We have developed a novel Q compensation approach for adjoint-based seismic imaging by pseudodifferential scaling. The algorithm is stable, because it doesn’t involve amplitude amplification during wavefield extrapolations. We consider an image has correct amplitudes if, with the image as input, linearized Born modeling approximately produces the data. This can be achieved with the application of the inverse Hessian to the RTM image, to compensate propagation effects, including the Q effects. Pseudodifferential scaling (a dip and space dependent filter) is used to efficiently approximate the action of the inverse Hessian, and is applied to the viscoacoustic RTM image to compensate attenuation loss, and approximately recover the model perturbation. We evaluate the performance of the Q compensation using the Marmousi model. Numerical examples indicate that the adjoint RTM images with pseudodifferential scaling approximate the true model perturbation, and can be used as well-conditioned gradients for least-squares imaging.

Presentation Date: Wednesday, September 27, 2017

Start Time: 2:15 PM

Location: 371A

Presentation Type: ORAL

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