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The authors of this paper describe a suite of technologies that enables enhanced well robustness and performance modeling and monitoring of carbon storage facilities.

The authors of this paper describe an approach in which all available technologies are combined to improve understanding of reservoir depositional environments.

This paper presents the proof of concept of artificial-intelligence-based well-integrity monitoring for gas lift, natural flow, and water-injector wells.

Companies that can adapt, innovate, and stay ahead of the curve not only survive, but thrive. To achieve this, a fresh approach to innovation is required: one that harnesses the collective wisdom of customer advisory boards and prioritizes a strategy based on customer value.

The authors of this paper describe a project in which Raleigh frequency-shift distributed strain sensing monitored during production in a far-field observation well was translated to an estimated pressure profile.

Updates about global exploration and production activities and developments.

This paper defines conditions for optimized well-diagnostics investigation and describes a rigless solutions for common well-barrier failures and lessons learned from operator field trials.

SPE technical papers synopsized in each monthly issue of JPT are available for download for SPE members for 2 months. These December and January papers are available now.

The authors of this paper describe a project aimed at automating the task of cuttings descriptions with machine-learning and artificial-intelligence techniques, in terms of both lithology identification and quantitative estimation of lithology abundances.

Once considered as being on the brink of abandonment, aging reservoirs are proving to be valuable assets as innovative hydrocarbon recovery techniques and re-envisioning of these fields for decarbonization opportunities are transforming them into reservoirs of opportunity.