{"title":"A Novel Procedure for Analyzing Production Decline in Unconventional Reservoirs Using Probability Density Functions","authors":"Hamzeh Alimohammadi, Mehdi Sadeghi, Shengnan Chen","doi":"10.2118/208909-ms","DOIUrl":null,"url":null,"abstract":"\n In the past several decades, traditional decline curve analyses have been widely used as a quick and simple yet efficient method for reserve estimation and production forecasting. Several new models have been proposed since 2000s to address limitations of traditional decline models in shale and tight reservoirs especially multiple flow regimes and long-tail behavior of production profile which results in overestimating the reserve by the traditional models. Several of these newly proposed decline curve analysis (DCA) models are conservative and provide pessimistic reserve estimates.\n The main purpose of this work is to evaluate the application of six heavy-tailed probability density functions (PDFs) to approximate production in shale and tight reservoirs. A new class of DCA model suitable to capture the production decline trend in shale and tight reservoirs is examined using real and simulated production data. The proposed class of DCA has been demonstrated to predict production more accurately in tight and shale reservoirs especially when only limited data are available from wells with less than a few months of production history.","PeriodicalId":146458,"journal":{"name":"Day 1 Wed, March 16, 2022","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 1 Wed, March 16, 2022","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/208909-ms","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In the past several decades, traditional decline curve analyses have been widely used as a quick and simple yet efficient method for reserve estimation and production forecasting. Several new models have been proposed since 2000s to address limitations of traditional decline models in shale and tight reservoirs especially multiple flow regimes and long-tail behavior of production profile which results in overestimating the reserve by the traditional models. Several of these newly proposed decline curve analysis (DCA) models are conservative and provide pessimistic reserve estimates.
The main purpose of this work is to evaluate the application of six heavy-tailed probability density functions (PDFs) to approximate production in shale and tight reservoirs. A new class of DCA model suitable to capture the production decline trend in shale and tight reservoirs is examined using real and simulated production data. The proposed class of DCA has been demonstrated to predict production more accurately in tight and shale reservoirs especially when only limited data are available from wells with less than a few months of production history.