DSDE: In Practice
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This paper focuses on the vital task of identifying bypassed oil and locating the remaining oil in mature fields, emphasizing the significance of these activities in sustaining efficient oilfield exploitation.
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The authors of this paper propose hybrid models, combining machine learning and a physics-based approach, for rapid production forecasting and reservoir-connectivity characterization using routine injection or production and pressure data.
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The authors present an open-source framework for the development and evaluation of machine-learning-assisted data-driven models of CO₂ enhanced oil recovery processes to predict oil production and CO₂ retention.
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A novel approach uses the heart-shaped signal in low-frequency distributed acoustic sensing measurements to estimate the hydraulic fracture tip distance before the hydraulic fracture intersects the monitor well, offering critical insight into the characterization of hydraulic fracture propagation.
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Undocumented orphaned wells pose hazards to both the environment and the climate. Scientists are building modern tools to help locate, assess, and pave the way for ultimately plugging these forgotten relics.
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This investigation of fluid flow and particles movement uses a coupled CFD/DEM modeling approach to provide new insights into the multiscale mechanism of sand production.
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The authors of this paper discuss how intelligent completions in the Gulf of Mexico have allowed for increased production, reduction in operating expenses, enhanced overall reservoir recovery, and improved safety and environmental performance.
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The USGS has said up to 19 million tons of lithium resource is contained in the briny waters of the Smackover formation in Arkansas.
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This case study uses distributed temperature sensing (DTS) technology to monitor a cemented and plugged well in the Alaska North Slope, highlighting the versatile potential of DTS in long-term monitoring and establishing a workflow that makes the most of that potential.
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This paper reports the observation of stealth asphaltenes, a potential flow-assurance issue, by means of experimental analysis.
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