A joint inversion algorithm to process geoelectric and sutface wave seismic data. Part I: basic ideas¹

Abstract

For the exploration of near-surface structures, seismic and geoelectric methods are often applied. Usually, these two types of method give, independently of each other, a sufficiently exact model of the geological structure. However, sometimes the inversion of the seismic or geoelectric data fails.These failures can be avoided by combining various methods in one joint inversion which feads to much better parameter estimations of the model than the independent inversions.A suitable seismic method for exploring near-surface structures is the use of dispersive surface waves : the dispersive characteristics of Rayleigh and Love surface waves depend strongly on the structural and petrophysical (seismic velocities) features of the near-surface Underground.Geoelectric exploration of the structure Underground may be carried out with the well-known methods of D C resistivity sounding, such as the Schlumberger, the radial-dipole and the two-electrode arrays.The joint inversion algorithm is tested by means of synthetic data. It is demonstrated that the geoelectric joint inversion of Schlumberger, radial-dipole and twoelectrode sounding data yields more reliable results than the single inversion of a single set of these data. The same holds for the seismic joint inversion of Love and Rayleigh group slowness data. The best inversion result is achieved by performing a joint inversion of both geoelectric and surface-wave data.The effect of noise on the accuracy of the solution for both Gaussian and nonGaussian (sparsely distributed large) errors is analysed. After a comparison between least-square (LSQ) and least absolute deviation (LAD) inversion results, the LAD joint inversion is found to be an accurate and robust method.

Detection of sub-basaltic sediments by a multi-parametric joint inversion approach

“…Manglik and Verma (1999) included DC resistivity inversion to their joint MT -seismic inversion algorithm. Hering et al (1995) reported an example of combining DC electrical data with surface wave data. Recently, Gallardo and Meju (2007) presented an algorithm for the joint inversion of MT and seismic refraction data for two dimensional structures.…”

Parameter sensitivity maps of surface geoelectric arrays I. Linear arrays

“…Among the first geoelectric studies in this field were published by Gyulai (1989) and by Noel and Xu (1991). Noel and Xu (1991) carried out two-dimensional parameter sensitivity studies for geoelectric tomography; Hering et al (1995) carried out 1D parameter sensitivity studies with the Schlumberger, radial (axial) dipole and two-electrode arrays, in order to reveal their potential in various (geoelectric and seismic-geoelectric) joint inversions; Gyulai (1995) discussed parameter sensitivity of two-electrode, three-electrode, Wenner-, Sclumberger-and radial-dipole arrays in case of inclined layered models; Gyulai (1998) calculated parameter sensitivities in case of several arrays in investigation of subsurface holes. As a practical example of parameter sensitivity studies, Nyári and Kanli (2007) studied effect of small 3D inhomogeneities on 2D interpretation carried out with various arrays.…”

Joint inversion for mapping subsurface hydrological parameters

“…Sena and Toksöz (1990) used high-frequency EM data to derive subsurface electrical conductivity and permittivity, and Zhang and Oldenburg (1999) used EM data to map magnetic susceptibility and electrical conductivity simultaneously. Hering et al (1995) showed that improved results may be obtained through joint inversion if multitudes of data are available. For the resistivity problem Schlumberger, radial-dipole and two-electrode sounding data were jointly used to improve resistivity imaging, and for the seismic problem Love and Rayleigh group slowness data were used to obtain improved near-surface velocity structures.…”