Data & Analytics

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

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.

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

The trial phase of the agentic program used AI agents and combined large-language-model technology with data collected from more than 15% of ADNOC’s onshore and offshore wells.

SLB said it plans to integrate INT’s technology into its digital data and artificial intelligence platforms.

Chevron’s announcement comes on the heels of ExxonMobil’s announcement in December of a similar project to deliver natural gas-fueled electricity to US data centers.