Coupled characterization of stratigraphic and geo-properties uncertainties A conditional random field approach

Site characterization, which aims to characterize the subsurface stratigraphic configuration and the associated geo-properties, has long been a significant challenge in geological and geotechnical practice. Due to the complexity and inherent spatial variability of the geological bodies and the limited availability of borehole data, uncertainty is unavoidable in the characterized subsurface stratigraphic configuration and the associated geoproperties. In previous studies, the stratigraphic uncertainty and the geo-properties uncertainty were characterized separately. This paper proposes a conditional random field approach for a coupled characterization of stratigraphic and geo-properties uncertainties. The spatial correlation of the stratum existence between different subsurface elements and the spatial correlation of geo-properties are characterized by two autocorrelation functions, determined with the maximum likelihood principle. With the knowledge of the spatial correlation of the stratum existence, the stratigraphic configuration can be sampled using a modified random field approach. Then, the spatial correlation of the geo-properties is updated based on the sampled stratigraphic configuration. With the updated spatial correlation of the geo-properties, the spatial distribution of the geo-properties can readily be simulated with the conditional random field theory. The effectiveness of the proposed approach is demonstrated through a case study of probabilistic site characterization of an offshore wind farm site in Taiwan. To extend the applicability of the proposed approach, a probabilistic evaluation of liquefaction potential at this site under a given seismic shaking level is performed.

Automated summary

Characterizing site uncertainties, especially in subsurface stratigraphy and geo-properties, is a significant challenge in geological and geotechnical practice due to complexity and spatial variability. This paper proposes a conditional random field approach to couple stratigraphic and geo-property uncertainties, determining spatial correlations with two autocorrelation functions. The effectiveness of the approach is demonstrated through a case study on an offshore wind farm site in Taiwan, showcasing the method's potential for probabilistic site characterization.