watex: machine learning research in water exploration
Water exploration is a scientific domain mostly devoted to the hydro-geophysics field. For instance, geophysical methods such as direct-current, electromagnetic (EM), and logging are primarily used in companionship with pure hydrogeological techniques to propose the right location for drilling opera...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-05-01
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| Series: | SoftwareX |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352711023000638 |
| _version_ | 1797818658703015936 |
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| author | Kouao Laurent Kouadio Jianxin Liu Rong Liu |
| author_facet | Kouao Laurent Kouadio Jianxin Liu Rong Liu |
| author_sort | Kouao Laurent Kouadio |
| collection | DOAJ |
| description | Water exploration is a scientific domain mostly devoted to the hydro-geophysics field. For instance, geophysical methods such as direct-current, electromagnetic (EM), and logging are primarily used in companionship with pure hydrogeological techniques to propose the right location for drilling operations and determine the permeability coefficient (k) parameter. Unfortunately, despite this combination, unsuccessful, unsustainable boreholes are persisting and the k parameter collection remains difficult and costly thereby creating a huge loss for funders, geophysical and drilling ventures. watex library brings efficient algorithms and smart approaches to solve these issues. Indeed, the recovery of loss EM signals, the automatic location detection for drilling operations, the prediction of flow rate, and the mixture learning strategy using machine learning are some sustainable solutions developed by watex to reduce the numerous losses for future hydro-geophysical engineering projects. |
| first_indexed | 2024-03-13T09:11:12Z |
| format | Article |
| id | doaj.art-a5fb71175d12436e9191553354724bd5 |
| institution | Directory Open Access Journal |
| issn | 2352-7110 |
| language | English |
| last_indexed | 2024-03-13T09:11:12Z |
| publishDate | 2023-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | SoftwareX |
| spelling | doaj.art-a5fb71175d12436e9191553354724bd52023-05-27T04:25:53ZengElsevierSoftwareX2352-71102023-05-0122101367watex: machine learning research in water explorationKouao Laurent Kouadio0Jianxin Liu1Rong Liu2School of Geosciences and Info-physics, Central South University, Changsha, Hunan 410083, China; Hunan Key Laboratory of Nonferrous Resources and Geological Hazards Exploration, Changsha, Hunan 410083, China; UFR des Sciences de la Terre et des Ressources Minières, Université Félix Houphouët-Boigny, Abidjan, 22 BP 582 Abidjan 22, Cote d’IvoireSchool of Geosciences and Info-physics, Central South University, Changsha, Hunan 410083, China; Hunan Key Laboratory of Nonferrous Resources and Geological Hazards Exploration, Changsha, Hunan 410083, ChinaSchool of Geosciences and Info-physics, Central South University, Changsha, Hunan 410083, China; Hunan Key Laboratory of Nonferrous Resources and Geological Hazards Exploration, Changsha, Hunan 410083, China; Corresponding author at: School of Geosciences and Info-physics, Central South University, Changsha, Hunan 410083, China.Water exploration is a scientific domain mostly devoted to the hydro-geophysics field. For instance, geophysical methods such as direct-current, electromagnetic (EM), and logging are primarily used in companionship with pure hydrogeological techniques to propose the right location for drilling operations and determine the permeability coefficient (k) parameter. Unfortunately, despite this combination, unsuccessful, unsustainable boreholes are persisting and the k parameter collection remains difficult and costly thereby creating a huge loss for funders, geophysical and drilling ventures. watex library brings efficient algorithms and smart approaches to solve these issues. Indeed, the recovery of loss EM signals, the automatic location detection for drilling operations, the prediction of flow rate, and the mixture learning strategy using machine learning are some sustainable solutions developed by watex to reduce the numerous losses for future hydro-geophysical engineering projects.http://www.sciencedirect.com/science/article/pii/S2352711023000638Python, machine learning, algorithms, hydro-geophysics, water |
| spellingShingle | Kouao Laurent Kouadio Jianxin Liu Rong Liu watex: machine learning research in water exploration SoftwareX Python, machine learning, algorithms, hydro-geophysics, water |
| title | watex: machine learning research in water exploration |
| title_full | watex: machine learning research in water exploration |
| title_fullStr | watex: machine learning research in water exploration |
| title_full_unstemmed | watex: machine learning research in water exploration |
| title_short | watex: machine learning research in water exploration |
| title_sort | watex machine learning research in water exploration |
| topic | Python, machine learning, algorithms, hydro-geophysics, water |
| url | http://www.sciencedirect.com/science/article/pii/S2352711023000638 |
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