用改进的模拟退火算法进行叠后时移地震数据反演

本文以广义Boltzmann—Gibbs统计理论为基础，采用依赖于温度的似Cauchy分布产生新的扰动模型，选用改进的接收概率公式，并在实际计算中设置记忆器，记忆搜索到的最好结果，得到适合时移地震反演的模拟退火算法。通过分析地震数据和模型之间的关系，选择了合适的目标函数和流程进行时移地震数据反演，经理论模型试算，取得了较好的效果。新的反演算法有较好的抗噪能力，反演结果稳定性好、精度高，较好地实现了时移地震中较小波阻抗变化的反演。

Inversion of poststack time-lapse seismic data by modified simulated annealing algorithm.

Based on generalized Boltzman-Gibbs statistical theory,the paper adopted a new disturbed model produced by temperature-dependent pseudo-Cauchy distribution. Choosing modified acceptance probability formula and setting memory in practical computation, the best results can be searched out by memory and the simulated annealing algorithm suitable for inversion of time-lapse seismic data can be acquired. Through analysis of relations between seismic data and models,we chose proper objective function and flow for inversion of time-lapse seismic data and achieved good results through theoretical models tests. The new inversion algorithm has better anti-noise ability, good stability and high-precision for inversion results,better finishing the inversion for small impedance changes in time-lapse seismic data.