Geologic Modeling and Uncertainty Analysis of a Gulf of Mexico Reservoir
Yuhong Liu, Peter G. Rigsby, Rohit Sinha, Steve Peterson, Joy Thomas, Gregory Zimmerman, 2011. "Geologic Modeling and Uncertainty Analysis of a Gulf of Mexico Reservoir", Uncertainty Analysis and Reservoir Modeling: Developing and Managing Assets in an Uncertain World, Y. Zee Ma, Paul R. La Pointe
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Uncertainty analysis in a deep-water turbidite reservoir in the Gulf of Mexico is discussed in this chapter. Six major factors were addressed in the study to capture uncertainty: reservoir compartmentalization; acoustic impedance (AI) attenuation caused by the salt overhang; AI attenuation caused by fluid effects; petrophysical properties; pressure, volume, and temperature; and aquifer strength uncertainty. We characterized and quantified the uncertainties in the reservoir by integrating information from various disciplines: geophysics, petrophysics, geology, and engineering. This uncertainty workflow enabled us to make sound business decisions in a timely manner.
A base case scenario model was first built integrating well and seismic data. Multiple realizations were then simulated by varying petrophysical parameters such as porosity, permeability, and saturation; turning on and off various potential barriers; and processing the impedance volume for different scenarios. The effect of the drive mechanism on ultimate recovery was also studied by running scenarios with varying amounts of aquifer size and strength. The outputs of various scenarios were compiled to generate a probability distribution curve of the expected reserves and production rates. The outputs were then incorporated into an economic model to evaluate the viability of the project.
The field in this study was discovered in 2001 with the drilling of the exploration well 3 (Figure 1). Two sidetracks were subsequently drilled from the discovery well to delineate the size of the reservoir. After analysis of all available data, it did not appear that the reservoir potential, considering the expected costs of developing this remote field, would provide an economic project, especially with oil prices fluctuating between $20 and $30/ bbl at the time. Analysis of this opportunity continued throughout the next several years, but the project remained uneconomic.
A commercial agreement was reached with a host platform to process the production in 2007. The increase in oil prices further improved project economics. However, an increase in project costs accompanied the increase in oil price, and a great deal of uncertainty associated with reservoir performance still exists, despite having drilled three additional wells in the prospect area. Because of the immense cost associated with this project, coupled with the limited and uncertain resource base, it was paramount from a business perspective that the range of possible outcomes for this project be defined so that the economics could be evaluated from a stochastic perspective. Providing a range of possible outcomes is required in the portfolio management tool as it provides the management with more information than one can glean from a single deterministic economic scenario.
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This publicaton presents a comprehensive survey of cutting-edge approaches used by industry to quantify the uncertainty in both conventional and unconventional reservoirs. Balanced between case histories and theory, the chapters in this volume equip experienced practitioners and those just entering the field with the theory, workflows and case history examples needed to make better reservoir management decisions in the uncertain world of the modern oil and gas field.