Using game theory and confidence interval outputs from a machine learning model to risk adjust oil well returns

In this video we walk through how Novi Shapley data and confidence interval data can be used to gain confidence in machine learning model predictions and handicap prospect well performance using model confidence as a proxy for risk. You can review the blog post here.

Questions or comments? Want to see how Novi can do the something similar for your assets. Drop us a line using the form under the video or click here.



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.