Reservoir
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.
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Well testing has enjoyed a recent uptick in activity and interest as operators continually realize the value in understanding and monitoring the dynamic performance of their reservoirs. -
Uncertainty comes in all scales and dimensions. This challenges us to learn at all scales possible, from the fume hoods in the laboratory to magnificently exposed outcrops and through deep narrow boreholes that drill through subsurface reservoirs. The combined efforts often convert learnings to actionable intelligence.
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Chevron has some new ideas on how to get more oil for less cost out of shale wells in their early years.
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Casing deformations are common in the south-west shale regions of China and the Middle East, where the widespread use of 5.5-in., 26- and 26.8-lb/ft casing is the norm. In these regions, the majority of frac plugs are designed with an outer diameter (OD) of 4.055 in. or slightly larger, which frequently encounter restrictions resulting in the loss of bottomhole assemb…
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The authors of this paper propose an artificial-intelligence-assisted work flow that uses machine-learning techniques to identify sweet spots in carbonate reservoirs.
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In this paper, the effect of cold-water injection on pressure transient analysis (PTA) of geothermal reservoirs is studied by varying the temperature of the injected cold water from room temperature to reservoir temperature.
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This paper describes an effort to use multiple technologies to better understand an Arkoma Basin reservoir and the interdisciplinary relationship between the reservoir’s subsurface hazards and a stimulation treatment.
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The authors of this paper describe a seismic reprocessing campaign for an Egyptian oil field that had yielded poor seismic data.
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This paper describes a method with multitiered analysis to leverage machine-learning techniques to process passive seismic monitoring data, pumping and injection pressure, and rate for fracture and fault analysis.
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The main objective of this paper is to investigate the relationship between strain change and pressure change under various fractured reservoir conditions to better estimate conductive fractures and pressure profiles.
