The Future
of Reservoir
Management
Real-time reservoir management is an emerging
concept in the exploration and production (E&P)
industry. However, there are numerous definitions of
real-time reservoir management, which reflects the
fact that there have been many attempts to implement
it. In this article, Fikri Kuchuk, Andrew Carnegie, and
Mahmut Sengul define the scope and processes of
real-time reservoir management and explore its
significance to the various disciplines within E&P.
magine an oil field where a few
multiskilled geoscientists and
engineers control every aspect of
development and production from a
control room or iCenter* immersive
visualization systems. When presented
with a continuous stream of reservoir,
well facilities, and pipeline information,
these geoscientists and engineers have
automated systems to analyze the data,
others to help them formulate effective
responses to changing surface and
subsurface conditions, and the means
to implement these responses in real
time. The emerging technology allows
them to respond quickly to economic
factors and increase or reduce
production rates from individual wells
to reflect changing quotas or market
conditions. And they are doing all
of this from offices hundreds or
thousands of kilometers from the
reservoir (Figure 4.1). A few years
ago this might have been just a dream,
but recent technological advances
and closer cooperation between oilfield
disciplines are near to making it a
reality. Field optimization will drive the
future development of oil fields, and
I
Production stops for
logging, testing, and
remediation
facilities that process the fluids being
produced from the reservoir.
The development of these
automated systems represents the first
step toward a transformation of the
upstream business and the emergence
of autoengineered smart oil fields. The
industry is beginning to make full and
effective use of the World Wide Web
and associated intranets to access
data, applications, and expertise,
wherever they are available throughout
the world. Once they have made the
connections, each oil company must
focus these capabilities on the key
opportunities within its asset portfolio.
Real-time reservoir management has
already been implemented, for
example, in some modern deepwater
fields that contain subsea wellheads
producing from multizone reservoirs,
and in which many problems, such
as a zone watering out, cannot be
economically solved by a simple
downhole intervention.
Permanent downhole monitoring
Oil
Water
Locate problem
Production
Production
Surface monitoring
this article focuses on a key part of this
process—reservoir optimization.
Effective real-time reservoir
management will require development
in at least five key areas:
■ downhole monitoring and
acquisition systems
■ software to manage large and
continuous streams of data. This
will help asset teams to identify
value-adding opportunities and
to optimize asset performance.
■ software that integrates the data
into the subsurface model, so
that asset teams can identify
discrepancies in the model at an
early stage. This opens the way
for real-time history-matching.
■ methods for downhole, mostly
rigless, intervention. These may
require devices that are preinstalled
into the production system of the
field such as intelligent completions,
or advanced and highly compact
conveyance systems such as tractors.
■ control systems that allow the
reservoir to be more closely linked,
perhaps eventually managed, by the
dictates of the refinery and other
Shut down water zone
Continuous oil
production
Reduced water cut
Time
Time
Figure 4.1: Asset managers need to respond quickly to changing reservoir or economic conditions so that they can increase or reduce production rates
from individual wells to meet their technical and business objectives.
52 Middle East & Asia Reservoir Review
Reorganization during the 1980s and
1990s reduced employee numbers in
many oil and gas companies. However,
oil and gas consumption has grown by
about 2% per year during the last two
decades, but oilfield employment has
remained almost constant, or has even
decreased slightly during this time.
Downsizing, combined with the
retirement of those in senior positions,
means that today’s upstream industry
is lean in terms of an experienced,
professional workforce. However,
some companies have overcome this
challenge by using new technologies
that allow them to find and produce
hydrocarbons at lower cost and with
fewer people. Real-time reservoir
management has the potential to take
this process a stage further and enable
the industry to maximize efficiency
and increase revenues.
Any system that delivers true,
real-time reservoir management
and control must combine all the
relevant disciplines, encourage
greater cooperation, and increase
the efficiency of data utilization and
sharing. Continuing improvements
in computer processing power and
greater connectivity between
remote locations are critical to the
development of modern reservoirmanagement processes.
Reservoir management is a complex
decision-making process that is
influenced by technical, logistical,
health, safety, environmental, and
economic issues (Figure 4.2). Planning
is probably the most important aspect
of reservoir management. Successful
planning defines the problem and
develops possible solutions, but it also
involves setting the objectives and
limits, such as production targets and
budgets, that will influence the project.
The first priority for geoscientists
and engineers is to identify and
evaluate the factors that control the
flow of oil, gas, and water in the porous
and, sometimes, fractured and faulted
rocks that comprise their reservoirs.
This involves understanding the
physical controls and the combined
effects of capillarity, gravity, and rock
heterogeneity, as well as the chemical
reactions and phase changes associated
with multiphase flow conditions. The
technical challenges include modeling
pore-scale processes, the complex
heterogeneities encountered in some
reservoirs, and macroscopic flow
instabilities; and conducting large-scale
modeling of enhanced oil recovery.
Once the reservoir has been
reasonably characterized and
modeled, the asset team can begin to
predict how possible modifications to
production or field-development
strategies would affect hydrocarbon
production rates and recovery. These
predictions can then be tested against
logistical and economic constraints.
The team must also determine the
safe design limits for pipelines and
other production facilities. This is
an important task, particularly when
planning how to deal with health and
safety hazards, or when designing
expensive one-off facilities such as
those associated with deepwater
developments. The design of
production facilities involves being
able to confidently predict and then
handle unwanted compounds such
as asphaltenes, waxes, and hydrogen
sulfide. More importantly, the design
process must establish how to handle
ever increasing levels of water
production. Production scenarios are
obtained from the reservoir model,
which, in turn, must be based upon a
thorough and accurate understanding
of the fluid compositions and the
rock chemistry.
Better models—better results
Modern reservoir models provide the
fundamental framework for reservoir
management and a flexible logistical
tool. But, establishing static (rockrelated) and dynamic (flow-related)
reservoir properties (Figure 4.3) is
only one stage in a process designed
to maximize production and recovery
rates. Once the team of geoscientists
has established the static reservoir
description, the discipline of reservoir
engineering usually assumes the lead
responsibility for the next stage of
modeling (but it must be noted that
all the geoscientific disciplines remain
part of the team). The role of the
reservoir engineer involves monitoring
changes in key physical reservoir
parameters, assessing how proposed
development and production strategies
will affect the field, and implementing
Figure 4.3: The first step in maximizing
production and recovery rates is establishing
the static and dynamic reservoir properties.
Middle East & Asia Reservoir Review
Number 5, 2004
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Figure 4.2: Technical, logistical, and economic issues all influence the long, complex decision-making process that is reservoir management.
Smaller teams—bigger
responsibilities
53
the necessary changes to optimize field
performance. Until recently, these
steps were conducted intermittently
and the time between the initial data
gathering and the implementation of
the approved changes was generally
measured in months.
The various disciplines involved in
reservoir characterization were based
in different departments; there was
little interaction between them; and
they often had slightly different
business objectives. For example,
geologists created maps of the asset
and passed them to the reservoir
department. This was effectively a
one-way transfer; the geologists were
never informed of the drastic changes
that reservoir engineers might make
to fit the map to the production
data. The drilling department was
often responsible for the testing
of exploration wells, and drilling
priorities or production issues
determined how well tests were
performed and their duration. This
meant that tests were conducted with
little consideration of the wider issues
of reservoir characterization such as
fault boundaries and aquifers.
The delays and lost production
associated with these methods led
to the emergence of an asset-team
approach, where specialists from
different departments work in close
association on a particular field asset.
Asset teams have investigated new
technology and new ways to use
existing technology. This has greatly
reduced the time between data
gathering and intervention
(Figure 4.4). The world’s leading
oil companies now organize their
experts into multidisciplinary teams.
Interaction between the various
disciplines is well established but,
until recently, this was generally
achieved without a formal framework
for data sharing.
Over the past decade, the industry
has focused its research and
development efforts on the issues
surrounding the static aspects of
reservoir characterization. The
introduction of 3D seismic surveys
has helped companies to make
significant progress in 3D reservoir
modeling, but merging the static and
dynamic features of a reservoir—to
provide the vital link between earth
science and production engineering—
is not yet well established.
Measuring dynamic properties
The modern E&P industry combines
time-lapse surface and borehole
seismic monitoring, directional
drilling, permanent downhole
monitoring, advanced well
completions, fiber-optic sensor
technology, data management,
Internet technology, and shared earth
models to extract and share details
about the structure, fluid content, and
production capacity of oil and gas fields.
Time-lapse seismic methods can be
used to monitor injected fluid fronts;
locate bypassed oil; map pressure
compartmentalization and pressure
changes; and establish the sealing
properties of faults. High-resolution,
time-lapse seismic monitoring has
been conducted in the borehole, in
both vertical seismic profile and crosswell geometries. Multicomponent
seismic receivers can be installed for
little more cost than acoustic sensors.
The additional information gained
from the shear wave-data obtained
could help the reservoir engineer to
monitor pressure fronts, in-situ stress,
and fracturing.
Similarly, newly emerging deep
resistivity measurements, acquired
using tools available from
Schlumberger and run on wireline
into a wellbore, can now monitor
water fronts several hundreds of
meters into the reservoir.
Downhole instrumentation and
borehole technology have developed
rapidly over the past few years.
Downhole sensors can now measure
key reservoir variables such as
pressure, temperature, and oil
saturation. When permanently
installed, these sensors can deliver
Figure 4.5: Projecting 3D images of geological structures onto an immersive, panoramic screen has changed the way reservoirs are assessed and
developed—ideas can be exchanged, hypotheses tested, and problems solved on a team basis.
continuous data streams to surface
control centers using dedicated fiberoptic links. When linked to advanced
completion technology, downhole
sensors can help to optimize the
drainage of multiple reservoir targets
by measuring flow rates and pressure
during production, and can also help
in modifying completion parameters
in an effort to maximize recovery,
optimize production, and minimize
unwanted gas and water production.
The rise of visualization
Data gathering
Data processing
Data analysis
Intervention planning
Intervention
Traditional
Time
Modern
Time
Figure 4.4: Continuous monitoring of key physical reservoir parameters and assessment of proposed development and production strategies reduce the
time between data gathering and intervention, and help to prevent the delays and lost production associated with conventional methods.
Before the mid 1980s, interest in
numerical reservoir modeling was
limited. Engineering teams used
numerical simulation to create
models that estimated and predicted
reservoir behavior in a simplistic way.
This generally involved setting up a
4D numerical simulation model and
adjusting its parameters by historymatching production pressure and
water-cut data that are normally 2D
(1D spatially and 1D temporally).
This incompatibility created a long
and arduous history-matching process
that was carried out by specialists
and often resulted in unrealistic
parameter distributions and
production predictions. A major
problem with this was one of
nonuniqueness—the reservoir model
created through history-matching
could often be one of several plausible
models, all of which could satisfy the
historical performance of the field
in the simulator. This presented a
major problem—understanding the
uncertainties associated with historymatched models.
Unfortunately, this meant that
predictions about reservoir behavior
could be extremely inaccurate. This
approach also encouraged those
responsible for assets to downgrade
the value of the measurements made
at the reservoir. For example, some
operators would question the value of
acquiring core permeabilities because
these would be changed drastically
during the history-matching process.
During the mid 1980s, the concept
of reservoir description was introduced
to provide a realistic framework
for history-matching. Although
field measurements were used to
constrain the simulations, and so
reduce the problems associated with
nonuniqueness, they did not provide a
consistent methodology or any of the
benefits of modern techniques such as
3D reservoir modeling.
A better view
The introduction of large collaborative
and immersive visualization systems
has had a major impact on the
upstream industry. Visualization was a
vital part of E&P activities long before
computers became commonplace, but
then it was carried out on paper, with
visualization being achieved using bar
charts, graphs, well logs, and seismic
sections. Once computer technology
had been introduced, there was a
rapid increase in the use and value of
visualization. However, it took time to
develop visualization tools (charts,
graphs, etc.) for computer applications.
At first, everything remained on paper
or was presented in a paper-like format
on small computer screens. Over the
past three to five years, computergenerated displays have undergone
dramatic improvements in resolution,
physical size, and interactivity,
particularly since the introduction of
3D seismic data. And the upstream
sector is benefiting as a result.
The emergence of virtual-reality
systems has taken the trend even
further. Being able to interpret huge
volumes of seismic, drilling, and
reservoir data, and then project the
resulting 3D images of geological
structures onto an immersive,
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54 Middle East & Asia Reservoir Review
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55
panoramic screen has changed the
way reservoirs are assessed and
developed. The continued growth of
computing power has helped to turn
the concept of a shared earth model
into reality. Now, many teams have
access to modern visualization
technology that helps them to
exchange ideas, test hypotheses, and
investigate different scenarios on a
team basis (Figure 4.5).
iCenter immersive visualization
systems from Schlumberger offer
mini-theater-sized, curved screens
and powerful image-handling
technologies. These systems present
the subsurface environment in a way
that allows users to view, manipulate,
walk, and even fly through reservoirs
in their quest for solutions to drilling
and production challenges. Using
these systems, asset teams can
inspect an entire field or just a small
corner of it, thus allowing them to
agree on the most efficient and costeffective strategies for reservoir
development. Schlumberger has an
Inside Reality* ‚ 3D visualization
iCenter system in all the major oil and
gas provinces; the Abu Dhabi facility
opened in 2002.
A 4D seismic monitoring project
involves repeating 3D seismic surveys
for a field, or its subsection, after a
given period. The results from these
surveys help the asset team to monitor
fluid movement over time. The images
produced by 4D seismic monitoring
help to identify fluid flow and reveal
spatial and temporal variations in fluid
saturation and possible pressure and
temperature changes. The most
important applications include
mapping bypassed oil; monitoring
injected reservoir fluids such as water,
steam, gas, and carbon dioxide;
studying the effect that production
and/or injection has upon pressure
throughout the field; estimating the
fluid-flow variations related to pressure
compartmentalization; and assessing
the hydraulic properties of faults and
fractures (Figure 4.6).
Monitoring fluid flow with 4D
seismic techniques requires close
collaboration between the disciplines
of structural and stratigraphic
geology, fluid-flow simulation, rock
physics, and seismology. Seismic
reservoir monitoring can significantly
help to understand recovery in new
and existing fields by helping the
asset team to monitor and predict the
interwell positions and the movement
of reservoir fluids. Fluid monitoring
helps the team to locate bypassed oil,
avoid premature water breakthrough,
optimize infill well locations, and
evaluate enhanced-oil-recovery pilots
before full-field implementation.
Modeling for management
Reservoir management is based on
a series of decisions that enables oil
and gas companies to meet their
technical and business objectives
(Figure 4.7). The process requires
an accurate model of the reservoir
system and the ability to predict
the consequences of implementing
possible, alternative strategies.
Reservoir characterization, a vital
part of the model creation process,
involves generating an editable,
mathematical subsurface model. The
model is calibrated to reproduce the
past, observed dynamic performance
of the reservoir, and is expected to
be able to predict future performance.
Since the objective in making
predictions is to optimize production,
it may be necessary to take surface
processing facilities into account.
The calibration process does not
Time-lapse monitoring
1985
0
HC indicator
1996
1
No change
Changes
Significant
change
Figure 4.6: 4D seismic images help to identify heterogeneous fluid flow and reveal both spatial and temporal variations in fluid saturation, pressure, and
temperature. They are very useful for mapping bypassed oil; monitoring injected reservoir fluids; estimating fluid-flow heterogeneity related to pressure
compartmentalization; and assessing the hydraulic properties of faults and fractures.
necessarily provide a unique solution,
but the level of uncertainty can be
reduced by increasing the amount
and range of information incorporated
into the model and by verifying that
the selected model is consistent with
all the available data.
Reservoir characterization is a
continuous process that must be
updated as new information is gathered
from the asset. For simplicity, it may be
considered to be divided into three
major consecutive steps:
1. Generate data interpretations for
each technical discipline.
2. Integrate these interpretations into a
model of the reservoir.
3. History-match this model.
Generally, the models in steps 2 and 3
are grid based, i.e., the reservoir
(structure, rock fabric, and fluids) is
represented by a set of cells.
The models created as part of step 2
are called geocellular models and do
not generally have the capability to
simulate fluid flow. This takes place as
part of step 3—the geocellular models
of step 2 are transformed into the flow
simulation models in step 3. The cells
in geocellular models are generally at
a finer scale (i.e., smaller) than those
in the equivalent flow simulation
model. Hence, a process known as
upscaling is required to convert the
properties from geocellular models
into those in simulation models. The
process involves two consecutive
steps: generating data interpretations
for each technical discipline and
integrating these interpretations into
the reservoir model.
Combining data
Asset team members may generate
their own data interpretations, but
they usually use in-house experts,
consultants, and/or service companies.
The interpretation process may differ
drastically from one company to
another and may depend on the
importance of the field. In any case,
these data will typically include
static data (geology, geophysics,
geochemistry, and petrophysics)
that correspond to a description of the
reservoir’s shape and structure, and
dynamic data (fluids, geomechanics,
tracers, production logs, well tests,
and production) that relate to
reservoir behavior.
Data interpretations use widely
varying scales and resolutions (surface
seismic interpretations are measured
in meters, while core samples are
measured in millimeters) and reveal
different aspects of the formation
and the reservoir and its behavior.
Geophysical data modeling, for
example, reveals acoustic impedance
contrasts, whereas pressure transient
data at different scales (from wireline
formation testing to conventional
buildup testing) primarily identify
mobility and storativity contrasts.
Understanding the significance of such
diverse information and measurements
requires cooperation across the asset
team as well as the involvement of
many other professionals.
Transferring data into the
Middle East & Asia Reservoir Review
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56 Middle East & Asia Reservoir Review
Figure 4.7: The DecisionPoint* personalized E&P Web workflow solution enhances collaboration and provides access to validated information using
proven Internet technology. This aids production of the accurate model of the reservoir system and prediction of the consequences of implementing
possible, alternative strategies that are required for reservoir management.
57
cellular reservoir model
The asset team can incorporate direct
and interpreted data into the reservoir
model using deterministic or stochastic
methods. A stochastic approach allows
the team to integrate knowledge from
different data interpretations (a
process known as conditioning) while
taking into account the different levels
of reliability (uncertainty) associated
with each interpretation. Stochastic
modeling provides multiple,
equiprobable 3D realizations of the
reservoir model that can then be used
to explore, and perhaps even quantify,
the effects of the uncertainty about
various aspects of the reservoir
characterization on the predicted
performance of the field (Figure 4.8).
Stochastic techniques are most
useful where data are sparse, typically
during the early stages of field
development, and/or when significant
heterogeneities such as thin, highpermeability streaks are at a smaller
scale than those of the available
measurements. Deterministic
techniques are more appropriate for
fields with high data density—those
with lots of wells and years of
production information (though
stochastic modeling is still useful for
evaluating the level of uncertainty in
an established reservoir model).
Cased hole neuton porosity
0.45
AIT 60
2
?
?
Gamma ray
0
2000 300
150
(ohm-m)
2000 0.45
CHFR resistivity
2
(ohm-m)
(µs/m)
100
Openhole neutron porosity
(p.u.)
Compressional
and shear
coherence
-0.15
Openhole density porosity
2000 0.45
(p.u.)
-0.15 100
(µs/m)
700
Zone of
interest
Figure 4.9: Model data must be upscaled
before an asset team can examine model
behavior, as the grids applied in numerical
simulators are coarser than those used in the
reservoir model.
Figure 4.11: Modern logging can deliver precise information on fluid content and movement, and the latest sampling methods can retrieve formation fluid
samples from behind casing.
to evaluate production behavior add
a further complication to reservoir
management. The grids applied in
numerical simulators are coarser
than those in the reservoir model.
Consequently, the asset team must
upscale the model data before it can
examine model behavior (Figure 4.9).
Though essential, the upscaling
process introduces errors that affect
model verification.
Figure 4.8: Stochastic modeling provides
multiple, equiprobable 3D realizations of the
reservoir model and quantifies the
associated uncertainties. In this simplified
example, available well data allow several
possible interpretations or realizations of
interwell structure.
Measure to manage
Figure 4.10: Electrical coring to characterize
producing formations was the start of
downhole operations.
Surface monitoring of wells has
been routine since the oil and gas
industries were in their infancy. For
commercial and material balance
reasons, oil companies have always
needed to know the volumes of
produced fluids. Through the early
decades of the twentieth century,
engineers and geoscientists came to
realize how complex the subsurface
environment could be and began to
extract information about reservoir
rocks and fluids in situ.
Downhole data gathering started
with electrical coring to characterize
producing formations (Figure 4.10).
Service companies emerged to
conduct these specialized tasks and,
over the years, have improved and
extended their technology, thus
providing the operating companies
with better information about their
vital hydrocarbon assets (Figure 4.11).
For example, the CHDT* Cased Hole
Dynamics Tester drills through casing
and cement, and into the formation;
measures reservoir pressure and fluid
resistivity; collects fluid samples; and
plugs the hole with a bidirectional
seal that can withstand pressures of
up to 10,000 psi.
Until relatively recently, data
gathering could only be conducted in
discrete testing and logging periods.
Unless performed in a well that was
dedicated to reservoir monitoring
(an observation well) this process
interrupted production, was
considered expensive, and was
conducted at infrequent intervals
with months or years between each
assessment. Moreover, in some
regions, wells were only logged when
the operator wanted to diagnose
production problems or look at
injection profiles.
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58 Middle East & Asia Reservoir Review
(gAPI)
2
-0.15
DSI delta-t compressional
AIT 90
Cement
bond
(ohm-m)
Validation, history-matching,
flow simulation
Once the team has completed its
reservoir description, it must ensure
consistency with all the available
information and data interpretations.
This process is known as validation.
The model must honor all of the data
that were used in the characterization
process—seismic, log, and well- and
production-test data if available. If
the reservoir model is consistent with
the available information and the
data interpretations, the correlation
between the field data and the model
responses is normally good and,
therefore, relatively simple to improve
by adjusting the reservoir model
parameters within the limits imposed
by available knowledge. This is
history-matching.
The numerical simulators used
(ohm-m)
Casing resistivity
(p.u.)
Middle East & Asia Reservoir Review
59
A permanent solution
1970s
1973 First permanent downhole gauge
installation in West Africa using
wireline logging cable and equipment
1975 First pressure and temperature
transmitter on a single wireline cable
1978 First subsea installations in the
North Sea and West Africa
1980s
1983 First subsea installation with
acoustic data transmission to surface
1986 Fully welded,
metal-tubing-encased
permanent downhole cable
1986 Introduction
of quartz crystal
permanent pressure
gauges in subsea wells
1990 Fully supported copper conductor
in permanent downhole cable
The first permanent downhole gauges
were installed during the 1970s
(Figure 4.12). These early systems
were often hindered by poor reliability,
but the benefits of continuous
monitoring encouraged the pioneers
to overcome these problems.
Since the early 1990s, permanent
reservoir-monitoring systems (mainly
pressure gauges) have been installed
in a number of reservoirs around the
world. The principal aims of permanent
monitoring are to improve asset
management and optimize production
through the acquisition, management,
and interpretation of a continuous
stream of real-time data. The key
requirements for a successful downhole
monitoring system are good reliability
and durability, and the design flexibility
to meet the operator’s requirements.
Downhole monitoring sensors are
deployed in extremely hostile and
demanding environments. The
challenges include high temperature
and pressure, and harsh chemical and
physical conditions (Figure 4.13).
Consequently, reliable transducer
technology is essential. Conventional
electronic gauge technology has been
deployed successfully in a range of
downhole monitoring applications,
predominantly in wireline-retrievable
systems, but also, more recently, for
permanent reservoir monitoring.
Unfortunately, electronic systems
have inherent limitations that render
downhole applications particularly
challenging, for example, electronic
260
1994 Permanent
quartz gauge performance
substantiated by gauge
accreditation program at BP.
Start of long-term laboratory testing
1994 FloWatcher* integrated
permanent production monitor
installed for mass flow-rate
measurement
Downhole fluid measurements
Flow-rate and multiphase meters for
downhole use will be vital elements
of the real-time reservoir-management
strategy, but are still in the early
stages of development.
Useful information on downhole
flow rates and fluid compositions
can be inferred from downhole
temperature and pressure
measurements in combination with
surface measurements. For example,
downhole production logging using
the PS Platform* new-generation
production services platform in
combination with PhaseTester*
multiphase well testing equipment at
the surface has proved effective for
multiphase flow characterization
and production testing (Figure 4.14).
Downhole electrically or hydraulically
actuated control valves allow engineers
to determine flow rates from individual
well intervals by closing all other
intervals and measuring flow at the
surface (Figure 4.15).
HPHT wells
Ultra-HPHT wells
235
210
Mary Ann
185
Arun
160
Embla
Marnock
135
Kotelnevsko
North Ossum
110
40
50
60
F15
Laco
Lille Frigg
70
Shearwater
Thomasville
Franklin
Villa/Trecate
Elgin
Erskine
Trecate
Puffin
West
Malossa
Cameron
Eugene Island
80
90
100
110
Initial reservoir pressure (MPa)
60 Middle East & Asia Reservoir Review
Figure 4.13: Downhole monitoring sensors have to meet challenges that include extremes of
temperature and pressure, and harsh chemical conditions.
120
Innovation in action
Figure 4.14: Downhole production logging using the
PS Platform services platform in combination with
PhaseTester multiphase well testing equipment at the
surface offers multiphase flow characterization and
production testing.
Figure 4.15:
Engineers can
determine flow rates
from individual well
intervals by closing
all the other intervals
and measuring flow
at the surface using
downhole electrically
or hydraulically
actuated control
valves.
Technical innovation has been the key
to recent improvements in reservoir
management. The Schlumberger
portfolio of products geared to
achieving optimum run life and
reservoir production has expanded
dramatically in recent years; for
example, WellWatcher*, FloWatcher,
and PumpWatcher* monitoring
systems are operating successfully in
some of the world’s most demanding
reservoirs (Figure 4.16).
Saturation monitoring is a crucial
part of reservoir management. In
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Number 5, 2004
Figure 4.12: The first permanent downhole
gauges were installed in the 1970s.
When a permanently installed
downhole gauge stops working,
reservoir engineers lose their window
on the reservoir. It is vital, therefore,
that gauges remain operational
throughout their planned working life.
Over the past decade, Schlumberger
has focused on improvements in
engineering and testing processes,
system design, risk analysis, training,
and installation procedures to
enhance the reliability of its
permanent monitoring systems.
The development of a permanent
gauge system follows a sequence
of engineering operations, with
dependability being paramount during
each stage. The engineering sequence
begins with a careful description of
the technical concept that sets out
possible applications for the gauge.
This serves as a framework and defines
the role of each component and the
environmental conditions that it will
encounter during its expected lifetime.
System components are generally
tested and qualified to withstand the
expected conditions. Accelerated
destructive tests subject the
components to conditions that are
more extreme than those expected
in service, such as greater mechanical
shocks and vibrations, and higherthan-downhole temperatures and
pressures. This type of testing helps
to determine the causes and modes
of failure. Long-term testing of the
system enables engineers to validate
reliability models and quantify
measurement stability. Feedback from
field engineers is a vital input to all
laboratory-testing methods.
Mobile Bay South Texas
Temperature (˚C)
1990s
1993 New generation of quartz and
sapphire crystal permanent gauges
Reliable? You can
depend on it
systems are less reliable at high
temperatures.
Today, fiber-optic technology is
becoming an important part of the
reservoir-monitoring toolbox. The
advanced sensor systems developed
by companies such as Sensa have
applications across the oil and gas
industries where, through downhole
monitoring, they are helping to
change the way reservoirs are
developed and managed.
Middle East & Asia Reservoir Review
61
18,000
16,000
14,000
Oil rate (STB/D)
12,000
10,000
8,000
4,000
Hourly average fiscal rate
Flow rate derived from venturi
2,000
0
1
13
25
37
49
61
73
85
97
109
Time (hr)
Figure 4.16: Because Strathspey field wells in the North Sea are produced commingled, production
allocation was a key reservoir-management issue. Two high-precision PressureWatch* quartz gauges
were installed across a venturi at 9000 ft to monitor pressure, temperature, and flow rate.
A third PressureWatch gauge was installed at 8000 ft to provide water holdup data. Measurements
from all three gauges were transmitted in real time through the subsea control module.
Cross-well electromagnetic
technology
62 Middle East & Asia Reservoir Review
Figure 4.17: The data from the CHFR tool are much closer to those obtained from openhole logging, as
the tool reads deeper into the formation and is unaffected by mud filtrate.
for more than a decade to develop
deep-reading, electromagnetic
borehole sensors that can produce 3D
resistivity images on a reservoir scale.
At present, there are two options,
both are conveyed using conventional
electric wireline and can be
customized to suit specific
requirements. The first system
investigates large rock volumes around
a single wellbore. This single-well
logging tool can investigate rock for
tens of meters around the borehole.
The second system images formation
between adjacent wells. The vertical
resolution of this cross-well system is
approximately 5% of the well spacing.
The volume of rock measured is much
greater than can be achieved with
conventional wireline technology.
Cross-well electromagnetic technology
can provide an interwell resistivity
distribution and so map water
saturation and reservoir structure
between wells. By mapping resistivity,
engineers can identify faults and
fractures; locate bypassed hydrocarbon
zones; and monitor water, steam, and
polymer flooding operations. This
wealth of subsurface information allows
asset teams to make better decisions
about their reservoirs.
The cross-well technique has been
used for more than five years to image
thermal oil-recovery operations
(steamfloods) and, more recently,
for reservoir waterflood monitoring.
The resistivity contrast between the
zones flooded with saline water and
the hydrocarbon-filled pay zones
usually provides an excellent
electromagnetic signal.
One-year resistivity change
1000
OB9
Producer (fractured)
1250
Injector
1500
1750
2000
OB10
1125
1125
1250
1250
1375
1375
1500
1500
1625
1625
1750
1750
1875
1875
2000
0
38
75
113 150
Location (ft)
188
225
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Cross-well electromagnetic
technology is an emerging method
that promises to revolutionize the
industry’s understanding of what
goes on between wells (Figure 4.18).
Scientists and engineers at
Electromagnetic Instruments Inc.,
a Schlumberger company based in
California, USA, have been working
Figure 4.18: Electromagnetic imaging
methods (top) are emerging as key tools for
reservoir monitoring. The technology has
proven its potential value in a number of pilot
studies such as the Lost Hills survey, in
California, USA, (middle) where it has been
used to track changing resistivity values for
extended periods (bottom).
6,000
Depth (ft)
the past, engineers relied on pulsed
neutron methods—such as that
implemented with the RST* Reservoir
Saturation Tool—to assess fluid type
(oil, water, or gas) and its associated
saturation through casing. The
relatively shallow readings achieved
with the RST tool mean that nearwellbore effects such as poor cement
and residual acid from stimulation
jobs may severely affect the reading.
However, the CHFR* Cased Hole
Formation Resistivity tool reads
deeper into the formation and is
little affected by the near-wellbore
environment. Its measurements are
often much closer to those obtained
from openhole logging (Figure 4.17).
Despite increasing interest in the
new gauges, very few of the world’s
oil and gas wells have continuous
downhole monitoring. Many wells have
been allowed to produce for years
without checking how production
has modified the reservoir around the
well—this is all right while the well
is producing at a reasonable rate
with a low water cut. But it can be
very difficult to establish the cause
and even harder to select the most
appropriate remedial action when a
problem occurs.
The few wells that do have
monitoring systems generate a wealth
of data. Changing pressure–volume–
temperature conditions and flow rates
can be measured every few hours,
minutes, or seconds, depending
on the needs of the reservoir
management. Special software
packages have been developed
to manage the flow of data from
downhole gauges and to pass these
data around the world using secure
Internet and intranet connections.
Once the data have been distributed,
the asset team can get to work on the
critical decision-making process.
-13 0 13 25 38 50
Resistivity difference
Middle East & Asia Reservoir Review
63
Waterflood monitoring in Oman
In 1998, Shell and Schlumberger
launched a joint project to prove
the feasibility and value of dynamic
reservoir-drainage imaging (DRDI).
The aim was to develop time-lapse
monitoring of water saturation that
would allow engineers to evaluate
drainage efficiency in reservoirs.
The method selected was resistivity
monitoring. The development team
applied this technique by cementing in
an array of electrodes at reservoir level
to provide continuous measurement of
formation resistivity.
In 1999, a field test was set up
with Petroleum Development Oman
to demonstrate the technology and to
evaluate the value of data gathered at
Fahud field, Oman.
The DRDI installation for the test
program was located at the center
of a waterflooding cell between dual
horizontal injectors and producers
(Figure 4.19). Two resistivity arrays
were deployed behind casing and
across the reservoir zone. The
monitoring period was estimated at
around 18 months. Readings were
taken at regular intervals from late
1999 until early 2000 to indicate the
water-saturation variations at several
Figure 4.19: The
DRDI installation for
the test program was
located at the center
of a waterflooding
cell between dual
horizontal injectors
and producers.
Turning data into decisions
The production process involves a
series of decisions on how to drain the
reservoir efficiently. Efforts are usually
focused on cash flow and maximizing
revenues. Eventually, as the asset
matures, production priorities change
and, in the latter stages of field life,
the team aims to maximize ultimate
recovery and minimize operating
expenditure.
Many oil companies are changing
the way they develop and manage
reservoirs. Identifying and implementing
best practice helps a company to
optimize initial field development so that
plateau production is maintained for as
long as possible and the challenge of
efficient production from a mature asset
base is met. This is not a particularly
new approach. For example, in some
Middle East countries, where the
reservoirs are large and owned by the
national oil companies, the overriding
reservoir-management priority has
always been to implement best practice
to maximize the long-term recovery of
the fields.
The value of real-time data
provided by sensors installed
within the well is becoming widely
recognized. Downhole pressure,
temperature, and flowmeters can
be distributed within the well to
provide the required resolution.
These distributed measurements
enable, for example, location of
specific regions of high water
production in a horizontal well. This
ability to determine when and where
intervention is needed is of critical
importance. In addition to direct
production monitoring, the tracking
of distributed pressure, temperature,
and multiphase flow measurements
within a reservoir over time provides
valuable input to the reservoir model.
By increasing the fidelity of reservoir
characterization, modern systems
enable more effective management
of the hydrocarbon reservoir.
Observation, evaluation, and
planning are vital steps, but once
the asset team has selected the best
strategy it must be implemented
across the field.
580
580
580
1
2
600
600
600
620
620
620
640
640
640
660
660
660
Start
680
November 1999
680
Water saturation
680
0
10
20
30
Apparent resistivity (ohm-m)
0.00
0.04
0.08
0.12
0.16
580
0.20
0.24
0.28
0.32
0.36
0.40
580
3
4
600
600
620
620
640
640
660
660
January 2000
680
Intervention—making
the changes
Today, production and reservoir
engineers have an extensive range of
production and drilling technologies,
all designed to maximize production
rates and boost recovery. These
include gas-lift methods, electrical
submersible pumps, horizontal drilling,
and multilateral and intelligent
completions. These solutions often
create a complicated network of
vertical, deviated, and horizontal wells
that produce varying proportions of
oil, water, and gas from multiple
reservoir zones (Figure 4.21).
Modern technology allows asset
teams to control fluid flow in the
borehole, for example, by shutting off
sections of a well when a particular
zone is watered out, and increasing
or reducing production on demand. In
fields where this technology is applied
in several wells, asset teams can set
production rates and squeeze more
oil and gas from the reservoir while
maintaining low water cuts.
At present, monitoring of reservoir
conditions is extremely sparse
Figure 4.20: Readings were taken at regular
intervals over the period late 1999 until
early 2000 and showed water saturation
variations at several depths.
March 2000
680
because of its expense and technical
difficulty. New data sets such as well
logs are not easily incorporated into
the knowledge base. Consequently,
the reservoir model is updated
infrequently, and an asset team has
to make decisions based on old or
inadequate information. Opportunities
to accelerate or increase production
and continuously improve operational
efficiency are, therefore, either lost
or delayed, with consequent loss of
income and value.
Efficient oil and gas production
and recovery require continuous
monitoring, prediction, and
reevaluation of interpreted behavior.
The most sophisticated approach
uses reservoir simulators that predict
performance by modeling the
reservoir as a mesh of grid blocks.
Similarly, performance monitoring
uses production logging of wells to
identify vertical variation in reservoir
behavior. Often, however, engineers
use more traditional analytical
interpretation methods.
Engineers who are managing
hydrocarbon recovery will map fluid
fronts by comparing predicted
performance with simulated behavior.
They do this by generating crosssectional and areal views of the
reservoir. This approach is highly
interpretative because information
is only obtained at the wells and
its reliability is reduced by the
heterogeneous and anisotropic nature
of most formations. The ability to
visualize fluids between wells would
clearly make it easier to locate
bypassed hydrocarbon areas within
the reservoir and reduce the risks in
drilling and completing the wells
designed to drain them.
Bringing it all together
The drive toward real-time reservoir
management is a major opportunity
for the industry—a chance to change
the emphasis in oil and gas from a
race to extract natural resources to
a controlled process industry where
production can be monitored and
optimized. Oil companies that seize
this opportunity will be transforming
one of their core competencies—asset
management. This, in turn, will help
them generate additional growth,
Middle East & Asia Reservoir Review
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64 Middle East & Asia Reservoir Review
depths (Figure 4.20). These data
showed that the reservoir was being
unevenly swept and that water
breakthrough times were reduced. The
findings were confirmed by production
data, which indicated a rising water
cut, and by a logging campaign, which
indicated localized saturation increases.
65
establish important business
advantages, and position themselves
as technological leaders within the oil
and gas sectors.
In establishing systems that will
deliver real-time management,
operating companies will have to rely
on tested technology to create new
asset-management team structures.
These new asset teams will help
companies reduce development
capital needs, generate operating cost
advantages, and improve recovery
rates and yield.
+
Development
Maturity
Maximize recovery
Cash flow
Accelerate production
Traditional development
Reservoir optimization
0
Time
Minimize operating
expenditure
Defer abandonment
Minimize capital
expenditure
–
Figure 4.21: The extensive range of sophisticated production and drilling technologies designed
to maximize production rates and boost recovery often create a complicated network of vertical,
deviated, and horizontal wells, producing varying proportions of oil, water, and gas from multiple
reservoir zones.
Well
Gather data
Model
Review
Test options
Plan
Reservoir
Facilities
Modify field operations
Figure 4.22: Cooperation could result in asset-management systems that link data from the
reservoir, well, and facilities monitoring and sensing devices directly to the subsurface model.
Figure 4.23: Business objectives and economic conditions change through the lifetime of an oil field. For modern developments, the aim is
usually to start production quickly at a relatively low cost and then maintain high levels of oil production until it drops below economic levels.
Better performance through the
life of the field
There are generally four key stages
in the development of an oil field:
1. exploration—reservoir structure
and contents are being investigated,
but are not well defined
2. delineation—the size and extent of
the reservoir is being assessed
3. development—the reservoir is fairly
well understood and production is
rising toward peak level
4. maturity—the reservoir is well
understood and its contents are
changing as it is depleted.
Every asset team faces several
fundamental challenges at each stage
of field development: accelerating cash
flow, achieving a greater return on
investment, and extending the useful
life of the reservoir (Figure 4.23).
These objectives are the main
reasons for real-time reservoir
management. Real-time technologies
can be applied when the first well
is drilled in a field. High-resolution
3D seismic surveys help to delineate
the detailed structure of the field
and provide the baseline for future
monitoring of fluid movement.
Once the field has started to
produce oil and gas, real-time
reservoir management helps to
maximize production, minimize
operating expenditure, maximize
recovery, and extend the productive
life of the reservoir. These benefits
rely, to a large extent, on the asset
team’s ability to collect, process, and
analyze large volumes of data and,
crucially, to translate these analyses
into corrective actions.
Systems built on dynamic databases
will upgrade the reservoir model
continuously and provide the asset
manager with the best and latest
information for optimizing the
economic model that the company
has chosen for the field. Sophisticated
reservoir simulators may be used on
a daily basis and become an integral
part of the decision-making process.
These advances will allow the
industry to improve its financial
returns and to respond faster and
more effectively to changing oilfield
and market conditions.
A major consequence of these
trends will be that, in the future, a
small team could handle the entire
reservoir-management process. The
team will use advanced software
systems to integrate all the tasks
of reservoir management in a
transparent manner. This system
will handle a continuous feed of
automatically acquired data. The
reservoir team will then be able to
analyze these data, update the
reservoir model, make predictions
and recommendations, and implement
the recommendations, subject to
management approval.
Number 5, 2004
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66 Middle East & Asia Reservoir Review
Delineation
Maximize production
Speed is of the essence
Real-time reservoir management will
allow asset teams to identify quickly,
and then capitalize on, opportunities
to improve field productivity and
efficiency. The new approach reduces
cycle time, which allows the asset team
to identify and rectify problems rapidly
with less disruption to production.
This approach also promotes rapid
assessment of data that will modify
the reservoir model, thus enabling
the earth scientists to reach a better
understanding of asset structure and
reservoir engineers to make betterinformed development decisions.
Achieving this will require the
integration and modification of diverse
technologies that give the asset team
improved understanding of the day-byday performance of the field and the
means to assimilate this information
and transform it into good business
decisions. A cooperative approach,
where operators work with key
research and development companies,
vendors and, even, other oil companies,
will help to ensure that the technology
is developed quickly and efficiently,
and at a reasonable cost.
The result could be assetmanagement systems that link data
from the reservoir, well, and facilities
monitoring and sensing devices directly
to the subsurface model (Figure 4.22).
This approach would support asset
team decisions and help to capture
and retain each individual’s knowledge
of the asset more effectively. The
challenge is to integrate existing and
emerging technologies and to modify
work processes to take full advantage
of these opportunities. In some parts of
the industry, these changes are already
taking place.
Exploration
Middle East & Asia Reservoir Review
67