Elizaveta S. Gladchenko , Anna E. Gubanova , Denis M. Orlov , Dmitry A. Koroteev
{"title":"克里金法增强 CR 建模,用于快速充填钻探优化","authors":"Elizaveta S. Gladchenko , Anna E. Gubanova , Denis M. Orlov , Dmitry A. Koroteev","doi":"10.1016/j.petlm.2023.09.003","DOIUrl":null,"url":null,"abstract":"<div><p>The capacitance-resistance model (CRM) has been a useful physics-based tool for obtaining production forecasts for decades. However, the model's limitations make it difficult to work with real field cases, where a lot of various events happen. Such events often include new well commissioning (NWC). We introduce a workflow that combines CRM concepts and kriging into a single tool to handle these types of events during history matching. Moreover, it can be used for selecting a new well placement during infill drilling. To make the workflow even more versatile, an improved version of CRM was used. It takes into account wells shut-ins and performed workovers by additional adjustment of the model coefficients. By preliminary re-weighing and interpolating these coefficients using kriging, the coefficients for potential wells can be determined. The approach was validated using both synthetic and real datasets, from which the cases of putting new wells into operation were selected. The workflow allows a fast assessment of future well performance with a minimal set of reservoir data. This way, a lot of well placement scenarios can be considered, and the best ones could be chosen for more detailed studies.</p></div>","PeriodicalId":37433,"journal":{"name":"Petroleum","volume":"10 1","pages":"Pages 39-48"},"PeriodicalIF":4.2000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S240565612300055X/pdfft?md5=df77d62d6383fe68a19d95d6f8f9fe42&pid=1-s2.0-S240565612300055X-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Kriging-boosted CR modeling for prompt infill drilling optimization\",\"authors\":\"Elizaveta S. Gladchenko , Anna E. Gubanova , Denis M. Orlov , Dmitry A. Koroteev\",\"doi\":\"10.1016/j.petlm.2023.09.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The capacitance-resistance model (CRM) has been a useful physics-based tool for obtaining production forecasts for decades. However, the model's limitations make it difficult to work with real field cases, where a lot of various events happen. Such events often include new well commissioning (NWC). We introduce a workflow that combines CRM concepts and kriging into a single tool to handle these types of events during history matching. Moreover, it can be used for selecting a new well placement during infill drilling. To make the workflow even more versatile, an improved version of CRM was used. It takes into account wells shut-ins and performed workovers by additional adjustment of the model coefficients. By preliminary re-weighing and interpolating these coefficients using kriging, the coefficients for potential wells can be determined. The approach was validated using both synthetic and real datasets, from which the cases of putting new wells into operation were selected. The workflow allows a fast assessment of future well performance with a minimal set of reservoir data. This way, a lot of well placement scenarios can be considered, and the best ones could be chosen for more detailed studies.</p></div>\",\"PeriodicalId\":37433,\"journal\":{\"name\":\"Petroleum\",\"volume\":\"10 1\",\"pages\":\"Pages 39-48\"},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2024-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S240565612300055X/pdfft?md5=df77d62d6383fe68a19d95d6f8f9fe42&pid=1-s2.0-S240565612300055X-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Petroleum\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S240565612300055X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Petroleum","FirstCategoryId":"1087","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S240565612300055X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Kriging-boosted CR modeling for prompt infill drilling optimization
The capacitance-resistance model (CRM) has been a useful physics-based tool for obtaining production forecasts for decades. However, the model's limitations make it difficult to work with real field cases, where a lot of various events happen. Such events often include new well commissioning (NWC). We introduce a workflow that combines CRM concepts and kriging into a single tool to handle these types of events during history matching. Moreover, it can be used for selecting a new well placement during infill drilling. To make the workflow even more versatile, an improved version of CRM was used. It takes into account wells shut-ins and performed workovers by additional adjustment of the model coefficients. By preliminary re-weighing and interpolating these coefficients using kriging, the coefficients for potential wells can be determined. The approach was validated using both synthetic and real datasets, from which the cases of putting new wells into operation were selected. The workflow allows a fast assessment of future well performance with a minimal set of reservoir data. This way, a lot of well placement scenarios can be considered, and the best ones could be chosen for more detailed studies.
期刊介绍:
Examples of appropriate topical areas that will be considered include the following: 1.comprehensive research on oil and gas reservoir (reservoir geology): -geological basis of oil and gas reservoirs -reservoir geochemistry -reservoir formation mechanism -reservoir identification methods and techniques 2.kinetics of oil and gas basins and analyses of potential oil and gas resources: -fine description factors of hydrocarbon accumulation -mechanism analysis on recovery and dynamic accumulation process -relationship between accumulation factors and the accumulation process -analysis of oil and gas potential resource 3.theories and methods for complex reservoir geophysical prospecting: -geophysical basis of deep geologic structures and background of hydrocarbon occurrence -geophysical prediction of deep and complex reservoirs -physical test analyses and numerical simulations of reservoir rocks -anisotropic medium seismic imaging theory and new technology for multiwave seismic exploration -o theories and methods for reservoir fluid geophysical identification and prediction 4.theories, methods, technology, and design for complex reservoir development: -reservoir percolation theory and application technology -field development theories and methods -theory and technology for enhancing recovery efficiency 5.working liquid for oil and gas wells and reservoir protection technology: -working chemicals and mechanics for oil and gas wells -reservoir protection technology 6.new techniques and technologies for oil and gas drilling and production: -under-balanced drilling/gas drilling -special-track well drilling -cementing and completion of oil and gas wells -engineering safety applications for oil and gas wells -new technology of fracture acidizing