Reservoir
This paper documents the testing, integration, and field deployment of a metal expandable packer used as an openhole toe isolation plug in a deepwater well under high-pressure, high-temperature conditions.
Three papers are highlighted as the primary contributions because of their broad industry relevance. They focus on improving formation particle-size characterization, expanding the application of openhole gravel packs in depleted and compartmentalized reservoirs, and advancing the understanding of capillary pressure in sand production.
This paper aims to establish a set of best practices for generating particle-size-distribution data from core samples.
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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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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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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 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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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 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.
