Training - Introduction to Data Analytics and Machine Learning Techniques for Geosciences and Reservoir Engineering

Code
MLRES-EN-P
Level
Awareness
Certificate

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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Objectives

3 days
This course is designed for employees from the same company and can be delivered either at one of our training centers or at a location of your choice. The content can be customized to meet your specific needs.
    • Face-to-face only
This training course is provided by IFP Training. To choose a session and register, visit the IFP Training website.
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      Coordinator
      IFP Training instructors, with expertise in the field and trained in modern teaching methods adapted to the specific needs of learners from the professional world

      Expected skills

      • Operate an industrial plant or equipment
      • Optimize operation of an industrial plant or equipment

      Training - Introduction to Data Analytics and Machine Learning Techniques for Geosciences and Reservoir Engineering

      http://www.ifptraining.com/web/image/product.template/394/image_1920?unique=0887e80 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

      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

      1.00 € EUR

      1.00 €

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      Language: English
      Modality: Face-to-face only

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