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Multiple Regression Analysis of Geoelectric Imaging and Geotechnical Site Investigation Test Results


Affiliations
1 Department of Earth Sciences, IIT Roorkee, Roorkee 247 667, India
2 Department of Civil Engineering, IIT Roorkee, Roorkee 247 667, India
 

Geotechnical site characterization through non-invasive and cost-effective electrical resistivity imaging (ERI) and induced polarization imaging (IPI) offers promise compared to conventional point-geotechnical site investigations (standard penetration test, SPT), for which a basic understanding of factors (grain size (sand, fines) and water content) influencing them is needed. Here we perform a multiple regression analysis of ERI, IPI and SPT results in a site investigation at Lucknow, India. The results show that grain size and water content influence both chargeability and SPT values in a similar manner, while resistivity values are affected differently with a low RMS prediction error for chargeability.

Keywords

Geoelectronic Imaging, Geotechnical Site Characterization, Multi-Regression Analysis, Grain Size, Water Content.
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  • Bowles, J. S., Foundation Analysis and Design, McGraw Hill International, Singapore, 2001, 5th edn, p. 171.

  • Murthy, V. N. S., Soil Mechanics and Foundation Engineering, CBS Publisher and Distributors, 2008, p. 1043.

  • Gautam, P. K., Sastry, R. G. and Mondal, S. K., The utility of multi-electrode resistivity data in geotechnical investigations – a case study. In 20th Symposium on the Application of Geophysics to Engineering and Environmental Problems, 2007, pp. 731–737.

  • Cocker, J. O., Integration of geophysical and geotechnical methods to site characterization for construction work at the school of management area, Lagos State Polytechnic, Ikorodu, Lagos, Nigeria. Int. J. Energy Sci. Eng., 2015, 1(2), 40–48.

  • Terzaghi, K. and Peck, R. B., Soil Mechanics in Engineering Practice, John Wiley, New York, 3rd edn, 1996, p. 549.

  • Schon, J. H., Physical properties of rocks: fundamentals and principles of petrophysics. In Handbook of Geophysical Exploration, Elsevier, New York, 1996, vol. 18, p. 583.

  • Rucker, D. F. and Noonan, G. E., Using marine resistivity to map geotechnical properties: a case study in support of dredging the Panama Canal. Near Surf. Geophys., 2013, 11(6), 625–637.

  • Sudha, K., Israil, M., Mittal, S. and Rai, J., Soil characterization using electrical resistivity tomography and geotechnical investigations. J. Appl. Geophys., 2009, 67, 74–79.

  • Abidin, M. H. Z., Saad, R., Ahmad, F., Wijeyesekera, D. C. and Baharuddin, M. F. T., Correlation analysis between field electrical resistivity value (ERV) and basic geotechnical properties (BGP). Soil Mech. Found. Eng., 2014, 51(3), 117–125.

  • Siddiqui, F. I. and Osman, S. B., Integrating geo-electrical and geotechnical data for soil characterization. Int. J. Appl. Phys. Math., 2012, 2(2), 104–106.

  • Siddiqui, F. I. and Osman, S. B., Simple and multiple regression models for relationship between electrical resistivity and various soil properties for soil characterization. Environ. Earth Sci., 2013, 70, 259–267.

  • Ranjan, G., and Rao, A. S. R., Basic and Applied Soil Mechanics, New Age International Publishers, 2000, p. 762.

  • Loke, M. H. and Barker, R. D., Least-squares deconvolution of apparent resistivity pseudosections. Geophysics, 1995, 60, 1682–1690.

  • Rai, S. K., Singh, S. K. and Krishnaswami, S., Chemical weathering in the plain and peninsular sub-basins of the Ganga: impact on major ion chemistry and elemental fluxes. Geochim. Cosmochim. Acta, 2010, 74, 2340–2355.

  • Singh, S., Parkash, B., Rao, M. S., Arora, M. and Bhosle, B., Geomorphology, pedology and sedimentology of the Deoha/ Ganga–Ghaghara interfluves, Upper Ganetic Plains (Himalayan Foerland Basin) – extensional tectonic implications. Catena, 2006, 67, 183–203.

  • Srivastava, P., Pal, D. K., Aruche, K. M., Wani, S. P. and Sahrawat, K. L., Soils of the Indo-Gangetic Plains: a pedogenic response to landscape stability, climatic variability and anthropogenic activity during Holocene. Earth Sci. Rev., 2015, 140, 54–71.

  • Parkash, B., Kumar, S., Rao, M. S., Giri, S. C., Kumar, C. S., Gupta, S. and Srivastava, P., Holocence tectonic movements and stress field. Curr. Sci., 2000, 79(4), 438–449.

  • Pazdirek, O. and Blaha, V., Examples of resistivity imaging using ME-100 resistivity field acquisition system. In EAGE 58th Conference and Technical Exhibition Extended abstr., Amsterdam, 1996.

  • Loke, M. H., Electrical imaging surveys for environmental and engineering studies – a practical guide to 2D and 3D surveys. A Report, 2000, p. 60.

  • Press, W. H., Teukolsky, S. A., Vetterling, W. T. and Flannery, B. P., Numerical Recipes – The Art of Scientific Computing, Cambridge University Press, New Delhi, 2007, 3rd edn, p. 1195.

  • Gujrati, D. N., Porter, D. C. and Gunasekar, S., Basic Econometrics, McGraw Hill Education (India), New Delhi, 2012, 5th edn, p. 886.


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  • Multiple Regression Analysis of Geoelectric Imaging and Geotechnical Site Investigation Test Results

Abstract Views: 214  |  PDF Views: 78

Authors

Rambhatla G. Sastry
Department of Earth Sciences, IIT Roorkee, Roorkee 247 667, India
Sumedha Chahar
Department of Earth Sciences, IIT Roorkee, Roorkee 247 667, India
Mahendra Singh
Department of Civil Engineering, IIT Roorkee, Roorkee 247 667, India

Abstract


Geotechnical site characterization through non-invasive and cost-effective electrical resistivity imaging (ERI) and induced polarization imaging (IPI) offers promise compared to conventional point-geotechnical site investigations (standard penetration test, SPT), for which a basic understanding of factors (grain size (sand, fines) and water content) influencing them is needed. Here we perform a multiple regression analysis of ERI, IPI and SPT results in a site investigation at Lucknow, India. The results show that grain size and water content influence both chargeability and SPT values in a similar manner, while resistivity values are affected differently with a low RMS prediction error for chargeability.

Keywords


Geoelectronic Imaging, Geotechnical Site Characterization, Multi-Regression Analysis, Grain Size, Water Content.

References





DOI: https://doi.org/10.18520/cs%2Fv114%2Fi09%2F1946-1952