Prior geological knowledge enhanced Markov random field for development of geological cross-sections from sparse data
Qualified subsurface geological cross-sections are indispensable for efficient site planning and risk management of underground infrastructure. Nevertheless, delineating a qualified geological cross-section from sparse site-specific data is challenging, especially when dealing with heterogeneous str...
Saved in:
Main Authors: | Qian, Zehang, Shi, Chao |
---|---|
Other Authors: | School of Civil and Environmental Engineering |
Format: | Article |
Language: | English |
Published: |
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/180899 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Stochastic simulation of geological cross-sections from boreholes: a random field approach with Markov Chain Monte Carlo method
by: Yang, Haoqing, et al.
Published: (2024) -
Modeling spatially-dependent extreme events with Markov random field priors
by: Yu, Hang, et al.
Published: (2013) -
GEOTAGE: GEOLOGICAL SHAREWARE APPLICATION FOR GEOLOGY
OBJECT
by: Tara Shinta Dewi, at. al
Published: (2015) -
Practical configured microtremor array measurements (MAMs) for the geological investigation of underground space
by: Ku, T., et al.
Published: (2021) -
Environmental Geology
by: Klaus Knödel, Gerhard Lange, Hans-Jürgen Voigt
Published: (2017)