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...
Главные авторы: | Suguru Yabe, Yohei Hamada, Rina Fukuchi, Shunichi Nomura, Norio Shigematsu, Tsutomu Kiguchi, Kenta Ueki |
---|---|
Формат: | Статья |
Язык: | English |
Опубликовано: |
SpringerOpen
2022-06-01
|
Серии: | Earth, Planets and Space |
Предметы: | |
Online-ссылка: | https://doi.org/10.1186/s40623-022-01651-0 |
Схожие документы
-
A new method for the empirical conversion of logging data to clay mineral fraction in the Nankai accretionary prism
по: Suguru Yabe, и др.
Опубликовано: (2020-10-01) -
Simultaneous estimation of in situ porosity and thermal structure from core sample measurements and resistivity log data at Nankai accretionary prism
по: Suguru Yabe, и др.
Опубликовано: (2019-11-01) -
Feature Selection for Hidden Markov Models and Hidden Semi-Markov Models
по: Stephen Adams, и др.
Опубликовано: (2016-01-01) -
Visual tracking using interactive factorial hidden Markov models
по: Jin Wook Paeng, и др.
Опубликовано: (2021-08-01) -
UTILIZING DISCRETE HIDDEN MARKOV MODELS TO ANALYZE TETRAPLOID PLANT BREEDING
по: Nahrul Hayati, и др.
Опубликовано: (2024-10-01)