Reservoir
Coreflood experiments reveal that alkali significantly reduces viscosity loss in polyacrylamide flooding systems by minimizing adsorption and improving polymer stability under shear stress. The findings position viscosity retention as a key screening criterion for successful alkali-polymer enhanced-oil-recovery applications.
This SPE technical section editorial synthesizes six technical themes shaping CO2 transport and storage and interprets them through a petroleum engineering capability lens.
The UAE project is expected to produce up to 345 MMscf/D by 2029, with expansion potential to 1 Bcf/D.
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Suriname's wait to become a significant oil producer may be nearing an end as the French supermajor begins early development studies. -
Diamondback Energy has agreed to spin off its water operations. Now, who’s next?
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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.
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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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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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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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This paper presents a comprehensive technical review of applications of distributed acoustic sensing.
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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.
