SBIR/STTR Phase I: Analytic Simulation Method for Oil/Gas Field Management and Optimization

This Small Business Innovation Research (SBIR) Phase I project assesses the feasibility of new oil and gas reservoir management tools for optimization of hydrocarbon recovery. It proposes extension of state-of-the-art analytic solution methods for potential flow in porous media from 2-D to 3-D. It will incorporate 3-D analytic fluid flow simulation technology into large-scale optimization routines where reservoir recovery performance is required. Unlike previous analytic solution methods, complex heterogeneous reservoir architecture can be entertained. Well conditions are modeled directly, making possible design of complex wells. Phase I will also address the possible extension of the method to alternate subregion shapes to allow even faster and more flexible implementations. This project will provide a new class of reservoir management tools capable of rapidly and accurately screening what-if scenarios for field development. The objectives of the research as to 1) generalize analytic solution boundary element methodology to three dimensions; 2) build a prototype, 3-D, analytic simulation tool; 3) propose and test algorithms or well and field optimization using an analytic solution performance evaluation; and 4) extend algorithms to include additional geometric shapes for enhanced flexibility. The next phase of the research involves algorithm refinement, generalization, optimization shell implementation, and testing. Subsequently, concentration will be on commercial software development and a user interface. There is a recognized need for speed, accuracy, and simplicity in reservoir engineering management tools. There is also a demand for such tools without the high-end computational horsepower expected of most numerical reservoir simulators. Potential Research Solutions envisions a PC software product as a deliverable from this research and development, allowing improved management of existing hydrocarbon resources, especially in mature reservoirs. The proffered software product would benefit in-fill drilling programs, allocation of production rates to balance well load and drainage volumes, and screening of a large portfolio of reservoir management options--all with accurate reservoir performance predictions in complex reservoir architecture--and, it will be of particular interest to independent oil and gas producers with limited access to high-end computers