Formation - Introduction to Data Analytics and Machine Learning Techniques for Geosciences and Reservoir Engineering
This course provides an extensive and practical knowledge for applying data analytics in reservoir modeling and predicting the well performance; the data driven approach is used to understand the main factors affecting the reservoir performance, using the fuzzy logic to rank these parameters and build a predictive model to optimize the reservoir response. Emphasis will be put on the use of supervised and unsupervised neural networks algorithms
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Objectifs
Programme
Pédagogie
Evaluation des acquis
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Compétences visées
- Operate an industrial plant or equipment
- Optimize operation of an industrial plant or equipment
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Formation - Introduction to Data Analytics and Machine Learning Techniques for Geosciences and Reservoir Engineering
This course provides an extensive and practical knowledge for applying data analytics in reservoir modeling and predicting the well performance; the data driven approach is used to understand the main factors affecting the reservoir performance, using the fuzzy logic to rank these parameters and build a predictive model to optimize the reservoir response. Emphasis will be put on the use of supervised and unsupervised neural networks algorithmsThis course provides an extensive and practical knowledge for applying data analytics in reservoir modeling and predicting the well performance; the data driven approach is used to understand the main factors affecting the reservoir performance, using the fuzzy logic to rank these parameters and build a predictive model to optimize the reservoir response. Emphasis will be put on the use of supervised and unsupervised neural networks algorithms
| Langue: Anglais |
| Modalité: Présentiel |