Topological Characteristics of Digital Models of Geological Core - Machine Learning and Knowledge Extraction
Conference Papers Year : 2018

Topological Characteristics of Digital Models of Geological Core

Rustem R. Gilmanov
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Andrey A. Yakovlev
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Abstract

We discuss the possibility of applying stochastic approaches to core modeling by using tools of topology. The study demonstrates the prospects of applying topological characteristics for the description of the core and the search for its analogs. Moreover application of topological characteristics (for example, in conjunction with machine learning methods) in the long term will make it possible to obtain petrophysical properties of the core samples without carrying out expensive and long-term filtration experiments.
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hal-02060056 , version 1 (07-03-2019)

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Rustem R. Gilmanov, Alexander V. Kalyuzhnyuk, Iskander A. Taimanov, Andrey A. Yakovlev. Topological Characteristics of Digital Models of Geological Core. 2nd International Cross-Domain Conference for Machine Learning and Knowledge Extraction (CD-MAKE), Aug 2018, Hamburg, Germany. pp.273-281, ⟨10.1007/978-3-319-99740-7_19⟩. ⟨hal-02060056⟩
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