Elastic Impedance Inversion Based on Improved Particle Swarm Optimization

Particle Swarm Optimization has the advantages of fast convergence, simple programming and less parameters, therefore it has been widely used in solving the problems of continuous function optimization in many fields. In recent years, it begins to apply to seismic data inversion. Conventional seismic inversion adopts linear inversion methods, which strongly depend on the initial models and easily fall into local extremum. We propose an improved particle swarm optimization by adding simulated annealing, which enhances the efficiency and feasibility of the algorithm. Then we apply the improve algorithm to seismic elastic impedance inversion. After the model test of this algorithm, it is used to invert the seismic data of a certain area in Shengli Oilfield, and a number of elastic parameter profiles are obtained, which are in agreement with the actual drilling results. This method provides an effective and feasible way for the exploration and development of complex oil and gas reservoirs. (paper)