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Understanding the Risk of Souring in the Bakken Using Advanced Analytics

Date Published: 5/22/2024
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Resource Abstract

This slide deck was presented to BPOP Members on May 22, 2024, as part of the EERC's ongoing BPOP webinar series. Recent EERC research using sulfur isotopes measured in Bakken Petroleum System (Bakken) H2S, rock, and water samples identified potential sources of H2S outside of the Middle Bakken (MB) and Three Forks reservoirs. Other published studies also suggest long-distance fracture propagation in stimulated wells, resulting in reservoir communication and drainage of fluids from reservoirs adjacent to the Bakken. The present work used machine learning to understand the mechanisms of souring in Bakken wells. The H2S concentration database was updated and now comprises over 6000 data points across the Bakken. Heat maps were built to quantify the risk of souring across the Bakken. A machine learning prediction model, Random Forest, was used to evaluate the importance of geologic, reservoir, production, and completion parameters for predicting souring

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