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Panelists said AI is helping companies analyze permits, contracts and production data faster, but human judgment still matters most.
Artificial intelligence is increasingly being adopted across the oil patch, with energy companies discovering diverse applications for the technology. This trend was a central topic of discussion at the recent Permian Basin Environmental Regulatory Seminar, co-hosted by Midland College’s Petroleum Professional Development Center and the Permian Basin Petroleum Association. The seminar highlighted how AI is transforming operations, from initial data analysis to complex decision-making processes. Companies are finding that AI offers significant benefits in terms of efficiency and insight, enabling them to handle vast amounts of data more effectively and derive actionable intelligence. This broad embrace of AI signifies a major shift towards technology-driven solutions in the energy sector, aiming to optimize various stages of oil and gas operations.
In the technical realm, AI is being proactively utilized for critical tasks such as monitoring geologic features and subsurface fault mapping, as noted by Yogashri Pradhan of Iron Lady Energy Advisors. By analyzing historical data, AI can extrapolate and identify potentially seismically sensitive sites, allowing for more informed and safer operational planning. Akash Sharma, Vice President of Product Management at Enverus, emphasized that AI serves as a tool to achieve specific outcomes, enabling companies to connect AI-generated data with other datasets for comprehensive problem-solving. These applications demonstrate AI's capacity to enhance predictive capabilities and technical precision, which are crucial in the complex and high-stakes environment of oil and gas exploration and production.
AI significantly boosts data efficiency and the analytical capabilities of energy companies. Wil Vark, Business Solutions and Application Development Manager at University Lands, explained that AI streamlines data processing by extracting information from various documents, permits, and plats uploaded by operators. This automation frees analysts from manual data entry, allowing them to focus on interpreting the information and making strategic decisions. Sharma further highlighted the importance of understanding the geographic area and connecting diverse data points to maximize AI's effectiveness. This allows for better decision-making, such as identifying potential fault triggers, thereby improving operational safety and resource management. The ability of AI to rapidly synthesize and present complex data from disparate sources is proving invaluable for modern energy operations.
Despite AI's advanced capabilities, the panel collectively stressed that human judgment remains irreplaceable. This is particularly true in critical decision-making processes, such as the approval cycle for authorizations for expenditures (AFEs). While AI can provide a more complete picture of expected production and potential opportunities, human expertise is essential for final validation and strategic oversight. The panelists acknowledged AI's strength in tasks like extracting and summarizing information from contracts for landmen and analysts. However, Vark cautioned about the need to educate staff on the nature of AI responses, as AI is programmed to always provide an answer, even if it doesn't fully 'understand' the question, necessitating careful human verification.
The path to wider AI adoption in the energy sector faces several challenges and misconceptions. A primary concern, articulated by Pradhan, is the fear that AI will lead to job displacement. There's also a general lack of understanding regarding how AI functions and the underlying reasons for its generated responses. Vark underscored the critical need to integrate sensitive information protection into AI training protocols to maintain data security. Henkhaus emphasized the importance of transparency and proper citations when utilizing AI. The prevailing misconception, that AI will outright replace human jobs, was strongly refuted by the panelists. Pradhan clarified that AI serves as a decision-support tool, leveraging existing human experience rather than supplanting it. Sharma added that AI is not a universal solution, requiring a clear understanding of its limitations and appropriate applications.
Looking ahead, Wil Vark described AI as a rapidly evolving field, suggesting that the best approach for companies is to remain continually aware of AI trends and developments. He envisions AI seamlessly integrating into technology, becoming an 'invisible layer' that enhances existing systems without overt presence. This perspective highlights a future where AI is not a standalone solution but an embedded component that augments human capabilities and operational efficiency. The continuous evolution of AI necessitates ongoing learning and adaptation within the energy industry to harness its full potential as an integral part of technological advancement.