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

Award Information
Agency: National Science Foundation
Branch: N/A
Contract: 0236569
Agency Tracking Number: 0236569
Amount: $500,000.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: N/A
Solicitation Year: N/A
Award Year: 2003
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
1818 Shelmire Drive, Dallas, TX, 75224
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Randy Hazlett
 () -
Business Contact
Phone: () -
Research Institution
This Small Business Innovation Research (SBIR)Phase II project provides the foundational R&D for new oil and gas reservoir management tools to optimize 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 incorporates 3-D analytic fluid flow simulation technology into large-scale optimization routines where reservoir recovery performance is required, such as in the optimum placement of new wells or the optimum operation of existing wells. Unlike previous analytic solution methods, complex heterogeneous reservoir architecture can be managed without a loss of accuracy. This project will provide a new class of reservoir management tools capable of rapidly and accurately screening what-if scenarios for field development. Phase II will: i) generalize analytic solution boundary element methodology to three dimensions, ii) build a prototype, 3-D, well optimization tool, iii) develop analytic stream-function technology for optimization of improved recovery operations, and iv) extend algorithms to additional geometric shapes for enhanced flexibility. Powerful analytic solution technology has been developed that allows robust solution of fluid flow problems with complex, heterogeneous rock properties. This general analytic solution methodology is an industry first, providing the ability to generate a brand new line of desktop hydrocarbon reservoir management tools. In particular, the results of this project will provide software and services to optimally locate new wells within existing hydrocarbon reservoirs. While reservoir simulation and well planning software both exist in the marketplace, no current commercial product offers the ability to rigorously compute well productivity within a feedback loop of a powerful gradient search optimization method to automatically select the best drilling location for new wells. This technology also addresses the optimum performance of existing wells in improved recovery operations. Using analytic stream-function optimization, well configurations in mature fields can be optimized for maximum productivity and ultimate recovery, thus minimizing unrecoverable natural resources.

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