Reservoir

In this study, forward simulation is executed by a commercial reservoir simulator while external code is developed for backward calculations.

This paper presents a workflow that leverages a multiagent conversational system to integrate data, analytics, and domain expertise for improved completion strategies.

Findings from two new SPE papers argue that the tight-rock sector needs to rethink longstanding assumptions about how hydraulic fractures form underground.

In this study, the authors propose the use of a deep-learning reduced-order surrogate model that can lower computational costs significantly while still maintaining high accuracy for data assimilation or history-matching problems.

This paper demonstrates the effectiveness of integrating dynamic gas separation with existing gas-avoidance methods within the same electrical submersible pump string to address these issues.

The authors propose a deep-learning-based approach enabling near-real-time CO2-plume visualization and rapid data assimilation incorporating multiple geological realizations for predicting future CO2 plume evolution and area-of-review determination.

The three featured papers illustrate how emerging computational methods—ranging from gradient-based optimization to data-driven proxies—are reshaping reservoir characterization, uncertainty assessment, and real-time decision support across diverse subsurface applications.

The newest recipient of the title SPE Legend of Hydraulic Fracturing talks about his career, the evolution of fracture stimulation, the development of increasingly useful simulators, and the future of the oil and gas industry. The honor was given at the 2026 SPE Hydraulic Fracturing Technology Conference and Exhibition.

The operator developed a solution that has kept the well at stable production for over a year after treatment.

The rise in China’s gas production, now exceeding that of Qatar and of Australia, is also limiting growth in its LNG demand.