Fusion of Hydraulic Tomography and Displacement Back Analysis for Underground Cavern Stability Investigation

Xu Gao, Tian Chyi Jim Yeh, E. Chuan Yan, Wen ke Wang, Jing Sen Cai, Yue Liang, Jian Ge, Yue ming Qi, Yong hong Hao

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


This paper first elucidates the importance of hydraulic heterogeneity of a rock mass on the design of an underground water-sealed storage cavern. It then introduces an information fusion approach that integrates hydraulic tomography, displacement back analysis, and a stochastic successive linear estimator to map spatially varying hydraulic conductivity (Ks), Young's modulus (E′), cohesion (c′), and internal friction angle (ϕ′). This algorithm yields statistically unbiased estimate of the Ks, E′, c′, and ϕ′ fields and their uncertainty due to insufficient samples of their heterogeneity. Afterward, this uncertainty is translated into the probability of failure distribution around the cavern for the risk assessment. Results show that heterogeneity of Ks plays an important role in the deformation and failure of the cavern. They also show that the proposed approach can reveal more detailed parameter distributions than kriging approach, based on a large number of samples of the parameters before excavations. Further, the predicted probability of failure distribution based on the proposed approach can effectively reflect the actual failure locations.

Original languageEnglish (US)
Pages (from-to)8632-8652
Number of pages21
JournalWater Resources Research
Issue number11
StatePublished - Nov 2018


  • Young's modulus
  • heterogeneity
  • hydraulic conductivity
  • shear strength
  • stochastic data fusion
  • underground water-sealed storage rock cavern

ASJC Scopus subject areas

  • Water Science and Technology


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