粒子群算法炮点偏移校正技术

在地震勘探数据采集的过程中，常会遇到炮点实际位置与设计位置不一致的情况，进而影响后续的地震数据处理。为了解决这个问题，基于近炮检距近地表速度接近常速的假设，本文提出使用粒子群方法对炮点位置进行校正。首先估算近地表直达波的速度，通过观测初至与计算初至建立误差目标函数，通过粒子群算法求解目标函数得到最优解即炮点位置。与常规的网格搜索方法相比，该方法计算效率明显提升，且保持了较高精度，为地震数据质量监控提供了一种可靠且高效的方法。

Source point deviation correction based on particle swarm optimization

For seismic data acquisition in the field, source points deviate sometimes from their designed locations. In these conditions, the subsequent seismic data processing will be affected. To solve the problem, we propose to use the particle swarm optimization to correct source point deviation in given the condition that the near surface velocity is constant. First, we calculate near surface velocity. And then we set up objective functions based on observed first arrivals and calculated first arrivals. Finally source point locations are obtained by objective function calculation with the particle swarm optimization. Compared with the grid searching method, the particle swarm optimization improves the computation efficiency while the calculation accuracy remains the same. The proposed method provides a reliable and high efficient way for quality control for seismic data acquisition.