Geo-electrical Imaging Based In-Situ and Site-Specific Transforms for Geotechnical Characterization of a Civil Construction Site

Major civil engineering structures require a good quality geotechnical soil testing to assess the bearing capacity for planning foundation structures. While geotechnical tests provide geo-mechanical information on a very refined depth scales, their advantage is offset by their inherent point-wise information attended by drilling, which is costly. Further, in a complex geological setting, the problems get compounded due to excessive drilling budget to fulfill the geotechnical site investigation needs. So, to meet this need, civil engineers include a very high factor of safety in their 1-D model parameters. While geophysical imaging being non-invasive and cost-effective with proven spatial resolutions of different scales in subsurface exploration, yet their results can’t be directly translated to geotechnical knowledge due to absence of site-specific suitable transforms. So, a leveraged approach is needed to yield better quality subsurface information at a much lesser cost. It concerns prediction of different formation and geotechnical parameter images of subsurface on the basis of few geotechnical investigations and ample number of geo-electric image results. Here, 2-D resistivity and IP image profile data along with projected geotechnical data (Standard Penetration Test, SPT / Dynamic Cone Penetration Test, DCPT / Static Cone Penetration Test, SCPT) from nearby boreholes have been used in a case study for predicting different 2-D formation and geotechnical parameter sections along the same profile. This prediction method is based on site-specific validated regression equations describing actual correlations of geo-electrical and geotechnical data and site-independent well established empirical relations of SPT ‘N’ with different formation and geotechnical parameters. Even though the eported rresults are SPT based, the outlined methodology is quite general enough to deal with any other relevant geotechnical data sets for a comprehensive geotechnical assessment of a site.