Topological characteristics of digital models of geological core

Rustem R. Gilmanov, Alexander V. Kalyuzhnyuk, Iskander A. Taimanov, Andrey A. Yakovlev

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationMachine Learning and Knowledge Extraction - Second IFIP TC 5, TC 8/WG 8.4, 8.9, TC 12/WG 12.9 International Cross-Domain Conference, CD-MAKE 2018, Proceedings
EditorsPeter Kieseberg, Edgar Weippl, Andreas Holzinger, A Min Tjoa
PublisherSpringer Verlag
Pages273-281
Number of pages9
ISBN (Print)9783319997391
DOIs
Publication statusPublished - 1 Jan 2018
Externally publishedYes
Event2nd International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2018 - Hamburg, Germany
Duration: 27 Aug 201830 Aug 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11015 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2018
CountryGermany
CityHamburg
Period27.8.1830.8.18

Keywords

  • Betti numbers
  • Digital core
  • Geological modeling
  • Topological characteristics

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Gilmanov, R. R., Kalyuzhnyuk, A. V., Taimanov, I. A., & Yakovlev, A. A. (2018). Topological characteristics of digital models of geological core. In P. Kieseberg, E. Weippl, A. Holzinger, & A. M. Tjoa (Eds.), Machine Learning and Knowledge Extraction - Second IFIP TC 5, TC 8/WG 8.4, 8.9, TC 12/WG 12.9 International Cross-Domain Conference, CD-MAKE 2018, Proceedings (pp. 273-281). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11015 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-99740-7_19