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...
मुख्य लेखकों: | Suguru Yabe, Yohei Hamada, Rina Fukuchi, Shunichi Nomura, Norio Shigematsu, Tsutomu Kiguchi, Kenta Ueki |
---|---|
स्वरूप: | लेख |
भाषा: | English |
प्रकाशित: |
SpringerOpen
2022-06-01
|
श्रृंखला: | Earth, Planets and Space |
विषय: | |
ऑनलाइन पहुंच: | https://doi.org/10.1186/s40623-022-01651-0 |
समान संसाधन
-
A new method for the empirical conversion of logging data to clay mineral fraction in the Nankai accretionary prism
द्वारा: Suguru Yabe, और अन्य
प्रकाशित: (2020-10-01) -
Simultaneous estimation of in situ porosity and thermal structure from core sample measurements and resistivity log data at Nankai accretionary prism
द्वारा: Suguru Yabe, और अन्य
प्रकाशित: (2019-11-01) -
Feature Selection for Hidden Markov Models and Hidden Semi-Markov Models
द्वारा: Stephen Adams, और अन्य
प्रकाशित: (2016-01-01) -
Visual tracking using interactive factorial hidden Markov models
द्वारा: Jin Wook Paeng, और अन्य
प्रकाशित: (2021-08-01) -
UTILIZING DISCRETE HIDDEN MARKOV MODELS TO ANALYZE TETRAPLOID PLANT BREEDING
द्वारा: Nahrul Hayati, और अन्य
प्रकाशित: (2024-10-01)