{"title":"用地震图像对离散裂缝网统计模型进行标度","authors":"D. Kolyukhin, M. Protasov","doi":"10.3997/2214-4609.201902219","DOIUrl":null,"url":null,"abstract":"Summary The presented paper addresses the modeling and seismic imaging of fractured reservoirs. A three-dimensional statistical model of a discrete fracture network is developed. A flexible and efficient method to generate the random realizations of the statistical model for an arbitrary computational grid is suggested. The problem of scaling the developed fracture model using the analysis of seismic images for different grid steps is studied. Particular attention is paid to the models with a multifractal distribution of fractures.","PeriodicalId":186806,"journal":{"name":"Petroleum Geostatistics 2019","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using Seismic Images for Scaling of Statistical Model of Discrete Fracture Networks\",\"authors\":\"D. Kolyukhin, M. Protasov\",\"doi\":\"10.3997/2214-4609.201902219\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary The presented paper addresses the modeling and seismic imaging of fractured reservoirs. A three-dimensional statistical model of a discrete fracture network is developed. A flexible and efficient method to generate the random realizations of the statistical model for an arbitrary computational grid is suggested. The problem of scaling the developed fracture model using the analysis of seismic images for different grid steps is studied. Particular attention is paid to the models with a multifractal distribution of fractures.\",\"PeriodicalId\":186806,\"journal\":{\"name\":\"Petroleum Geostatistics 2019\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Petroleum Geostatistics 2019\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3997/2214-4609.201902219\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Petroleum Geostatistics 2019","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3997/2214-4609.201902219","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using Seismic Images for Scaling of Statistical Model of Discrete Fracture Networks
Summary The presented paper addresses the modeling and seismic imaging of fractured reservoirs. A three-dimensional statistical model of a discrete fracture network is developed. A flexible and efficient method to generate the random realizations of the statistical model for an arbitrary computational grid is suggested. The problem of scaling the developed fracture model using the analysis of seismic images for different grid steps is studied. Particular attention is paid to the models with a multifractal distribution of fractures.