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Oil And Gas Subsurface Management By Artificial Intelligence
![]() Oil And Gas Subsurface Management By Artificial Intelligence Published 7/2026 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 1h 59m | Size: 1.29 GB What you'll learn Oil and Gas Asset Development and Planning Basics of subsurface expertise and management Defining an oil and gas asset with AI Analysis and integration of Surface and Subsurface Data AI Supported Subsurface Management Selection of Infill Drilling Location Supported by AI Requirements Oil and Gas Reservoir Knowladge Description This course contains the use of artificial intelligence. 30+ years of oil and gas industry experience and accumulated expertise material were used to develop this course material AI is not simply another software tool for the upstream industry-it is changinghow technical decisions are made. Historically, upstream improvements came from better seismic imaging, faster simulators, or more computing power. AI introduces a different paradigm: it augments human expertise by helping professionals extract knowledge from massive amounts of structured and unstructured data, automate repetitive analyses, and support more informed decisions under uncertainty. For upstream organizations, the key question is no longer"Can AI interpret a well log?" but"How can AI help us make better asset decisions faster?" - AI addresses the industry's growing data volume, complexity, and workforce challenges. - The goal isbetter and faster decisions, not replacing technical professionals. - AI is most valuable when combined with engineering knowledge, domain experience, and sound governance. - Successful organizations will integrate AI into existing workflows while maintaining human accountability. - Future subsurface leaders will combinetechnical expertise, data literacy, AI fluency, and decision-making skills. Unlike generic AI courses, this program is centered onsubsurface decision-making rather than software development. Participants learn to embed AI into exploration, reservoir management, surveillance, production optimization, and strategic asset governance while maintaining engineering judgment. The outcome is not just AI literacy, but the ability to leadAI-enabled subsurface organizations and improve the quality, speed, and consistency of technical and business decisions. Who this course is for Geologists Reservoir Engineers Reservoir Simulation Engineers Geophysicist Petrophysicist |
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