Fracturing/pressure pumping
This case study from ARC Resources and DarkVision outlines the use of acoustic imaging tools in two active fracturing programs in Canada to monitor well casing deformation.
The creation of SPE’s Acid Stimulation Technical Section shines a light on the technique that improves injectivity and productivity. JPT talked with the chair of the new section about the importance of the technical area.
Fracture modeling continues to be used to evaluate and design novel applications, and integration with diagnostics and other forms of field-data collection are crucial to success.
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Two US test sites have fractured hot, dry rock with plans to create a network of fractures for water heating. They will soon find out if the fractures worked as expected. -
This article presents a new data-driven analysis to locate low-frequency seismic sources, referred to as near-infrasound or infrasound sources. Combining these infrasound signals with microseismicity signals allows for better characterization and monitoring of the stimulated reservoir volume.
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Fracturing hot rock to create a geological water-heating system is like fracturing an oil well, but for a different purpose, so is proppant really necessary?
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When confronted by extremely hot wells drilled into hard rock, engineers start looking for new tools and then ask, is there a cheaper option?
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From refracturing old wells to ones that don’t have to be fractured at all, notable producers argue that experiments are paying off.
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The SPE Hydraulic Fracturing Technology Conference and Exhibition is being held 31 January–2 February in The Woodlands, Texas.
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ProPetro will provide committed services for a 3-year period to an undisclosed Permian Basin operator.
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This paper presents a numerical simulation work flow, with emphasis on hydraulic fracture simulation, that optimizes well spacing and completion design simultaneously.
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Recent studies have reignited the question of whether US oil and gas companies are ignoring the opportunity to refracture large swaths of maturing assets.
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The authors discuss the development of a deep-learning model to identify errors in simulation-based performance prediction in unconventional reservoirs.
