Client: A leading US-based Oil & Gas company.

Objective: To come up with an AI system that identifies how a well’s yield will change over time using its historical data.

Solution and Outcome: Company datasets collected over the years from multiple sources were structured and used to create a database for the training of a predictive AI system. With enough of the right data, AI detects patterns and provides metrics on well performance; thereby identifying potential stress points, and extrapolating accordingly. This allows pumpers to focus on high-value problems, and not data finding missions thereby offering enormous reductions in well downtime.