Salt Tectonic Modeling Using Reverse Time Migration Imaging and Sensitivity Kernel Wavelength Analysis

It is of particular importance for structural geology, geophysical exploration and also obvious economical purposes to retrieve structures possibly hidden below salt domes. And these domes could trap hydrocarbon or gas. We thus propose a sensitivity analysis of seismic data in salt tectonic areas to identify different wavelengths associated with the geological structures under study involving salt domes. The wavelengths associated with the density or seismic velocities of the medium can give us information about the localization of shallow or deep geological structures surrounding salt domes in off-shore contexts. Seismic data can be more sensitive to density or to seismic velocities. Depending on the wavelengths associated with those two different properties, the dome shape and the different interfaces can be located and recovered at different depths. In a first approach, using velocity and density models from a salt tectonic region in the Gulf of Mexico we simulate a two-dimensional seismic data acquisition. Using these synthetic data, we aim at retrieving the salt dome shape as well as the surrounding and deepest geological layers. For this purpose, we propose to compute better imaging conditions by attenuating free surface multiples and introducing an adjoint theory-based reverse time migration (RTM) method, enhancing the limits of salt bodies and also the layers under salt structures. To obtain these imaging conditions, we compute the compressional and density sensitivity kernels K λ and K ρ using seismic sources activated separately. To attenuate the free surface multiples, the synthetic “observed” data computed with the free surface are introduced as adjoint sources and we replace the free surface condition by PML absorbing conditions in both the forward, backward and adjoint simulations needed to compute the kernels. We compare the quality of the kernels applying different strategies related to the normalization of kernels by the forward or adjoint energy, and different property parametrizations were tested to improve the imaging conditions. The specific wavelengths associated with the different (shallow to deep) interfaces are obtained using signal-to-noise ratios (SNRs) applied to both density and seismic velocity kernels. In some cases, density or seismic velocity kernels are more suited to retrieve the interfaces at different depths.