A New Hybrid Optimization Algorithm for the Estimation of Archie Parameters
Archie formula, which contains three fundamental parameters (a, m, n), is the basic equation to compute the water saturation in a clean or shaly formation. These parameters are known as Archie parameters. To identify accurately the water saturation for a given reservoir condition, it depends crit...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
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Springer
2015
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| Online Access: | http://link.springer.com/chapter/10.1007/978-3-662-47044-2_7#page-1 http://hdl.handle.net/20.500.11937/10930 |
| _version_ | 1848747669402419200 |
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| author | liu, J. Xu, Honglei Wu, G. Teo, Kok Lay |
| author2 | Honglei Xu |
| author_facet | Honglei Xu liu, J. Xu, Honglei Wu, G. Teo, Kok Lay |
| author_sort | liu, J. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Archie formula, which contains three fundamental parameters (a, m, n), is the basic equation to compute the water saturation in a clean or shaly formation. These parameters are known as Archie parameters. To identify accurately the water saturation for a given reservoir condition, it depends critically on the accurate estimates of the values of Archie parameters (a, m, n). These parameters are interdependent and hence it is difficult to identify them accurately. So we present a new hybrid global optimization technique, where a gradient-based method with BFGS update is combined with an intelligent algorithm called Artificial Bee Colony. This new hybrid global optimization technique has both the fast convergence of gradient descent algorithm and the global convergence of swarm algorithm. It is used to identify Archie parameters in carbonate reservoirs. The results obtained are highly satisfactory. To further test the effectiveness of the new hybrid global optimization method, it is applied to ten non-convex benchmark problems. The outcomes are encouraging. |
| first_indexed | 2025-11-14T06:52:49Z |
| format | Conference Paper |
| id | curtin-20.500.11937-10930 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:52:49Z |
| publishDate | 2015 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-109302023-02-27T07:34:27Z A New Hybrid Optimization Algorithm for the Estimation of Archie Parameters liu, J. Xu, Honglei Wu, G. Teo, Kok Lay Honglei Xu Song Wang Soon-Yi Wu Archie parameters Gradient-based method ABC algorithm Hybrid global optimization Archie formula, which contains three fundamental parameters (a, m, n), is the basic equation to compute the water saturation in a clean or shaly formation. These parameters are known as Archie parameters. To identify accurately the water saturation for a given reservoir condition, it depends critically on the accurate estimates of the values of Archie parameters (a, m, n). These parameters are interdependent and hence it is difficult to identify them accurately. So we present a new hybrid global optimization technique, where a gradient-based method with BFGS update is combined with an intelligent algorithm called Artificial Bee Colony. This new hybrid global optimization technique has both the fast convergence of gradient descent algorithm and the global convergence of swarm algorithm. It is used to identify Archie parameters in carbonate reservoirs. The results obtained are highly satisfactory. To further test the effectiveness of the new hybrid global optimization method, it is applied to ten non-convex benchmark problems. The outcomes are encouraging. 2015 Conference Paper http://hdl.handle.net/20.500.11937/10930 http://link.springer.com/chapter/10.1007/978-3-662-47044-2_7#page-1 Springer restricted |
| spellingShingle | Archie parameters Gradient-based method ABC algorithm Hybrid global optimization liu, J. Xu, Honglei Wu, G. Teo, Kok Lay A New Hybrid Optimization Algorithm for the Estimation of Archie Parameters |
| title | A New Hybrid Optimization Algorithm for the Estimation of Archie Parameters |
| title_full | A New Hybrid Optimization Algorithm for the Estimation of Archie Parameters |
| title_fullStr | A New Hybrid Optimization Algorithm for the Estimation of Archie Parameters |
| title_full_unstemmed | A New Hybrid Optimization Algorithm for the Estimation of Archie Parameters |
| title_short | A New Hybrid Optimization Algorithm for the Estimation of Archie Parameters |
| title_sort | new hybrid optimization algorithm for the estimation of archie parameters |
| topic | Archie parameters Gradient-based method ABC algorithm Hybrid global optimization |
| url | http://link.springer.com/chapter/10.1007/978-3-662-47044-2_7#page-1 http://hdl.handle.net/20.500.11937/10930 |