Near-surface and anisotropy modeling for efficient land seismic depth imaging in low-relief geology

Abstract

Prestack depth migration of land data presents unique characteristics and challenges that distinguish it from the workflows applied for marine data. Such unique characteristics are primarily related to the near surface. In areas of low-relief geology, near-surface velocity variations can obscure the reservoir structure. The remaining deeper earth model section has good lateral continuity and can be described effectively by smooth velocity fields. Strategies for estimating the near-surface effects and incorporating them into a processing workflow are of primary importance for the successful depth imaging of land seismic data. The second important aspect of a depth imaging workflow is that the seismic image must honor the well markers or formation tops. The subhorizontal fine-scale layering of low-relief structures can cause anisotropy that needs to be taken into account to achieve accurate well ties and good image quality. We have evaluated the application of an efficient workflow to achieve fast and reliable depth imaging in layered geology; this involves the decomposition of the near-surface velocity into short-, medium-, and long-wavelength terms followed by reflection velocity analysis and anisotropic parameter scanning. The long-wavelength components are solved by dynamic velocity analysis, whereas the medium- and short-wavelength terms are evaluated by surface-consistent analysis applied to refracted and reflected data. Interaction with seismic interpreters and geology-consistent updates mitigates the possibility of introducing errors in areas not covered by wells. The workflow is applied to a structure-controlled wadi in central Saudi Arabia showing complex near-surface conditions and imaging problems. The study incorporates high-resolution helicopter-borne transient electromagnetic data that are used to constrain seismic traveltime inversion through cross-gradient structural regularization (joint inversion). Fast and robust depth imaging constrained by well data is obtained through accurate estimation of near-surface velocities, anisotropy, and geology-consistent analysis.