- develop significant theories to prevent ...

Cloud Service Model for Safety Monitoring and Assessment of Oil and Gas
Si-jian Lin 1, Xiao-lie Liao2, Wei Long 1, Jun-bi Liao 1
School of Manufacturing Science and Engineering, Sichuan University, Chengdu, China
School of Materials Science and Engineering, Xihua University, Chengdu, China
(Corresponding Author: [email protected] )
Abstract - The traditional assessment model that is used
to assess the safety and predict the remaining life of oil and
gas pipelines consumes substantial resources, such as
manpower and materials. In a sense, it hampers the
development of assessment technology. So, we set up a new
assessment model, Cloud Service Model, which is based on
Cloud Computing, Field Signature Method (FSM) and
Dynamic Assessment Technology. With the characteristics of
timeliness, high efficiency, resource sharing and low cost, it
may have a great application prospect.
Keywords - Cloud Computing, dynamic assessment,
Field Signature Method, pipelines, safety monitoring
Pipelines play an irreplaceable role in the transport of
oil and gas. A small oil spill of pipelines can become a big
catastrophe, as it did in the 2006 spill in the Prudhoe Bay
oil field of Alaska. So, it’s absolutely necessary to ensure
that pipelines work in a safe condition.
In most situations, we don’t need to inspect the
whole pipelines because of the predictability of most
defects’ positions. According to the working condition,
structure of pipelines and experience of inspectors, we can
obtain the sections which have a greater possibility of
failure. Then, we can use some useful techniques, such as
straight beam ultrasonic thickness examination (UT),
Radiographic examination (RT), Magnetic Particle (MT),
Dye Penetrant (PT) to get the size of defects [1].
When having gotten the size of defects and material
data of pipelines and other data that are necessary to
assessment, we can assess the security or fitness-forservice and estimate the remaining life of the equipment
according to standards or codes available, such as API
510, API 570, API 653, API 579 and ANSI/NB-23[1].
Then we can make the plan of checking or take some
remediation methods to prevent or minimize the rate of
further damage [1].
However, it’s not enough! It’s very difficult to check
out the whole pipelines, because it may be used in the
open-air, underground or subsea condition and often it’s
not too short[2][3]. Stem from competitive consideration,
oil and gas companies possessing a large number of
pipelines won’t share the inspection and assessment
equipment with each other, which may occupy large
amount of resources. For the so-called data security
consideration, they also may not provide the inspection
data of defects to research institutes, although they may
develop significant theories to prevent the defects in
return. So, there must be a more effective service model
to manage the data.
A. Cloud Computing
Cloud Computing has been regarded as a new largescale
computational power is provided similar to utilities like
water, electricity, gas and telephony [4]. It involves Grid
computing, Distributed computing, parallel computing,
utility computing, network storage technology,
virtualization and load balance techniques [5]. It delivers
infrastructure, platform, software, storage as services,
which are made available as subscription-based services
in a pay-as-you-go model to consumers [4]. These services
in industry are respectively referred to as Infrastructure as
a Service (IaaS), Platform as a Service (PaaS), Software
as a Service (SaaS), and Storage as a Service (StaaS) [6].
Users access services based on their requirements without
regard to where the services are hosted [7].
Since the CEO of Google, Eric Schmidt, put forward
the concept of cloud computing for the first time in 2006,
Cloud Computing develops rapidly and is widely used in
Internet Technology applications, for example, BT for
IaaS, Amazon EC2 for PaaS, Google apps for SaaS,
Amazon S3 for StaaS [6].
With the characteristics of service-oriented, loose
coupling, scalability, strong fault tolerant, ease use,
virtualization and high security[8][9], it will make a lot
sense to introduce Cloud Computing into the service of
oil pipeline’s safety monitoring and assessment.
B. Field Signature Method
As has been noted, pipelines may be in a severe
working condition where manpower can’t reach easily.
So, we need a practical and effective inspection method to
detect and monitor the defects of pipelines on line.
Because corrosion is the main defect that results in the
failure of pipelines [2], the Field Signature Method (FSM)
is the best option.
FSM is a nondestructive, on-line, reliable inspection
method, which was put forward and developed by the
CorrOcean ASA in Norway [10]. In case of having metal
Cloud computing
(Service providers)
Inspection communication
SaaS, PaaS
StaaS, IaaS
Inspection communication
Oil and gas
Fig. 1. Structure of Cloud Service Mode
loss and cracks on the steel object and current flowing
through it, the electrical resistance of these regions will
rise [11]. According to Ohm’s law, the potential difference
will rise in proportion to the increase of electrical
resistance. FSM detects corrosion and cracks by detecting
the changes of voltage measurements of the sensing pins
(electrodes) which are distributed in an array over the
monitored area.
With the advantages of nonintrusion, accuracy and
adaptability in extreme conditions [11], FSM has been used
in oil and gas industry, in petrochemical plants, in
refineries, in power plants and in nuclear reactors. With
the improvement of FSM technology [12], using FSM
technology has become an unavoidable trend.
cracks as an example, we often utilize Failure Assessment
Diagram(FAD) to judge the security of pipelines by
determining whether the assessment point is in the
acceptable region or not. For dynamic assessment method,
the failure routine and failure rate can be simulated
through a system based on dynamic assessment
technology. The residual life is found by dividing the
failure routine by the failure rate after considering all
sensitive factors, such as loads, material properties and
Undoubtedly, this method is intelligent, the results of
which are more intuitive and practical. Because of the
powerful data processing ability, it will take less time to
obtain the assessment results.
C. Dynamic Assessment Technology
There are many methods to assess the security or
fitness-for-service and estimate the remaining life of the
equipment, such as finite element method[13], linear-elastic
fracture mechanics[14], fracture mechanics[15], most of
which are based on the residual strength of pipelines.
With the application of these methods, enormous
economic benefits have been gained. However, most of
these methods are either too conservative or too restrictive,
such as the ANSI/ASME B31G-1991 based on fracture
mechanics. And they belong to static assessment methods,
that is, they can only gain the security of current working
condition and predict the residual life of the condition that
is the same as the current conditon. It is known to us that
the working conditions having a huge influence on the
security and residual life may change, so the results we
obtained by paying a heavy price sometimes may be
inaccurate and impractical. Thus, dynamic assessment
method is developed.
Dynamic assessment technology, which was firstly
put forward by School of Manufacturing Science and
Engineering of SICHUAN UNIVERSITY, is based on
computer technology. Taking the safety assessment of
A. Structure of Cloud Service Model
Given that the traditional service model has many
disadvantages and can’t meet the need of society, we put
forward a new service model, Cloud Service Model,
which is mainly based on Cloud Computing, Field
Signature Method (FSM) and Dynamic Assessment
Technology. In fig. 1, the structure of the new model is
B. Characteristics of Cloud Service Model
Timeliness: The inspection communication
equipment can conduct real-time data acquisition and the
Cloud Service Center will deliver the safety information
of pipelines to the oil and gas companies in time in a way
that is accessible to them. The oil and gas companies can
also use Mobile Terminals (MT), such as cell phone,
tablet PC and laptop computer, to get the safety
information at any place and any time through the Cloud
Service Provider (CSP).
Oil or gas
Fig.2. Structure of traditional assessment model
High efficiency: Because the amount of
inspection data is very large, it may take the processing
center of oil and gas companies a lot of time to process it,
which is the last thing they want. Cloud Computing can
solve this problem very easily and quickly, because of the
enormous data processing capacity and system scalability.
3) Resource sharing: The confidentiality of the
inspection data of pipelines which is completely
unnecessary impedes the progress of assessment
technology. Through the Cloud Service Center (CSC) can
we overcome this barrier, and the institutes, Oil and Gas
companies and pipe manufacturers take what they need.
Because what the institutes are concerned with are the
laws behind the inspection data, the oil companies is the
safety of pipelines, the pipe manufacturers are the
problems resulting from the use of pipelines, through the
CSC can the rational allocation of resources be achieved.
Low Cost: Compared with the traditional
assessment model, see Fig. 2, it will take the oil and gas
companies less money to get what they want, because the
institutes and pipe manufacturers pay the rest[16].
Based on Cloud Computing technology, Field
Signature Method and Dynamic Assessment technology, a
new service model, Cloud Service Model, is set up.
Compared with the traditional assessment model, we
conclude that the Cloud Service Model has many
advantages. We can define it as a resource conserving
model with a great deal of promise.
The present study was supported in part by the
National Natural Science Foundation of China entitled
“Defects failure routine and failure rate simulation and
research of dynamic safety margin of pressure vessel”
under Grant NO.51075286, Project duration 1st January
2011 to 31st December 2013 (3 years).
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