{"title":"Uncertainty Quantification and History Matching for Naturally Fractured Carbonate Reservoirs","authors":"S. D. Hoop, D. Voskov, G. Bertotti","doi":"10.3997/2214-4609.201903106","DOIUrl":null,"url":null,"abstract":"Summary Carbonate reservoirs host a major part of the world’s hydrocarbon reserves and over the past decade(s) have shown an increase in geothermal potential all over the world. However, naturally fractured carbonate reservoirs (NFR) contain a large uncertainty in their flow response and mechanical behavior due to the poor ability to predict the spatial distribution of discontinuity networks at reservoir-scale. In this work, we present a potential workflow for performing uncertainty quantification and data assimilation in fractured carbonate reservoirs. This workflow consists of a pre-processing step in which the original fracture network is cleaned and can be represented at the desired discretization accuracy. This method can then be used to transform a high-fidelity ensemble of models to some coarser representation. This coarser representation can be subsequently used to determine ensemble representatives. Finally, a history matching routine can be performed on each ensemble representative which characterizes the main flow patterns present in the NFR.","PeriodicalId":237705,"journal":{"name":"Third EAGE WIPIC Workshop: Reservoir Management in Carbonates","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Third EAGE WIPIC Workshop: Reservoir Management in Carbonates","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3997/2214-4609.201903106","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Summary Carbonate reservoirs host a major part of the world’s hydrocarbon reserves and over the past decade(s) have shown an increase in geothermal potential all over the world. However, naturally fractured carbonate reservoirs (NFR) contain a large uncertainty in their flow response and mechanical behavior due to the poor ability to predict the spatial distribution of discontinuity networks at reservoir-scale. In this work, we present a potential workflow for performing uncertainty quantification and data assimilation in fractured carbonate reservoirs. This workflow consists of a pre-processing step in which the original fracture network is cleaned and can be represented at the desired discretization accuracy. This method can then be used to transform a high-fidelity ensemble of models to some coarser representation. This coarser representation can be subsequently used to determine ensemble representatives. Finally, a history matching routine can be performed on each ensemble representative which characterizes the main flow patterns present in the NFR.