Estimation of in-situ maximum horizontal principal stress magnitudes from borehole breakout data using machine learning

This paper presents a technique for in-situ horizontal stress prediction in vertical boreholes based on borehole breakout data using a machine learning-based meta-modelling technique, i.e. Kriging. This model is generated based on the deterministic mean function and a stationary Gaussian process fun...

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Veröffentlicht in:	International journal of rock mechanics and mining sciences (Oxford, England : 1997) England : 1997), 2020-02, Vol.126, p.104199, Article 104199
Hauptverfasser:	Lin, H., Kang, W.-H., Oh, J., Canbulat, I.
Format:	Artikel
Sprache:	eng
Schlagworte:	Borehole breakout Borehole wall strength Boreholes Data points Gaussian process In-situ stress Kriging Learning algorithms Machine learning Reliability Stress Stress measurement
Online-Zugang:	Volltext
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