Monday, May 07
Attendees will become familiar with the fundamentals of data-driven analytics and the most popular techniques that are used to perform such tasks such as conventional statistics, artificial neural networks, and fuzzy set theory.
This course will demonstrate through actual case studies (real field data from hundreds of shale wells) how to build a data-driven predictive model and how to use them in order to perform an analysis.
- How to treat data in the context of data-driven analytics
- Organize and prepare the data for predictive modeling
- How to make sure that the physics of fluid flow in shale is honored during the predictive analytics
- How to build predictive models using data as the main building block
- How to avoid over-training (memorization) while promoting generalization