Reservoir

Operators are turning to new gas-lift and nanoparticle-fluid technologies to drive up production rates.

This paper addresses the difficulty in adjusting late-stage production in waterflooded reservoirs and proposes an integrated well-network-design mode for carbon-dioxide enhanced oil recovery and storage.

This work presents the development of fast predictive models and optimization methodologies to evaluate the potential of carbon-dioxide EOR and storage operations quickly in mature oil fields.

The authors of this paper apply a deep-learning model for multivariate forecasting of oil production and carbon-dioxide-sequestration efficiency across a range of water-alternating-gas scenarios using field data from six legacy carbon-dioxide enhanced-oil-recovery projects.

This paper assesses the technical feasibility of geological carbon storage in the operator’s Brazilian brownfields, focusing on mature oil fields and associated saline aquifers.

As the industry accelerates carbon capture, use, and storage initiatives, modeling innovations for carbon-dioxide injection and enhanced oil recovery have become critical for optimizing recovery and ensuring secure storage. Recent studies highlight a shift toward data-driven and hybrid approaches that combine computational efficiency with operational practicality.

The $1.3-billion deal targets DJ Basin assets producing 35,000 BOEPD, and Japex aims to increase that output to 50,000 BOEPD around 2030.

Sustainability in reservoir management emerges not from standalone initiatives but from integrated, data-driven workflows, where shared models, closed-loop processes, and AI-enabled insights reduce fragmentation and make sustainable performance a natural outcome.

The $100-billion project is widely considered the largest unconventional development outside of the US and is noted by Aramco as the largest nonassociated gas development in the kingdom.

This study presents a novel hybrid approach to enhance fraud detection in scanned financial documents.