TY - JOUR
T1 - Lithology dicrimination from physical rock properties
AU - Bosch, Miguel
AU - Zamora, Maaria
AU - Utama, Widya
N1 - Funding Information:
The authors want to specially acknowledge J. l? Pozzi (Ecole Normale SuperiCure de Paris) for providing the measurements of the magnetic susceptibility for our data sets. C. Jaupart (Institut de Physique du Globe de Paris) and G. Bienfait (Institut de Physique du Globe de Paris) provided part of the rock samples. Discriminant analysis and clustering analysis were performed using the licensed software package SPSS. This research was partially funded by the TEKVOLC program (European Union), the GeoFrance-3D program (France), the CDCH of the Universidad Central de Venezuela, and the ITS of Surabaya-Indonesia. The authors acknowledge Andreas Ganps, an anonymous referee, and Associate Editor Keith Hirsche for their constructive reviews.
PY - 2002
Y1 - 2002
N2 - The estimation of lithology from multiple geophysical survey methods needs to be addressed to develop advanced tomographic methods. An initial requirement for lithology discrimination is that lithology should be discriminable from the media properties physically related to the geophysical observations. To test this condition for different combinations of the most common crustal rocks, we performed several lithology discrimination exercises on rock samples under laboratory conditions. The physical properties included mass density, compressional velocity, shear velocity, electric conductivity, thermal conductivity, and magnetic susceptibility. A categorical description of the sample lithology was followed; hence, the inference consisted of predicting the sample rock category (lithotype) membership. The joint information provided by the physical properties of the rocks allowed us to discriminate the sample lithotype correctly, with an overall success rate of 100% in the most favorable situation and over 85% in the least favorable situation. We obtained successful classification results for a variety of common lithotypes (granite, gabbro, limestone, tuff, marble, basalt, and gneiss) using three common classification methods: clustering analysis, Gaussian classification, and discriminant analysis. Although discrimination was positive with each of these multivariate classification techniques, discriminant analysis showed some advantages for the classification and graphic analysis of the data. These results support our postulate that lithology can be estimated reliably if multiple geophysical observations are considered jointly.
AB - The estimation of lithology from multiple geophysical survey methods needs to be addressed to develop advanced tomographic methods. An initial requirement for lithology discrimination is that lithology should be discriminable from the media properties physically related to the geophysical observations. To test this condition for different combinations of the most common crustal rocks, we performed several lithology discrimination exercises on rock samples under laboratory conditions. The physical properties included mass density, compressional velocity, shear velocity, electric conductivity, thermal conductivity, and magnetic susceptibility. A categorical description of the sample lithology was followed; hence, the inference consisted of predicting the sample rock category (lithotype) membership. The joint information provided by the physical properties of the rocks allowed us to discriminate the sample lithotype correctly, with an overall success rate of 100% in the most favorable situation and over 85% in the least favorable situation. We obtained successful classification results for a variety of common lithotypes (granite, gabbro, limestone, tuff, marble, basalt, and gneiss) using three common classification methods: clustering analysis, Gaussian classification, and discriminant analysis. Although discrimination was positive with each of these multivariate classification techniques, discriminant analysis showed some advantages for the classification and graphic analysis of the data. These results support our postulate that lithology can be estimated reliably if multiple geophysical observations are considered jointly.
UR - https://www.scopus.com/pages/publications/0036494428
U2 - 10.1190/1.1468618
DO - 10.1190/1.1468618
M3 - Article
AN - SCOPUS:0036494428
SN - 0016-8033
VL - 67
SP - 573
EP - 581
JO - Geophysics
JF - Geophysics
IS - 2
ER -