Geomechanical parameters assessment and geological characterization using fuzzy C means clustering of electrical resistivity and seismic data

Abstract

A broad understanding of the subsoil characteristics is required to deal with uncertainty in the infrastructure planning phase or even in the diagnosis of infrastructure damage. In this work, electrical resistivity and seismic methods have been employed for lithological characterization and geomechanical parameters assessment. The study area is characterized by high variability in geotechnical characteristics due to complex lithology. For lithological discrimination, we have used a soft clustering method to combine the independently electrical- and seismic-derived models. The outputs of this integration process are zonal models that help to decrease interpretation uncertainties. From single seismic profiles, both Vp and Vs information are extracted allowing geomechanical parameters to be estimated. All this information is critical for assessing the variance and inhomogeneity of the subsoil characteristics. The methodology shown in this work can be used in the infrastructure planning phase as well as to ascertain the causes of detected damage on built infrastructure.