基于二次编解码网络的适应性叠前反演方法  

Adaptive prestack inversion method based on quadratic encoder-decoder network

作　　者：单博 邢宇鑫 张繁昌[3] 李志伟 陈默[1,2] SHAN Bo;XING Yu-Xin;ZHANG Fan-Chang;LI Zhi-Wei;CHEN Mo(Oil&Gas Resources Survey,China Geological Survey,Beijing 100083,China;Key Laboratory of Unconventional Oil and Gas,China Geological Survey,Beijing 100083,China;School of Geosciences,China University of Petroleum(East China),Qingdao 266580,China)

机构地区：[1]中国地质调查局油气资源调查中心,北京100083 [2]中国地质调查局非常规油气重点实验室,北京100083 [3]中国石油大学(华东)地球科学与技术学院,山东青岛266580

出　　处：《物探与化探》2025年第1期158-165,共8页Geophysical and Geochemical Exploration

基　　金：国家自然科学基金项目(41874146);中国地质调查局地质调查项目(DD20230713,DD20242673)。

摘　　要：AVO反演以Zoeppritz方程为基础,可从叠前地震资料中提取多种隐藏的岩石物性参数。在地震资料中,角度数据是以偏移距形式记录的范围值,两者相互转换容易产生计算误差;在不同工区使用同一套近似式,适用性会受到实际地质条件影响;而精确Zoeppritz方程较复杂,会产生更大的计算量。为此,构建一种基于二次编解码网络的适应性叠前反演方法,利用深度学习极强的特征关系提取能力代替传统关系式,来弥补角度误差,适应不同工区、不同地质条件的差异。该网络以二次型算法为优化算法,改进了常规编码—解码(Encoder-Decoder)结构,达到效率最大化;同时结合Xavier方法让模型初始化更具随机性,提高网络抗干扰能力。结果表明,通过正交试验优选后的二次编解码网络比单解码网络预测效果更好,与实际测井曲线吻合程度更高,反演所得的纵、横波速度和密度成果剖面均符合研究区地质情况,横向连续性强,能够实现高效、高稳定的叠前反演任务。AVO inversion,based on the Zoeppritz equation,extracts various hidden petrophysical parameters from pre-stack seismic data.In seismic data,angle information is recorded in the form of offset values,and converting between offset values and angles is prone to generate errors.In addition,using the same approximate formula for different acreage types may lead to reduced applicability due to varying actual geological conditions.The exact Zoeppritz equation will lead to increased computational demands due to its high complexity.Therefore,this study developed an adaptive prestack inversion method based on the quadratic Encoder-Decoder network.This inversion method used the high feature and relationship extraction abilities of deep learning to replace traditional relationships,thereby reducing the angle errors and adapting to varying acreage types and geological conditions.The quadratic Encoder-Decoder network used a quadratic algorithm as the optimization method,maximizing the efficiency of the standard Encoder-Decoder structure.Additionally,the Xavier initialization method was incorporated to enhance the randomness of model initialization,thus improving the robustness of the network.The results indicate that the quadratic Encoder-Decoder network,selected through orthogonal experiments,outperforms the single-decoder network in prediction and exhibits greater consistency with actual log curves.The P-wave velocity,S-wave velocity,and density profiles obtained from inversion are consistent with the geological conditions of the study area,exhibit strong lateral continuity,and can effectively achieve high-precision prestack inversion.

关 键 词：叠前反演 深度学习 编码—解码模型 二次型算法 正交试验法 

分 类 号：P631.4[天文地球—地质矿产勘探]