Evaluating the performance of advanced wells in heavy oil reservoirs under uncertainty in permeability parameters
Advanced wells play a crucial role in maximizing the efficiency of oil production. To achieve a successful design for advanced wells, several parameters must be considered and evaluated. Uncertainty in these parameters can have a significant impact on the performance assessment of the well in its li...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-11-01
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| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484722012197 |
| _version_ | 1797901922685943808 |
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| author | Ali Moradi Nastaran A. Samani Amaranath S. Kumara Britt M.E. Moldestad |
| author_facet | Ali Moradi Nastaran A. Samani Amaranath S. Kumara Britt M.E. Moldestad |
| author_sort | Ali Moradi |
| collection | DOAJ |
| description | Advanced wells play a crucial role in maximizing the efficiency of oil production. To achieve a successful design for advanced wells, several parameters must be considered and evaluated. Uncertainty in these parameters can have a significant impact on the performance assessment of the well in its lifetime. Absolute permeability, relative permeability, and permeability anisotropy are the parameters that determine reservoir permeability and are among the most important design parameters to be considered. This paper aims to assess the performance of advanced wells completed with passive and reactive downhole Flow Control Devices (FCDs) under uncertainty in the reservoir permeability parameters. The assessment is conducted through a case study on a synthetic heavy oil reservoir with a strong water drive. The EclipseSM reservoir simulator is used as a simulation tool and the Latin Hypercube Sampling (LHS) approach is applied as a sampling tool for uncertainty analysis in this study. According to the obtained results, under the presence of uncertainty, advanced wells with Autonomous Inflow Control Device (AICD) and Autonomous Inflow Control Valve (AICV) completions are able to mitigate the risk of water production by 53.20% and 71.12% respectively compared to conventional wells. However, Inflow Control Device (ICD) completion can only reduce the risk by 0.87%. |
| first_indexed | 2024-04-10T09:09:38Z |
| format | Article |
| id | doaj.art-2a725837eb674995bbcb5b2252e9dfd2 |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-04-10T09:09:38Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-2a725837eb674995bbcb5b2252e9dfd22023-02-21T05:12:15ZengElsevierEnergy Reports2352-48472022-11-01886058617Evaluating the performance of advanced wells in heavy oil reservoirs under uncertainty in permeability parametersAli Moradi0Nastaran A. Samani1Amaranath S. Kumara2Britt M.E. Moldestad3Correspondence to: Kjølnes Ring 56, 3918 Porsgrunn, Norway.; Department of Process, Energy and Environmental Technology, University of South-Eastern Norway, Porsgrunn, NorwayDepartment of Process, Energy and Environmental Technology, University of South-Eastern Norway, Porsgrunn, NorwayDepartment of Process, Energy and Environmental Technology, University of South-Eastern Norway, Porsgrunn, NorwayDepartment of Process, Energy and Environmental Technology, University of South-Eastern Norway, Porsgrunn, NorwayAdvanced wells play a crucial role in maximizing the efficiency of oil production. To achieve a successful design for advanced wells, several parameters must be considered and evaluated. Uncertainty in these parameters can have a significant impact on the performance assessment of the well in its lifetime. Absolute permeability, relative permeability, and permeability anisotropy are the parameters that determine reservoir permeability and are among the most important design parameters to be considered. This paper aims to assess the performance of advanced wells completed with passive and reactive downhole Flow Control Devices (FCDs) under uncertainty in the reservoir permeability parameters. The assessment is conducted through a case study on a synthetic heavy oil reservoir with a strong water drive. The EclipseSM reservoir simulator is used as a simulation tool and the Latin Hypercube Sampling (LHS) approach is applied as a sampling tool for uncertainty analysis in this study. According to the obtained results, under the presence of uncertainty, advanced wells with Autonomous Inflow Control Device (AICD) and Autonomous Inflow Control Valve (AICV) completions are able to mitigate the risk of water production by 53.20% and 71.12% respectively compared to conventional wells. However, Inflow Control Device (ICD) completion can only reduce the risk by 0.87%.http://www.sciencedirect.com/science/article/pii/S2352484722012197Uncertainty assessmentAdvanced wellsWater cutHeavy oilICDAICD |
| spellingShingle | Ali Moradi Nastaran A. Samani Amaranath S. Kumara Britt M.E. Moldestad Evaluating the performance of advanced wells in heavy oil reservoirs under uncertainty in permeability parameters Energy Reports Uncertainty assessment Advanced wells Water cut Heavy oil ICD AICD |
| title | Evaluating the performance of advanced wells in heavy oil reservoirs under uncertainty in permeability parameters |
| title_full | Evaluating the performance of advanced wells in heavy oil reservoirs under uncertainty in permeability parameters |
| title_fullStr | Evaluating the performance of advanced wells in heavy oil reservoirs under uncertainty in permeability parameters |
| title_full_unstemmed | Evaluating the performance of advanced wells in heavy oil reservoirs under uncertainty in permeability parameters |
| title_short | Evaluating the performance of advanced wells in heavy oil reservoirs under uncertainty in permeability parameters |
| title_sort | evaluating the performance of advanced wells in heavy oil reservoirs under uncertainty in permeability parameters |
| topic | Uncertainty assessment Advanced wells Water cut Heavy oil ICD AICD |
| url | http://www.sciencedirect.com/science/article/pii/S2352484722012197 |
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