The book has three parts. In Part I (Methodology
of EM data interpretation) two alternative approaches to EM data
inversion are considered: the Bayesian statistical inversion and
neural networkebased algorithms. The former one provides
flexible tools for taking into account prior information and expert
estimates during EM data inversion and quantifying its results in
terms of posterior parameters’ uncertainties. The latter one is
especially useful in the case of constructing 3-D models (in
particular, in terms of macroparameters) from sparse, irregularly
distributed or a single-profile electromagnetic data. Finally, a
review of the methods used for joint analysis and inversion of EM
and other geophysical data is presented.
In Part II (Models of geological medium) the approaches
considered in the Part I are applied to study methodological issues
of EM modeling volcanoes (by examples of Vesuvio, Kilauea,
Elbrus, Komagatake, Hengill), geothermal and hydrocarbon reservoirs. Conceptual models of the Icelandic type crust, a lens in the upper crust and copper-porphyry ore formation are suggested
based on joint analysis of EM and other geophysical data.
In Part III (Forecasting petrophysical properties of rocks) the
techniques for estimating temperature, seismic velocities, and
porosity from the electrical resistivity as proxy parameter are
considered. This part is supplemented by Appendix, which
includes useful empirical relations between electrical resistivity,
seismic velocities and porosity.