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The TWA Editorial Board is accepting nominations for “TWA Energy Influencers 2025: Young Professionals Who Energize Our Industry.” Nominate a YP by 1 July 2025.

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 …

The authors propose a hybrid virtual flow and pressure metering algorithm that merges physics-based and machine-learning models for enhanced data collection.

This paper evaluates the effect of rapid cooling on the rock-cutting process and incorporates this effect as a component of drilling-performance optimization.

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This paper presents a comprehensive model of geothermal exploitation for depleted deep heavy oil reservoirs through supercritical CO₂ injection.

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 discusses the concept, applications, and continual evolution of a new 3D temperature and spectral-acoustics modeling and logging approach.