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...
Main Authors: | Suguru Yabe, Yohei Hamada, Rina Fukuchi, Shunichi Nomura, Norio Shigematsu, Tsutomu Kiguchi, Kenta Ueki |
---|---|
Format: | Article |
Jezik: | English |
Izdano: |
SpringerOpen
2022-06-01
|
Serija: | Earth, Planets and Space |
Teme: | |
Online dostop: | https://doi.org/10.1186/s40623-022-01651-0 |
Podobne knjige/članki
-
A new method for the empirical conversion of logging data to clay mineral fraction in the Nankai accretionary prism
od: Suguru Yabe, et al.
Izdano: (2020-10-01) -
Simultaneous estimation of in situ porosity and thermal structure from core sample measurements and resistivity log data at Nankai accretionary prism
od: Suguru Yabe, et al.
Izdano: (2019-11-01) -
Feature Selection for Hidden Markov Models and Hidden Semi-Markov Models
od: Stephen Adams, et al.
Izdano: (2016-01-01) -
Visual tracking using interactive factorial hidden Markov models
od: Jin Wook Paeng, et al.
Izdano: (2021-08-01) -
UTILIZING DISCRETE HIDDEN MARKOV MODELS TO ANALYZE TETRAPLOID PLANT BREEDING
od: Nahrul Hayati, et al.
Izdano: (2024-10-01)