Li Qiang, Chen Xin, X. Dengyi, Z. Min, Q. Qunli, Yang Jianfang, Liao Xiaoliang, P. Bo, A. Fuli, W. Bo, Gao Xiaoli, Yang Chen
{"title":"基于深度学习与地震谱分解相结合的细微断层预测技术","authors":"Li Qiang, Chen Xin, X. Dengyi, Z. Min, Q. Qunli, Yang Jianfang, Liao Xiaoliang, P. Bo, A. Fuli, W. Bo, Gao Xiaoli, Yang Chen","doi":"10.2118/211631-ms","DOIUrl":null,"url":null,"abstract":"\n Faults often control the movement and aggregation of oil and gas. With the development of oil fields, the role of subtle faults is becoming more and more important. The accuracy of fault interpretation directly affects the direction of exploration and development. However, due to the limitation of the seismic resolution, it is hard to identify these faults according to routine methods such as coherence, variance, curvature, etc. To overcome such kind of challenge and better match the demand for fine fault identification, a method integrated deep learning and spectral decomposition was proposed.","PeriodicalId":249690,"journal":{"name":"Day 2 Tue, November 01, 2022","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Subtle Fault Prediction Technique Based on the Integration of Deep Learning and Seismic Spectral Decomposition\",\"authors\":\"Li Qiang, Chen Xin, X. Dengyi, Z. Min, Q. Qunli, Yang Jianfang, Liao Xiaoliang, P. Bo, A. Fuli, W. Bo, Gao Xiaoli, Yang Chen\",\"doi\":\"10.2118/211631-ms\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Faults often control the movement and aggregation of oil and gas. With the development of oil fields, the role of subtle faults is becoming more and more important. The accuracy of fault interpretation directly affects the direction of exploration and development. However, due to the limitation of the seismic resolution, it is hard to identify these faults according to routine methods such as coherence, variance, curvature, etc. To overcome such kind of challenge and better match the demand for fine fault identification, a method integrated deep learning and spectral decomposition was proposed.\",\"PeriodicalId\":249690,\"journal\":{\"name\":\"Day 2 Tue, November 01, 2022\",\"volume\":\"57 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Day 2 Tue, November 01, 2022\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2118/211631-ms\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 2 Tue, November 01, 2022","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/211631-ms","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Subtle Fault Prediction Technique Based on the Integration of Deep Learning and Seismic Spectral Decomposition
Faults often control the movement and aggregation of oil and gas. With the development of oil fields, the role of subtle faults is becoming more and more important. The accuracy of fault interpretation directly affects the direction of exploration and development. However, due to the limitation of the seismic resolution, it is hard to identify these faults according to routine methods such as coherence, variance, curvature, etc. To overcome such kind of challenge and better match the demand for fine fault identification, a method integrated deep learning and spectral decomposition was proposed.