Using Machine Learning To Understand Well Performance Drivers and Inform Decisions with Data :: Novi’s SPE Presentation

USING MACHINE LEARNING FOR WELL PERFORMANCE ANALYSIS & FORECASTING

The presentation is about how machine learning forecasts can both confirm and complement traditional Rate Transient Analysis (RTA) methods in unconventional fields In the presentation, Scott McEntyre discusses the following:

  1. Ensemble Tree Machine Learning Methods
  2. Examples of ML Insight in Oil & Gas
  3. How ML Confirms & Complements RTA/PTA
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INTRODUCING CAUSAL MODELS

Accurate forecast on parent-child developments

In this live webinar, you will learn how Novi’s new algorithm improves model sensitivity for spacing and parent-child scenarios, providing powerful results for previously difficult-to-analyze problems.

Ted Cross, our VP of Product Management, will show you how this update improves spacing and infill scenario analysis without sacrificing model accuracy.