such that its unit weight is close to be unit
weight of the liquefied soils.
2.5.3 Effect of Large Soil Movements
Several mechanisms cause soil movements at the seabed, such as erosion,
turbidity (or suspension) currents, rapid soil depositions on steep slopes, and passage of
large surface waves. The mechanism of the interaction of ocean waves and large
movements of underwater slopes in soft, underconsilidated sediments is complex.
Efforts made to explain this mechanism have resulted in partial explanations due to the
various simplifying assumptions made (Mousselli, 1981).
36
In general, wave forces on the seabed can cause sediment instability in two ways.
First, the traveling wave will cause the cyclic stresses and increased pore pressure. The
soil shear strength may be greatly reduced and gravity forces may be sufficient to cause
slope movements. Besides that, seabottom wave will cause differential loading that
induce stresses in the underlying soil. If these stresses exceed the soil strength,
significant soil movement may occur.
To solve this, efforts have been made to calculate wave-induced seabottom
movements with considerations of gravity, cyclic and permanent soil movements; to
predict storm-induced seabottom movement using viscoelastic analysis; to determine the
ultimate soil restraining force (Hansen, 1961); and to compute wave-induced soil
movements and the consequent forces on buried pile (Marti, 1976); and to compute the
bearing capacity factor for ultimate soil static force (Mousselli, 1981).
Results of these studies show that the possibility of pipe failure under soil
loadings would depend on the pipe strength, soil forces which increase with depth, and
the width of the mud slide. These studies recommended that the pipe should be placed at
or slightly below the seabed to minimize forces on the pipe due to soil movement. These
forces may soon become extremely large when the depth of pipe burial is increased.
However, when the pipe is not buried, it is exposed to hydrodynamic forces on
the bottom. Therefore, the pipe specific gravity must be selected such that the weight of
pipe (including contents) is heavy enough for the pipe to remain stable under the most
severe wave and current conditions during its lifetime, yet light enough that the pipe
does not embed itself below the mud line.
37
2.6
Effect of Seabed Irregularities
During installation of a submarine pipeline, the pipeline may cross elevated
obstructions or lowered depressions along its route. As these bottom irregularities are
crossed, spans and bending stresses will be induced in the pipe that must be maintained
at a safe level, then damage. If these spans and stresses would exceed their safe level,
then measures must be taken either to alter the pipeline route or to minimize the bottom
irregularities by methods (e.g., presweeping). The computation flow of pipe stresses due
to bottom irregularities is shows in Figure 2.8.
Start
INPUT
pipe diameter (D); pipe thickness (WT); submerged weight (W),
span length (Ls), axial tension (AT), Obstruction elevation (G)
DimensionlessElevation ,
Characteristic Stress , Vc
G
Lc
13
x 100
Characteristic Length, L c
EC
Dimensionless Tension , E
Lc
Read from Figure 2.13
Maximum Dimensionless Stress, Vm
§ EI ·
¨ ¸
©W¹
T
WLc
Read from Figure 2.11
Maximum Dimensionless Stress, Vm
End
Note: the description of all formula symbols are available in “List of Notations
Figure 2.8:
Flow diagram of maximum dimensionless stress computation
38
First, consider the pipe configuration over a low depression as shown in Figure
2.9. Two distinct regions may be defined for the pipe: (a) pipe span in the depression
given by L, and (b) pipe span outside the depression given by Ls on either side of the
depression.
Figure 2.9:
Pipe configurations due to low depression
The variation of maximum bending stress versus the depression span is shown
for various values of pipe tension in Figure 2.10(A). Similarly, stresses as well as
deflections at midspan are depicted in Figure 2.10(B) and Figure 2.10(C), respectively.
Note that the maximum stress occurs at the boundary of the low depression.
An examination of these figures reveals that these stresses decrease as the pipe
tension is increased. In particular for large-depression spans, inclusion of tension
substantially reduces pipe stresses. Length of the pipe span induced outside the
depression is also depicted as a function of the depression span and tension in Figure
2.10(D). These pipe spans decrease in length as the pipe tension is increased. Similarly,
it is observed that, for large-depression spans, inclusion of tension reduces lengths of
induced spans outside the depression.
1.0
0.9
0.8
ȕ= 0
0.7
0.6
0.5
ȕ= 5
0.4
0.3
ȕ= 10
0.2
0.1
Dimensionless stress at mid-span, (ıo/ ıc)
Maximum dimensionless bending stress, (ım/ ıc)
39
1.0
0.9
0.8
0.7
ȕ= 0
0.6
0.5
0.4
0.3
ȕ= 5
0.2
0.1
ȕ= 10
0
0
0.5
0
1.0
1.5
2.0
2.5
3.0
0
3.5
0.5
1.0
2.0
2.5
3.0 3.5
B
1.0
0.8
0.6
ȕ= 0
0.4
ȕ= 5
0.2
0.1
0.08
0.06
ȕ= 10
0.04
0.02
0.01
Dimensionless induced pipe span, (Ls/ Lc)
A
Dimensionless deflection at mid-span, (į/ Lc)
1.5
Dimensionless span, (L/Lc)
Dimensionless span, (L/Lc)
2.0
ȕ= 0
1.8
1.6
1.4
ȕ= 5
1.2
1.0
ȕ= 10
0.8
0.6
0.4
0.2
0
0
0.5 1.0
1.5
2.0
3.0 3.5
(L/Lc)
2.5
Dimensionless span,
C
0
0.5 1.0
1.5
2.0
2.5
3.0 3.5
Dimensionless span, (L/Lc)
D
Figure 2.10: Stresses due to low depressions: (A) Maximum stress due to low
depression; (B) Stress at mid-span; (C) Deflection at mid-span; and (D) Induced pipe
spans (summarize from Mousselli, 1981)
40
Besides the stresses due to low depressions, the pipeline may also be affected by
an elevated obstruction as shown in Figure 2.11. Since the pipe span is symmetric about
the obstruction, it is sufficient to consider half the pipe span for the bending analysis.
The pipe-governing equations are solved employing familiar numerical techniques.
Figure 2.11: Pipe configurations due to elevated obstructions
According to Mousselli (1981), the pipe-governing equations are solved
employing familiar numerical techniques. Because the span length is not known a priori,
interactive procedures are employed to deduce this span length and pipe forces. Results
of the solutions are then presented in terms of dimensionless parameters described
earlier.
Graphs depicting variations in induced pipe spans and resulting maximum
stresses versus elevation of the obstruction are shown in Figure 2.12(A) & (B),
respectively. It is observed that maximum bending stresses caused by elevated
obstructions are virtually unaffected by variations in pipe tension. In contrast, pipe spans
are increased as the pipe tension is increased. It is noted, however, that tensile stress and
combined bending and tensile stress will increase when tension in the pipe is increased.
41
0.5
M aximum Dimensionless Stress, ( ı m / ı c )
4.0
Dim e nsio nless Span , (L /L c )
ȕ= 10
3.0
ȕ= 0
2.0
1.0
0
0.4
ȕ= 0-10
0.3
0.2
0.1
0
0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
Dimensionless Elevation, (į/Lc)*100
A
8.0
0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
Dimensionless Elevation, (į/Lc)*100
B
Figure 2.12: Stresses due to elevated obstructions: (A) Span due to elevated
obstruction; and (B) Maximum stress due to elevated obstruction (summarize from
Mousselli, 1981)
2.7
Scour and Erosion
In the surf zone and areas where bottom currents are large in magnitude, bottom
sediments may be eroded, suspended, and deposited elsewhere. This can cause pipe
exposure, loss of support, and pipe spanning, resulting in the potential of displacement,
vibration, and damage to the pipeline. To illustrate this phenomenon, consider a flat
bottom seabed containing sand with water flowing above it. When the velocity is low,
the seabed particles will not move. As the flow rate is gradually increased, sediment
grains begin to move (the sequence of this movement is illustrated in Figure 2.13).
42
Initially, the movement consists of random rolling and sliding of individual
grains. As the flow rate increases, turbulence increases near the seabed, and more
particles roll and slide near the seabed. This first incipient motion is referred to as the
threshold of particles move, with some lifted off the seabed for a short trajectory before
falling back on the seabed. The transportation of matter in this way is also referred as
siltation of sediments.
Figure 2.13: Modes of grain transport
As the flow becomes more turbulent, some of the sediment particles will be lifted
increasingly higher above the seabed until they are in suspension and can be transported
with the flow. The more turbulent the flow is, the more particles are in suspension. At
very high flow rates, the flow will cause irregularities on the seabed known as the
settling velocity.
Many theoretical and experimental efforts have been made in the past to quantify
the relationship between the flow rate and the velocities associated with sediment
transport. Plots have been generated by Mousselli (1981), to illustrate the minimum
43
erosion velocity, transport velocity, and the deposition velocity of the soil particles
versus grain size of the sand sediments, as shown in Figure 2.14. Note that this graph has
been plotted with the mean velocity at 1 m above the seabed, and the material grains are
assumed uniform.
Grain size, ĭ
10
6.7
3.3
0
-3.3
-6.7
Mean velocity, cm/sec
1,000
500
Erosion
100
50
25
10
5
Transportation
Deposition
1
0.5
0.1
0.001
0.01
0.1
1
10
100
Grain size, mm
Figure 2.14: Current velocity for sediment transport
Summarize from Mousselli, 1981
Measures to protect the pipeline from scour include burial of the pipeline to
sufficient depth of cover and anchoring the pipe. Burial of the pipe can be effective if the
line is buried beyond the depth of expected erosion during pipe lifetime. Determination
of the amount of erosion in a given area is complex. However, in most cases, and
particularly in sand, an estimate can be made of the depth of erosion.
44
2.8
GIS for Pipeline Routing Evaluation
Determining the best route through an area is one of the oldest spatial problems.
Meandering animal tracks evolved into a wagon trail that became a small road and
ultimately a superhighway. Although this empirical metamorphosis has historical
precedent, contemporary routing problems involve resolving complex interactions of
engineering, environmental and social concerns (Glasgow, et al, 2004).
As the solution of this, GIS is explicitly designed to determine the most preferred
route considering the myriad of complex spatial interactions. The Least Cost Path (LCP)
method is widely used to generate a new grid representing the shortest route between 2
selected destinations (Osborne & Abbott, 2003). Effectively, the command find a path of
least resistance (Figure 2.15) across the Accumulative Cost Map(ACM) (as discussed in
section 2.7.2 & Chapter 5, section 5.2.1.2). The Optimal Route (OR) indicates the best
connection between starting and ending locations. The Optimal Corridor (OC) relaxes
the considerations to identify the set of nearly optimal connections that might be
considered.
1
2
3
Figure 2.15: Concept of LCP Analysis
45
Figure 2.16 shows the methodology of Least Cost Path identification. The first
step of defining the Discrete Cost Map (DCM) is the most critical as it establishes the
relative “goodness” for locating a pipeline at any grid cell in a project area. It imparts
expert judgment in calibrating and weighting several routing criteria maps. The
remaining steps, however, are mechanical (deterministic) and require no user interaction
or expertise.
Figure 2.16: Methodology of LCP analysis
Source: Berry, J. K., 1996
In most practical applications, the weighting (and sometime calibration) of the
criteria maps are changed to generate alternative routes. This capability enable the user
to evaluate “…what if” scenarios that reflect different perspectives on the relative
importance of the routing criteria. When LCP is used in this manner it becomes a
“spatial spreadsheet” providing information on the sensitivity of pipeline routing
throughout a project area. If under several different assumptions the route always passes
through a particular location it indicates its importance. On the other hand, areas where
potential routes wander indicate locations with minimal routing importance.
46
2.8.1 Discrete Cost Map (DCM)
The first and critical step establishes the relative ‘goodness’ for locating a
pipeline at any grid cell in a project area (Figure 2.17). The individual map layers are
calibrated from the best to the worst conditions for a pipeline. In turn, the calibrated
maps are weight-averaged to form logical groups of criteria. Finally, the group maps are
weight-averaged to derive a Discrete Cost Map (DCM) as shown in Figure 2.17.
In Figure 2.17, the higher values form “mountains of resistance (cost)” are
avoided if at all possible. The flat (green) areas identify suitable areas and tend to attract
pipeline routing; the peaks (red) identify unsuitable areas and tend to repel pipeline
routing. Note that the saddle points between areas of high cost act as “passes” that
severely constrain routing in a manner analogous to early explorers crossing a mountain
range.
However, the explorers had to tackle each situation independently as they
encountered them and a wrong choice early in the trek could commit them to punishing
route that was less than optimal. The second and third steps of the LCP procedure, on
the other hand, enable a comprehensive analysis of the discrete cost map to identify the
optimal route.
Figure 2.17: Discrete Cost Map (DCM)
Source: Berry, J. K., 1996
47
2.8.2
Accumulated Cost Map (ACM)
The second step of the LCP procedure uses a propagating wave-front from a
starting location to determine the least “cost” to access every location in the project area
(Figure 2.18). It is analogous to tossing a rock or stick into a pond with the expanding
ripples indicating the distance away. In this case however, the computer moves one
“ripple” away from the start and incurs the cost indicated on the discrete cost map.
As the expanding ripples move across the discrete cost map an ACM is
developed by recording the lowest accumulated cost for each grid cell. In this manner
the total “cost” to construct the preferred pipeline from the starting location to
everywhere in the project area is quickly calculated.
Figure 2.18: Accumulated Cost Map (ACM)
Source: Berry, J. K., 1996
48
In Figure 2.18, the 3D surface has a bowl-like appearance with the starting
location at the bottom (0 cost). All of the other locations have increasing accumulated
cost values with the increase for each step being a function of the discrete cost of
traversing that location. The ridges in the bowl reflect areas of high cost; the valleys
represent areas of low cost. Also note that the effect around the low cost “pass” areas,
where the contour lines of accumulated cost seem to shoot out in these areas indicating
lower total cost than their surroundings. The same areas in the 3D view appear as
saddles along the ridges—points of least resistance (total cost) on the sloping bowl-like
surface
2.8.3
Optimal Route (OR)
The bowl-like nature of the accumulated cost map is exploited to determine the
Optimal Route (OR) from any location back to the starting location (Figure 2.19). By
simply choosing the steepest downhill path over the surface the path that the wave-front
took to reach the end location is retraced.
Figure 2.19: Optimal Route (OR)
Source: Berry, J. K., 1996
49
By mathematical fact this route will be the line having the lowest total cost
connecting the start and end locations.
Note that the route goes through the two
important “passes” that were apparent in both the discrete and accumulated cost maps.
2.8.4
Optimal Corridor (OC)
The optimal corridor identifies the Nth best route. These form a set of “nearly optimal”
alternative routes that a siting team might want to investigate. In addition, optimal
corridors are useful in delineating boundaries for detailed data collection, such as high
resolution aerial photography and ownership records.
Figure 2.20: Optimal Corridor (OC)
Source: Berry, J. K., 1996
50
The Optimal Corridor Map (OCM) is created by calculating an accumulation
cost map from the end as well as the starting location. The two surfaces are added
together to indicate the effective “cost” distance from any location along its optimal path
connecting the start the end locations.
In Figure 2.20, the lowest value on this map forms the “valley floor” and
contains the optimal route. The valley walls depict increasingly less optimal routes.
Nearly optimal routes are identified by “flooding” the surface. As illustrated in Figure
2.20, a five percent optimal corridor is shown. Notice the “pinch point” along the rout at
the location of the low cost “passes.” The corridor is allowed to spread out in areas
where there is minimal discrete cost difference but tightly contained around critical
locations.
2.8
Summary
Submarine pipeline routing design is a complicated business, which requires high
precision assessment of all potential hazardous conditions to ensure the maximum safety
of the pipeline during its operation lifetime. Since most of these consideration elements
are related to spatial dataset, the GIS is explicitly designed to determine the most
preferred route considering the myriad of complex spatial interactions. The concept of
LCP in GIS can greatly help the pipeline engineers to identify the best route of the
pipeline in terms of safety, cost and legality.
51
CHAPTER 3
SUBMARINE PIPELINE INSPECTION
3.1
Introduction
As pipeline infrastructures age, proper design and adequate inspection
programs are needed to maintain integrity and promote longevity. However, the
selection of appropriate, yet cost-effective inspection methods is still widely
considered to be more of an art than science (Darbaghi, 1998). This Chapter
discovered most of these methods which have significantly improve the acquisition
and presentation of submarine pipeline inspection results. The protection methods of
submarine pipeline are carefully evaluated as well throughout this Chapter.
Ultimately, this Chapter discussed the integration of GIS technology, as a system of
computer-based information storage will evolve in which pipeline data, obtained by
these technologies, may be readily compared with observations by diver of
submersible television; all referenced to a common distance measurement.
52
3.2
The Need of Pipeline Inspection Survey
Underwater inspection can be considered a continuation of the detailed
inspection necessary during the onshore fabrication of a structure through towage to
location, installation and operation. In the course of the installation of the structure
on the seabed, an almost continuous underwater surveillance is carried out to ensure
that the integrity of the structure is maintained. During the operational life of the
structure, whether a platform or submarine pipeline, underwater inspection may be
carried out for several reasons, the three most prominent reasons given by Atkins
Planning (1979) are:
x
Certification, of the maintenance of a certificate of fitness;
x
Operator’s assurance of reliability and safety; and
x
Work associated with accidents, repairs after accidents and other
modification.
In recent years, the installation of oil and gas pipelines has taken place in
increasingly deeper and rougher waters. In such adverse environments, the
combination of installation and environmental hazards to pipelines, plus the threat of
damage by ship’s anchors or fishing trawl boards (see Table 3.1 for complete
summary) make it essential to inspect the condition of pipelines on a regular basis,
preferably at least once a year (Corbishley and Luynenburg, 1985). Occasionally, in
areas where there is high seabed mobility (e.g., sandwaves ) this type of survey may
be more frequent (Atkins Planning, 1979).
According to Milne (1980), the common problems that have been revealed on
submarine pipeline are (a) exposure of buried length including complete
undercutting and bridging; and (b) damage on exposed lengths for a variety of
reasons including the impact of trawls and anchors (as described in Chapter 2,
53
Section 2.6). Table 3.1 outlined the major needs of submarine pipeline inspection
during its operation lifetime (Willianms, 1990; Karal, 1987; Palmer, 1985; King &
Geary, 1985, Str‡mmen, 1985 and Gravesen, 1985).
Table 3.1
Damage
Major needs of submarine pipeline inspection
Description
Anchoring
Vessels
A dragging anchor can hook a pipeline and displace it or sever it
completely, and no reasonable amount of burial will guarantee
protection in this case because anchors can penetrate too deeply into
the seabed.
Fishing Gear
A heavy trawl board can scratch or spall concrete and scuff the
coating of a flexible and, if the trawl board becomes trapped behind
the pipeline, the line can be dragged sideways.
Ship impact
Three main types of forces are exerted on a pipeline during the
passage of a vessel, namely: a force in the forward ship direction
before the vessel reaches the pipe, a combined lift and backward force
just after the vessel bow has passed the pipe and a combined lift and
forward thrust when the stern of the vessel passes the pipe.
Dropped
objects
Dropping equipment off a platform or vessel, such as containers,
drilling tubulars or scaffolding possibly can hit and dent or buckle a
pipeline.
Material and
welding
defects
Although considerable control is exercised over the manufacture and
welding of steel, leaks have occurred due to cracks in both the welds
and the main body of pipelines and risers.
Corrosion
In the corrosive environment (e.g., high acid or alkaline contents),
coated in bitumen and concrete-like the pipelines are inadequate.
Cases of external corrosion have been common and might result in
rupture of a line. Internal corrosion problems can arise when operating
conditions or the product carried are changed and the corrosiveness of
the new medium is not properly understood.
Design faults
In certain cases, pipelines have suffered damage to weight coating.
This is most likely when the concrete used for weight coating is low
strength and poorly reinforced.
Fitting such as flanges, connectors and valves are well designed and
their location selected carefully, but leaks have still occurred.
Furthermore, clamp bolts can come loose, due to very bad weather or
inadequate design, causing the riser to drop. This has resulted in a
pipeline buckling and a leak at a flange.
Fitting failures
Construction
Trenching has resulted in damage to pipelines. Number of the earliest
pipelines to be installed was damaged by trencher to the extent that
they split during hydrotest.
54
Obviously, the careful planning of an inspection and maintenance
programme is essential to ensure the continued integrity of seabed pipelines. Where
the pipeline is exposed, visual inspection is no problem, but the inspection of
submarine pipeline is seriously hampered by the normal burial or normal bituminous
coating technique which make the pipework and the anode system inaccessible for
visual survey. Subsequently, once the pipeline is buried it is essential to use special
techniques for pipe tracking, either metal detectors, magnetometers, acoustic devices
or a magnetic radiometer (Messervy, 1977).
In general, pipeline inspection tasks have been divided into four categories
by Durrand and Stankoff (1978), that are:
x
Visual inspection, use of TV (Television) camera, still or cine cameras, and
conventional or SSS. Underwater navigation systems are required for
position fixing to locate accurately each point of interest;
x
inspection of trench and burial conditions, the determination of the actual
seabed conditions by taking profiles of the seabed at right-angles to the
pipeline to determine the pipeline’s location in the trench, relative to the
original seabed;
x
cathodic protection inspections, to check the satisfactory protection of the
pipe against corrosion, by examining the sacrificial anode bracelets installed
at approximately 150m intervals;
x
Leak detection, the rapid location and repair of pipeline leaks during testing
and operation.
55
These methods are well documented (Table 3.2) and aim to ensure that the
pipelines do not become defective or damaged ('proactive' methods) and damage or
defects could be detected before they cause serious problems ('reactive' methods)
(Jones and Hopkins, 2004). The pipeline engineers should assess the greatest
damage/defect risk to the pipeline, then select a monitoring/inspection method to
reduce that risk.
Table 3.2
Pipeline inspection and monitoring methods
Source: Jones and Hopkins, 2004
DEFECTS /
DAMAGE
Monitoring / Inspection Methods (excluded visual examinations)
P = Proactive Method, R = Reactive Method
Aerial/G Intelligent Product Leak
round
PIGs
Quality Survey
Patrols
3rd Party Damage
P
Geotech
Survey &
S. Gauges
R
Ext. Corrosion
R
Int. Corrosion
R
Fatigue Cracks
R
Hydro
Test
R
P
P
R
R
R
Coatings
P
Material Construct
Defects
R
R
Ground Movement
Leakage
CP
Coating
Surveys
R
R
P
R
R
Sabotage/Pilfering P
3.3
Internal Pipeline Inspection (IPI)
In the simplest form, an effective In-Line Inspection (ILI, or descript as
Internal Pipeline Inspection, IPI in this report) requires two basic things, that are a
vehicle that can access all areas and locations and the sensor technology that can
quickly identify, quantify, and accurately locate all ‘problem’ areas (e.g., internal
corrosion).
56
Internal corrosion of pipelines is generally accepted to be caused by one or
more of five corrosion mechanisms due to carbon dioxide, hydrogen sulphide,
microbiological degradation, acids and erosion corrosion (the complete description
is available at King & Geary, 1985). However, the normal corrosion monitoring,
measurement of chemical additive concentrations and discrete spot-testing cannot be
done on submarine pipelines due to its inaccessibility.
(a)
(b)
Figure 3.1
Pigs
Image source: (a) Pigs Unlimited, Inc. and (b) BJ Services Company
By contrast, routine monitoring is restricted to its ends and, instead of
injection at regular distances along the pipeline, chemical treatment can only be
effected offshore using continuous dosing, the efficacy of which is often
questionable (King & Geary, 1985). As the solution, pigs (Figure 3.1) are widely
implemented to monitoring or inspecting the internal corrosion of submarine
pipeline.
A Pig is defined as "A device that moves through the inside of a pipeline for
the purpose of cleaning, dimensioning, or inspecting." According to Hiltscher, et al
(2003), there are various reasons to pig a pipeline. After the pipeline is built, it will
be necessary to run pigs to remove any debris left in the line from new construction;
items such as lunch boxes, tools, welding rods, dead animals trapped in the line, etc.
Pigging will also remove mill scale or welding icicles in the line. The owner may
also require a pig to verify the ovality of the pipeline. This will require a gauging pig
and sometimes a geometry pig.
57
After the pipeline has been cleaned, the next phase is acceptance testing
where pigs are used for filling the line with water for hydrostatic testing, dewatering (removing the water after testing), and drying. If it is a liquid line, a pig is
used to fill the line with a product during the commissioning and start up of the line.
When the pipeline is in service, it will be necessary to pig the line to maintain line
efficiency and aid in the control of corrosion. It is necessary to remove the liquids in
wet gas systems, remove accumulated water in product pipelines, and paraffin
removal and control in crude oil pipelines. pigs are also used to batch inhibitors.
As time passes special cleaning applications may arise. Pre-Inspection
pigging before running an IPI tool will not only require the pipe be clean but a
dummy pig be run to assure the IPI tool will go through the line. Under certain
conditions pipelines may require chemical cleaning or a train of gel pigs may be
used for certain cleaning conditions. Lines are sometimes abandoned and require
cleaning before moth balling the line. Other applications include running a
Geometry pig to determine if there are any dents or buckles in the line. To determine
the amount of corrosion or metal loss in the pipeline, an ILI tool is used. The
running of pigs in dual diameter lines always poses a challenge. Table 3.3
summarized the technologies used in intelligent pigs that would greatly help for the
activities of internal pipeline inspection:
Table 3.3
Technologies used in intelligent PIGs
Source: Penspen Integrity, Inc.
Type of Intelligent Pig
Caliper Pig
Technologies Used
Mechanical Induction
Function
Dents, Ovalities, etc.
Inertia (Mapping) Pig
Gyroscope (Inertial
Navigation)
Pressure Difference
Ultrasound
Radiation (Neutron
Irradiation)
Eddy Current, Pulsed
Eddy Current,
Ultrasound
Magnetic Flux
Leakage Ultrasound
Route Surveying, Route Profile and
Bends
Detection/Location of Leaks
Leak Detection Pig
Burial and Coating Pig
Crack Detection Pig
Metal Loss Pig
Loss of Coating cover and detection of
free spans
Detection and sizing of cracks
Detection and sizing of metal loss
defects
58
3.4
Pipeline external inspection
In general, the external inspection of a submarine pipeline can be carried out
by a variety of methods depending on depth, location and the specific EPI
requirements. The objective of this section is to simply elaborate the latest
technologies of submarine EPI, such as multibeam echo-sounding (see section
3.4.1), Side Scan Sonar (see section 3.4.2) and ROV ( see section 3.4.3).
Furthermore, this section attempts to evaluate each of these technologies in EPI
operation with some sample results.
3.4.1
Multibeam Technology
In the pipe inspection application, multibeam technology can be used in
various configurations to measure the bathymetry of the pipeline corridor. As shown
in Figure 3.2, transducer 2 would be used in a high-resolution mode, which at a
range of 30 metres will gather data from a 15 metre wide section of seabed with a
sample spacing of 4 - 20cm across-track. The dimensions of the transmitter
transducer will determine the along-track width of illumination for each sample - for
detailed pipe inspection this will be 10cm at a depth of 30 metres. Thus independent
samples can be gathered with a grid spacing of 10cm in both directions, with a depth
resolution of 1cm and a depth accuracy of ±7.5cm in 30 metres of water. The two
outer transducers (transducer 1 & 3) can be used also in the high resolution mode but
are more likely to be used in a wider coverage mode as shown in Figure 3.2,
providing samples within a corridor at least 3 times water depth and possibly up to 5
times water depth (Chapman, et al, 1999).
59
Figure 3.2
Multibeam survey for EPI operation
Source: Chapman, et al, 1999
In order to inspect a submarine pipeline, multibeam technology can be used
to obtain a continuous echo of relatively constant intensity (represented by the red
trace in Figure 3.3a). The hard reflective surface of the pipe now reflects the incident
sound waves from tranducers, rather than the more general scattering occurring from
the seabed. This results in a strong echo being returned from the surface of the pipe
which is most normal to the incident sound wave and very little reflection from any
other parts of the pipe. This is the blue echo shown in Figure 3.3a.
The centre of this echo will lie on the line joining the centre of the pipe and
the origin of the transducer as shown in Figure 3.3a. The model of the pipe can then
be positioned relative to the seabed echo using the range and bearing information
from the sonar echo and knowledge of the pipe diameter. The pipe diameter may not
be as it was when installed due to damage but the variation is likely to be within the
10cm position accuracy which should be achieved for the pipe position. If the pipe
echo is not connected to the seabed echo and is more than 20cm shallower then it
will be removed from the digital terrain file from which the seabed model will be
built.
Ra
th
in g
ch
r
No
a rt
da
tu
m
60
ng
Top of pipe
n tr e
e ce
Seabed echo
P ip
Easting
lin e
e
Loud echo from
the top of pipe
Bearing
Depth below chart
datum at each KP
Depth of
Exposure
Depth
(a)
(b)
Figure 3.3
EPI for exposed pipes (a) position of pipe determined by range and
bearing to top of pipe ; and (b) definition of pipe position and degree of exposure
The pipe echo will be used to generate a Pipe Information File (PIF) in
which the position, depth and depth of burial of the pipe are recorded for each unit
distance down the route of the pipe. The file will normally be indexed using the
Kilometres Position (KP) numbers.
In this case, the pipe can be considered as a separate entity from the seabed
model, the definition of its degree of exposure needs clarification. In general, pipe
exposure is a result of the surrounding seabed being eroded, rather than the pipe
changing its vertical position. Pipes certainly change their horizontal position and
this can obviously result in vertical position changes. Where this occurs, a new PIF
would be formed. The degree of exposure of the pipe should indicate the difference
in depth between the top of the pipe and the immediately adjacent mean seabed. The
vertical position of the pipe relative to the chart datum will indicate if the pipe is
sinking. These two indicators are illustrated in Figure 3.3b.
61
Relatively, Figure 3.4 shows that this red echo trace is the only information
available from which to estimate the position of the pipe beneath the seabed. The
horizontal position can be estimated as the centre of the hump, the vertical position
can be estimated to be the top of the hump. Clearly there is scope for small errors in
these estimates if that is all the information available. However, if it appears that the
pipe is still covered by a layer of seabed material it is not of major concern in terms
of exposed or free span situations.
Pipe position determined from centre of hump
Seabed Echo is continuous
and of constant intensity
Pipe top estimated from
top of hump
Figure 3.4
EPI of burial pipe
ng
Ra
e
Bearing
Top of pipe
D1
D2
Bottom of pipe
Free-span height
Interpolated seabed
Figure 3.5
EPI of free-spanning pipe
62
For the scoured pipes, the echoes received will be the loud (blue) echo from
the top of pipe as before and the seabed echoes shown in red. The seabed echoes
may extend some distance under the pipe due to the diffraction of the sound waves
by the pipe. In this situation, extracting the depth of exposure figures will result in
two depths, (D1 and D2) from each side of the pipe, both of which will be greater
than the pipe diameter as shown in Figure 3.5. This should indicate a free span
condition, but it appears that the pipe is still supported. This dilemma is one of the
difficulties which currently exist with conventional pipe inspection procedures.
The true free span condition shown in Figure 3.5 will produce a gap between
the echoes from the seabed and those from the top of the pipe. The dimension of this
gap will exceed the diameter of the pipe. The definition of the free span height of the
pipe is shown in Figure 3.5. It is necessary first to calculate the depth of the seabed
immediately under the centre of the pipe. This is determined by a straight-line
interpolation between the two points on the seabed (typically one pipe diameter each
side of the pipe) used for the depth of exposure measure. The free span height is then
taken as the height of the bottom of the pipe above this seabed model. This
calculation will use the design pipe diameter subtracted from the top of pipe depth to
provide a bottom of pipe depth.
Figure 3.6
Pipe DTM generated from echoes measurement
63
As the survey progresses along the pipe route, the large quantities of data
returned from the adjacent echo traces will be formed into a high-resolution Digital
Terrain Model (DTM) to gain more information about the likely pipe position as
shown in Figure 3.6. This DTM greatly helps in studying the position of the pipeline
(e.g., pipeline displacement, buckling analysis, etc). Besides that, pipeline engineers
can also study the occurrences of free-span along the pipeline.
However, it should be noted that the pipe DTM is limited when dealing with
the buried pipeline, especially when the pipeline is buried deeper (as illustrated in
Figure 3.4). Moreover, this DTM could not be used to study the potential external
corrosion for a submarine pipeline. This is because no matter how accurate the DTM
can be generated (Figure 3.6), it is just a computer-simulated model and did not
represent the actual condition of that particular pipeline.
3.4.2
Side Scan Sonar (SSS)
To overcome the limitations of multibeam technology, Side Scan Sonar
(SSS) has been introduced with the capabilities of image-scanning for seabed
features. By definition, a sonar system is one which uses acoustic energy for remote
sensing, observation or communication underwater. Thus sonar is a branch of
applied acoustics which uses water as the propagating medium. Sonar systems
comprise a source of acoustic energy, a path over which the energy propagates a
receiver and a display unit.
An ‘active’ side-scan sonar is a well defined signal pulse that transmitted the
signal insonifies a swept volume of water from the transducer. If there is any
acoustic scattering medium within the volume will reflect part of the incident
acoustic energy back to the towed transducer (Rainbow, et al, 1985). The reflected
64
acoustic signal are detected by the transducer, processed and displayed as
amplitudes on some form of graphic recorder. By moving from point to point, a
form of relief map or sonograph of the target area can be formed.
Generally, SSS holds the similar measurement concept with multibeam
technology. In common practice, SSS survey can be divided into two techniques,
that are single side-scan and dual side-scan. As shown in Figure 3.7, the single sidescan will scan only one specified side from the towfish, and dual side-scan produce
the seabed image for both side. However, the scanned image of single side-scan
would be clearer as it is produced in larger scale.
Towfish
Scanned coverage
Figure 3.7
Typical SSS configurations and its result: Single Side Scan (left) and
Dual Side Scan (right)
According to Rainbow, et al, (1985), pipeline inspection surveys by SSS are
used (1) to obtain a rapid overview of the pipeline and the immediate emplacement
zone or corridor; (2) to identify and locate any significant changes in the seabed
geomorphology, such as evidence of current action and active erosion or scouring
along the pipeline; and (3) to identify and locate evidence of local shipping activity
such as seabed marks or scars caused by trawl boards or anchor drag.
65
3.4.3
Remotely Operated Vehicle (ROV)
Figure 3.8
ROV surveying
Source: Huseby and Gundersen, 2005
Previously, submarine EPI equipments are produce the bathymetric datasets
or the seafloor imageries as discussed in section 3.41 & 3.4.2, which may not be able
to represent the actual condition of the pipeline. However, with the latest electronic
technology, scientists have developed a submersible to obtain pipe information with
the degree of accuracy needed for detailed analysis and planning of remedial action.
Remotely Operated Vehicle (ROV) is one of such ROV as illustrated in Figure 3.8.
Basically, ROV is a submersible combination with various components (as
illustrates in Figure 3.9) to success an EPI operation (Corbishley and Luynenburg,
1985). These components include: (1) long-base positioning system for locating the
submersible relative to a pre-positioned transponder adjacent to the pipeline; (2) a
short-base navigation system to provide for accurate positioning of the submersible
relative to the support vessel; (3) an accurate pressure-sensitive depth measuring
device; (4) a pipe tracker to enable the submersible to follow a buried pipeline, even
with 3 metres cover; (5) a continuous seabed profiler; (6) sector scanning trench
profile to provide cross-sections of the pipe and trench; and (7) optical equipment
such as video system and still-photography to facilitate to provision of permanent
records, and hence an assessment of overall span condition
66
Figure 3.9
Common configurations of a ROV
Source: SEATREK Org., 2005
Unlike the multibeam and SSS surveys, ROV surveys not only provide the
information of pipe position, water depth and pipe imageries, but also included the
Video Tracking System (VTS) that enable pipeline engineers to inspect their
pipeline in continuous and clearer features. With VTS, pipeline engineers can now
easily analyse the condition of a submarine pipeline (Figure 3.10), such as pipeline
profile extraction, free-span analysis, potential corrosion or leakage detection and so
forth. Figure 3.11 illustrates some of the EPI results on different real situations with
VTS.
67
Figure 3.10
Video Tracking Systems (VTS)
Source: SSP&T Ltd., 2005
Figure 3.11
a
b
c
d
Some results of the pipeline edge extraction algorithm on different
real situations : (a) pipeline on sand and seaweed, (b) pipeline on seaweed, (c)
pipeline partially covered by sand. (d) pipeline with a border completely covered by
sand. (source: Foresti and Gentili, 2000)
68
3.5 Pipeline Protection Methods
To minimize potential risks of damage to the pipeline, the environmental
hazards must first be identified in the specific site, then measures be taken to protect
the pipeline from these hazards. The protection methods include trenching the
pipeline below the seabed; anchoring of the pipeline; increased concrete coating;
installation of supports installation of load/protection mattresses; gravel dumping
and strengthening the pipeline (as shown in Figure 3.12. & Table 3.4).
Table 3.4
Protection method of submarine pipeline
Summaries from Melegari &Bressan, 1990
To support free spans of cover exposed pipelines. It is very often the simplest
and most cost effective method for depths down to 50m.
To be installed by hyperbaric divers under normal environmental and technical
Grouting
conditions, is based on a well proven flexible fabric which is constructed to form
(support)
bags or mattresses when filled with cement grout.
The fabric formwork used for the installation of grouted supports can also be
Grouting
(protection) tailored in the form of saddlebag to provide additional weight coating or
protection over the pipeline
Is used to reduce the length of free spans with variable bottom clearance. It is
Jack-ups
(mechanical suitable for installation at depth exceeding 500m with the assistance of a D. P.
vessel or a manned submarine.
supports)
Widely used for correcting free spans. However, the backfill material must
Gravel
remain in place during the different environmental conditions that may occur.
dumping
(backfilling) Also, it must not prevent fishing with bottom towed fishing gears in the area.
Suitable for the protection/ stabilisation of exposed sections of pipelines in deep
Bitumen
water. The bituminous filler combined with dense aggregates is used to provide
mattresses
weight flexibility and long lasting protection to the pipeline.
Suitable for the uneven seabed profile, or multiple applications in remedial
Concrete
works on the pipelines or scour prevention.
mattresses
Can be easily installed by divers or remotely controlled vehicles. It is used to
Concrete
ensure additional weight coating and protection on the pipeline and to protect it
saddles
from local mechanical damage.
It is depending on the seabed soil types, mostly implemented in the critical areas
Anchoring
of pipeline (e.g. a shore approach), to eliminate longitudinal or lateral
systems
movements.
Is used to overcome the drawbacks of scour protection techniques. It is based on
Artificial
building stable mass fibre reinforced banks, to apply viscous drag which reduces
seaweed
the current velocity so that particles of sands are deposited into the mat.
mats
Sandbags
69
Sanbagging
Grouting (Support)
Jack ups
Grouting (protection)
Concrete Mattress
Figure 3.12
Bitumen Mattress
Artificial Seaweed Met
Concrete Saddle
Protection Methods of Submarine Pipeline
Edited from Melegari &Bressan, 1990
In the choice and the application of the most adequate and effective
protection method, water depth plays a relevant role as a determining factor. There
are methods suitable for installation and actuation by a manipulator arm operated
from inside a submarine or from the surface on a Remotely Operated Vehicle
(ROV), whilst there are other methods which require the hyperbaric diver and can be
actuated by the direct intervention of the human hand only. Some protection
methods, on the other hand, can be put into action in more than one way depending
upon the water depth and whether the human hand or a remotely controlled work
system is used. Definitely, the different installation system and procedure has an
economical impact basically dependent on the implementation of man-in-the-sea
techniques (Melegari & Bressan, 1990).
70
3.6
GIS in Pipeline Inspection
The advanced inspections technologies as described in earlier sections have
been proven to significantly improve the quality of offshore structures assessment
operation. A consequence of these advanced technologies is producing the survey
datasets in their separate and unique formats. The integrity management of these
datasets has become the nightmare to the industry. Data integration is a critical
process in an Integrity Management Plan (IMP), and GIS has already proven itself
as a key-element to successfully manage the data necessary for a Submarine Pipeline
Integrity Management (SPIM).
3.6.1
IPI with GIS
The Pemex Refinacion’s pipeline system in the Valley of Mexico consisting
of 11 lines, NPS 8 to 16 was surveyed with the in-line metal loss inspection tools in
1998. However, locating the corrosion defects in the field was very difficult, as there
were several lines running in the same right-of-way and crossing each other at
various locations (Czyz, et al, 2000). The accurate location of features requiring
excavation is important as to avoid pipeline disruption. This has created a need of
integration between ILI Survey with a high accuracy geographical-oriented
information system, that is GIS.
As to overcome this problem, BJ Pipeline Inspection Services used the
GEOPIG technology to perform inertial and caliper survey for the same pipelines in
year 1999, in order to obtain continuous coordinates of pipe centerline, as well as to
detect and measure pipe features and anomalies (e.g., girth weld, dents, ovalities,
wall thickness, bending strain and curvature radius and orientation). The metal loss
features detected in the previous corrosion surveys were integrated into the pipeline
71
database after correlating the weld logs from the corrosion and inertial surveys
(Czyz, et al, 2000).
All these IPI survey datasets were then combined with the digital maps to
create a single GIS system, called Sistemas De Informacion Geographica, S.A.
(SIGSA). Each map was created at a 1:5000 scale by rectifying and digitizing aerial
photographs. The digital images were then coded with attribute information using
ArcInfo that specified all landmarks, street names, bodies of water and political
boundaries.
Figure 3.13
Tracking pig with GIS
Source: Czyz et al, 2000
With all data being geographically referenced, relationships between the data
are more apparent and the data itself becomes more valuable. The GIS gives the
ability to create detailed maps, query data for effective solutions, visualize scenarios,
and make complex problems easier. As shown in Figure 3.13, pipeline inspectors
can now retrieve the absolute position of pipelines, its features and even generating
the relevant 3D model, while displaying its relative position to each other as well as
72
to the landmarks by using SIGSA. Obviously, this would greatly help in proper
identification of lines, accurate location of pipeline features and easy management of
various pipeline data.
Figure 3.14
IPI application with MapObjects
Source: Porter and Parsons, 2000
Meanwhile, Porter and Parsons (2000), constructed numerous map and IPI
datasets in a synchronized application framework with ESRI-MapObjectsTM (Figure
3.14). This approach provides a highly visual, multi-perspective presentation to
assist in identification, location, and prioritization of potential pipeline anomalies.
With the integration of spatial and attribute information via a GIS framework, a
more comprehensive interface to risk assessment systems can be provided. This
facilitates the most efficient and effective means to address pipeline operational
safety.
73
3.6.2 EPI with GIS
A number of efforts had been made in order to integrate the VTS with GIS
technology. Recently, Veisze (2005). carried out a study to hot-linked the videocaptured images of ROV surveys in ArcView via UTC (Figure 3.15a). Meanwhile,
CEOM and Regione Sicilia developed a GIS application called “ArcheoEgadi”
(Figure 3.15b), during a project carried out to verify the possibility of using
electroacoustic and magnetometric equipments for marine archaeological research.
(A)
(B)
Figure 3.15
GIS Applications for EPI
Source: Veisze,2005; and Laluna et al, 2004
According to Laluna et al, (2004), “ArcheoEgadi” GIS was used to produce
thematic charts, 3D elaboration, video sequences about the geomorphologic,
stratigraphic, bathymetric and magnetic characteristics of the Egadi Islands area
(Figure 3.15b). In other words, this application can also be used in submarine
pipeline inspection as it has been customized to integrate with ROV datasets
Besides that, MAPIX Technologies Ltd. has developed a “Pipeline
Inspector” application with ESRI-ArcGIS software, named “VideoDRS”, to manage
all survey information from pipeline route, as-laid, and inspection surveys. With a
simple GUI (Graphical User Interface), VideoDRS enable pipeline engineers to
74
directly access the inspection data, reports, video, CAD and documents (Figure
3.16). The application removes the need to store thousands of videotapes in a
warehouse or use dedicated facilities to review ROV inspection video. Snapshot can
be extracted directly from the raw video and reporting is made more efficient, by
generating them at a touch of a button (See Chatper 5, section 5.3 for complete
illustration of VideoDRS).
Figure 3.16
3.7
EPI with VideoDRS
Summary
To ensure the safety and operational efficiency is not compromised, the
management of submarine pipelines is both a legal and essential requirement. The
data associated with a submarine pipeline (e.g. engineering, hydrographic or
inspection records) must be easily accessible to ensure decisions can be made
effectively without delay.
75
This data however is supplied to the engineer by different contractors in
many different formats, throughout the lifetime of the Asset, making the task of data
management increasingly more onerous. A new approach to Asset Integrity
Management (AIM) utilizes the fact that the common denominator for the majority
of the submarine pipeline data is the geographical position component associated
with each dataset. Utilizing this component to manage the datasets within a GIS has
many benefits and additionally provides a new dimension to the analysis of
submarine pipeline information. In short, GIS technology can enhance, or even add
value to the data collected from submarine pipeline inspection surveys, by providing
the ability to view, analyse and chart data from many different sources using a single
geographical viewer.
76
CHAPTER 4
RESEARCH METHODOLOGY
4.1
Introduction
This Chapter presented the methodology of this study which can generally be
divided into five parts as shown in Figure 1.5 (see Chapter 1, section 1.6). The first
part of this study covers the preliminary works such as assessment of the research
problem; research objectives, research scopes identification; and literature review of
the relevant studies. The second part of this study accounts for system design which
consist the conceptual design, logical design and physical design of the system.
Following that, the third step is system development by using ArcGIS-ArcInfo 8.3.
During the fourth phase of this study, the reliability of the developed system
would be carefully evaluated, this include (1) the application of pipeline routing with
spatial analysis; and (2) simultaneously access multiple channels of pipeline
inspection video in ArcGIS-ArcMap according to its geographic features. Eventually,
the fifth step is to compile the research documentation for future reference.
77
4.2
Phase I-Preliminary Works
To ensure the practicalities of this study, some preliminary works had been
carried out in the earliest stage, such as need assessment analysis, research purposes
identification, research objectives and scopes specification (Figure 4.1). To achieve
these tasks, require (1) overall examination of the relevant issues (e.g., submarine
pipeline routing considerations and regulations, technologies of pipeline inspection,
GIS applications for routing design and DVS integration); (2) cautiously evaluate the
capabilities and performance of the necessary tools of this study (desktop, scanner,
software and its extensions as described in Table 1.1 in Chapter 1); (3) seeking for
support from the relevant organizations (e.g. oil & gas companies, offshore
engineering firms and GIS software vendor & other relevant consultancy companies);
and (4) ensure the accessibility of the required datasets.
Start
Literature Review
(e.g. Conference, meeting, journal etc)
Research Specification
(e.g. Objectives & scopes)
If that is not
support, find
other supplier
or minimize
the research
scopes
Research Support
(e.g. Consultancy, data & tools)
Research Preparation
(e.g. Data & Tools)
No
Enough?
Yes
Phase
II
Figure 4.1:
Flow diagram of preliminary works
78
These assignments had been used as the guideline for this study. For example,
the determination of the required tools and datasets are interconnected with the
objectives of this study. Additionally, the scopes of this study are defined according to
the accessible supports (e.g., tools, data, advise and so forth) within the research
period.
As the result, various datasets have been collected as outlined in Table 1.2 (see
Chapter 1, section 1.5). Petroliam National Barhad (PETRONAS) agreed to release 3
pipeline survey reports, which compiled the dataset of bathymetry survey, Side-Scan
Sonar (SSS), sub-bottom profiler, gravity survey and so forth. Besides that, MAPIX
Technologies Ltd supplies the DVS files and the relevant software. Dr. Sofia Caires,
the scientist under contract from the Meteorological Service of Canada (MSC),
provides the monthly oceanographic dataset (e.g., significant wave height, its period
and direction) for the selected study area from year 1960 to 2000.
4.3
Phase II -System Design
Although various datasets have been collected from the preliminary works,
most of these datasets are stored in its unique and different formats. For example,
Petronas National Berhad has compiled the survey reports in PDF formats; MAPIX
Technologies Ltd. supplies the DVT files in PKT formats; and the oceanographic
datasets from Dr. Sofia Caires are in TXT format.
These datasets are in separate and unique formats and could not be directly
used in this study. Hence, a database system has to be created to integrate, manipulate
and analyse these datasets. To develop such a database system, an appropriate system
design should be carried out as shown in Figure 4.2.
79
Phase
I
Conceptual Design
No
Check
Yes
Logical Design
No
Check
Yes
Physical Design
No
Check
Yes
Phase
IT
Figure 4.2:
Flow diagram of system design
This section presents the methodology of GIS system design concerns mainly
on the design of Geodatabase. According to Elmasri and Navathe (2000), database
system is the information system planning activity where the contents of the intended
database are identified and described. Database design is usually divided into three
major activities, that are: (1) conceptual data modeling: identify data content and
describe data at an abstract, or conceptual, level; (2) logical database design:
translation of the conceptual database design into the data model of a specific
software system; and (3) physical design: representation of the data model in the
schema of the software.
80
4.3.1
Conceptual Design
The purpose of the conceptual data modeling process is to prepare an
unambiguous and rigorous description of the data to be included in the database in a
form that: (1) is understandable by the proposed users of the database or system; and
(2) is sufficiently structured for a programmer or analyst to design the data files and
implement data processing routines to operate on the data. The emphasis is on the
communication between the user and the programmer/analyst; or review and
verification of the data model and database design by both user and analyst (Zorica
and Jeffrey, 1999).
The key task in conceptual design is to precisely define the set of objects of
interest and to identify the relationships between them in the ‘Entity-Relationship
(E-R) Diagrams’ (Zeiler, 1999). The process of constructing an E-R diagram
uncovers many inconsistencies or contradictions in the definition of entities,
relationships, and attributes. Many of these are resolved as the initial E-R diagram is
constructed while others are resolved by performing a series of transformations on the
diagram after its initial construction (Zorica and Jeffrey, 1999). The standard E-R
symbology are summarized in Table 4.1
The final E-R diagram should be totally free from definitional inconsistencies
and contradictions. If properly constructed, an E-R diagram can be directly converted
to the logical and physical database schema of the relational, hierarchical or network
type database for implementation. In this study, the entities of interest are the
existence pipelines & cables, water depth, wave height, soil properties, offshore
platform, fisheries & coral areas, and others. Thus, the appropriate relationships of
these objects would be represented in terms of “Installed in”, “Located at”, “Consist
of”, “Connected to” and “Distance from” as shown in Figure 4.3.
81
Table 4.1:
Spatial E-R model symbology
Entity
Relationship
Attribute
Regular Object Name
Name
Type
G
T
Topology Indicator
XY Coordinate Indicator
Associated Spatial
Object Type
Spatial
Descriptive
Common GIS
E-R Model
Relationship
Verbs
Implementation
Symbol
Connectivity
Connect, link
Topology
Contiguity
Adjacent,
abutt
Topology
Containment
Contained,
containing,
within
X, Y coordinates.
operation
Proximity
Closest,
nearest
X, Y coordinates.
operation
Coincidence
Coincident,
Coterminous
X, Y coordinates.
operation
Soil
G
T
Length
Polygon
G
Obstructions
Types
Types
G
T
Types
Pipeline
Polyline
Diameter
Size
Point
Owner
Length
T
Consist
G
G
T
T
Connected
to
Size
etc
Conceptual model
Length
Polygon
Coral_Area
Located at
Point
ID
T
Water_Depth
Depth
Installed
in
G
Platform
Point
Figure 4.3:
Types
Connected
to
Types
Owner
etc
Point
G
Stn_Ocean
Wave Length
T
Length
Wave Period
Wave Direction
T
Wave Height
Types
G
Cable
Polyline
Owner
82
83
4.3.2
Logical Design
Table 4.2:
Basic elements of logical data model
Logical elements
Objects
Attribute
Class
Database elements
Row
Column, Field
Table
Table 4.2 shows the basic elements of the logical data model and their
corresponding database elements. A logical data model is an abstraction of the objects
that GIS administrators encounter in a particular application. This abstraction is
converted into database elements. An object represents an entity such as a district, lot,
or road. An object is stored as a row. An object has a set of attributes. Attributes
characterize qualities of an object, such as its name, a measure, a classification, or an
identifier (key) to another object. Attributes are stored in a database in columns
(fields).
A class is a set of similar objects. Each object in a class has the same set of
attributes. A class is stored in a database as a table. The rows and columns in table
form 2D (Two-Dimensional) matrix. Building a logical model is an iterative process
and is an art that is acquired through experience. There is no single ‘correct’ model,
but there are good models and bad models. It is difficult to determine precisely when a
model is correct and complete, Zeiler (1999) has suggested an indication to identify
the accuracy of a logical model, that is when:
™
the logical data model represent all data without duplication;
™
the logical data model support an organization’s business rules; and
™
the logical model accommodate different views of data for distinct groups of
users.
84
4.3.3
Physical Design
A physical database model is built from the logical model by using the
database administration tools to define the database schema and create new database
ready for data transfer and entry (Zeiler, 1999). As shown in Figure 4.4, the physical
design involves the actual creation of the geodatabase tables from the abstract features
defined in the conceptual or logical design (as described earlier in section 4.3.1 and
4.3.2).
Block
Pipeline
Block
Platform
Logical Data Model
Figure 4.4:
Platform
No
Name
Name
Block
1
Bk-1
A
Bk-1
Database Implementation of Physical Design
Implementation of physical design
Ideally, the physical design involves the development of a geodatabase
template that is a skeleton of the final geodatabase. Every feature dataset, feature
class, and attributes will be defined and created in this template, so the actual data
layers can be placed into the geodatabase. Generally, ArcGIS 8x offers 3 techniques
to create a geodatabase physical design, that are:
™ migrating existing coverage/shapefile data into the geodatabase
™ creating a new geodatabase from scratch using ArcGIS-ArcCatalog
™ use Unified Modeling Language (UML) and Computer-Aided Software
Engineering (CASE) tools
85
In this study, all the collected data have been digitized into series of shapefiles,
hence the first method has been selected to use ‘wizard’ GUI in ArcGIS-ArcToolbox
to convert these shapefiles into a geodatabase (Figure 4.5). ArcGIS-ArcToolbox
offers series of functions to convert various file format into a geodatabase, such as
CAD, coverage, shapefile, Dbase, Raster images and so forth. Beside that, the ‘Batch’
function as shown in the red circle in Figure 4.5, can be used to convert multiple files
together into a geodatabase.
Before
After
Figure 4.5:
ArcToolbox migration wizards
86
4.4
Phase III - System Development
Figure 4.6 represents the workflow of system development .In general, the key
task of system development is to produce an integration information system for all the
collected datasets, and to proceed the relevant analysis for submarine pipeline routing
and inspection.
Section 4.4.1 attempts to illustrate the processes of format conversion for the
collected datasets. The procedures of map digitizing & editing are discussed in section
4.4.2 followed by the methodology of geodatabase development in section 4.4.3. The
programming tasks with VBA (Visual Basic for Application) in this study, such as the
development of wave and hydrodynamic calculator, are in section 4.4.4. At the end of
system development, some customization works (see section 4.4.5) had been carried
out to develop the Graphic User Interface (GUI) as well as evaluate the reliability of
the developed programs.
Figure 4.6:
Flow diagram of system development
87
4.4.1
Format Conversion
Figure 4.7:
Methodology of format conversion
As discussed earlier, various dataset had been collected in their separate and
unique formats (e.g., *.pdf, *.txt, *.pkt and so forth) and could not be directly used in
this study. Hence, the proper conversion of these formats must be carried out as
shown in Figure 4.7. The survey reports which were collected from Petroliam
National Berhad (PETRONAS) have been converted from PDF format to series of
raster images (*.tif) by using Adobe Acrobat Professional v6.0. Meanwhile,
Microsoft Excel has been used to convert and edit the oceanographic datasets from
TXT format into DBF files. On the other hand, the DVS files provided by MAPIX
Technologies Pte. Ltd. will be processed into geodatabase features (*.mdb) by using
the extension of VideoDRS (see Chapter 5, section 5.3.1 for more details).
88
4.4.2
Map Digitizing & Editing
Figure 4.8 shows the procedures of map digitizing and editing in this study.
The survey reports have been digitized by using conventional ‘on-screen digitizing’
method, shown at the left-hand side of Figure 4.8. Several shapefiles (*.shp) have
been created from the survey report, such as the feature of existing pipelines, cables,
sounding points, soil samples, offshore platforms and other seabed feature &
obstructions. While Table 4.3 summarise the RMS (Root Mean Square) error of the
georefencing works.
Figure 4.8:
Methodology of map digitizing & editing
89
The oceanographic datasets (in DBF format) can be directly ‘add-event’ into
ArcMap according to its X & Y coordinates. After those data are exported into
shapefiles format, the operation of Spatial Analyst could be proceeded by using
Geostatistical Analyst. In this study, the method of “Kriging” (Table 4.4) has been
selected to spatially interpolate the measured wave height and its direction to the
unmeasured area. Figure 4.9 shows the sample results of signification wave height,
wave period and its direction.
Table 4.3:
Map
Sheet 1
Sheet 2
Sheet 3
Sheet 4
Sheet 5
Sheet 6
Sheet 7
Sheet 8
Sheet 9
Sheet 10
Sheet 11
Sheet 12
Sheet 13
Sheet 14
Sheet 15
Sheet 16
Sheet 17
Sheet 18
Sheet 19
Sheet 20
Sheet 21
Sheet 22
Sheet 23
Map georeferencing accuracies
From KP
0
4
11
20
29
38
48
57
66
75
84
93
103
112
121
130
139
149
158
167
175
184
194
Average RMS
RMS Standard Deviation
To KP
4
11
20
29
38
48
57
66
75
84
93
103
112
121
130
139
149
158
167
175
184
194
202
RMS
0.08665
0.04421
0.06160
0.00977
0.08221
0.03621
0.09245
0.10214
0.08167
0.02388
0.08558
0.08668
0.05574
0.11308
0.07752
0.03206
0.11755
0.05213
0.02865
0.05948
0.06583
0.04322
0.06628
0.065417
0.028978
Deterministic
Deterministic
Deterministic
Stochastic
Stochastic
Global
Polynomial
Local
Polynomial
Radial basis
functions
Kriging
Cockriging
2
Prediction;
prediction
standard errors;
probability; and
Quantile
Prediction;
prediction
standard errors;
probability; and
Quantile
Prediction
Prediction
Prediction
Prediction
Output surface
types
Moderately
Fast/
Slowest
Moderately
Fast/
Moderate
Moderately
Fast/
Moderate
Moderately
Fast/ Slower
Fast/Fast
Computing
time/
modelling
time
Fast/Fast
Yes without
measurement
error; No with
measurement
error
Yes without
measurement
error; No with
measurement
error
Yes
No
No
Yes
Exact
Interpolator
Flexible and automatic
with some parameter
decision
Very flexible; allows
assessment of spatial
autocorrelation can
obtain prediction
standard error; many
parameter decisions
Very flexible; can use
information in multiple
datasets; allows
assessment of spatial
cross-correlation; many
parameter decision
More parameter decision
Few parameter decisions
Few parameter decisions
Advantages
Source: Johnston, et al. (2001)
Need to make many decisions
on transformations, trends,
models parameters, and
neightborhoods
Need to make many decisions
on transformations, trends,
models parameters, and
neightborhoods
No assessment of prediction
errors; may be too automatic
No assessment of prediction
errors; produces ‘bulls eyes’
around data locations
No assessment of prediction
errors; may be too smooth;
edge points have a large
influence
No assessment of prediction
errors; may be too automatic
Disadvantages
Comparison of spatial interpolation methods
Data comes from a
stationary stochastic
process and some
methods require that
the data comes from
a normal distribution
Data comes from a
stationary stochastic
process and some
methods require that
the data comes from
a normal distribution
none
None
None
None
Assumption
Assume that all methods are predicting a smooth surface from noisy data
Computing time is computer-processing time to create surface. Modelling time includes user-processing time to make decision on model parameters and search Neighbourhoods
Deterministic
IDW
1
Status
Method
Table 4.4:
90
91
Figure 4.9:
Oceanographic maps for January 1960: Significant wave height (top);
Average wave period (centre); and Average wave direction (bottom)
92
4.4.3
Geodatabase Development
Figure 4.10: Methodology of geodatabase development
As soon as the digitizing works are completed, a geodatabase is created as
designed previously, by using ArcGIS-ArcCatalog and the extension of VideoDRS
(for the DVT Files). However, note that not all the digitized shapefiles are used to
develop the geodatabase. The soil samples had been exported to RockWorks 2004 for
sub-surface modelling purpose (see Chapter 5, section 5.2.4. page for more detail) by
using Microsoft Excel (left-hand side of Figure 4.10). Besides that, the interpolated
wave height and its period had been summarised to compute its serve condition during
the study period (1960-2001).
93
4.4.4
Programming
NO
OK
NO
OK
Figure 4.11: Programming flow
In order to achieve the research objectives as stated in Chapter 1, several
programs have been develop with VBA, such as Wave Calculator, Hydrodynamic
Calculator, security protection and so forth.
Wave Calculator (see Figure5.13 in Chapter 5) is the program which is used
to compute wave characteristics with the formulae stated in Table 2.4, such as to
compute wave length, wave celerity, wave velocity, subsurface pressure and wave
particle velocity, accelerations & displacement for horizontal and vertical axis. On the
other hand, Hydrodynamic Calculator (see Figure5.13 in Chapter 5) is the program to
analyse the hydrodynamic forces toward the submarine pipeline, such as drag force,
lift force and inertia force. Besides that, Hydrodynamic Calculator also includes the
computation of requested submerged weight for the pipeline based on the
hydrodynamic forces.
94
4.4.5
System Customization
Figure 4.12: Flow diagram of system customization
For the convenience of end user, the system has been customized before it
being evaluated. This covers four primary tasks, that are (1) to ensure the performance
of Wave Calculator, Hydrodynamic Calculator by using part of the data or the
simulated data; (2) to create the Graphic User Interface (GUI) for each program; (3)
set the administration code for the system to ensure its security; and (4) customized
the visible scale of each dataset (layer) as well as the linkage of each feature.
95
4.5
Phase IV -System Evaluation
After system development, the reliability of the developed system would be
carefully evaluated during the fourth phase of this study, this includes (1) the
application of pipeline routing with spatial analysis; and (2) simultaneously access
multiple channels of pipeline inspection video in ArcGIS-ArcMap according to its
geographic features.
The routing analysis of submarine pipeline with GIS technology would be
discussed throughout Chapter 5. In section 5.2, not only the developed programs are
being tested, the capabilities of Spatial Analyst, Geostatistical Analyst and 3D
Analyst for submarine pipeline routing design are carefully evaluated. Besides that,
Chapter 5, section 5.3 focuses mainly on the evaluation of GIS technology in
submarine pipeline inspection. In other words, section 5.3 attempts to elaborate the
integration result of DVS & GIS technology. Besides that, the functionalities of
VideoDRS are demonstrated.
4.6
Phase V -Research Documentation
As for the reference of future campaign, all the research documentation has
been compiled into a thesis report, that consists the research description (Chapter 1),
literature review (Chapter 2 & 3), research methodology (Chapter 4), research results
(Chapter 5), research remarks and some recommendations for future studies (Chapter
6).
96
4.7
Summary
Various datasets has been collected from the relevant organizations to conduct
this study. However, these datasets are stored in several formats and hence the proper
format conversion is requested. Meanwhile, an appropriate geodatabase has to be
developed in order to efficiently manipulate these datasets.
To do so, a conceptual database model has been designed to precisely define
the relationships between every entity of interest. Sequentially, logical model design
is then carried out to translate the conceptual database design into the data model of a
specific software system; and physical design to represent the data model in the
schema of the software is carried out.
Besides that, some customization has been made to achieve the specified
objectives in this study. Some programming scripts have been written to compute the
wave characteristics as well as the hydrodynamic forces.
97
CHAPTER 5
RESULT AND ANALYSIS
5.1
Introduction
Submarine pipeline routing and inspection is a complicated business. All
factors must be taken into consideration to ensure the maximum safety to the
pipeline during its operational lifetime. As discussed in Chapter 2 & 3, submarine
pipeline routing design requires various tools to prudently analyse the condition of
the pipeline under hydrodynamic stability, soils liquefaction, seabed irregularities,
vortex-induced oscillations and so forth.
With the assistance of GIS technology, this chapter attempts to put all the
theories in Chapter 2 & 3 into practice. This Chapter elaborates the GIS application
in submarine pipeline routing from SpringField platform to AutumnField platform.
Besides that, this Chapter prudently discusses implementation of GIS in DVS data
management, that is to simultaneously record multiple channels of video into a
geodatabase and review them synchronously according to its geographic features.
98
5.2
GIS in Submarine Pipeline Routing
The operation of submarine pipeline route reconnaissance started with
identifying potential hazards, crossings & obstructions. As discussed in Chapter 2,
the basic criteria in selecting pipeline route, particularly in unstable seabottoms,
include the following:
x
Avoid bottom obstructions or possible pipe spans which may exist along the
proposed route,
x
Avoid other pipeline crossings whenever possible,
x
Avoid anchoring areas if present,
x
Minimize pipe length in unstable seafloors and route the pipe in a relatively
more stable area, if these can be identified,
x
Avoid any mounded and depression obstructions which may cause spans to
the extent possible,
x
In mud-flow areas, minimize any soil-movement risks of damage to pipe by
routing the pipe in such a way that it runs in the same directions as the mud
flow. This can be accomplished by having the pipeline route in a direction
perpendicular to the bottom depth contours.
Other factors may also have to be considered in selecting the pipeline route,
depending on the specific site area, including bottom faults, particularly in
earthquake areas (if present), rock outcrops, fishing-trawl activities. In addition,
other considerations of selecting a pipeline route may include a study of the biologic
activities in the area, including coral reefs, environmental aspects in the area, and
economic trade-offs. This section attempts to illustrate the GIS application in
submarine pipeline routing from SpringField platform to AutumnField platform,
with considerations of hydrodynamic stability, soils liquefaction, seabed
irregularities, vortex-induced oscillations and so forth.
99
5.2.1
LCP Selection
As discussed in Chapter 2, section 2.8, GIS provides the powerful and
flexible solution for calculating the accumulated cost of travelling through the
landscape with a rich set of information from which to make decisions. Figure 5.1
illustrates the flow diagram of LCP analysis which consists 3 main steps, that are
Discrete Cost Map (DCM), Accumulated Cost Map (ACM) and Optimal Route
(OR).
Discrete Cost Map
Accumulated Cost Map
Optimal Route
Figure 5.1:
LCP methodology
DCM is to establish the relative ‘goodness’ for locating a pipeline at any grid
cell from SpringField platform to AutumnField platform. The individual map layers
are calibrated from the best to the worst conditions for submarine pipeline routing
according to various criteria. In turn, the calibrated maps are weight-averaged to
form logical groups of criteria to derive a DCM. In the second step, ACM uses a
propagating wave-front from a starting location to determine the least “cost” to
access every location from SpringField platform to AutumnField platform.
Eventually, the bowl-like nature of the ACM is exploited to determine the Optimal
Route (OR) from SpringField platform to AutumnField platform.
100
5.2.1.1 DCM Analysis
The processes to create source and cost datasets can be divided into four
steps as shown in Figure 5.2, that are (1) create or identify the source dataset
(location map of SpringField platform); (2) derive datasets to gain new information;
(3) reclassify datasets to a common scale; and (4) weighting and then combining
those datasets.
Figure 5.2:
Procedures of source and cost datasets creation
As to precisely define the routing cost, Table 5.1 summarizes the relevant
hazards as well as the minimum requirements to ensure the safety of the submarine
pipe routing from these hazardous conditions. Note that although the offshore
platforms itself may not be harmful to the submarine pipelines, the dropped objects
from the platform (due to its construction, maintenance or other accidental activities)
can strike the pipeline with sufficient force to cause damage. Hence, the common
practice is to protect the pipelines by trenching the pipelines into a depth of 3ft (or
0.9114 m) beneath the seabed within the radius of 500 ft (or 61 m to 152 m) from
the centre point of the platform (Muhlbauer, 2004).
101
From that, Figure 5.3 illustrates the procedures of cost dataset creation by
taken into account each of the hazardous condition from Table 5.1. The input
datasets are water depth, soil types, location of platform, pockmark features, coral
areas and other seabed obstructions (e.g., geologic faults, mounded or depressions
features). Based on these datasets, various information of submarine pipeline routing
design (Figure 5.4) have been generated with several geoanalytical analyses, such as
reclassification and buffering. For example, the value of water depth has been used
to generate the slope of seabed for that particular area. These datasets are then
classified into a common scale (from 1 to 10), by giving the higher values to the
more suitable attributes as shown in Table 5.2 , 5.3 and 5.4.
Table 5.1:
Hazards constraint & its requirements
Hazards Item
Geology Faulting
Pipe Safety Requirements
The pipeline should be installed as far as possible from the geology faulting.
The shorter the better if the pipeline must be installed across the geology faulting.
Fishing/Crabbing
Area
i Burial requirement is dependent on the severity for that area.
(e.g., 3 m trenching were required for TBGP and AGA-OKI pipeline in 1974)
Anchoring Area
i In most cases, burial requirements were severe (10 ft cover) for pipeline crossing
anchorage areas
i For the ship size of 60,000 tons, the anchor penetration in moraine clay is 3 m
and 7 m in mud area.
Crossings
(pipeline, cables,
etc)
i In most cases, the pipeline should be installed as far as possible from each other,
or even worse if crossing each other (e.g. The minimum safe pipeline separation
is 200 m in mud area to avoid the dragging effect by the ship size 60,000 tons).
Platform
i Pipeline must be buried into a depth of 3ft beneath the seabed within the radius of
500 ft from the centre point of the platform
Seabed Profile
As flat as possible
Coral Area
The pipeline should be installed as far as possible from the coral area
Soil
i If in mud slide area, pipe route should be selected to parallel direction of slide.
Water Depth
i Pipeline must be buried to 3ft. below the natural seabed out to a water depth
of 60.96m or 200 ft.
Others
i Burial of all valves and taps at any water depth to a minimum of 1ft coverage
(or 3ft required by USGS)
The pipeline should be installed as far as possible from any other obstruction
Note: i
Mousselli, 1981
§
Colquhoun and Thygesen, 1985
*
Muhlbauer, 2004
8 - 10
0.05 – 0.08
0.02 – 0.05
8
9
Note:
=
=
=
Coral Dist.
Pock. Dist
Obs.Dis t
0 – 0.02
5-8
0.08 – 0.11
7
0-1
3-5
0.11 – 0.14
6
10
1.5 - 3
0.14 – 0.17
5
Distance to other obstructions
Distance to pockmark features
Distance to coral areas
Medium cense silty sand
Sandy clay
Silty to very silty sand
20-50
10-20
1 – 1.5
0.17 – 0.20
4
stiff silty to very soft silty clay
0.5 - 1
0.2-0.5
Coral Dist.
(km)
0 -0.2
0.20 – 0.30
Stiff to very stiff clay
Soil types
3
Slope
(%)
0.5 - 131
0.3 – 0.5
Boundary
(km)
1 - 45
25 - 50
16 – 25
8 -16
4–8
2–4
1–2
0.5 – 1
0.1 – 0.5
0.05 – 0.1
Pock. Dist
(km)
0 – 0.05
40 - 50
30 – 40
20 – 30
10 – 20
5-10
0.1 – 5
0.05 – 1
0.3 – 0.5
0.1 – 0.3
Obs. Dist.
(km)
0 – 0.1
Discrete cost map classifications – Basic considerations
2
1
Class
Table 5.2:
50 – 60.96
Water Depth
(m)
71 - 60.96
102
103
Table 5.3:
Class
1
2
3
4
5
6
7
8
9
10
Discrete cost map classifications – Oceanographic considerations
Wave
Height
(ft)
3.79 - 3.83
3.75 - 3.79
3.71 - 3.75
3.66 - 3.71
3.62 - 3.66
3.58 - 3.62
3.54 - 3.58
3.50 - 3.54
3.45 - 3.50
3.41 - 3.45
Wave
Celerity
(ft/sec)
4.92 – 5.00
4.85 – 4.92
4.78 – 4.85
4.71 – 4.78
4.63 – 4.71
4.56 – 4.71
4.49 – 4.56
4.42 – 4.49
4.34 – 4.42
4.27 – 4.34
Group
Velocity
(ft/sec)
7.66 – 7.69
7.63 – 7.66
7.60 – 7.66
7.57 – 7.60
7.54 – 7.57
7.51 – 7.54
7.48 – 7.51
7.45 – 7.48
7.42 – 7.45
7.38 – 7.42
WP
Velocity
(ft/sec)
12.4 – 12.7
12.1 – 12.4
11.8 – 12.1
11.5 – 11.8
11.2 – 11.5
10.9 – 11.2
10.6 – 10.9
10.3 – 10.6
10.0 – 10.3
9.6 – 10.0
WP
Acce
(ft/sec2)
26.7 – 27.5
25.9 – 26.7
25.1 – 25.9
24.3 – 25.1
23.5 – 24.3
22.7 – 23.5
21.9 – 22.7
21.1 – 21.9
20.3 – 21.1
19.6 – 20.3
WP
Disp.
(ft)
5.73 – 5.83
5.62 – 5.73
5.51 – 5.62
5.40 – 5.51
5.29 – 5.40
5.18 – 5.29
5.07 – 5.18
4.96 – 5.07
4.85 – 4.96
4.74 – 4.85
Note:
Table 5.4:
Class
1
2
3
4
5
6
7
8
9
10
WP Velocity
=
Water Particle Velocity
WP Acce
=
Water Particle Accelerations
WP Disp
=
Water Particle Displacement
Sub Pres
=
Subsurface Pressure
Discrete cost map classifications – Hydrodynamic considerations
Subsurface
Pressure
157.7 – 165.7
149.7 – 157.7
141.7 – 149.7
133.7 – 141.7
125.7 – 133.7
117.7 – 125.7
109.7 – 117.7
101.7 – 109.7
93.7 – 101.7
85.7 – 93.7
Drag
Force
(Ib/ft)
1.53 – 1.63
1.43 – 1.53
1.33 – 1.43
1.23 – 1.33
1.13 – 1.23
1.03 – 1.13
0.93 – 1.03
0.83 – 0.93
0.73 – 0.83
0.62 – 0.73
Lift
Force
(Ib/ft)
1.93 – 2.06
1.79 – 1.93
1.65 – 1.79
1.51 – 1.65
1.37 – 1.51
1.23 – 1.37
1.09 – 1.23
0.95 – 1.09
0.81 – 0.95
0.67 – 0.81
Inertia
Force
(Ib/ft)
1.21 – 1.27
1.15 – 1.21
1.09 – 1.15
1.03 – 1.09
0.97 – 1.03
0.91 – 0.97
0.85 – 0.91
0.79 – 0.85
0.73 – 0.79
0.67 – 0.73
104
Sounding
Platforms
Water
Depth
Other
Obstructions
Cables
Coral
Areas
Soil Types
Modified
Seabed Slope
Distance from
Platforms
Trenching
constraints
Distance from
Obstructions
Distance from
Cables
Distance from
Coral Area
Soil Types
Constraints
Distance from
Cables
Distance from
Coral Area
Classify
Modified
Seabed Slope
Distance from
Platforms
Trenching
Constraints
Distance from
Obstructions
Soil Types
Constraints
Suitable Pipe Route
Figure 5.3:
Methodology of discrete cost map creation
As classified in Table 5.2, 5.3 and 5.4, the pipeline is aimed to be routed in
the flat seafloor to avoid the effects of seabed irregularities to the pipeline. In
addition, the pipeline should also be away from the pockmark features or other
obstructions which were detected from SSS imageries in order to minimise freespanning (as discussed in Chapter 2, section 2.6). In this study, the pipeline is
assumed to be routed on the hard seabed as to avoid the pipeline from sinking (in
this study, the geologic modelling is carried out by using RockWorks2004, see
section 5.24 for detail description). Besides that, the pipeline is assumed to be
installed in water depth less than 60.96m (or 200 ft) to minimize the burial pipeline
which will cause difficulties during inspection survey (as discussed earlier in
Chapter 3, section 3.5).
Water Depth
Legend :
Legend (m):
Legend (Degree, qC):
105
Soil Types
Legend (m):
Legend (m):
Legend (m):
Seabed Slope
Distance from
Pockmark Features
Distance from
Coral Area
Figure 5.4:
Distance from Other
Obstructions
Basic considerations for DCM
106
Note that the available datasets in this study does not cover the entire area
generated by Spatial Analyst as shown in Figure 5.5. In other words, the boundary
of available datasets should be included in LCP analysis with the heaviest influence
rate (Table 5.5) in order to exclude the ineffectual features.
Bound
ar
Figure 5.5:
y
Special consideration of reclassifications
To analyse the suitable locations of pipeline routing, the last step in DCM is
to weight and combine all these reclassified datasets according to the specific
influence rate (will be discussed in the next section).
107
5.2.1.2 ACM Analysis
To perform cost weighted distance analysis in ArcGIS8.3-ArcInfo, the
“Source” (SpringField platform) and “Cost datasets” (as described in section 5.2.1)
has been used as inputs. The Cost-Weighted Distance (CWD) is implemented in this
study, to analyse the least accumulative cost from each cell to the nearest, cheapest
source. The cost can be money, time or other preference (such as to avoids a
particular hazardous condition).
In general, CWD is similar to the “Straight-Line Distance” computation, but
instead of calculating only the actual distance from one point to another, CWD
compute the accumulative cost of travelling from each source and the cost to travel
through it. The straight line distance between two points is not necessary the best
path. Figure 5.6 shows that although the straight line between SpringField platform
and WinterField platform only approximate 161.663km, however it is across the
steepest seabed as shown in the magnified diagram of Figure 5.6.
AutumnField
SpringField
Figure 5.6:
Model of straight-line distance
108
Applying CWD will enable the pipeline engineers to specify preferences in
the input datasets (such as routing the pipeline while avoiding the steep slopes of
seabed. In this case, the steep slopes should be given a higher cost when finding a
suitable path). The “Distance” dataset created from CWD analysis is the cost raster
which identifies the cost of travelling through every cell. To create this raster, the
pipeline engineers need to identify the “cost” of installing the pipeline through each
cell. Although the cost raster is a single dataset, it is often used to represent several
criteria. In this study, soil and slope influence the installation cost. These datasets
are in different measurement systems (soil type and percent slope), thus they could
not be compared relative to one another and must be reclassified to a common scale.
The next step in producing the cost raster is to add the reclassified datasets
together. The simplest approach is to just add all these datasets together into one (as
shown previously in Figure 5.3 & 5.4). However, in most cases, some factors are
more critical compared to the others. Table 5.5 summarises the ‘influenceweighting’ of 10 models for each factor in this study. Figure 5.7 elaborates the
concept of accumulating cost raster for seabed profile and soil types with the
specific ‘influence-weighting’.
Seabed Profile
3
2
3
3
3
3
4
2
3
1.2 0.8 1.2
x (40/100)
1.2 1.2 1.2
1.6 0.8 1.2
+
Soil Types
2
4
3
2
3
3
1
2
9
0.4 0.8 0.6
x (20/100)
0.4 0.6 0.6
0.2 0.4 1.8
Figure 5.7:
Concept of cost maps accumulation
1.6
1.6
1.8
1.6
1.8
1.8
1.8
1.2
3
109
To achieve the objective of this study, twelve ‘cost’ models have been
produced as listed in Table 5.5. As discussed earlier, the collected dataset do not
completely cover the entire study area. In order to ensure the reliability of the LCP
analysis, the boundary of available datasets has been included in LCP analysis with
the heaviest weighting and convenience number (90%) to exclude the ineffectual
features which are generated by ‘Straight Line’ function. It is also noted that the first
three models (Model A, B & C) concern only the basic criteria of submarine pipeline
installation. Model A (Figure 5.8) provides the balance weighting for all basic
criteria, that is 1.67% for each factor. The influences of seabed slope and soil types
have been given a reasonable weight (2%) in Model B as shown in Figure 5.8. In
Model C, the crossing of coral site, pockmark features and other obstructions have
been given a heavier weight (2%) compared to seabed profile, soil types and water
depth constraint.
Table 5.5:
Weighting rate of LCP cost models
110
Meanwhile, Model D, E & F (see Figure 5.8) have been generated by taken
into account the wave characteristics, such as wave height, wave celerity, water
particle velocity, water particle accelerations, and water particle displacements (the
computation of wave characteristics would be discussed in detail in section 5.22).
As listed in Table 5.5, Model D divided the basic criteria and the oceanographic
considerations equally with each factor having 0.91 % of influence weighting.
Model E enhanced the rate of basic criteria up to 1.33 % and 0.4% for the
oceanographic considerations. Oppositely, Model F minimised the weighting of
basic criteria down to 0.33 % while the oceanographic considerations had been
increased up to 1.6 %.
In addition, another 3 models (Model G. H & I as shown in Figure 5.9) are
developed to consider the hydrodynamic factors, such as subsurface pressure, drag
force, inertia force and lift force (the computation of hydrodynamic analysis would
be discussed in detail in section 5.22). Model G provides the balance weighting
(0.67 %) for all criteria. Model H giving the heavier weight for the basic criteria
(0.83 %.), then oceanographic considerations (0.6 %) and finally 0.5 % for the
hydrodynamic factors. Relatively, hydrodynamic factors have been given the heavier
weight (1 %) in Model I.
The oceanographic considerations have been excluded in Model J & K
(Figure 5.9). In Model J, all the basic considerations and hydrodynamic factors are
rated equally with 1 %. Model K adjusted the basic criteria to 1.5 % while each of
the hydrodynamic factors holds only 0.25%. Rearrangement is made in Model L by
giving the heavier weight (2%) to seabed profile and soil types (2%), while other
basic criteria (1%). The hydrodynamic factors have been given weighting of 0.2 %
in Model L and the oceanographic considerations with 0.05 %, except wave celerity
which is excluded from Model L
Model D
Figure 5.8:
Leg en d :
Model C
L egen d :
L egen d :
Model B
L egen d :
Model A
L egend :
L egend :
111
Model E
Model F
Accumulated cost maps (Model A – F)
Legend :
Model J
Model K
Figure 5.9:
Model I
Legend :
Legend :
Model H
Legend :
Legend :
Model G
Legend (s):
112
Model L
Accumulated cost maps (Model G - L)
113
Although the cost-weighted distance raster has provided the information of
least accumulated cost of getting from each cell to the nearest source, it does not
include the information of “which way to go to get there?”. The “Direction” raster
provides a road map, identifying the route to take from any cell along the LCP, back
to the nearest source.
The algorithm for computing the direction raster assigns a code to each cell
that identifies which one of its neighbouring cells is on the LCP back to the nearest
source. In Figure 5.10, the value of 0 represents every cell in the cost-weighted
distance raster. Each cell is assigned a value representing the direction of the nearest,
cheapest cell on the route of the least costly path to the nearest source.
Figure 5.10: Concept of direction raster coding
For instance, in Figure 5.10, the cheapest way to get from the cell with a
value of 10.5 is to go diagonally, through the cell with a value of 5.7, to the source,
the SpringField platform. The direction algorithm assigns a value of 4 to the cell
with a value of 10.5 and 4 to the cell with a value of 5.7 because this is the direction
of the LCP back to the source from each of these cells. This process is done for all
cells in the CWD raster to produce the direction raster which provide the direction to
travel from every cell in the CWD raster back to the source.
114
5.2.1.3 Shortest Path Analysis
From the “Distance” and “Direction” datasets created from previous step, the
LCP between the “Source” (SpringField platform) and “Destination” (WinterField
platform) can be analysed by using the function of “Shortest Path” in Spatial
Analyst. The shortest path travels from the destination to the source and is
guaranteed to be the cheapest route (relative to the cost units defined by the original
cost raster). Figure 5.11 represent the LCP results of Model A to Model F, while
LCP of Model G, H, I, J, K, and L are shown as in Figure 5.12.
Generally, most of these LCPs are the same, except the LCP of Model F and
I where the LCPs are located at the eastern part of the study area. As summarised in
Table 5.6, the Route C is the shortest route (172.484 km) among all LCPs, followed
by Route E (182.335 km), Route B (183.472 km), and Route A (183.449 km).
Meanwhile, Model F and I have produced the longer LCP, that are Route F
(202.475km) and Route I (202.78 km).
Table 5.6:
Length of LCP
Route Name
2D Length
(km)
3D Length
(km)
Route A
182.409
183.449
Route B
182.38
183.472
Route C
171.351
172.484
Route D
185.462
186.976
Route E
181.235
182.335
Route F
201.553
202.475
Route G
186.073
187.965
Route H
187.314
188.68
Route I
201.266
202.78
Route J
187.814
183.502
Route K
183.076
184.104
Route L
188.589
189.832
115
Model A
Model B
Model C
Model D
Model E
Model F
Figure 5.11: Least cost path (Model A-F)
116
Model G
Model H
Model I
Model J
Model K
Model L
Figure 5.12: Least cost path (Model G - L)
117
5.2.2
Hydrodynamic Analysis
As discussed in Chapter 2, submarine pipelines are subjected to the
hydrodynamic forces (e.g., combined drag force, lift force, inertia force, etc) which
may seriously injure the pipeline during its operating lifetime. In this section, the
stability of the pipe due to these forces is carefully evaluated as illustrated in Figure
5.13.
Wave
Calculator
Hydrodynamic
Calculator
Required
Submerged
Weight
Determination
To compute wave characteristics, such as wave profile, wave
length, wave celerity, group velocity, water particle velocity,
water particle accelerations, water particle displacements and
subsurface pressure.
To compute the hydrodynamic forces (e.g. like lift force,
inertia force and drag force) based on the wave characteristics.
To evaluate the required submerged weight of the pipeline
based on the hydrodynamic forces.
Figure 5.13: Methodology of hydrodynamic analysis
To achieve the objective, two calculation programmes have been created
with VBA (Visual Basic for Application) in ArcGIS-ArcMap environment, to
simultaneously compute multiple wave and hydrodynamic parameters in point
pattern (Figure 5.14). Both of these programmes are developed based on the liner
(Airy) theory as described in Table 2.4 and hydrodynamic analysis as illustrated in
Figure 5.14.
118
DivdeoDRS
Figure 5.14: Interfaces of wave calculator & hydrodynamic calculator
Since the wave and hydrodynamic parameters are calculated in point pattern,
the high accuracy interpolation is required to forecast the wave parameters in the
entire study area. Based on the computed observation points, Geostatistical Analyst
(GA) has been used to interpolate these parameters to other unmeasured locations
within the study area. Besides that, GA which provides various Exploratory Spatial
Data Analysis (ESDA) tools have been used to evaluate its statistical properties.
According to Johnston, et al (2001), the important features of the distribution are its
central value, its spread, and its symmetry. The objective of cross-validation is to
identify the model that provides the most accurate predictions. For a model that
provides accurate predictions, the mean error should be close to 0, the Root Mean
Square (RMS) error and average standard error should be as small as possible (this
is useful when comparing models), and the RMS standardized error should be close
to 1. Table 5.7 outlined the “Cross-Validation” of each wave parameter model and
Figure 5.15, 5.16 & 5.17 show the modelling result for each of these parameters.
Note:
-
RMS
ASE
Average Standard Error
Root-Mean Square
Mean
0.00002063
-0.0000164
-0.0006571
-0.0004971
-0.001345
-0.00004211
-0.01957
-0.000657
-0.0006389
-0.002798
0.001447
0.0002736
-0.0004042
0.0002997
0.0003436
0.0001594
-0.00001145
RMS
0.001437
0.001487
0.01042
0.04511
0.02084
0.003809
1.997
0.0664
0.06578
0.1701
0.1428
0.03124
0.02843
0.02785
0.03189
0.01556
0.001036
RMS Std
Mean Std
ASE
0.001357
0.001607
0.01153
0.04871
0.02304
0.004115
2.196
0.06308
0.07326
0.168
0.1356
0.03019
0.03104
0.02647
0.03512
0.0148
0.001021
-
-
RMS Std
1.051
0.921
0.909
0.9214
0.9096
0.9211
0.9078
1.049
0.8958
0.9957
1.049
1.032
0.9125
1.05
0.907
1.049
1.009
Root-Mean Square Standardise
Mean Standardise
Mean Std
0.01391
-0.009274
-0.04864
-0.009268
-0.04995
-0.009299
-0.00697
-0.008426
-0.006817
-0.01344
0.008709
0.00758
-0.0118
0.009188
0.007611
0.008605
-0.01765
Result of Exploratory Spatial Data Analysis (ESDA)
Wave Height
Wave Period
Wave Profile
Wave Length
Wave Celerity
Group Velocity
Subsurface Pressure
Water Particle Velocity - Horizontal
Water Particle Velocity – Vertical
Water Particle Acceleration - Horizontal
Water Particle Acceleration – Vertical
Water Particle Displacement - Horizontal
Water Particle Displacement – Vertical
Hydrodynamic – Drag Force
Hydrodynamic – Lift Force
Hydrodynamic – Inertial Force
Hydrodynamic – Required Submerged Weight
Model Name
Table 5.7:
119
Wave Profile
Significant Wave Length
Wave Celerity
Figure 5.15: Wave characteristic maps- Part I
Legend (s):
Average Wave Period
Legend (m):
Legend (ft):
Significant Wave Height
Legend (m):
Legend (ft):
Legend (ft):
120
Group Velocity
Water Particle
Velocity - Vertical
Water Particle
Acceleration - Horizontal
Legend (m):
Legend (m/s 2):
Water Particle
Velocity - Horizontal
Legend (m):
Legend (ft/s):
Legend (ft/s):
Legend (m/s2):
121
Water Particle
Acceleration - Vertical
Water Particle
Displacement - Horizontal
Water Particle
Displacement - Vertical
Figure 5.16: Wave characteristic maps – Part II
Legend (Ib/ft):
B
Legend (Ib/ft):
C
D
Legend (Ib/ft):
Legend:
E
122
weight
Figure 5.17: Hydrodynamic maps: (A) Subsurface pressure; (B)Drag force; (C) Inertia force; (D) Lift force; and (E) Required submerged
A
Legend (Ib/ft):
123
5.2.3
LCP Finalization
From the LCP analysis, 12 appropriate pipe routes have been determined
based on the Accumulated Cost Maps (ACMs). However, only the best route among
these proposed LCPs would be selected to install the pipeline in the final stage. The
objective of this section is to prudently analyse each of these proposed LCPs, then
identify the best route among these LCPs.
Figure 5.18: LCP errors
As shown in Figure 5.18, some of the LCPs have not successfully achieve the
routing objectives. Few LCPs are located outside the boundary of available data and
partially crossing the coral areas, pockmark features as well as other obstructions.
For example, Figure 5.18 shows that Route F and I had not achieved the objective of
this study. This is because both of these LCPs are routed majority outside the data
boundary. In other words, these LCPs are not reliable and should not be considered
for the installation.
124
In order to precisely finalize the reliability of these LCPs, the evaluation
analysis has been carried out as shown in Figure 5.19. Various buffering are made to
the hazardous objects (e.g., coral areas, pockmark features, soil types and so forth)
and ‘clipped’ the buffering result with the LCPs, to compute the length of a particular
LCP across these harmful objects. The computed lengths are then classified by
dividing the range (maximum – minimum) with the number of classification range
(9) and select the highest value (10) as the most suitable LCP.
Compute
Length
Length
Referential
Water Depth
%
3D
Conversion
Coral
Crossings
Coral Area
Pockmark
Features
Other
Obstructions
Seabed
Irregularities
Pockmark
Crossings
Buffering
Compute
Length
%
Obstructions
Crossings
Data
Boundary
Within
Boundary
Depth
Limit
Located at >=
60.96m
Soil Types
Located at
Soil Types
Route
Finalization
Figure 5.19: Methodology of LCP evaluation
Firstly, the LCP fineness is evaluated from the perspective of data boundary
intersection. This is to compute the percentage of LCP length which is located within
the boundary of available datasets. As illustrated in Figure 5.5, the function of
‘Straight Distance’ in Spatial Analyst would generate some error to the LCP as the
available datasets has not fully covered the entire study area. As listed in Table 5.8,
Route C has the maximum length (98.61%) within the data boundary, followed by
Route A, E, J and K with 93.15% of intersection. Route L is the worst LCP (except
Route F & I) in terms of boundary intersection as only 86.69% is routed within the
boundary of available dataset. From that, the maximum range of these LCPs is
11.92% (98.61 % - 86.69%) and hence interval of classification for boundary
intersection is 1.324% after dividing the maximum range with the number of
classification range (9).
125
Table 5.8:
Route Name
LCP evaluation – Boundary intersection
Boundary Intersection
Class
Route A
93.15
6
Route B
91.59
5
Route C
98.61
10
Route D
91.59
5
Route E
93.15
6
Route F
Excluded
Route G
91.59
5
Route H
91.59
5
Route I
Note:
= Maximum value
= Minimum value
Maximum range = 11.92%
Interval of classification = 1.324%
Excluded
Route J
93.15
6
Route K
93.15
6
Route L
86.69
1
Secondly, the route profiles have been taken into consideration to analyse the
LCP perfection. To do so, the 2D and 3D distance of each LCP has been measured as
outlined in Table 5.9. The profile irregularity is then observed from the differential
between 2D and 3D distance for each LCP. According to the distance differentiation
as listed in Table 5.9, Route G is planned on the most irregular seabed profile or
crossing largest number of obstructions with 1.892km (approximate 1 %)
differentiation for 2D and 3D distance. This might be harmful as the seabed
irregularities would caused spans and bending stresses to the pipeline. Relatively,
Route K is routed through the flat seafloor with 1.023km (approximate 0.6%)
differentiation of its 2D and 3D profile.
The third evaluation is focused towards the depth constraints. As discussed
earlier in section 5.2.1.1, a submarine pipeline must be buried into a depth of 3ft
beneath the seabed within the radius of 500 ft from the centre point of the platform
(see Table 5.1). However, the submarine pipeline is assumed prefer to be installed
floating on the seabed in order to minimize the burial pipeline in this study. Table
5.10 summaries the percentage of each LCP across this specified depth limit. Route
C has been moderately planned with minimum length of 67.821km (39.3%) across
the installation depth constraint while Route L represents the worst design with
126
73.078km located across the specified depth limits. Aside from these, Route A, B, D,
E, G, H, J and K are routed with 73.049km in water depth more than 60.96m.
Table 5.9:
Route Name
LCP evaluation – Profile irregularities
2D Length
(km)
3D Length
(km)
Differential
(km)
Class
Route A
182.409
183.449
1.04
9
Route B
182.38
183.472
1.092
8
Route C
171.351
172.484
1.133
6
Route D
185.462
186.976
1.514
3
Route E
181.235
182.335
1.1
7
Route F
Excluded
Route G
186.073
187.965
1.892
1
Route H
187.314
188.68
1.366
4
Route I
Excluded
Route J
187.814
183.502
1.514
2
Route K
183.076
184.104
1.028
10
Route L
188.589
189.832
1.243
5
Meanwhile, Table 5.11 shows that most of the LCP are routed crossing three
types of soil, that are sandy clay, stiff silty to very soft silty clay, and stiff to very
stiff clay. In this study, the pipeline is assumed prefer to be routed on the hard seabed
in order to avoid the pipeline from sinking. Generally, the soil properties are mostly
the same for all LCPs. However, Route C is considered the best LCP with the most
stable soil properties, with 27.48% routed in sandy clay, 13.18 % on stiff silty to very
soft silty clay, and 59.34% stiff to very stiff clay. On the other hand, Route A, B, D,
E, G, H, J and K are routed on the poor properties of soil with sandy clay 27.35%,
stiff silty to very soft silty clay 13.12%, and stiff to very stiff clay 59.52%. Although
it is only a very small difference between the percentage of Route C and other LCPs,
this actually represents a significant value when converted to actual distance. For
example, Route C is routed 27.48 % or 47.399 km out of 172.484km in sandy clay,
while Route H is routed 27.35% or 51.604km out of 188.68km in sandy clay. In
other words, the difference of 0.13% between these LCPs represents 4.205km in
reality.
127
Table 5.10:
Route Name
LCP evaluation – Installation depth limits
Allocated in Water Depth >= 60.96m
Class
Route A
73.049
1
Route B
73.049
1
Route C
67.821
10
Route D
73.049
1
Route E
73.049
1
Route F
Excluded
Route G
73.049
1
Route H
73.049
1
Route I
Excluded
Route J
73.049
1
Route K
73.049
1
Route L
73.078
1
Note:
= Maximum value
= Minimum value
Maximum range = 2.257%
Interval of classification = 0.585%
Additionally, these LCPs have been finalized by avoiding the hazardous
features, such as the detected pockmark features, coral areas and other obstructions
from bathymetry survey. Since these features are harmful to the pipeline, it is
preferable that the purposed LCPs are safe from these features. Table 5.12 outlined
the analysis result of LCPs crossing with other obstructions which are identified from
the Side Scan Sonar (SSS) imageries. Note that all the values in bracket of each row
represent the classification value of the LCP in that particular evaluation.
Generally, less than 0.2% of the LCPs are routed across these obstruction
features. Route C achieved the minimum crossing of 0.07% while 0.17% of Route L
are routed across these obstructions. Nevertheless, the analysis of feature crossing
should not only be made based on its actual size. This is because a submarine
pipeline is typically operated for decades and hence some prevention analysis should
be considered to ensure the maximum safety to the pipeline.
128
To achieve this, various buffers had been created to assess the safety of a
LCP during pipeline operation lifetime. The final classification value for each LCP in
obstruction crossing is given according to the average value from all evaluation tests.
As shown in Table 5.12, Route C has accomplished the minimum crossing while
Route L represented the worst result for obstructions crossing with the overall
classification value of 2.5.
Table 5.11:
Route Name /
Crossing Length (%)
LCP evaluation – Soil properties
A
B
Route A
27.35
59.52
13.12
8
Route B
27.35
59.52
13.12
8
Route C
27.48
59.34
13.18
10
Route D
27.35
59.52
13.12
8
Route E
27.35
59.52
13.12
8
Route F
C
Class
Excluded
Route G
27.35
59.52
13.12
8
Route H
27.35
59.52
13.12
8
Route I
Excluded
Route J
27.35
59.52
13.12
8
Route K
27.35
59.52
13.12
8
Route L
27.45
59.48
13.07
9
Note:
A = Sandy clay
B = Stiff silty to very soft silty clay
C = Stiff to very stiff clay
Table 5.13 listed the evaluation result of LCP across coral areas. The
classification method in obstruction crossing (Table 5.12) is used for these evaluation
tests. Most of the LCP (except Route L) had not caused any impact to the coral areas.
0.016 % (approximate 3m) of Route L has been routed across the coral areas. On the
other hand, Route G is the safest LCP as 88.7% (or 21.240km) of the path are located
at least 2.5km from the existing coral areas. Route L is only slightly different
compared to other LCPs in terms of crossing coral area, i.e., 3m is a very small value
compare to the total length of Route L, that is 189.832km. However, coral areas are
always the top priority for submarine pipeline engineers to avoid in order to
minimize the environmental impact during construction. In other words, a LCP must
not be routed across any coral areas even if it is only for few metres.
129
LCP evaluation – Obstruction crossing
Table5.12:
Route Name /
Crossing Length (%)
Actual Size
(ǻ=0.1)
(C=0.02)
Buffer 5m
(ǻ=0.25)
(C=0.028)
Buffer 10m
(ǻ=0.36)
(C=0.04)
Buffer 50m
(ǻ=1.81)
(C=0.201)
Buffer 100m
(ǻ=2.14)
(C=0.238)
Buffer 500m
(ǻ=13.4)
(C=1.49)
Total
Class
(Total / 6)
Route A
0.15 (3)
0.38 (3)
0.65 (3)
4.81 (6)
9.9 (8)
80.7 (7)
30
5
Route B
0.14 (4)
0.35 (4)
0.6 (5)
4.70 (7)
9.86 (8)
79.1 (8)
36
6
Route C
0.07 (10)
0.19 (10)
0.39 (10)
4.06 (10)
10.23 (7)
89 (1)
48
8
Route D
0.14 (4)
0.35 (4)
0.59 (5)
4.66 (7)
9.58 (9)
78 (8)
37.2
6.2
Route E
0.14 (4)
0.35 (4)
0.6 (5)
4.61 (7)
9.61 (9)
79.6 (7)
36
6
Route F
Excluded
Route G
0.14 (4)
0.35 (4)
0.6 (5)
4.74 (7)
9.4 (10)
78.1 (8)
37.8
6.3
Route H
0.14 (4)
0.35 (4)
0.61 (5)
4.69 (7)
9.58 (9)
79.1 (8)
37
6.2
Route I
Excluded
Route J
0.14 (4)
0.36 (4)
0.63 (4)
4.76 (6)
9.53 (9)
80.6 (7)
34
5.7
Route K
0.14 (4)
0.36 (4)
0.63 (4)
4.76 (6)
9.74 (9)
80.6 (7)
34
5.7
Route L
0.17 (1)
0.44 (1)
0.75 (1)
5.87 (1)
11.54 (1)
75.6 (10)
25
2.5
Note:
= Maximum value
= Minimum value
ǻ = Differential (Maximum – Minimum)
LCP evaluation – Coral crossing
Table5.13:
Route Name /
Crossing Length (%)
Actual Size
C = Interval classification ( ) = Classification Value
Buffer
100m
Buffer
500m
Buffer
1000m
Buffer
1500m
Buffer
2500m
(ǻ=0.02)
(C=0.002)
Total
Class
(Total / 6)
Route A
None (10)
None (10)
1.46 (10)
4.27 (1)
6.33 (10)
11.32 (1)
42
7
Route B
None (10)
None (10)
1.46 (10)
4.27 (1)
6.33 (10)
11.32 (1)
42
7
Route C
None (10)
None (10)
1.46 (10)
4.27 (1)
6.33 (10)
11.32 (1)
42
7
Route D
None (10)
None (10)
1.46 (10)
4.27 (1)
6.33 (10)
11.32 (1)
42
7
Route E
None (10)
None (10)
1.46 (10)
4.27 (1)
6.33 (10)
11.32 (1)
42
7
Route F
Excluded
Route G
None (10)
None (10)
1.46 (10)
4.27 (1)
6.33 (10)
11.30 (10)
51
8.5
Route H
None (10)
None (10)
1.46 (10)
4.27 (1)
6.33 (10)
11.32 (1)
42
7
7
Route I
Excluded
Route J
None (10)
None (10)
1.46 (10)
4.27 (1)
6.33 (10)
11.32 (1)
42
Route K
None (10)
None (10)
1.46 (10)
4.27 (1)
6.33 (10)
11.32 (1)
42
7
Route L
0.016 (1)
0.14 (1)
1.54 (1)
4.26 (10)
6.33 (10)
11.31 (5)
30
5
Note:
= Maximum value
= Minimum value
ǻ = Differential (Maximum – Minimum)
C = Interval classification ( ) = Classification Value
Besides that, Table 5.14 represents the evaluation result of pockmark crossing
for each LCP. Table 5.14 shows that at least 0.38 % of all LCPs have been routed
across the pockmark features. Anyway, these pockmark features are just small in size
and hence would not significantly damage the pipeline. Based on the buffering
analysis, Route C has proved its perfection among all LCPs in terms of avoiding the
existing pockmark features. More the 97% of Route C has been routed 100m away
from the detected pockmark features. However, this percentage of obstruction
130
crossing is increased sharply for Route L, where at least 4.69% are across the
identified pockmark features.
Table 5.14:
Route Name /
Crossing Length (%)
Actual Size
(ǻ=0.1)
(C=0.02)
LCP evaluation – Pockmark crossing
Buffer 5m
(ǻ=0.25)
(C=0.028)
Buffer 10m
(ǻ=0.36)
(C=0.04)
Buffer 50m
(ǻ=1.81)
(C=0.201)
Buffer 100m
(ǻ=2.14)
(C=0.238)
Buffer 500m
(ǻ=13.4)
(C=1.49)
Total
Class
(Total / 6)
Route A
0.68 (3)
0.83 (3)
0.96 (3)
2.43 (4)
4.1 (4)
40.94 (7)
24
4
Route B
0.7 (2)
0.85 (2)
1 (3)
2.56 (3)
4.28 (3)
39.99 (8)
21
3.5
Route C
0.38 (10)
0.45 (10)
0.51 (10)
1.57 (10)
2.95 (10)
47.40 (1)
51
8.5
Route D
0.72 (2)
0.88 (2)
1.02 (2)
2.65 (3)
4.42 (2)
39.81 (8)
19
3.2
Route E
0.72 (2)
0.88 (2)
1.02 (2)
2.58 (3)
4.29 (3)
40.84 (7)
19
3.2
Route F
Excluded
Route G
0.72 (2)
0.88 (2)
1.02 (2)
2.65 (3)
4.42 (2)
39.64 (8)
19
3.2
Route H
0.72 (2)
0.88 (2)
1.02 (2)
2.64 (3)
4.39 (3)
39.71 (8)
20
3.3
Route I
Excluded
Route J
0.68 (3)
0.83 (3)
0.96 (3)
2.43 (4)
4.1 (4)
40.94 (7)
24
4
Route K
0.68 (3)
0.83 (3)
0.96 (3)
2.43 (4)
4.1 (4)
40.94 (7)
24
4
Route L
0.76 (1)
0.93 (1)
1.13 (1)
2.94 (1)
4.69 (1)
37.26 (10)
15
2.5
Note:
= Maximum value
= Minimum value
ǻ = Differential (Maximum – Minimum)
C = Interval classification ( ) = Classification Value
Ultimately, Table 5.15 summaries the route assessment classification for each
LCP. The best LCP can simply be identified by totalling up the classification value
from each evaluation factor. The average accumulated value of all LCPs is 37.14
points where Route L has the worst result with the lowest value of 27 points, and
Route C holds the highest score for 59.5 points. Consequently, Route C has been
selected as the final path to install the proposed pipeline from SpringField platform
to AutumnField platform as illustrated in Appendix A.
6
5
10
5
6
Route A
Route B
Route C
Route D
Route E
5
Route H
6
6
1
Route J
Route K
Route L
Route I
5
Route G
Route F
Boundary
Intersection
Route Name /
Evaluation Factor
5
10
2
4
1
7
3
6
8
9
Profile
Irregularities
1
1
1
1
1
1
1
10
1
1
9
8
8
Excluded
8
8
Excluded
8
8
10
8
8
Soil
Crossing
LCP Finalization
Depth
Depth
Limit
Table 5.15:
5
7
7
7
8.5
7
7
7
7
7
Coral
Crossing
2.5
5.7
5.7
6.2
6.3
6
6.2
8
6
5
Obstructions
Crossing
2.5
4
4
3.3
3.2
3.2
3.2
8.5
3.5
4
Pockmark
Crossing
27
40.7
32.7
33.5
31.9
37.2
32.4
59.5
37.5
39
Total
131
132
5.2.4
Subsurface Modelling
Although the soil properties have been taken into consideration during LCP
analysis (as described in section 5.2.1 and 5.2.3), it concerns only the soil types on
sea-surface. The stratigraphic model is required for the common practice of
submarine pipeline routing, in order to analyse the subsurface stability.
RockWork2004 has been selected to develop the subsurface modelling as shown in
the flow diagram in Figure 5.20. Firstly, the soil samples are entered into Microsoft
Excel
Workbook
(*.xls)
and
sequentially
imported
into
RockWork2004
environment. The map projection has been defined as Universal Transverse
Mercator (UTM), before the borehole elevation map can be produced in
RockWork2004.
Start
Input Borehole file
Form Ms. Excel (*.xls)
Define Boreholes Projection
(UTM; XYmin & XYmax)
Create Borehole Location Map
Map Ÿ Borehole Locations
Set up Stratigraphic Table
Stratigraphic Fences Modeling
Stratigraphy Ÿ Fence Ÿ Modeled
Stratigraphic Model
Stratigraphy Ÿ Model
Stratigraphic 3D Structure Maps
Stratigraphy Ÿ Structural Elevations Ÿ 3 Dimension Ÿ All Surfaces
Start
Figure 5.20: Methodology of subsurface modelling in RockWorks2004
133
After the surface map is created, edit a “Stratigraphy Table" to define the
name of soil types and the graphic pattern / color to use for each soil type. The
“Stratigraphy Table" serves as the reference library for the downhole stratigraphic
data in ASCII format. The “Stratigraphy Table” also lists each soil types’ percent fill
for the pattern (when displayed in strip logs), the formation density for volume/mass
computations, and the "G" value to be assigned for that layer in stratigraphic models
(in this study, the default setting has been made due to the data inaccessibility as
stated in Chapter I, section 1.5). Figure 5.21 shows the maps of soil types for the
entire study area. In general, the stratigraphic model can be represented either with
solid model, 3D fences, or 3D structural maps as illustrated in Appendix B.
Legend:
Stiff to very stiff clay
Firm clay
Soft clay
Stiff silty to very soft silty clay
Medium cense silty sand
Sandy clay
Silty to very silty sand
Above
Bottom
Figure 5.21: Map of soil types
134
5.3
GIS in Submarine Pipeline Inspection
As discussed earlier in Chapter 3, various tools and techniques have been
designed to directly or indirectly inspect the condition of submarine pipelines. In
practical, the petroleum industry will use any technology that is safe, cost-effective
and meets the needs of engineers for submarine pipeline inspection. A consequence
of these detailed datasets is the ever increasing data volume, with the data
management and subsequent analysis becoming more and more of an issue.
Providing the tools and methods to manage and analyse the various datasets
from an offshore survey requires a new approach. This approach should ensure that
the maximum value can be derived from the data, irrespective of data volume,
through efficient data management, archiving and simple access to data (Riemersma,
2004). The objective of this section is to elaborate the integration of DVS and GIS
for submarine pipeline inspection.
Digital video is a relatively new concept to the submarine pipeline industry,
where DVS offers a complete replacement of VHS tapes for digitally recording,
reviewing and reporting submarine pipeline inspection surveys. DVS has speeded up
the entire process and save money at the same time. In the past, many video tapes
have been recorded and once reviewed is discarded into cardboard boxes to lie in a
warehouse for eternity. This valuable information source has in the past been very
much under utilised and the introduction of DVSs should improve this situation
(Hydro INTERNATIONAL, 2004).
The aim of DVS should be to make the data acquisition, eventing, video
reviewing and reporting process simpler, cheaper and more efficient than with
current technology. This whilst also delivering significant additional benefits to the
135
end client such as ease of access, faster reporting and higher quality electronic
reports.
To attain the maximum benefit from the medium, a fully integrated approach
is required throughout the process from data acquisition to final reporting, DVS
should offer a comprehensive set of tools which automates these functions to ensure
higher productivity and reduce operator error (Evans, 2004). These functions are
include:
x
Automated video capture and archiving
x
Merging survey data and cross profiles with video data
x
Merging of video data with online or offline eventing
x
Automated data management and indexing of all data
x
Integrated eventing and video review processes
x
Automated processes for final reporting and generation of easy-to-access
electronic reports.
However, the management of these digital video files collected can become a
nightmare for all pipeline engineers. As a solution, MAPIX Technologies Ltd., has
developed VideoDRS, an extension for ESRI's ArcGIS version 8.x. VideoDRS
which operates in the ArcMap environment and is designed to manage, play-back
and review digital geo-referenced video.
VideoDRS uses the NETmc Marine Ltd toolkit to review digital georeferenced video captured using their range of video capture software and hardware.
The digital video can be multi or single channel and will additionally contain a
telemetry channel in which the position and navigation information of the camera is
stored. Video DRS uses this telemetry channel to geo-reference the video within
ArcMap (Figure 5.22).
136
Figure 5.22: Screenshot of VideoRDS
The “Telemetry” section of the “Display” contains the navigation
information stored within the video data file as shown in Figure 5.23 Video
telemetry consists of several information bits (Table 5.16) which are embedded at
regular time intervals in the digital video data. The telemetry is configured at the
start of a video survey by the online surveyor and it can only be assumed that they
have stored the correct information in the designated telemetry fields.
137
Figure 5.23: Telemetry Display with VideoDRS
Table 5.16
Field
Date
Time
Easting
Northing
Kp
Dcc
Video Time code
Telemetry contents in VideoDRS
Description
Date at which the current telemetry package was recorded.
Time at which the current telemetry package was recorded.
Easting of camera position
Northing of camera position.
Kilometre Post / Chainage of camera position.
Distance from Centreline to camera position.
Time in seconds relative to the start of the recording.
Figure 5.24 represents the procedures to operate VideoDRS in ArcGIS-ArcMap
environment. Table 5.17 illustrated part of the submarine pipeline inspection results
with VideoRDS. In general, the EPI functionalities of VideoRDS are summaried as
follows:
i.
Extract telemetry from digital video and create a polyline within an ArcGIS
Personal Geodatabase (Figure 5.24).
ii.
Extract telemetry from digital video and output to ASCII file.
iii.
Play-back Multi-channel Digital Video in *.pkt format.
iv.
Goto Video Time Code and start play-back from that point.
138
v.
Select position along video route in ArcMap and start play-back from that
point.
vi.
Display telemetry information in textual format and shown position within
ArcMap.
vii.
Capture still images of video at various resolutions and colour depths.
viii
Capture video clips for single or multiple channels
Figure 5.24:
General flow of VideoDRS operation
Port Channel
Centre Channel
Visual Examination
Side Channel
Information
Telemetry
Results of Pipeline Inspection
as soon as possible by divers or remotely controlled vehicles
KP: 20.756
Dcc: 20.1
The pipeline is dragged by fishnet and hence should be dismantled
pipeline and to protect it from local mechanical damage.
used to ensure additional weight coating and protection on the
The pipeline is broken where the additional concrete mattress is
considered.
probably caused by vessel anchoring. Additional coating should be
Northing: 6813365.53
Easting: 414730.38
Dcc: 21.37
KP: 20.751
Northing: 6813370.85
Easting: 414728.94
Dcc: 21.56
KP: 20.735
Northing: 6813386.07
Easting: 414728.51
The left-hand side (port channel) of the pipeline coating is cracked,
Additional coating should be considered.
KP: 20.643
Dcc: 18.31
Both sides of the pipeline coating show the significant crack.
Description
Northing: 6813479.59
Easting: 414733.38
Table 5.17:
139
140
5.4
Summary
The analyses results proved that GIS is explicitly designed for assembling,
manipulating and analysing georeferenced datasets. With the advancement of GIS
analytical functions, this study had successfully identified the LCP between SpringField
platform to AutumnField platform. This study has also integrated DVS datasets into
ArcGIS-ArcMap environment to simultaneously record multiple channels of inspection
video (from SummerField platform to WinterField platform), into a geodatabase and
replay them synchronously according to their geographic features.
In short, the analyses results proved that GIS is a much more valuable tool than
merely as a database and mapping platform in submarine pipeline engineering,
especially for routing design and inspection.
141
CHAPTER 6
CONCLUSION AND RECOMMENDATIONS
6.1
Conclusion
Submarine pipelines play an important role in offshore hydrocarbon
transportation. In order to ensure the maximum safety of these pipelines, large
numbers of efforts have been carried out to study the relevant issues to submarine
pipelines. As a result, various tools and techniques are used to design the routing as
well as to inspect the condition of the submarine pipelines. However, a consequence
from these tools and techniques is the ever increasing data volume, with the
management and subsequent analysis of the data becoming more and more of an
issue to the pipeline engineer. To overcome this problem, this study has
implemented GIS capabilities, as the Spatial Decision Support System (SDSS) for
submarine pipeline routing and inspection activities.
The routing design of submarine pipeline is complicated as all factors must
be taken into consideration to ensure the maximum safety to the pipeline during its
operational lifetime. However, with the advance GIS analytical functions, various
datasets have been reclassified into a common class scale according to the routing
criteria in this study. These classified datasets are then weighted and combined to
analyse the suitability or adherence to a given set of rules. As a result, the Least Cost
142
Path (LCP) for the purpose pipeline from SpringField platform to AutumnField
platform has been identified, with respect to various criteria such as hydrodynamic
stability, soils liquefaction, seabed irregularities, vortex-induced oscillations and so
on and so forth.
Besides the spatial analytical function in routing design, this study also
demonstrated the capabilities of GIS in managing submarine pipeline inspection
datasets. Through this study, GIS has been used to simultaneously review multiple
channels of inspection videos from SummerField platform to WinterField platform,
according to its geographic features in ArcGIS-ArcMap environment. In other
words, GIS offer means to gain new insights into inspection survey data where
pipeline engineers can now directly and efficiently locate the potential failure
features of a submarine pipeline while reviewing the inspection videos in
ArcGIS-ArcMap environment.
In short, GIS has proven its capabilities as a much more valuable tool than
merely as a database and mapping platform in submarine pipeline engineering
through this study. Efforts should be made so that this valuable tool could bring
maximum benefit of Asset Integrity Management (AIM) to the offshore industry.
Meanwhile, encouragement should also be made to enhance the application of GIS
into other applications in offshore engineering, such as offshore platform and
windfarm design.
143
6.2
Recommendations
Considering the results of this study and future campaign, the following
recommendations are suggested.
™ To successfully identify the LCP of a submarine pipeline, the severity of
oceanographic condition must be defined as in Figure 2.1. In this study, the
linear (Airy) wave characteristics formulae have been used to accomplish
this objective as listed in Table 2.4. The advance analysis of wave
characteristics should be considered for future studies in order to improve the
result of wave characteristics, such as nonlinear wave theories, Korteweg and
de Vries and Boussinesq wave theories, Cnoidal wave theory, Solitary wave
theory and so on and so forth.
™
As stated earlier, some assumptions have been made for the success of this
study, mainly due to the inaccessibility of the relevant datasets. For example,
RockWorks2004 has been selected to proceed the subsurface modelling in
this
study.
However,
some
information
which
are
required
by
RockWorks2004 are not available in this study and hence the typical settings
have been made (as described in Chapter 1, section 1.5). To achieve the
precise model of subsurface, all this information should be included in future
campaign. In addition, a study of subsurface modelling with GIS software
(particularly, ArcGIS) is strongly recommended in terms of completely
integrating all tasks of routing design with one system instead of using other
third party software, such as 3D Master, HydroGeo Analyst, MODFLOW,
FEFLOW, EVS and RockWorks2004 as carried out in this study.
144
™
This study has successfully develop the stratigraphic model with
RockWorks2004. However the pipeline-soil stability analyses (see Chapter
2, section 2.5, 2.6 and 2.7) are excluded due to data inaccessibility. In order
to improve the result of routing design, a study of pipeline stabilities on the
seabed or embedded in the soil is strongly recommended in future campaign.
™
In this study, all the video files that are collected during inspection survey
had been simplified by using the Packet format (*.pkt) which stores multi
channels of video and telemetry within a single file. These files are then
reviewed within ArcGIS-ArcMap environment. In other words, this study
primarily deals with the post-processing (review) integration but not the realtime integration because of the hardware inaccessibility. In further studies,
this issue should be considered to upgrade this to real-time integration of
VTS with GIS technology.
™
Various datasets of submarine pipeline inspection survey (e.g., ROV, SSS,
etc) had been successfully integrated through this study. However, it is still
limited to external pipeline inspection, as the Internal Pipeline Inspection
(IPI) datasets have been excluded from this study. As a consequence, this
study can only detect the external damage (from the DVS datasets, as shown
in Chapter 5, Table 5.17) but not the internal damages of the pipeline due to
the data inaccessibility. Although, a number of studies have been carried out
to integrate GIS with intelligent pigs (as discussed in Chapter 2, section
3.6.1), but yet, the EPI was neglected from these studies. In order to provide
the general information of submarine pipeline inspection, it is strongly
recommended that further studies should combine both types of inspection
datasets in order to assist the pipeline engineers to precisely inspect the
condition of the pipeline.
145
™
Twelve ACMs of pipeline routing design have been simulated to determine
the best LCP in this study and each of these models produce different LCP
routes (see Figure 5.8 & 5.9 in Chapter 5). Since these ACMs are just
simply assumed in this study and hence the reliability of the LCP results
might also be affected. In order to analyse the LCP precisely, efforts should
be made to study the ‘influence-rating’ of each submarine pipeline design
criteria. Muhlbauer (2004) has carried out a general survey on failure mode
rating for pipeline engineering. However, this survey was not specially made
to submarine pipeline. Furthermore, the ‘influence-rating’ of submarine
pipeline criteria may be different from a region to another. Thus, a research
on hazard-influence-rate for submarine pipeline routing from SpringField
platform to AutumnField platform is recommended to be carried out in order
to improve the reliability of this study.
™
Besides the appropriate weight model, some error are also generated during
LCP analysis in this study. The LCPs generated from Model F & I (see
Figure 5.11, 5.12 & 5.18 in Chapter 5) are routed at the eastern part of the
study area. These LCPs have not successfully achieve the routing objectives
in this study as the majority are routed outside the boundary of available
datasets. In other words, these LCPs are not reliable and should not be
considered for the installation. To overcome this problem, it is strongly
encouraged to study the cause of this error in future study so as to improve
the quality of this study.
™
Major considerations of submarine pipeline routing had been taken into
account in this study. However, there are still some analyses that had been
excluded, such as buckle analysis (Mousselli, 1981, Jensen and Pedersen,
1985; Richards, 1990); pipeline spanning problems with 3D wave analysis
(Nielsen and Gravesen, 1985) and probability of pipeline damage due to ship
anchoring/grounding (Bobbit and Clemence; 1987; Karal, 1987; and
Bouazza and Finlay, 1990). These analyses should be taken into account to
improve the safety of the planned pipe route.
146
™
Vortex-shedding is one the major cause of submarine pipeline failure. It
should be taken into consideration while designing the route of a submarine
pipeline and re-evaluated from time to time to ensure the safety of the
pipeline. Although, the fundamental computation of vortex-induced
oscillations (see Chapter 2, section 2.4) had been made in this study while
analysing the optimal route of the pipeline (see Chapter 5, section 5.2.1.1 &
5.2.1.2); it will certainly be beneficial if the vortex-shedding or scouring
could be simulated in detail, in order to study the submarine pipeline
displacement due to the variability of environment factors. For this reason, a
function for CFD simulation with GIS analytical capabilities should be
considered for future campaign to improve the quality of this study.
™
It is noted that the planned route of this study is simply started and end-up at
the centroid of SpringField and AutumnField platforms (as shown in
Appendix A). Typically, a submarine pipeline is connected to a riser which
extends to a surface producing facility. The selection of a particular riser
installation method is normally influenced by several factors, including water
depth, project schedule, economics and platform design (Mousselli, 1981).
Specialized analysis of the pipeline and riser are needed to ensure flexibility
of the connection and safety of the riser system, such as flanged connections,
hyperbaric welding, mechanical connectors and subsea atmospheric welding
(Stephens and Ginnard, 1985; Karal, 1987; and Pettersen, et al, 1990). To
achieve this, future studies should try to include the design of pipeline riser
to connect the submarine pipeline to surface facilities.
™
Besides the routing design and inspection, it is strongly believed that GIS
could also be beneficial to other activities in submarine pipeline engineering,
such as prediction of the pipeline lay-stress analysis (Mousselli, 1981;
Abbott , et al, 1985; and Karal, 1987); pipeline trenching evaluation
(Mousselli, 1981; and Karal, 1987) and the oil spill caused by the pipeline
leaking (Berry, 2003).
147
™
Since GIS is explicitly designed to manipulate, manage and analyse spatial
data, it should not be limited to submarine pipeline engineering but extended
to other offshore structures to minimise the risk of the industries. For
example,
to
evaluate
the
optimal
design
of
offshore
platforms
(Kokkinowrachos, 1987; Mazurkiewicz; 1987; and Mazurkiewicz &
Topolnicki, 1987) or offshore windfarm due to the environmental impact.
148
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