AI and ML Workflows Enhance ConocoPhillips’ Decision-Making for Permian Basin Assets

ConocoPhillips is leveraging automated artificial intelligence (AI) and machine learning (ML) workflows to make more efficient and economically sound decisions for its nonoperated assets in the Permian Basin. According to Tom Williford, a reservoir engineer at ConocoPhillips, these tools are crucial for rapidly evaluating opportunities and responding to asset operators within the required decision-making window, typically 30 days.

The Permian Basin, known for its prolific resources, presents challenges such as well communication, spacing, and bench performance, which must be considered in reserve exploitation planning. With numerous drilling and workover proposals needing timely responses, the AI- and ML-driven workflow enables ConocoPhillips to perform robust analyses quickly, ensuring decisions are based on economics rather than deadlines.

At the Unconventional Resources Technology Conference (URTeC), Williford and Johan Daal, another reservoir engineer at ConocoPhillips, highlighted the workflow’s ability to screen opportunities and return investment decisions in less than 30 days. The complex geology, stratigraphic variability, and fluid properties of the Permian Basin necessitate a thorough and rapid understanding of each development opportunity. The ML-based tool developed by ConocoPhillips integrates geological, completion, development, and performance data to optimize development strategies.

This automated workflow not only benefits nonoperated programs but also shows potential for operated programs, significantly reducing decision turnaround times from days to hours and elevating the decision-making process in unconventional reservoir development.

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