Guest Editorial: The Agentic Oil Field—No Longer a Vision, It Is Inevitable
Satyam Priyadarshy
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The oil and gas industry, while working at the cutting edge of engineering physical systems, remains a laggard in adopting digital disruption. If this imbalance between physical and digital technologies persists, capital destruction will continue to grow, the time to identify sweet spots will lengthen, and the trauma of a future workforce shortage will intensify. The industry has discussed digital oil fields, integrated reservoir management, and real-time, data-driven decision-making for over 3 decades, yet many of these concepts remain in their infancy. Today, the upstream oil and gas industry is at a crossroads, facing another strategic inflection point (SIP). This SIP proposes adopting generative artificial intelligence (AI) and agentic AI now to advance the industry and build resilience. Otherwise, the industry will continue to incur the costs of delayed action, as has been the case with big data and traditional AI. For example, the Open Subsurface Data Universe (OSDU) Forum, now known as The Open Group OSDU Forum, was established in 2018 to break down silos in the oil and gas industry through an open-source, standardized data platform. It has been almost 7 years since its inception, and the forum is working to bring traditional AI into the fold, underscoring the industry's slow adoption of emerging technologies. The industry needs to leapfrog from digital oil fields to agentic oil fields to remain a key player in the energy transition landscape. What is the agentic oil field, and how can one plan for, deploy, and benefit from it? I define an agentic oil field as one that uses advanced AI systems—especially generative AI and AI agents—across its operations to work more independently and intelligently. These systems can understand information, make decisions, and take actions with less human intervention while operating within clear, flexible rules and regulations. This approach goes beyond small improvements. It changes how the oil field runs, making it faster, smarter, safer, and more productive. The agentic oil field goes well beyond a digital oil field. In simple terms, the digital oil field focuses on connecting equipment, collecting data, and giving greater visibility to professionals, with humans remaining at the center of command. In an agentic oil field, AI agents and generative AI systems understand data, reason through scenarios and options, and make decisions with minimal human intervention. This allows seamless integration of the industry’s typical silos—exploration, drilling, production, operations, and others. Let me illustrate the importance of the agentic oil field within the context of three grand challenges the oil and gas industry faces at scale. The first grand challenge is declining productivity and margins in mature assets and complex reservoirs. The digital oilfield solution improves visibility and helps optimize operations manually, yielding incremental gains that fall short of reducing high costs. However, with the agentic oilfield practice, autonomous real-time adjustments enhance production while reducing costs caused by delays in manual intervention, resulting in sustained performance improvement across the asset life cycle. This reflects my research, which incorporates input from academics, companies, and national authorities, and indicates that production uplift may rise to 8% with the agentic oil field, compared with less than 4% if the industry focuses only on the digital oil field.
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计算机 / AIArtificial Intelligence Applications
Digital Transformation in Industry · Impact of AI and Big Data on Business and Society
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