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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.

This paper examines how real-time monitoring can improve both incident prevention and emergency response in the oil and gas industry. Drawing from real-world examples and case studies, it provides practical strategies for implementing this technology effectively.

This paper addresses the difficulty in adjusting late-stage production in waterflooded reservoirs and proposes an integrated well-network-design mode for carbon-dioxide enhanced oil recovery and storage.

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This article is the sixth and final Q&A in a series from the SPE Research and Development Technical Section focusing on emerging energy technologies. In this final edition, Matthew T. Balhoff, SPE, of The University of Texas at Austin shares his views on the future of upstream education.

This paper introduces a system that leverages sophisticated algorithms and user-friendly interfaces to tackle the challenge of developing complex, compartmentalized reservoirs effectively.

This paper presents a novel application of artificial intelligence in computer vision for automating blowout-preventer pressure-chart-data extraction, demonstrating significant efficiency gains and a high return on investment.

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.

What do today’s membership trends mean for SPE? While declining numbers and an aging demographic can be unsettling, the reality is that these challenges are not unique to SPE. As professional associations everywhere face generational shifts, SPE members have an opportunity to hear about the success stories ongoing now and reflect on what will sustain our community in …

As the industry accelerates carbon capture, use, and storage initiatives, modeling innovations for carbon-dioxide injection and enhanced oil recovery have become critical for optimizing recovery and ensuring secure storage. Recent studies highlight a shift toward data-driven and hybrid approaches that combine computational efficiency with operational practicality.