DSDE: In Practice
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The paper demonstrates the ability of deep-learning generative models to enable new shale-characterization methods. -
The paper presents a model for shale gas production in which CO2 is injected by huff ’n’ puff into a hydraulic fracture surrounded by a shale matrix.
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This paper describes how severe rig limitations were overcome through an optimization plan in which an optimal bottomhole assembly was designed and drilling practices were customized.
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The survey was part of a project led by the University of Aberdeen, looking at the effects of decommissioning oil and gas structures on marine ecosystems.
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This paper presents experiences from an automated drilling-fluids-monitoring initiative and resulting real-time hydraulic measurements and models for automatic drilling control.
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This paper analyzes several configurations of convolutional neural networks suited for predicting upscaled fracture permeabilities and shape factors required to close a dual porosity/dual permeability model.
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This paper describes a novel control scheme developed and tested on simulation for both hydrodynamic slugging and severe riser-induced slugging for a new facility in Angola.
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The authors write that simple and straightforward observations on outcrops can be used to build 3D models that mimic geological relationships accurately.
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TGS, BGP, and CGG signed an agreement with state-owned Staatsolie to acquire, promote, and license multiclient seismic programs, including new 3D acquisition, in the shallow waters offshore Suriname.
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The authors describe how tools in machine learning are used to develop data-driven models that can be used for accurate and efficient fatigue-damage prediction for marine risers.
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