Data & Analytics
Major increases in hydrocarbon production require both incremental and revolutionary technologies, industry leaders said during the SPE Hydraulic Fracturing Technology Conference.
This paper presents a multifaceted approach leveraging precise rig control, physics models, and machine-learning techniques to deliver consistently high performance in a scalable manner for sliding.
This guest editorial explores the rise of agentic AI and its potential impact on oil and gas professionals.
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The authors of this paper apply a deep-learning model for multivariate forecasting of oil production and carbon-dioxide-sequestration efficiency across a range of water-alternating-gas scenarios using field data from six legacy carbon-dioxide enhanced-oil-recovery projects. -
This paper details a data-driven methodology applied in Indonesia to enhance flare-emission visibility and enable targeted reduction strategies by integrating real-time process data with engineering models.
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Are we in an AI bubble? The question may seem academic to petroleum engineers who are already capitalizing on the momentum of digitalization across the industry, yet any engineer, regardless of their career stage, could be forgiven for feeling overwhelmed by the sheer scope of specialized skills now demanded in this rapidly evolving digital landscape.
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This paper describes an auto-adaptive workflow that leverages a complex interplay between machine learning, physics of fluid flow, and a gradient-free algorithm to enhance the solution of well-placement problems.
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Experience in subsurface production and lift design is shaping a new generation of geothermal operations built for reliability and scalability.
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Even as output hits record highs, a growing recognition of the Permian’s maturity is opening the door for new technologies to improve performance.
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Switching from continuous circulation to cyclic huff-‘n’-puff operation in enhanced geothermal systems can significantly delay thermal breakthrough, sustain higher production temperatures, and improve long-term economic performance.
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The two companies say they plan to work together to use agentic AI to increase the capabilities of technical experts.
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This article is the first in a Q&A series from the SPE Methane Emissions Management Technical Section (MEMTS) on methane intelligence and how oil and gas teams translate emissions data into credible decisions and measurable reductions.
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This paper presents a robot integrated with a microcontroller that provides multiple functions to help with data logging, analysis, and reporting to identify hazards and improve safety protocols.
