Fully coupled conditional simulation of geological and geotechnical variabilities for sparse geotechnical data in three dimensions
Journal
Engineering Geology
Journal Volume
364
Start Page
108609
ISSN
00137952
Date Issued
2026-03-26
Author(s)
Abstract
This study proposes a fully coupled conditional simulation framework for jointly characterizing geological uncertainty and geotechnical variability under sparse site investigation data. In conventional practice, soil-category simulation (Task 1, T1) and soil-property simulation (Task 2, T2) are treated in a decoupled manner, conditioning on observed categorical data (L) and continuous soil property data (X) separately. The proposed framework departs from this paradigm by adopting a fully coupled strategy in which both L and X are simulated by conditioning jointly on {L, X}, thereby explicitly accounting for their statistical dependence. Implementing such a framework requires knowledge of site-specific X-L and X-X correlations, which are often weakly identifiable from sparse target-site data. To address this challenge, a modified hierarchical Bayesian model (HBM) is developed to learn these correlation characteristics from a newly compiled global soil database and transfer them to the target site as an informative prior. The framework is further equipped with an efficient conditional simulation algorithm for X, enabling practical three-dimensional applications. The performance and advantages of the proposed framework are demonstrated through a real case study and comparative analyses with existing methods.
Subjects
Conditional simulation
Geological uncertainty
Geotechnical site characterization
Geotechnical variability
Hierarchical Bayesian model
Markov random field
Publisher
Elsevier B.V.
Type
journal article