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Transitioning to a low-carbon economy demands large-scale CO2, natural gas, and hydrogen storage. In this context, the application of AI/ML technology to uncover geochemical, microbial, geomechanical, and hydraulic mechanisms related to storage and solve complicated history-matching and optimization problems, thereby enhancing storage efficiency, has been prominently …

This paper aims to investigate the use of an optimization workflow to maximize both hydrogen storage and the net present value to obtain an optimal reservoir development strategy.

This paper describes how ramp-up operations and commercialization of an underground storage asset were combined, rapidly providing a wide range of commercial services to the Italian gas system while long-term UGS performance increased continuously.

The authors introduce a novel framework combining dynamic mode decomposition, a data-driven model-reduction technique, with direct data assimilation to streamline the calibration of carbon-dioxide plume evolution models.

This paper presents various functionalities and benefits of a monitoring tool developed for and used with all critical flowmeters in the operator’s production system.

The path forward is not just about automation—it is about augmentation. AI is not replacing human expertise; it is amplifying it. Those who master this balance will define the future of oil and gas in a rapidly evolving energy landscape.

In the Marcellus, Repsol is slicing and dicing legacy data to evolve its completions strategy, while in the Permian, ExxonMobil is mastering the 4-mile lateral drillout using lessons learned.

Mentorship programs equip women with the tools to excel and help close the gender gap in leadership.

This section lists with regret SPE members who recently passed away.

The service giant shares new details about its automated fracturing spreads that slash human operator workload by 88%.