SPE 143923
Transforming a Digital Reservoir System into Reality: How to Get Things
Right
D.A. Castillo SPE, M. Bratovich SPE and R. Early SPE, Reservoir Development Services, Baker Hughes Inc.
Copyright 2011, Society of Petroleum Engineers
This paper was prepared for presentation at the SPE Digital Energy Conference and Exhibition held in The Woodlands, Texas, USA, 19–21 April 2011.
This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been
reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers, its
officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. Permission to
reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright.
Abstract
The geophysical, geologic, engineering and operational data that makes up the digital spectrum of information in
the energy industry certainly has value when analyzed within its respective discipline. Elevating this value to
create attainable dividends in the context of the overall reservoir development will depend upon our relentless
commitment to integration. This will be especially important as the targeted reservoirs become more complex,
volumes smaller, environments more challenging and our need to intervene to enhance production becomes an
integral part of field management.
An incomplete or incorrect understanding of the earth model (reservoir and overburden) can result if we fall short
in utilizing all data gathered, or ignore or incorrectly interpret the information at hand. This is especially true in
today’s world of lean resourcing strategies and pressures of reduced decision cycles times. The value of
integrating and rigorously interpreting the wide range of data collected from modern technologies and optimizing
or automating the workflows can become a measured reality that serves to maximize reservoir performance
during a field development program.
As scientists and engineers who are charged with responsibly exploring and exploiting earth’s resources,
understanding the geomechanical and flow dynamics and petrophysical rock character existing over the entire
life-cycle of the reservoir, especially during production and field rejuvenation, positions us to better use modern
drilling and completion technologies for optimal well planning and reservoir drainage. Constraints on how the
reservoir, overburden, faults and natural fractures behave in time and space will be directly linked to how well we
have integrated our data to understand the reservoir and how well we execute a fine-scale production monitoring
program.
Integrating this expected influx of digital information will require an industry-wide paradigm shift in how we
manage, evaluate and interpret information. The purpose of this paper is to use case studies to describe the
critically important role geomechanics, petrophysics and reservoir performance analysis plays in an integrated
interpretation with the intent to develop and execute effective management strategies.
Problem Definition
The present-day physical state of the reservoirs we are actively exploring and exploiting is a complicated system
due to its complex geologic and tectonic history. Understanding the spatial and temporal nature of how the
reservoir(s) vary is largely limited by the data collected (seismic, well and production data) and in some cases,
further limited by an incomplete or narrow interpretation that fails to capture a more integrated approach to
reservoir management. Despite the fact that the oil and gas companies have access to a vast array of modern
technologies capable of collecting high-resolution seismic, in-situ information while drilling, during wireline logging
and during production, operators still struggle with confidently predicting drilling and reservoir performance.
2 SPE 143923
This is not new news, but it is nonetheless surprising given our current-day technologies have never been better.
Within our ranks are highly trained experts, specialized and committed to professionalism. When these
technologies and people work together complex drilling and reservoir issues can be addressed in an integrated
manner. That’s the theory. In practice, this flow or exchange of information is difficult to manage, even for the
most talented. Mistakes still occur during drilling, our understanding of the reservoir is still incomplete and our
production predictions do not always come to fruition.
Technology today in the oil and gas industry has never been better. In the last few decades, technology has
provided the opportunity to remove many of the barriers that forced us to use our intuitive talents. Along with this
growing plethora of information, more advanced technologies have enabled us to explore and exploit reservoirs
previously believed to be too difficult to reach and characterize (e.g., subsalt, unconventional and ERD). And yet,
we still get it wrong sometimes.
Perhaps we need new ideas and perspectives to better understand the mechanics of our assets. Hydrocarbon
reservoirs cannot be classified as a closed system in isolation from the surrounding environment. Reservoirs are
open to external processes and forces, some of which are controlled by nature and some manipulated by human
intervention. The complexity of our hydrocarbon reservoirs is constantly being highlighted by the emergence of
new technologies making advanced measurements in space and time. The plethora of information types when
examined in isolation makes it very difficult to model the self-regulating behavior of reservoirs because we fail at
treating this new information as part of a greater system of science and engineering components. An important
question to ask ourselves is how can we enhance our protocol in communicating the learnings from each
specialized discipline so as to interpret and model with the intent of understanding the reservoir as a ‘system’?
In 1947, a mathematician named Norbert Wiener coined the term Cybernetics that broadly describes the self-
regulating interactions between nature and human intervention. It is a science of direct and targeted control of
complex processes (Blanchard and Fabrycky, 2006), which in our case, is the reservoir. Cybernetics rests on the
premise that these complex systems can be unified by a systematic integration of multidisciplinary subsystems we
have neatly separated into nature (geologic processes) and human intervention (engineering).
Feedback is paramount to cybernetic processes. More specifically, we are confronted in the hydrocarbon energy
business by a dynamic system of governing laws in physics, chemistry, earth processes and engineering
sciences that requires transparent communication across these disciplinary boundaries if we are to understand
their interrelationships and extrapolate learnings away from the borehole to predict reservoir performance.
Technology
The state of humankind today is the product of the progress technology has made, especially in the last two
centuries. Our lives and our ability to achieve what humankind has accomplished have resulted, in many
respects, in a better life. The development of new technologies comes from an industry-based “pull” driven by a
self-demanding “push” to enhance our understanding of complex systems, which in our case; the complexity is
our hydrocarbon reservoir system.
We can easily resort to living comfortably within the boundaries of our specialized technology, whether it is
geologic, geophysical, chemical, or engineering, and in some respects we can view this segregation as an effort
to ensure a better chance of achieving success in our own right. However, the interaction between natural and
human-made systems tells us that the boundaries between these various self-imposed disciplines are blurred.
Despite the inherent complexities each of these specialized disciplines holds, it is the interpretation and inter
connectivity of operative processes in each of these separate disciplines that will enable us to understand the
complexity and purpose of the reservoir system.
This information has resulted in an additional problem that will continue to challenge us as we endeavor to
accurately integrate a wide range of multi-disciplinary information to better understand complex reservoir systems.
Basically, we don’t get it right because of simple mistakes or we don’t invest enough time to understand the
reservoir as a system.
Human Capital
The new information generated using modern technologies has expanded our awareness of how nature operates,
and at the same time, has taxed our ability to properly manage this information for maximum benefit. These
problems are not unique to the energy industry. They occur in engineering, medicine, investment banking,
SPE 143923 3
government and other ventures where our ability to manage the complex nature of our science has far exceeded
the ability of individuals and disciplines in isolation to reliably and correctly synthesizes information in the context
of a system of processes.
There are basically two reasons why mistakes occur in our industry, or any other industry for that matter. The first
reason is due to ignorance. Ignorance usually stems from the absence or incompleteness of information available
at the time critical decisions are made. For instance, during the exploration, appraisal and development stages of
the reservoir life-cycle, there was limited data needed to quantify the geologic complexity of the basin and
therefore accurately predict attributes of the reservoir and overburden. Acquiring high-resolution 3D seismic data
coupled with sophisticated basin modeling and real-time information may remove many of the unknown elements
that contributed to that ignorance.
The second reason why mistakes occur in our industry is because of ineptitude. Mistakes due to ineptitude occur
because we either failed to apply the information we had access to, failed to apply the information correctly or we
failed to even acquire the information. The consequence of any of these is the failure to reach our objectives. The
failure to get it right could be due to lack of discipline or skill in using the information readily available in a creative
and integrated manner. This is not an indication of short-comings in intelligence. The professional behavior of
individuals and teams in handling available information in a simplistic manner has more to do with the difficulty in
integrating a broad range of multidisciplinary data that may be outside of any individuals’ expertise.
Capturing experiences in the medical industry, Gawande (2010) summarized that highly trained professionals are
faced with two strong tendencies for failure. The first tendency is related to our human nature and it’s fallibility for
memory recall exacerbated by environmental distractions. This is especially true when a few or many routine and
mundane tasks are overlooked which could lead to poor or misinformed decisions later. The second tendency is
also related to human nature but it’s driven by a rational decision to skip routine steps because it’s believed it
simply does not matter much or is not important. We are not referring to the disciplined responsibilities of a risk
management specialist; clearly, these individuals have an important role in any industry. It’s these routine tasks
that have value which, when not completed properly or not completed at all, do not always lead to failure; until the
one day it does matter and then the consequences can be grave. To help avoid falling victim to our own human
tendencies, Gawande proposed a checklist manifesto to be used in medical emergency room practices. The
outcome was a dramatic reduction in human procedural error and patient fatalities.
Specifically, without falling victim to innocent and inevitable human error, how do we keep track of the volume of
information collected prior to and during the drilling process in our exploration and development drilling programs,
whose value and correct interpretation serves to enhance the experience and knowledge of our scientists and
engineers? It would appear that we need a strategy that forces us to be more systematic in how complex
decisions are made. In a sense this strategy cannot be an added layer mounting on top of what is already a
complex situation.
Reservoir Systems Engineering and Approach
Establishing an approach to field development or field management for hydrocarbon reservoirs is usually a
function of the background and experience of an individual or organization. From the outset, if the reservoir were
treated as a complex system of interacting processes, the approach to reservoir systems engineering would have
to adopt a culture of interdisciplinary collaboration to derive, refine, and verify a life cycle appreciation which
satisfies expectations of maximum reservoir exploitation. Details of how this approach can be efficiently executed
follows four basic principles.
1. Top-Bottom approach to reservoir system analysis
The subsurface nature of hydrocarbon reservoirs forces us to use remote or in situ measurements to characterize
the ways our engineering practices embedded in a natural environment interact; desirable and undesirable.
Clearly, we have today an arsenal of advanced technologies designed to perform focused tasks or make specific
measurements, but before these are unleashed in our front-end engineering program, understanding how the
natural world operates should drive a top-down approach to establish a baseline understanding of our reservoirs.
It is not uncommon in our industry to initiate a bottom-top approach especially when we start out with the premise
that a particular technology that worked in one reservoir (somewhere else on the planet) would work equally well
elsewhere. Not fully capturing the natural processes that have shaped and transformed our reservoir through
geologic time, as well as the present-day dynamic forces that temporally and spatially impact reservoir
performance, leaves us in an unfortunate position of not focusing on the reservoir as a ‘system’.
4 SPE 143923
2. Perspective thinking within a reservoir system life-cycle framework
Some of our reservoir management experiences have shown us that achieving an understanding of a reservoir
system that is operating in an optimal manner was not a consequence of efforts solely applied after the reservoir
came on line. A seriously disciplined approach of understanding the reservoir system in the early stages is
needed to ensure the system design, development and management captures the life-cycle of the reservoir
system. In this case the life-cycle begins with a thorough understanding of the reservoir fabric and subsurface
fluid properties inferred from well and seismic data, interpreted in the context of the geologic history. Once these
conceptual ideas have been thoroughly measured and verified, it becomes a well-constrained process of detailed
design and development, production and reservoir rejuvenation.
3. Top-down reservoir system design traceability across subdisciplines
Predicting reservoir system performance is as difficult as predicting geology. There is certainly a well
accomplished practice of descriptive geology, but predicting geologic fabric and subsurface fluid flow properties is
an extremely difficult enterprise. Prior to executing a field development project that captures the reservoir system
life-cycle from reservoir appraisal to reservoir rejuvenation, there needs to be a parallel and disciplined design
process that loops feedback information across the multidisciplinary community to ensure the effectiveness of
early decisions. This is imperative because all too often we experience cases where valuable information from
one technical discipline was never looped back to evaluate whether this new information or interpretation could
impact the design process for other technical disciplines.
This disciplined traceability process forces us to preserve the top-down integrity of our reservoir system analysis.
In this context, this looped back information compels us to re-evaluate recurring questions about how this
information impacts our understanding of subsurface fluid properties, and in turn, impact our predictions of
reservoir performance. A common consequence of failing to practice disciplined traceability processes results in
greater individual re-design efforts during the later stages of the life-cycle.
4. Integrated and disciplined culture
Perhaps the most intuitively obvious process necessary to capture the essence of a reservoir system involves
ensuring a multidisciplinary team approach is implemented. Establishing a culture of integration across multiple
disciplinary groups that are measured by how well they integrate is paramount to a sound design concept. This
team culture would echo the same reservoir questions and embrace identical design objectives in an efficient and
effective manner. It is a daunting challenge because it requires a complete and thorough understanding of the
various design disciplines, especially in how the data and technologies are interrelated.
However, this culture of integrated disciplines is difficult to create, retain and manage. Although there is certainly
the shortage in human capital and expertise required to establish a baseline talent pool, perhaps the largest
obstacle is the shortage of open lines of communication or shared framework perspectives. We are not referring
to an unwillingness to communicate. Rather, a multidisciplinary group is often made up of members who may be
legends in their own right but their expertise is not always communicated in a perspective outside of their own
reference. It requires a dedicated and disciplined approach from leaders who can force a culture of integration
into existence by educating members of the team that their respective disciplines are interrelated to one another.
Case Studies
It would be futile to treat a particular case study as an example of what happens when the design team gets it
right. It’s unfortunate, but these case studies don’t exist. They don’t exist for very legitimate reasons; the earth is
complicated and we are still learning as go. Perhaps, if reservoirs were all created equal, we could learn
empirically how to avoid mistakes, catch surprises before they become a detriment to reservoir performance and
maximize reservoir performance by optimizing well placement in a constant unchanging system. Even reservoirs
with similar fluid types and similar porosity/permeability properties will behave differently depending on where they
are on the planet. As scientists and engineers charged with exploring and exploiting hydrocarbons across the
globe, we are broadening our search window to include harsh environments where information is sparse or
technological capabilities are limited.
However, there are cases where information was available but was not fully appreciated or utilized in a manner
that would have maximized their understanding of the reservoir system, and in turn, would have designed their
field development program for optimizing well placement to maximize reservoir performance.
SPE 143923 5
Fractured Reservoirs
In one case study, an operator developed a well placement strategy dictated by drilling directional wells that
maximized each well’s exposure to the greatest population of natural fractures, knowing that fracture permeability
was controlling reservoir permeability. Reservoir performance was clearly economical since this field had over a
thousand wells in multiple structures. A geomechanical model had been constructed for the structure but closer
examination found that the data interpretation was incorrect based on flawed physics. The immediate impact of
formulating an accurate and robust geomechanical model was the realization that there were critically-stressed
natural fractures that were of a particular orientation and placement suitable for controlling directional permeability
in the reservoir. This new information which more accurately described the reservoir system was incorporated in
the well placement strategy such that a new directional drilling program was implemented to intersect these
critically-stressed natural fractures with the wellbore. The result was a six-fold increase in sustained production.
Directional and Secondary Reservoir Permeability
Nearly ten exploration and appraisal wells were drilled to delineate an offshore gas field. A series of drill-stem and
production tests were used to define the subsurface fluid flow matrix. In this particular field, the major reservoir-
bounding faults are sufficiently stable for providing a regional seal for hydrocarbon trap integrity. Although the
present-day stress state in the field is consistent with a critically-stressed crust, the reservoir-bounding faults are
not optimally oriented for shear failure that could compromise fault seal integrity. However, fault zones are
inherently characterized not by a single fracture plane but rather a broad zone of distributed fractures that bound
the principal displacement zone of the reservoir-bounding faults. Some of these fractures are optimally oriented
with respect to the present-day stress field and would therefore be capable of enhancing directional permeability
in the reservoir, albeit, in a spatially focused context in close proximity to the faults. This information was not
recognized at the time the field development well placement designs were created. As a consequence, some
wells unexpectedly over-performed because it was not recognized that secondary reservoir permeability existed.
Other wells unexpectedly under-performed due to subsurface fluid flow was locally influenced by the secondary
reservoir permeability. If the geologic structure been interpreted in the context of fault mechanics and the present-
day stresses operative in the reservoir, well placement would have been designed differently.
Unconventional Reservoir Systems
The ability to accurately quantify the mineral composition of a reservoir is a relatively new technology.
Petrophysicists and geologists may inherently appreciate the implications to improved reservoir characterization
this technology can provide but drilling engineers as well as other discipline specialists may view the increased
logging time as a negative rather than a positive. The value of this technology has been best illustrated in the
evaluation of unconventional reservoirs.
In the early stages of exploration and exploitation of shale gas reservoirs vertical wells were routinely referred to
as “science wells” and used to acquire as much technical information about the reservoir as possible. In one
instance two wells were drilled by an operator in the Haynesville shale in North America (LeCompte, et al., 2009).
Previously the operator had drilled, logged, stimulated, completed and brought on line wells that appeared to be
similar yet experienced significantly different production performance. In these two wells the porosity, TOC, and
mineralogy were similar and differences in computed fracture gradient could be attributed to a difference in
vertical depth. The fracture and production performance of the two wells was not the same. One well produced
75% less gas than the other. Tracer logs were run which indicated that most of the hydraulic fracture energy
propagated along the wellbore without significant formation penetration. After study, the difference in
performance was determined to be the intervals selected for perforation and their lithology/mineralogy
differences. Analysis showed that there was a correlation between reservoir performance and perforation in the
siliceous facies intervals determined from the mineral spectroscopy data. Perforating the siliceous facies intervals
also resulted in more contained fracture containment which resulted in increased lateral fracture propagation. In
addition, the ability to characterize the reservoir mineral composition allowed a stimulation treatment program to
be developed which reduced possible negative consequences related to pre-stimulation and stimulation fluid
composition with the reservoir.
The Future
Oil and Gas resources are becoming more challenging and expensive to develop. This challenge can be
demonstrated in the deepwater developments around the world (Gulf of Mexico, West Africa, and Brazil) where
the high cost environment and the corresponding pressures on cycle time and reservoir complexity have resulted
in more reservoir characterization uncertainty being carried over into the development phase. Once in production
many operators are finding that fields are underperforming. To continue to support these investment decisions the
industry must develop more efficient work practices and enhanced analysis techniques to provide greater
6 SPE 143923
assurance that reservoir and well performance ranges are fully described and characterized and that risks can be
mitigated.
Despite the advances in data gathering using modern technologies, the interpretation and analysis of the data
gathered is often undertaken using simplified analytic models which are insufficient to predict the multi-scale
(spatial and temporal) inflow characteristics of the well and reservoir structural performance in the near wellbore
region. The use of these tools for design and analysis generally leads to overly simplistic analyses of what is a
complex nonlinear problem, and often results in sub-optimal decisions due to the inadequate prediction of
outcomes and uncertainty ranges.
These applications must expand the seismic to simulation common platform applications to incorporate the well
and production aspects thus allowing data to be processed via integrated workflows and analyzed more
rigorously across the classical discipline boundaries to ensure effective exploitation of the reservoir’s resources
throughout its life-cycle. In essence Operators require solutions that deliver:
• High performance wells and completions that yield the predicted recoveries per well and well production
rates so that well count can be reduced,
• Reliable wells and completions to avoid incurring the high cost of intervention, and
• Robust reservoir management and flow assurance solutions consistent with the complexities of subsea
development and operations that provide flexibility to respond to production uncertainties.
Conclusion
We have before us an opportunity to better manage the data that our modern technologies can provide today. It’s
merely a question of how we organize ourselves to invest in the time needed to understand this new and
multidisciplinary information in the context of a ‘reservoir system’.
Norbert Wiener also offered a word of warning to remain diligent in our stewardship of new technologies by
stating "The future offers very little hope for those who expect that our new mechanical slaves will offer us a world
in which we may rest from thinking. Help us they may, but at the cost of supreme demands upon our honesty and
our intelligence."
References
Blanchard, B.S. and Fabrycky, W. J. 2006. Engineering Systems and Analysis, fourth edition. Upper Saddle
River, New Jersey: Prentice-Hall International.
Gawande, A. 2010. The Checklist Manifesto-How to Get Things Right, first edition. New York, New York:
Metropolitan Books.
LeCompte, B., Franquet, J.A. and Jacobi, D. 2009, Evaluation of Haynesville Shale Vertical Well Completions
with a Mineralogy Based Approach to Reservoir Geomechanics, SPE 124227, SPE Annual Technical Conference
and Exhibition held in New Orleans, Louisiana, USA, 4–7 October 2009.
