Multi-parameter Inversion Of Reformulated BISQ Model Based On The Method Of Adaptive Predatory Search Genetic Algorithm

Multi-parameter inversion based on two-phrase media is one of the most popular methods in exploration of oil and gas resources, and marine seismic survey fields. Ideal model and effective algorithm are the most important section s of Multi-parameter inversion. The reformulated BISQ model has better efficiency in parameter inversion than BISQ model, which has the same accuracy with BISQ model. It is because the reformulated BISQ model has simpler structure compared with BISQ model. For studying reformulated BISQ model’s superiority, Multi-parameter inversion based on the reformulated BISQ model was completed. With drawing predatory search algorithm and adaptive concept, the predatory search genetic algorithm was designed.With compared with traditional genetic algorithms and Penalty Function Niche Pareto genetic algorithm, the predatory search genetic algorithm are more superior in accuracy and efficiency. At the same time, parameters inversion based on the reformulated BISQ model by the method of predatory search genetic algorithm is more superior to parameters inversion with the method of predatory search genetic algorithm in BISQ model. The parameters inversion in reformulated BISQ model has better efficiency than it in BISQ model. For testing the detection accuracy, the test of reformulated BISQ model’s antinoise capability was conducted. The result show that Multi-parameter inversion by the method of predatory search genetic algorithm in reformulated BISQ model has high ant jamming capability. For researching the practicability of the method, the predatory search genetic algorithm was used in practical Multi-parameter inversion of multi-frequency in ocean acoustic test in situ. Inversion parameter was set from three to six. The results show that method of predatory search genetic algorithm can obtain high precision parameters. The method is an effective and practical method. Fitting results between inverse and measured velocity are very great. This coherence demonstrates the applicability of the predatory search genetic algorithm.