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The proposed joint venture aligns with Eni's satellite model strategy to create entities that manage operations and access capital markets separately from the parent company.

Mero expects to increase its production capacity to over 700,000 B/D.

The new burner, created with the help of machine learning and additive manufacturing, promises high methane destruction efficiency and combustion stability even in windy conditions.

The supermajor is making a major course correction as it plans to slash renewable investment and focus more on oil and gas development.

The operator plans to acquire seismic and carry out appraisal drilling at the site later this year; the find could be fast-tracked as a tieback to the Goliat FPSO.

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

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.

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.

This article kicks off a Q&A series from the SPE Research and Development Technical Section, focusing on emerging energy technologies. In this piece, Amy Bason of the Oil and Gas Climate Initiative highlights decarbonization efforts in global transportation.

Few things are more essential to the now global hydraulic fracturing revolution than access to fresh water, yet this dependency use has raised environmental concerns and operational challenges.

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