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In this paper, example machine-learning models were trained using geologic, completion, and spacing parameters to predict production across the primary developed formations within the Midland Basin.

The authors of this paper describe a technology built on a causation-based artificial intelligence framework designed to forewarn complex, hard-to-detect state changes in chemical, biological, and geological systems.

This paper presents a family of machine-learning-based reduced-order models trained on rigorous first-principle thermodynamic simulation results to extract physicochemical properties.

This paper is a summary of a study that covers through-life economics for producing green hydrogen from offshore fixed wind turbines.

The authors of this paper present the results of an assessment of two regions in Uruguay suitable for bottom-fixed offshore wind technologies.

New studies are a reminder that the effort to identify, classify, and nullify frac hits remains paramount to the future of the unconventionals business.

The heated global floating rig market has day rates for high-end units climbing over a half million dollars and toward a newbuild cycle that will (likely) never come.

Lebanon hopes to join the club of EastMed gas producers as TotalEnergies and its partners spud an appraisal well near Beirut’s maritime border with Israel where gas is already being produced.

Fervo Energy’s bet that fracturing methods can be used for geothermal power is looking like a winner.

Over a 10-year period, sensors monitoring the motion and loads near subsea wellheads have been mounted on more than 300 drilling campaigns. Integrity parameters were calculated to assess whether subsea conductors provided the intended amount of support during drilling operations. In several of these campaigns, loss of conductor support due to integrity issues was obse…

Wave power plus a subsea battery can be a reliable source for subsea operations, to a point.

Woodside confirms key contracts for deepwater Mexican Gulf development.