An adaptive wavenumber sampling strategy for 2.5D seismic-wave modeling in the frequency domain

Simulation of seismic waves from a 3D point-source in a 2D medium may be performed in the frequency-wavenumber domain (called 2.5D modelling). It involves computing the Fourier-transformed Green's function for a number of frequency (ω) and strike direction wavenumber (k_y) values and doubly inverse transforming to convert to the traveltime and distance space. Such modeling produces a wavefield with 3D features but the computation becomes pseudo 2D (i.e., in the xz-plane) rather than 3D (in the xyz-frame). The common sampling strategy for the wavenumber is inefficient for 2.5D wave modeling because it employs a large number of wavenumbers (k_y). This leads to a high cost of computer time in the linear-equation-solving processing, which detracts from the advantages of 2.5D modeling. In this paper, we use two analytic frequency-wavenumber-domain solutions for seismic waves in a homogeneous medium and an inhomogeneous media (two semi-infinite media in contact) to investigate the properties of the solutions and an efficient sampling strategy for choosing the wavenumbers. We have carried out analytic and numerical experiments with these solutions, and present adaptive Gauss-Legendre abscissae for the wavenumber sampling in terms of a modeling situation. We show that the effective range and the number of sampling points of the wavenumber define the adaptive sampling strategy, and they can be estimated in terms of the wavelength and the maximum source-receiver offset. We apply this sampling strategy to the finite-element method and demonstrate that the range and number of sampling points may be adapted for obtaining significant computational efficiency and satisfactory accuracy for every frequency component. Such 2.5D wave modeling can be readily applied for frequency-domain full-waveform inversion for seismic surface measurements and crosshole seismic waveform tomography.