Lithology discrimination from physical rock properties

Abstract

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.

MT+, Integrating Magnetotellurics to Determine Earth Structure, Physical State, and Processes

“…Thus, even with perfect data and a unique inverse solution (neither of which generally exist), lithology cannot be uniquely determined from a single geophysical technique. It is for this reason that geophysical methods are applied in combination, with the determination of multiple physical properties being used to break the degeneracy (Bosch 1999;Bosch et al 2002). Granite and limestone, for example, have similar electrical conductivities, but differing magnetic susceptibility.…”

The influence of lithology and depth on acoustic velocities in South-east

“…Vertical profiling can be used to identify lithologic boundaries, faults, bedrock topography; including structural highs and buried channels, it can also be used to predict overpressure zones and reservoirs. Velocity variations are known to correlate well with the lithological character of the formation materials, thus, providing important structural and lithological information as well as information on dynamic soils and rocks properties for earthquake designed analysis of structures (Bosch et al, 2002;Polymenakos et al, 2005).…”

Lithological discrimination based on statistical analysis of multi-sensor drill core logging data in the Matagami VMS district, Quebec, Canada

“…Multivariate statistical approaches provide robust and quantitative algorithms for data classification and statistical modeling. The approach used here is cluster analysis, which permits the interpretation and the recognition of patterns and groups inside large datasets (e.g., Delfiner et al, 1987;Harris et al, 1999;Maerz and Zhou, 1999;Bosch et al, 2002).…”

“…Multivariate statistics have been shown in sedimentology and hydrocarbon exploration to objectively classify the data into lithological units or lithofacies (e.g., Rice et al, 1976;Delfiner et al, 1987;Bosch et al, 2002;Reátegui et al, 2005;Kaźmierczuk and Jarzyna, 2006;Tang and White, 2008;Rowe et al, 2012). Since the early 1960s, several multivariate statistical techniques have been developed for automatic segmentation of log data (e.g., Testerman, 1962;Gill, 1970;Hawkins, 1972;Hawkins and Ten Krooden, 1979).…”

“…Since the early 1960s, several multivariate statistical techniques have been developed for automatic segmentation of log data (e.g., Testerman, 1962;Gill, 1970;Hawkins, 1972;Hawkins and Ten Krooden, 1979). The main hypothesis is that measurements of specific physico-chemical properties on cores allows for the fullcharacterization of the lithology while automating, at least in part, its characterization (Kileen et al, 1997;Maerz and Zhou, 1999;Bosch et al, 2002;Hill et al, 2015).…”