Laterally and Mutually Constrained Inversion of Surface Wave Seismic Data and Resistivity Data

Abstract

The laterally and mutually constrained inversion (LCI and MCI) techniques allow for the combined inversion of multiple geophysical datasets and provide a sensitivity analysis of all model parameters. The LCI and MCI work with few-layered models, and are restricted to quasi-layered geological environments. LCI is used successfully for inversion of surface wave (SW) seismic data and MCI for combined inversion of SW data and continuous vertical electrical sounding (CVES) data. The primary model parameters are resistivity or shear wave velocity and thickness, and depth to layer interfaces is included as a secondary model parameter. The advantages and limitations of LCI and MCI are evaluated on synthetic SW data. The main conclusions are: Depth to a high velocity halfspace is generally well-resolved even if thicknesses of overlaying layers and the velocity of the halfspace are unresolved; Applying lateral constraints (LCI) between individual SW soundings improves model resolution, particularly for velocities and depths, and; Adding mutual constraints (MCI) to resistivity data improves model resolution of all parameters in the shear wave velocity model. When applied to field data, model resolution improves significantly when LCI or MCI is used, and resistivity and velocity models correlate structurally with better correlation to lithological interfaces identified in drill logs.