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Panelists from energy companies around the globe gathered to share their personal and company’s experiences in community engagement.

The Habshan project aims to capture and sequester 1.5 million tonnes of carbon dioxide per year.

While innovative solutions are being examined for decarbonization, there is one topic that is rarely emphasized as a key driver in the path toward a more-sustainable future—brownfield optimization.

In this inaugural podcast episode and transcript, Terry Palisch, who will officially begin his 2024 SPE presidency in October, discussed his views of the challenges facing our industry and SPE members, his outlook for our industry, and what his goals will be during his presidency.

This paper presents a comprehensive technical review of applications of distributed acoustic sensing.

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 analyze a robust, well-distributed parent/child well data set using a combination of available empirical data and numerical simulation outputs to develop a predictive machine-learning model.

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 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 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.