What is the minimum amount of geological data required to build a predictive model?
Traditional basin modeling approaches utilize expensive datasets and significant time expenditure to understand and predict fluid distribution around the basin. Machine learning offers an empirical method to generate similar predictions. In contrast to the forward-modeling method of traditional basin modeling, machine learning looks for implicit relationships between training and target variables.
In this study, we investigate whether a machine learning model fed only geologic tops as input geological data can accurately predict well performance in the Bakken-Three Forks play of the Williston Basin
Tuesday, Wednesday, and Thursday, 9-10 AM & 3-4 PM (central time). Theme 3: Geochemistry, Basin Modeling, and Petroleum Systems