Comparison of Simulated Annealing, Genetic, and Tabu Search Algorithms for Fracture Network Modeling

The mathematical modeling of fracture networks is c ritical for the exploration and development of natural resources. Fractures can help the productio n of petroleum, water, and geothermal energy. They also greatly influence the drainage and production of methane gas from coal beds. Orientation and spatial distribution of fractures in rocks are impo rtant factors in controlling fluid flow. The object ive function recently developed by Masihi et al. 2007 w as used herein to generate fracture models that incorporate field observations. To extend this meth od, simulated annealing, genetic, and tabu search algorithms were employed in the modeling of fractur e networks. The effectiveness of each algorithm was compared and the applicability of the methodology was assessed through a case study. It is concluded that the fracture model generated by simu lated annealing is better compared to those generated by genetic and tabu search algorithms.

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