Three Generations of Reservoir Modeling
Scott W. Tinker
Bureau of Economic Geology, Austin, Texas
It has been said many times, perhaps correctly, that most of the “easy stuff” has been found. Global oil and natural gas production will come from increasingly more complex reservoir systems. Because complex reservoirs require significant technological understanding and advanced reservoir management to make oil and gas recovery economic, the need for advanced reservoir characterization will increase in the 21st century.
Over the past two decades, a growing percentage of global reserve additions have come from enhanced recovery in known—and more complex—fields. In other words, we are discovering as many reserves in known fields as we are in new fields. Over the past several years U.S. reserve growth has accounted for as much as 80% of annual “new discoveries,” compared with 20% added from new-field discoveries. Reserve growth—reserves added as an extension of known fields, through reserve estimates revisions, by new-pool additions, and as a function of application of new technology to improved recovery—is expected to continue to play a major role in future reserve additions globally. The need for advanced reservoir characterization to produce fossil energy resources efficiently and economically has never been greater.
When my father joined Shell Oil Company in 1955, “development geology” was largely a 1-D well-bore process. Development geologists in the 1950’s supported engineers and helped identify “good sands” to perforate from spontaneous potential and resistivity logs. Fields were being discovered across the United States, most were on primary production, and well spacing was commonly uniform. The need for advanced reservoir characterization as we know it today did not exist then.
Throughout the 1960’s and 1970’s—led by some of the major oil company research labs and supported by several key universities—studies of modern depositional systems (sensu Ball, 1967; Bernard et al., 1970; LeBlanc, 1972) and ancient outcrops (sensu Pray, 1961; Wilson, 1967) resulted in advanced understanding of ancient depositional systems (Fisher and McGowen, 1967) in the subsurface. Two-dimensional studies of oil fields consisted of linking well-log cross sections, supported by qualitative core descriptions, between wells and constructing isopach and structure maps to identify sand trends (Berg, 1968; Sneider et al., 1978). Maps were used to calculate volumetrics and to help design field management strategies. Two-dimensional seismic data resolution was too poor to support development geology, and stratigraphic understanding as we know it today was too poorly understood to help construct adequate reservoir architecture frameworks.
When I began working in the industry in early 1980’s, there was a growing need for secondary and tertiary recovery processes in many of the larger U.S. fields. Development geology became known as reservoir geology, no longer simply a well-based process to identify key productive sands, but instead one of true volumetric reservoir understanding. Multidisciplinary approaches—integrated teams of engineers and geoscientists—were beginning to be recognized for the value they added to the corporate bottom line. Seismic stratigraphy, introduced by several seminal papers in AAPG Memoir 26 (Vail et al., 1977), was becoming mainstream for exploration-scale studies but for the most part was not yet being applied at the field scale, and reservoir work was still done using paper logs, seismic sections, and hand-drawn maps.
In the late 1980’s and 1990’s—with the explosion of computer technology, digital data, 3-D modeling software tools, and the early promise of 3-D seismic—rock, log, seismic, and production data began to be fully integrated into digital reservoir models, visualized in color and animated 3-D space. The term “flow units” (Ebanks, 1987) was introduced as a means to capture the understanding that reservoirs behaved as volumes.
Advanced outcrop studies were being conducted to define the nuances of high-frequency sequence stratigraphy and to place reservoir parameters into a proper stratigraphic framework (sensu Sonnenfeld and Cross, 1993; Kerans et al., 1994). Lessons from the outcrop were being applied at the reservoir scale to open new levels of reservoir architecture understanding (sensu Tinker, 1996), and complex 3-D models were being scaled up and used in fluid-flow simulation. Modern 3-D reservoir characterization had arrived (Kerans and Tinker, 1997; Uland et al., 1997; Chapin et al., 2002).
When my kids enter the energy industry in the 2010’s, theirs will be a 4-D world of instrumented fields and real-time data streaming. They will face many exciting challenges, including
- Linking matrix properties, diagenetic process and products, and fractures of all scales to result in a total system permeability understanding.
- Evolving from a scalar (magnitude) single-component seismic world, through a vector (magnitude and direction) multicomponent seismic world, into a tensor (Nth dimensional space) anisotropic seismic world to improve our knowledge of complex permeability and dynamic fluid systems.
- Processing, interpreting, and integrating 4C3D (four-component, three-dimensional), 9C3D, and 9C4D seismic data with other subsurface data using rock and fluid physics, rather than statistical approximations.
- Applying land- and air-based laser, radar, electromagnetic, and other remote sensing technology to advanced 3-D outcrop understanding, and linking that understanding to the subsurface.
- Designing reservoir management plans—including risk and economic analysis—that take full advantage of the 4-D reservoir understanding.
- Applying the remarkable knowledge from the energy industry to broader societal challenges such as sequestration of greenhouse gases, efficient management of the commodity called water, and safe disposal of radioactive wastes.
The editorial at the beginning of Forbes Magazine commonly begins, “With all of thy getting, get understanding.” We in the energy industry have certainly been getting—all types of surface and subsurface data, cutting-edge computer hardware and software, advanced operational technology that allows us to explore the most remote regions on the planet—for the past 50 years. As we transition to a global gas economy over the next several decades, advanced characterization, which takes advantage of all of the data that we have been “getting,” will be critical in order to understand the evermore complex hydrocarbon reservoirs that we will encounter.
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