A Novel Model for Forecasting Production Performance in Waterflood Oil Reservoirs
The importance of production performance forecasting in reservoir development and economic evaluation cannot be overstated. Previous models have shown deficiencies in accurately predicting production performance, necessitating the development of a new semianalytical model to enhance its application...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-01-01
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| Series: | Geofluids |
| Online Access: | http://dx.doi.org/10.1155/2024/4584237 |
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| _version_ | 1832569158056804352 |
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| author | Yajun Gao Yang Liu Xiaoqing Xie Lihui Tang Yuqian Diao Yuhua Ma |
| author_facet | Yajun Gao Yang Liu Xiaoqing Xie Lihui Tang Yuqian Diao Yuhua Ma |
| author_sort | Yajun Gao |
| collection | DOAJ |
| description | The importance of production performance forecasting in reservoir development and economic evaluation cannot be overstated. Previous models have shown deficiencies in accurately predicting production performance, necessitating the development of a new semianalytical model to enhance its application scope and prediction accuracy. This study proposes a novel semianalytical model based on the Buckley–Leverett (BL) equation and a newly proposed linear relationship between outlet water saturation and average water saturation, as well as Willhite’s formula of oil/water relative permeability. The results demonstrate the universality of this new model, as it can generate three equivalent log-linear relations, including the previously proposed model. Sensitivity analysis confirms the applicability of the model in various reservoirs. In addition, both model and field case studies highlight the advantages of this technique in forecasting water cut and cumulative oil production, with an extensive application scope covering over 90% of the water cut range. A comparison of oil production prediction results from six different predictive methods reveals that the proposed semianalytical model exhibits the lowest error rate of −0.01%. Moreover, the semianalytical model can be utilized to directly solve for the approximate values of the exponents in Willhite’s oil/water relative permeability equations. In summary, this novel semianalytical forecasting model demonstrates a robust ability to forecast water cut, cumulative oil production, and recovery efficiency. |
| format | Article |
| id | doaj-art-eb1d97a9c25344ca9a3512e8258036fb |
| institution | Kabale University |
| issn | 1468-8123 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geofluids |
| spelling | doaj-art-eb1d97a9c25344ca9a3512e8258036fb2025-02-02T23:15:36ZengWileyGeofluids1468-81232024-01-01202410.1155/2024/4584237A Novel Model for Forecasting Production Performance in Waterflood Oil ReservoirsYajun Gao0Yang Liu1Xiaoqing Xie2Lihui Tang3Yuqian Diao4Yuhua Ma5NKLOOGE (National Key Laboratory of Offshore Oil and Gas Exploitation)China Petroleum Engineering &Construction Corporation Beijing CompanyNKLOOGE (National Key Laboratory of Offshore Oil and Gas Exploitation)NKLOOGE (National Key Laboratory of Offshore Oil and Gas Exploitation)CNOOC Research InstituteNKLOOGE (National Key Laboratory of Offshore Oil and Gas Exploitation)The importance of production performance forecasting in reservoir development and economic evaluation cannot be overstated. Previous models have shown deficiencies in accurately predicting production performance, necessitating the development of a new semianalytical model to enhance its application scope and prediction accuracy. This study proposes a novel semianalytical model based on the Buckley–Leverett (BL) equation and a newly proposed linear relationship between outlet water saturation and average water saturation, as well as Willhite’s formula of oil/water relative permeability. The results demonstrate the universality of this new model, as it can generate three equivalent log-linear relations, including the previously proposed model. Sensitivity analysis confirms the applicability of the model in various reservoirs. In addition, both model and field case studies highlight the advantages of this technique in forecasting water cut and cumulative oil production, with an extensive application scope covering over 90% of the water cut range. A comparison of oil production prediction results from six different predictive methods reveals that the proposed semianalytical model exhibits the lowest error rate of −0.01%. Moreover, the semianalytical model can be utilized to directly solve for the approximate values of the exponents in Willhite’s oil/water relative permeability equations. In summary, this novel semianalytical forecasting model demonstrates a robust ability to forecast water cut, cumulative oil production, and recovery efficiency.http://dx.doi.org/10.1155/2024/4584237 |
| spellingShingle | Yajun Gao Yang Liu Xiaoqing Xie Lihui Tang Yuqian Diao Yuhua Ma A Novel Model for Forecasting Production Performance in Waterflood Oil Reservoirs Geofluids |
| title | A Novel Model for Forecasting Production Performance in Waterflood Oil Reservoirs |
| title_full | A Novel Model for Forecasting Production Performance in Waterflood Oil Reservoirs |
| title_fullStr | A Novel Model for Forecasting Production Performance in Waterflood Oil Reservoirs |
| title_full_unstemmed | A Novel Model for Forecasting Production Performance in Waterflood Oil Reservoirs |
| title_short | A Novel Model for Forecasting Production Performance in Waterflood Oil Reservoirs |
| title_sort | novel model for forecasting production performance in waterflood oil reservoirs |
| url | http://dx.doi.org/10.1155/2024/4584237 |
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