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Deep-Towed Array Geometry Inversion Based on an Improved Particle Swarm Optimization Algorithm

Xiaohu Luo    
Kai Liu    
Yanliang Pei    
Chenguang Liu    
Xishuang Li and Yibao Xiao    

Resumen

When marine deep-towed multichannel seismic data are processed, the description of the receiving array geometry significantly impacts the quality of the imaging profile. Therefore, achieving a highly precise description of the receiving array geometry is very important for the fine imaging of such data. While basic particle swarm optimization (PSO) is known for its ease of implementation and efficiency, it often exhibits a low convergence accuracy. Consequently, the PSO algorithm is improved by modifying the inertia weight and incorporating Gaussian mutation. In combination with the actual motion of the towing streamer during surveys, a strategy for inheriting particle positions is introduced. When each seismic shot is solved sequentially, the results from the previous shot can serve as the initial particle positions for the next shot. The results indicate that this strategy achieves superior fitness values and outperforms the basic PSO algorithm. This method exhibits simplicity, rapid optimization, and a favorable solution quality, thereby offering a valuable approach to deep-towed array geometry inversion. It enhances the efficiency of deep-towed seismic data processing and serves as a reference for similar applications.

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