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The authors present an artificial-intelligence and machine-learning technology to obtain a high-level, comprehensive view of all equipment in a facility to detect and map corrosion. -
It appears to be possible to sense how fractures change during production using ultrasensitive fiber-optic strain measurements.
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This paper introduces methods to fully couple reservoir simulation with wellbore flow models in fractured injection wells.
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The authors describe a study in which leakage-rate modeling was performed to identify and evaluate the associated risks for designing a remedial action plan to safeguard a CO2 storage site.
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When it comes to produced water from US shale plays, it’s either recycle and reuse or throw it away—and both are easier said than done.
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This paper provides an alternative solution to identifying, classifying, and vertically distributing fractures and a lateral distribution method for reservoir modeling.
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The paper demonstrates the ability of deep-learning generative models to enable new shale-characterization methods.
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A new dose of constraint may just be the best prescription for those making reserves estimates on prospective unconventional resources.
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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 a method to determine rig state from camera footage using machine-learning-based vision-analytics approaches.
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This paper examines current practices and developing trends in well construction and describes an alternative cementless approach to the discipline.
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This study explores pitfalls experienced when using capacitance/resistance modeling as a plug-and-play technique for waterflood optimization and discusses workarounds and mitigations to improve its reliability.
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