Indiana University Research & Creative Activity January 1998 Volume XX Number 3

Predicting Petroleum Reservoir Potential:
Computer Modeling of Basins
by William Rozycki

In his office at the Indiana Geological Survey, John Comer, a senior scientist at Indiana University, points to a well log from the Piceance Basin in Colorado. Wavy lines, like those of a seismograph, run vertically down the accordioned pages, and Comer's notes fill the margins. The log is from an experimental well commissioned by the U.S. Department of Energy in the Piceance Basin, an area with abundant coal and natural gas deposits. "These wavy lines indicate the density, fluid saturation, sonic velocity, radioactivity, and other properties of the rocks surrounding the borehole as detected by sensors as they are pulled through the borehole," Comer explains. His job at the Geological Survey at Indiana University Bloomington is to correlate this information with the alternating layers of sandstone, mudstone, and coal through which the exploratory well was drilled.

When Comer has assigned the readings to specific rock types at each foot of depth, he sends the data on to Peter Ortoleva, a distinguished professor of chemistry and geological sciences at IUB. Ortoleva and his team at the Laboratory for Computational Geodynamics then use the data to predict an extractable petroleum reservoir.

The data from the Piceance Basin is one of a number of sources that feed this ongoing research. Ortoleva and his laboratory team also draw on findings at basins in Texas, the Gulf Coast, and the North Sea, in their novel quantitative approach to geological systems: a computer simulation model using algorithms to replicate the complex processes by which organic sediment is turned into fossil fuel. With sufficient raw data, accurate algorithms, and modern computer power, the simulation predicts where petroleum reservoirs will be found, and which of them will be economically viable for production.

In addition to Colorado's Piceance Basin, this research applies to about one thousand other basins scattered around the world. In these basins, natural geologic processes have buried and sealed layers of sediment. Heat and pressure have worked over tens and even hundreds of millions of years on the organic matter trapped in the layers. The result is often the creation of fossil fuels: coal, oil, and natural gas. Previous methods of predicting such deposits have looked at simple, well-known processes, correlating, for example, the presence of organic sediment with a depth suitable for the development of heat and pressure. These methods are useful for predicting the presence of fossil fuels, but not for indicating the size, shape, and location of the reserves. More crucially, in the case of oil and gas, previous methods have failed to predict when the rock layers holding petroleum are sufficiently permeable to allow extraction.

The model developed by Ortoleva and his research team, using the acronym CIRF.B (Chemical Interaction of Rock and Fluid simulator for Basin analysis), not only predicts the presence of oil or gas, but also the porosity and permeability of the rock holding it. In addition to handling the large-scale parameters of a total reservoir, the model predicts the interaction of grain-scale to kilometer-scale mechanical and chemical processes. The model is three dimensional, so reservoirs are characterized by depth, length, and width. By applying algorithms that calculate the microscopic geological processes at work, and by factoring in the age of the layers, the model can predict the degree of natural fracturing within rocks. In many rocks, such as those in the Piceance Basin, fracturing makes the difference between reservoirs from which fluids can be extracted, and those from which production is not economical.

The geological formation of petroleum involves a complex network of coupled RTM (reaction, transport, mechanical) processes. These processes are interdependent on chemical reactions, mass transport and fluid flow, and mechanical forces at work in the earth. Through modeling, the laboratory team must effectively represent each of a wide variety of processes that are acting simultaneously, as well as preserve all the interactions taking place among these simultaneous processes. For example, changes in the porosity of a layer of sediment affect the mass and energy transport through that layer, which influences the temperature acting upon the layer. Temperature-dependent chemical reactions in their turn influence porosity. The computer model takes these interactions into account, using iteration (continuous feedback) procedures to simulate the changes that occur in nature.

Predicting the permeability of the rock is a particularly important task because the type and degree of connections between pores influence the ability of a well to produce natural gas and crude oil. The volume of interconnecting pores can be increased significantly by fracturing. The degree of fracturing is related to the stress, fluid composition, fluid pressure, and thermal histories of a given rock layer. The task of predicting this type of natural porosity is daunting. Ortoleva's CIRF.B simulator fully addresses all of the simultaneous processes, including rock formation, fluid and mineral reaction, and fluid transport. Data describing rock texture and composition of the grains in the known layers at selected sites in the sedimentary basin are entered into CIRF.B. The team then adds thermal, seismic, aeromagnetic, gravitational, electro-conductive, and other information.

Handling the vast amount of data generated by the linked algorithms requires considerable computing power. CIRF.B usually runs on a parallel processing computer in Ortoleva's laboratory. But for large simulations, Ortoleva's team uses a new 64-unit parallel processor at IUB's University Information Technology Services, the Origin 2000. "We could use our own computer for the data if we had weeks or months to wait for the results," Ortoleva explains.

The enormous amount of data needed for the simulations, the skilled scientists and programmers required to develop the equations and solve them, and the computing power to process this information‹all are supported by funds from both government and industry. "If our model can improve extraction by just 5 percent over present levels, then that's billions of dollars added to our national economy," Ortoleva states. "That's the significance of our work at the practical level. And at the same time, we're gaining new insights into problems in physical and geological sciences."

Ortoleva points out, "We cannot in good conscience expect the government and society to continually support our scientific efforts if we don't give something useful in return. But beyond that," he says, "the pursuit of practical applications yields fundamental results for science." He cites as an example his work on the flow of salt beds in basins, a part of the larger modeling study. "Under heat and pressure, salt beds sometimes behave like liquids. We have been able to study the flow of salt beds, and that has given us new insights into the self-organizing and chaotic dynamics of this highly nonlinear rheological system." The Gas Research Institute is funding the study of salt-bed flow. "Without the interest and funding from the gas industry, we never would have been able to gain these insights," Ortoleva states. "Other industry- and federally supported projects ongoing in my laboratory have led to breakthroughs in our understanding of other fundamental problems, such as self organization in phase transition, Markov processes in nonlinear mechanics, morphological instabilities, and boundary layer phenomena."

Starting out as a physicist (he received a Ph.D. in applied physics from Cornell University in 1970), Ortoleva has come to computer modeling of geologic formations through his long-standing interest in the concept of self-organization. The principles by which natural systems organize in complex manners fascinate him. "An example," Ortoleva explains, "is the human heartbeat. It continues in a regular pattern, without externally imposed timing. Unlike a linear oscillator, it draws energy from its surroundings to sustain oscillatory pumping."

Ortoleva focused his work on one aspect of self-organization, culminating in his 1992 book Nonlinear Chemical Waves. In the late 1970s he recognized that the natural growth of crystals in rocks was a clear example of self-organization. This realization brought him into the field of geochemistry, and resulted in a recent book, Geochemical Self-Organization. Though Ortoleva heads a major computer application project, no special interest in computers brought him to the modeling work; for him, computers were simply the best tools. "Although I have long enjoyed analytical, mathematical approaches, when handling so many numbers, computers are the only way to go," Ortoleva explains.

The multi-disciplinary project draws on the varied backgrounds of the team at the Laboratory for Computational Geodynamics, based in the Chemistry Building at IUB. The postdoctoral researchers and graduate students in the lab have backgrounds in physics, mathematics, computer science, chemistry, civil engineering, geology, and other fields; the design, operation, and testing of the CIRF.B simulator requires all their experience and knowledge.

This ambitious and comprehensive project also draws on outside sources for collaboration in data and research, as well as for funding. Scientists at Oklahoma State University, at the Institut Français du Pétrole, and at oil companies such as Chevron, Phillips, and Mobil, have all had a hand in some aspect of the project. Funding has come from the gas industry, oil companies, the U.S. Department of Energy, the U.S. Environmental Protection Agency, and the National Science Foundation.

The application of the model does not stop at predicting oil and gas reservoirs‹and it doesn't stop with our planet. "The computer tools we're developing," Ortoleva notes, "apply to planetary research." The NASA Johnson Space Center is collaborating with Ortoleva's laboratory to determine the evolution of subplanetary bodies in the early solar system. The computer model now in place will be fed data from astrophysics and then predict the process by which primitive bodies in space underwent changes to become our present planets and moons.

The Piceance Basin project comes full circle back at the Geological Survey with John Comer. Comer, who received a Ph.D. in geology from the University of Texas at Austin, and who currently heads the Geochemistry Section at the Geological Survey, brings to the project twenty-five years of experience in applied and basic research. His varied professional background includes three years at Amoco's international research center, thirteen years as an assistant and associate professor of geosciences at Tulsa University, and nine years as a senior scientist at IUB. Beyond collating and evaluating the data from Piceance Basin wells for CIRF.B, Comer draws on his geological knowledge to critically evaluate the computer model. Does the model simulate fractured reservoirs that look like what really occur in nature? With the output checked and modified by Comer's practical experience, the project moves ever closer to that day when accurate pinpointing of extractable reserves will raise exploration and production efficiencies. E

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