Probabilistic estimation of cross-variogram based on Bayesian inference

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

8 Scopus Citations
View graph of relations

Author(s)

  • Lulu Zhang
  • Changhong Wang
  • Jianguo Zheng
  • Yongtang Yu

Detail(s)

Original languageEnglish
Article number105813
Journal / PublicationEngineering Geology
Volume277
Online published18 Aug 2020
Publication statusPublished - Nov 2020

Abstract

Site characterization based on measurements is essential for geological and geotechnical engineering. However, measurements are usually limited and sparse because of many limitations, which can hardly be utilized to perform a well site characterization. Therefore, some data fusion methods are commonly utilized to integrate correlated data to improve the performance of site characterization. Among data fusion methods, cokriging is widely utilized to improve the performance of site characterization by integrating measurements of correlated variables. The correlation between correlated variables is expressed by a cross-variogram, which can only be calculated using co-located measurements between correlated variables. However, the measurements in geological and geotechnical engineering are commonly obtained by destructive sampling, which are usually not co-located and cannot be utilized to calculate the cross-variogram. In this study, a Bayesian inference method is developed to tackle this difficulty. The proposed method is illustrated and validated by two real datasets. The results show that the proposed method can estimate a well cross-variogram model, no matter whether the measurements of correlated variables are co-located or not. Moreover, the uncertainty of variogram models and cokriging estimation can be quantified by the proposed method. The proposed method can improve the wide utilization of the cokriging method, which can help characterize geology conditions of geological and geotechnical engineering.

Research Area(s)

  • Bayesian inference, Cokriging, Cross-variogram, Markov chain Monte Carlo simulation, Uncertainty

Citation Format(s)

Probabilistic estimation of cross-variogram based on Bayesian inference. / Xu, Jiabao; Zhang, Lulu; Wang, Yu; Wang, Changhong; Zheng, Jianguo; Yu, Yongtang.

In: Engineering Geology, Vol. 277, 105813, 11.2020.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review