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| Titre: | Application of Improved Artificial Neural Network Algorithm in Hydrocarbons’ Reservoir Evaluation: Artificial Intelligence in Renewable Energetic Systems |
| Auteur(s): | Doghmane, Mohamed Zinelabidine
Belahcene, Brahim
Kidouche, M. |
| Mots-clés: | Improved Artificial Neural Network Algorithm in Hydrocarbons’ Reservoir Evaluation
Artificial Intelligence in Renewable Energetic Systems |
| Date de publication: | 2019 |
| Résumé: | The aim of this work is to develop an artificial neural network software tool in Matlab which allows the well logging interpreter to evaluate hydrocarbons reservoirs by classification of its existing facies into six types (clay, anhydrite, dolomite, limestone, sandstone and salt), the advantage of such classification is that it is automatic and gives more precision in comparison to manual recognition using industrial software. The developed algorithm is applied to eleven wells data of the Algerian Sahara where necessary curves (Gama Ray, density curve Rhob, Neutron porosity curve Nphi, Sonic curve dt, photoelectric factor curve PE) for realization of this technique are available. A graphical user interface is developed in order to simplify the use of the algorithm for interpreters |
| URI/URL: | http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/6275 |
| Collection(s) : | Chapitres D'ouvrages
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