Reservoir
The UAE project is expected to produce up to 345 MMscf/D by 2029, with expansion potential to 1 Bcf/D.
This study investigates the potential for in-situ hydrogen generation from hydrocarbons using in-situ combustion, with particular emphasis on the role of kerogen content and heating mode.
This paper presents the application of degradable particulate-diverter technology to improve oil production by effectively diverting stimulation treatment fluids away from high-water-cut, high-permeability, high-temperature producing intervals or zones.
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On a pro forma basis, the mineral and royalty arm of the Midland-based oil company owns interests covering more than 32,000 net acres in the Permian Basin. -
SponsoredThe data that comes with mapping flow behavior at the stage level of unconventional wells was once accessible only through the installation of costly and intrusive diagnostic methodologies like fiber optic or running production logging. New-generation FloTrac ultrahigh-resolution nanoparticle tracer technology with subatomic spectroscopic measurement techniques now de…
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This paper presents a comprehensive technical review of applications of distributed acoustic sensing.
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This paper sheds light on newer frontiers of tracer applications with unconventional uses to gain flow insights from an oil and gas reservoir.
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The authors of this paper analyze a robust, well-distributed parent/child well data set using a combination of available empirical data and numerical simulation outputs to develop a predictive machine-learning model.
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This paper summarizes a collaborative industry study to compare observations between shale-play data sets and basins, develop general insights into parent/child interactions, and provide customized economic optimization recommendations.
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In this paper, example machine-learning models were trained using geologic, completion, and spacing parameters to predict production across the primary developed formations within the Midland Basin.
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New studies are a reminder that the effort to identify, classify, and nullify frac hits remains paramount to the future of the unconventionals business.
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The authors of this paper describe a technology built on a causation-based artificial intelligence framework designed to forewarn complex, hard-to-detect state changes in chemical, biological, and geological systems.
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North Dakota's EERC argues that the suboptimal frac jobs of yesterday explain why fracture interactions boost production in the tight-oil play.
