Prestack seismic stochastic inversion based on statistical characteristic parameters  

基于统计特征参数的叠前地震随机反演方法研究

作　　者：Wang Bao-Li Lin Ying Zhang Guang-Zhi Yin Xing-Yao 王保丽;蔺营;张广智;印兴耀;赵晨(中国石油大学(华东)地球科学与技术学院,山东青岛266580;海洋国家实验室海洋矿产资源评价与探测技术功能实验室,山东青岛266071)

机构地区：[1]School of Geosciences,China University of Petroleum(East China),Qingdao 266580,China [2]Laboratory for Marine Mineral Resources,Qingdao National Laboratory for Marine Science and Technology,Qingdao Shandong 266701,China.

出　　处：《Applied Geophysics》2021年第1期63-74,129,共13页应用地球物理（英文版）

基　　金：the National Science Foundation of China(No.42074136 and U19B2008);the Major National Science and Technology Projects(No.2016ZX05027004-001 and 2016ZX05002-005-009);the Fundamental Research Funds for the Central Universities(No.19CX02007A);China Postdoctoral Science Foundation(No.2020M672170).

摘　　要：In the conventional stochastic inversion method,the spatial structure information of underground strata is usually characterized by variograms.However,effectively characterizing the heterogeneity of complex strata is difficult.In this paper,multiple parameters are used to fully explore the underground formation information in the known seismic reflection and well log data.The spatial structure characteristics of complex underground reservoirs are described more comprehensively using multiple statistical characteristic parameters.We propose a prestack seismic stochastic inversion method based on prior information on statistical characteristic parameters.According to the random medium theory,this method obtains several statistical characteristic parameters from known seismic and logging data,constructs a prior information model that meets the spatial structure characteristics of the underground strata,and integrates multiparameter constraints into the likelihood function to construct the objective function.The very fast quantum annealing algorithm is used to optimize and update the objective function to obtain the fi nal inversion result.The model test shows that compared with the traditional prior information model construction method,the prior information model based on multiple parameters in this paper contains more detailed stratigraphic information,which can better describe complex underground reservoirs.A real data analysis shows that the stochastic inversion method proposed in this paper can effectively predict the geophysical characteristics of complex underground reservoirs and has a high resolution.常规的地震随机反演方法一般用变差函数表征地下地层的空间结构信息,但是变差函数很难有效表征实际复杂地层的非均质特性。本文利用多参数的思想充分发掘已知地震和测井资料中蕴含的地下地层信息,利用多个统计特征参数更全面地描述地下复杂储层的空间结构特征,并与地震随机反演相结合,提出了基于统计特征参数先验信息的叠前地震随机反演方法。该方法基于随机介质理论从已知的地震和测井资料中求取多个统计特征参数,选取符合实际地质特征的椭圆自相关函数,构建满足地层空间结构特征的先验信息模型,并将多参数约束融入似然函数中构建目标函数,用非常快速量子退火算法进行优化更新,实现目标函数的求解得到最终的反演结果。由模型试算可知,相比于传统的先验模型构建方法,本文基于多个参数构建的先验模型包含更丰富的地层信息,能更好地实现对地下复杂储层的描述。实际资料分析表明,基于统计特征参数先验信息的随机反演方法能够有效地进行地下复杂储层的地球物理预测,且具有较高的分辨率。

关 键 词：prior information random medium theory statistical characteristic parameters stochastic inversion very fast quantum annealing 

分 类 号：P631.4[天文地球—地质矿产勘探]