2021 年 62 巻 12 号 p. 1695-1702
One significant issue associated with in situ stress measurements is that the uncertainty of the results cannot be determined. In this study, we propose a novel analytical procedure for the anelastic strain recovery (ASR) method, an in situ stress measurement method, enabling us to conduct uncertainty quantification based on Bayesian statistical modeling (BSM). The new procedure consists of the following steps: i) measuring the ASR of a rock core with strain gauges, ii) applying a probability model based on BSM to the measured ASR data and simulating the probability densities of the elements of an in situ stress tensor and other parameters; and iii) regarding the probability densities as the results of in situ stress measurements with uncertainty. This paper presents the results obtained by applying the proposed procedure to simulated ASR data. The results show that the uncertainties of some parameters are reduced by giving the elastic moduli. Notably, the rates of uncertainty decrease vary for each parameter. To reveal the cause of these differences, we introduce the new evaluation tool, Sobol’ indices, which comprise a global sensitivity analytic tool, to facilitate a quantitative discussion.
This Paper was Originally Published in Japanese in J. Soc. Mater. Sci., Jpn. 70 (2021) 573–580.
