Breakthrough acquisition and technologies for subsalt imaging

Abstract

The recently introduced method of wide-azimuth data acquisition offers better illumination, noise attenuation, and lower frequencies to more accurately determine a velocity field for imaging. For the field data experiment to demonstrate the technologies, we used a Gulf of Mexico (GOM) wide-azimuth data set that allows us to take advantage of possible low frequencies, relatively large crossline offsets, and increased illumination. The input data was processed through true 3D azimuthal surface-related multiple elimination (SRME) with zero-phasing and debubble. Eliminating the surface-related multiples aids the velocity determination and helps uncover the subsalt sediments at the final imaging stage. After the initial velocity derivation, which was constrained to wells and geology, full-waveform inversion (FWI) was used to further update the velocity field to achieve an enhanced image. The methodology used follows the top-down approach where suprasalt sediment model is developed followed by the top of salt, salt flanks, base of salt, and finished with a limited subsalt update. To approximate the observed data by using an acoustic inversion procedure, the propagator includes effects of attenuation, anisotropy, acquisition source, and receiver depth. The geological environment is salt related, which implies that the observed data is highly elastic, even though it is input to an acoustic full waveform inversion. To use the proper constraints for the inversion, layer-stripping method is used to develop the high-resolution velocity field. The inversion stages were carefully quality controlled through gather displays to ensure the kinematics were honored. We then demonstrated the benefit of the FWI velocity field by comparing the images derived with the traditional ray-based tomographic velocity field versus the velocity field derived by FWI performing reverse time migration to produce these images. Finally, the images were compared at key well locations to evaluate the robustness of the workflow.