Quantitative logging data clustering with hidden Markov model to assist log unit classification

Quantitative logging data clustering with hidden Markov model to assist log unit classification

Abstract Revealing subsurface structures is a fundamental task in geophysical and geological studies. Logging data are usually acquired through drilling projects, which constrain the subsurface structure, and together with the description of drill core samples, are used to distinguish geological uni...

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Bibliografische gegevens
Hoofdauteurs:	Suguru Yabe, Yohei Hamada, Rina Fukuchi, Shunichi Nomura, Norio Shigematsu, Tsutomu Kiguchi, Kenta Ueki
Formaat:	Artikel
Taal:	English
Gepubliceerd in:	SpringerOpen 2022-06-01
Reeks:	Earth, Planets and Space
Onderwerpen:	Hidden Markov model Logging data Clustering Unit classification
Online toegang:	https://doi.org/10.1186/s40623-022-01651-0

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