{"title":"从再处理地震数据中识别二氧化碳储存的潜在风险因素","authors":"S. Carpentier, H. Abidin, P. Steeghs, H. Veldkamp","doi":"10.3997/2214-4609.201802950","DOIUrl":null,"url":null,"abstract":"CO2 storage needs economic business cases through cost-effective exploration and production and needs license-to-operate through public support. Re-interpretation and reprocessing of vintage geophysical data is a means to achieve cost-effective exploration whereas de-risking and conformance control of storage operations is a means to obtain public support. Seismic exploration should identify risk elements for CO2 storage such as the risk of leakage, risk of pressure build-ups or drops, unexpected increase or decrease of storage capacity and spill points to name a few. These risks elements are often caused by hidden features such as a failing overburden seal, closed or open faults in either reservoir or seal and high- or low-permeability streaks in the reservoir. We have investigated a seismic reprocessing workflow for imaging and de-risking CO2 storage reservoirs and seals. The workflow includes statics, demultiple, velocity modeling, Prestack Time Migration, high resolution sparse spike deconvolution and Non Local Means filtering. Non Local Means filtering increases signal to noise ratio while preserving edges and the sparse spike deconvolution produces results with superior vertical and lateral resolution. This workflow manages at low cost to considerably de-risk the CO2 storage reservoirs and seals by identifying previously hidden faults, seal-reservoir contacts and thin reservoir streaks. © 2018 European Association of Geoscientists and Engineers, EAGE. All rights reserved.","PeriodicalId":254996,"journal":{"name":"Fifth CO2 Geological Storage Workshop","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identifying Hidden Risk Elements For CO2 Storage From Reprocessed Seismic Data\",\"authors\":\"S. Carpentier, H. Abidin, P. Steeghs, H. Veldkamp\",\"doi\":\"10.3997/2214-4609.201802950\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"CO2 storage needs economic business cases through cost-effective exploration and production and needs license-to-operate through public support. Re-interpretation and reprocessing of vintage geophysical data is a means to achieve cost-effective exploration whereas de-risking and conformance control of storage operations is a means to obtain public support. Seismic exploration should identify risk elements for CO2 storage such as the risk of leakage, risk of pressure build-ups or drops, unexpected increase or decrease of storage capacity and spill points to name a few. These risks elements are often caused by hidden features such as a failing overburden seal, closed or open faults in either reservoir or seal and high- or low-permeability streaks in the reservoir. We have investigated a seismic reprocessing workflow for imaging and de-risking CO2 storage reservoirs and seals. The workflow includes statics, demultiple, velocity modeling, Prestack Time Migration, high resolution sparse spike deconvolution and Non Local Means filtering. Non Local Means filtering increases signal to noise ratio while preserving edges and the sparse spike deconvolution produces results with superior vertical and lateral resolution. This workflow manages at low cost to considerably de-risk the CO2 storage reservoirs and seals by identifying previously hidden faults, seal-reservoir contacts and thin reservoir streaks. © 2018 European Association of Geoscientists and Engineers, EAGE. All rights reserved.\",\"PeriodicalId\":254996,\"journal\":{\"name\":\"Fifth CO2 Geological Storage Workshop\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fifth CO2 Geological Storage Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3997/2214-4609.201802950\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fifth CO2 Geological Storage Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3997/2214-4609.201802950","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Identifying Hidden Risk Elements For CO2 Storage From Reprocessed Seismic Data
CO2 storage needs economic business cases through cost-effective exploration and production and needs license-to-operate through public support. Re-interpretation and reprocessing of vintage geophysical data is a means to achieve cost-effective exploration whereas de-risking and conformance control of storage operations is a means to obtain public support. Seismic exploration should identify risk elements for CO2 storage such as the risk of leakage, risk of pressure build-ups or drops, unexpected increase or decrease of storage capacity and spill points to name a few. These risks elements are often caused by hidden features such as a failing overburden seal, closed or open faults in either reservoir or seal and high- or low-permeability streaks in the reservoir. We have investigated a seismic reprocessing workflow for imaging and de-risking CO2 storage reservoirs and seals. The workflow includes statics, demultiple, velocity modeling, Prestack Time Migration, high resolution sparse spike deconvolution and Non Local Means filtering. Non Local Means filtering increases signal to noise ratio while preserving edges and the sparse spike deconvolution produces results with superior vertical and lateral resolution. This workflow manages at low cost to considerably de-risk the CO2 storage reservoirs and seals by identifying previously hidden faults, seal-reservoir contacts and thin reservoir streaks. © 2018 European Association of Geoscientists and Engineers, EAGE. All rights reserved.