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.

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, 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‟.

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 we 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.

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 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.