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