Fracturing/pressure pumping
This paper focuses on a replicable, quantitative workflow using completions-process simulation software.
This paper presents a high-fidelity, reservoir-centric stimulation-to-production modeling workflow to prevent fracture-driven interactions.
This work elaborates on recommended practices for calibrating a numerical model to a set of available infill-well field observations.
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Years in the making, the program sponsored by the US Department of Energy is celebrating its latest geothermal energy breakthrough in southwestern Utah. -
Operators are turning the tide on the Lower Tertiary trend with increasingly large stimulations that are also pushing the limits of offshore technology.
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Matthew Bryant has spent years trying to convince engineers that the API proppant testing standard has significant limitations. And he may well be right.
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The Midland-based service company operates a fleet that is now 65% either dual-fuel or electric-powered.
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The second major deal in the US proppant industry this year will see US Silica go forward as a private company.
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This paper explains how an operator’s projects in the Vaca Muerta have become more-efficient and cost-effective by increasing production and reducing well-delivery-cycle time while fostering the long-term sustainability of the project.
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Despite tens of thousands of potential candidates and the proven upsides, the unconventional industry has largely overlooked refracturing—possibly due to the way it’s discussed.
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The tie between US crude output and key indicators such as rig counts and the number of new wells has significantly weakened.
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High-pressure/high-temperature (HP/HT) resources continue to be a focus of efforts to apply new technologies that maximize productivity while addressing concerns related to capital expenditure, operating expenses, and high drilling costs. These cost-effective technologies will only grow in importance in exploiting HP/HT and ultra-HP/HT fields.
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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.
