comparison of simulated annealing, genetic, and tabu search algorithms for fracture network modeling

the mathematical modeling of fracture networks is critical for the exploration and development ofnatural resources. fractures can help the production of petroleum, water, and geothermal energy. theyalso greatly influence the drainage and production of methane gas from coal beds. orientation andspatial distribution of fractures in rocks are important factors in controlling fluid flow. the objectivefunction recently developed by masihi et al. 2007 was used herein to generate fracture models thatincorporate field observations. to extend this method, simulated annealing, genetic, and tabu searchalgorithms were employed in the modeling of fracture networks. the effectiveness of each algorithmwas compared and the applicability of the methodology was assessed through a case study. it isconcluded that the fracture model generated by simulated annealing is better compared to thosegenerated by genetic and tabu search algorithms.