Prestack waveform inversion of four-component, two-azimuth surface seismic data for orthorhombic elastic media parameters using a nondominated sorting genetic algorithm

摘要

Consideration of azimuthal anisotropy, at least to an orthorhombic symmetry is important in exploring the naturally fractured and unconventional hydrocarbon reservoirs. Inverting surface seismic data for subsurface orthorhombic properties is however a challenge. Such an inversion- needs multicomponent seismic data requiring inversion algorithms capable of simultaneously optimizing multiple objectives, one for each data component. In addition, an accurate extraction of subsurface azimuthal anisotropy requires multicomponent seismic data acquired at a fine spatial resolution along many source-to-receiver azimuthal orientations. Because routine acquisition of such-data is prohibitively expensive, they are typically available for two or at most three azimuthal orientations at a spatial resolution where such an inversion could be applied. In this work, we apply a multiobjective optimization method using a nondominated sorting genetic algorithm to extract the anisotropic elastic properties and density from multicomponent surface seismic data sorted along two different source-to-receiver azimuthal orientations that extracted the rotated elastic properties along these directions. We then use the extracted models along two azimuths and the azimuthal angle difference between them to construct the orthorhombic elastic properties of the subsurface. Applying our methodology on a multilayered model with different anisotropic symmetries, we demonstrate that our method is capable of extracting most of the elastic parameters and density to a reasonable accuracy. We conclude that inverting surface seismic data along two azimuths and then combining them into an orthorhombic subsurface model is a practical way to characterize the subsurface for azimuthal anisotropy