Unconventional/complex reservoirs
This paper provides details of a pilot study conducted on multiple wells, showcasing the potential of a novel biotechnology in Bakken enhanced oil recovery.
The authors of this paper describe a method of stimulating a multizone hydrocarbon-producing well wherein a tool is deployed downhole by wireline to generate acid vapor at a target depth, allowing each interval to be treated uniquely.
This work proposes a method to interpret far-field strain-change and pressure data to quantify fracture connectivity and properties at the cluster level.
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The authors of this paper present an artificial-lift timing and selection work flow using a hybrid data-driven and physics-based approach that incorporates routinely available pressure/volume/temperature, rate, and pressure information. -
This paper focuses on characterization of fracture hits in the Eagle Ford, methods to predict their effects on production, and mitigation techniques.
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As production dynamics evolve over the full life cycle of a tight-oil play, a single artificial lift method may not be the most cost-effective solution.
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SponsoredWhat are we, in the upstream oilfield service companies, doing about it? The Middle East upstream oil and gas industry is shifting its focus to unconventional and tight-gas resource development.
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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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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.
