Tarek Ganat , Meftah Hrairi , Amr Badawy , Vahid Khosravi , Mohammed Abdalla
{"title":"Advancing sandstone reservoir compressibility prediction: A correlation-driven methodology","authors":"Tarek Ganat , Meftah Hrairi , Amr Badawy , Vahid Khosravi , Mohammed Abdalla","doi":"10.1016/j.ptlrs.2024.01.006","DOIUrl":null,"url":null,"abstract":"<div><p>This study presents a correlation-based approach for predicting the compressibility of sandstone reservoir rocks. The study proposes a matrix of new empirical equations that significantly improve the precision of measuring the pore volume compressibility, with the most optimal fit of results based on a cubic polynomial model. The accuracy of the calculations was validated through comparison with actual data using root mean square method, and the suggested correlations significantly enhance the precise prediction of rock compressibility in sandstone reservoirs. In this study, the source of data collection is consolidated and unconsolidated sandstone from East Asia offshore oilfields. Accordingly, variations in compressibility with net overburden pressure over the course of the field's lifespan have been examined. The results demonstrate the application of regression analysis in establishing a network of linkages between independent and dependent variables. The proposed correlations for consolidated and unconsolidated sandstones offer a remarkable improvement in the accurate calculation of rock compressibility compared to traditional laboratory procedures, with an average error of 2.5% compared to 5–10% for laboratory measurements. The approach of this study offers a cost-effective and time-efficient alternative to remarkedly enhance the overall performance of sandstone reservoirs in the oil and gas industry.</p></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"9 2","pages":"Pages 273-279"},"PeriodicalIF":0.0000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096249524000061/pdfft?md5=b2aa0024892ab824ed2d7e109c077872&pid=1-s2.0-S2096249524000061-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Petroleum Research","FirstCategoryId":"1087","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2096249524000061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
This study presents a correlation-based approach for predicting the compressibility of sandstone reservoir rocks. The study proposes a matrix of new empirical equations that significantly improve the precision of measuring the pore volume compressibility, with the most optimal fit of results based on a cubic polynomial model. The accuracy of the calculations was validated through comparison with actual data using root mean square method, and the suggested correlations significantly enhance the precise prediction of rock compressibility in sandstone reservoirs. In this study, the source of data collection is consolidated and unconsolidated sandstone from East Asia offshore oilfields. Accordingly, variations in compressibility with net overburden pressure over the course of the field's lifespan have been examined. The results demonstrate the application of regression analysis in establishing a network of linkages between independent and dependent variables. The proposed correlations for consolidated and unconsolidated sandstones offer a remarkable improvement in the accurate calculation of rock compressibility compared to traditional laboratory procedures, with an average error of 2.5% compared to 5–10% for laboratory measurements. The approach of this study offers a cost-effective and time-efficient alternative to remarkedly enhance the overall performance of sandstone reservoirs in the oil and gas industry.