煤层气储层裂隙检测的WOA-BP算法及应用研究  

WOA-BP algorithm for crack detection in coalbed methane reservoirs and its application

作　　者：李琼[1,2] 李美琦 王睿 LI Qiong;LI MeiQi;WANG Rui(College of Geophysics,Chengdu University of Technology,Chengdu 610059,China;Key Laboratory of Earth Exploration and Information Technology of Ministry of Education(Chengdu University of Technology),Chengdu 610059,China)

机构地区：[1]成都理工大学地球物理学院,成都610059 [2]地球勘探与信息技术教育部重点实验室(成都理工大学),成都610059

出　　处：《地球物理学报》2022年第2期773-784,共12页Chinese Journal of Geophysics

基　　金：国家科技重大专项(2016ZX05026001-004);国家自然科学基金项目(41274129);2018年中央支持地方共建学科经费(80000-18Z0140504);四川省重点研发计划(2020YFG0157);2019年高校共建与发展—地物(双一流中央,80000-19Z0204)联合资助。

摘　　要：煤层气储层中裂隙的发育及空间展布特征对煤层气的勘探、开发和利用具有至关重要作用.煤层气储层裂隙检测的WOA-BP算法是将WOA(Whale Optimization Algorithm)与BP(Back Propagation)有机结合形成优势样本和二次误差控制的稳健而有效的储层裂隙检测方法.在实际地震数据中提取反映煤层裂隙的相干属性、方位角属性、倾角属性、曲率属性、构形张量属性、加权瞬时频率属性,并将其作为WOA改进的BP神经网络的输入数据,进行煤层气储层裂隙综合检测分析.以井数据、已知井产量数据、岩心薄片分析结果综合建立优势样本作为WOA优化算法改进的BP神经网络的输出评判标准,对研究区域煤层气储层裂隙综合检测分析的结果表明:WOA-BP网络能够继承和发展已有属性的优势,获得裂隙发育水平S_(evlt)值及分级标准,对煤层气储层裂隙发育程度进行了精细刻画,在研究区内,划分出四个裂缝存在区块,获得了优质煤层气储层,取得了很好的地质效果和勘探开发效果.WOA-BP方法促进了微裂缝预测的发展,将微裂缝预测提高到一个新的水平.Generation and spatial distribution of cracks in coalbed methane reservoirs play an important role in exploration,development and utilization of coalbed methane.The WOA-BP algorithm for crack detection in coalbed methane reservoirs is a combination of the WOA(Whale Optimization Algorithm)and BP(Back-Propagation)detection method in order to provide a robust and effective approach to detect reservoir cracks with dominant samples and secondary error control.This tool extracts attributes including coherence,azimuth angle,curvature,configuration tensor,and weighted instantaneous frequency of coal seam cracks from actual seismic data,and uses them as the input data of an improved WOA-BP neural network,which permits to conduct comprehensive detection and analysis of cracks in coalbed methane reservoirs.Using well data,known well production data,and core slice analysis results,it comprehensively establishes superior samples as the output evaluation standard of the BP neural network improved by the WOA optimization algorithm.Comprehensive detection in the study area and analysis results show that the WOA-BP network can inherit and develop the advantages of existing attributes,determine the fracture development level S_(evlt) value and classification standard,and finely describe the development degree of cracks in coalbed methane reservoirs.Four crack blocks are delineated in the study area and high-quality coalbed methane reservoirs are obtained,implying a good geological effect of exploration and development effect.It demonstrates that the WOA-BP method promotes the development of microcrack prediction and improves the micro-fracture prediction to a new level.

关 键 词：煤层气 裂隙 WOA-BP优化算法 地震多属性参数 

分 类 号：P631[天文地球—地质矿产勘探]