☆ 4.7 Article

Unsupervised learning monitors the carbon-dioxide plume in the subsurface carbon storage reservoir

EXPERT SYSTEMS WITH APPLICATIONS (2022)

Visualization of hydraulic fracture using physics-informed clustering to process ultrasonic shear waves

Aditya Chakravarty et al.

Summary: A novel workflow based on physics-informed unsupervised learning is developed to visualize geomechanical alterations due to hydraulic fracturing through processing transmitted ultrasonic-shear waveforms. The workflow assigns both statistically consistent and physically consistent clusters to shear waveforms, taking into account factors such as travel time and transmission coefficient. The generated maps of geomechanical alterations are in good agreement with independent techniques, and the workflow can be adapted for improved fracture characterization in the subsurface.

INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES (2021)

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Article Computer Science, Artificial Intelligence

Robust machine-learning workflow for subsurface geomechanical characterization and comparison against popular empirical correlations

Hao Li et al.

Summary: In this study, three shallow regression-type supervised-learning models were used to process conventional well logs and successfully synthesized subsurface geomechanical characteristics. The MARS model outperformed other models in a new well, showing its superiority in predicting compressional and shear travel times.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

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Article Geochemistry & Geophysics

Intelligent Image Segmentation for Organic-Rich Shales Using Random Forest, Wavelet Transform, and Hessian Matrix

Yaokun Wu et al.

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (2020)

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Article Energy & Fuels

Machine learning workflow to predict multi-target subsurface signals for the exploration of hydrocarbon and water

Oghenekaro Osogba et al.

FUEL (2020)

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Proceedings Paper Energy & Fuels

Three-million-metric-ton-monitored injection at the SECARB Cranfield project-project update

Susan D. Hovorka

GHGT-11 (2013)

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Unsupervised learning monitors the carbon-dioxide plume in the subsurface carbon storage reservoir

相关参考文献

Visualization of hydraulic fracture using physics-informed clustering to process ultrasonic shear waves

Robust machine-learning workflow for subsurface geomechanical characterization and comparison against popular empirical correlations

Intelligent Image Segmentation for Organic-Rich Shales Using Random Forest, Wavelet Transform, and Hessian Matrix

Machine learning workflow to predict multi-target subsurface signals for the exploration of hydrocarbon and water

Three-million-metric-ton-monitored injection at the SECARB Cranfield project-project update

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