{"title":"用于后续水力压裂候选井识别的井聚类","authors":"C. Aitov","doi":"10.3997/2214-4609.202156017","DOIUrl":null,"url":null,"abstract":"Summary This paper presents a methodology for selecting candidate wells for hydraulic fracturing. The technique is based on well clustering. Allocation of wells into clusters is carried out according to the most coinciding technological indicators of wells operation. Further selection of wells, one cluster or another, for hydraulic fracturing is performed using well-known optimization algorithms","PeriodicalId":266953,"journal":{"name":"Data Science in Oil and Gas 2021","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Well Clustering for The Subsequent Identification of Candidate Wells for Hydraulic Fracturing\",\"authors\":\"C. Aitov\",\"doi\":\"10.3997/2214-4609.202156017\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary This paper presents a methodology for selecting candidate wells for hydraulic fracturing. The technique is based on well clustering. Allocation of wells into clusters is carried out according to the most coinciding technological indicators of wells operation. Further selection of wells, one cluster or another, for hydraulic fracturing is performed using well-known optimization algorithms\",\"PeriodicalId\":266953,\"journal\":{\"name\":\"Data Science in Oil and Gas 2021\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Data Science in Oil and Gas 2021\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3997/2214-4609.202156017\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data Science in Oil and Gas 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3997/2214-4609.202156017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Well Clustering for The Subsequent Identification of Candidate Wells for Hydraulic Fracturing
Summary This paper presents a methodology for selecting candidate wells for hydraulic fracturing. The technique is based on well clustering. Allocation of wells into clusters is carried out according to the most coinciding technological indicators of wells operation. Further selection of wells, one cluster or another, for hydraulic fracturing is performed using well-known optimization algorithms