We develop an efficient scheme of illumination analysis along a target horizon. With this scheme, we can calculate the Directional Illumination (DI) from the sources and the Acquisition Dip Response (ADR) along a target horizon in very short turnaround time. Therefore, it can be a useful tool to study the influence of the model (e.g. salt body) and the acquisition system (e.g. shot distribution and aperture size). The result can be a guide for acquisition design and model building. With the illumination map along the target horizon, it also is helpful for the interpretation in areas where the image amplitudes are not reliable. Here, we use the wave-equation based migration and local plane wave decomposition method to get the frequency domain illumination in the local angle domain. We pre-calculated and saved the angle domain Green’s function along the target horizon. These Green’s functions are reusable so that we can save a lot of computational and I/O cost. We use the 3D SEG/EAGE salt model and a real model example to demonstrate the validity of our method.
Reverse time migration (RTM) suffers from low wavenumber noise especially above strong reflectors such as salt boundaries. The traditional method of removing the noise is applying low cut filtering, which could destroy real events. The inverse scattering imaging condition selectively removes the backscattering noise. We introduce a method of computing the inverse scattering weighting coefficient. Synthetic and field examples show that the inverse scattering imaging improves salt boundary imaging compared to post-processed conventional RTM. The complicated imaging algorithm requires more computing time. The main overhead comes from the increased amount of source wavefield data. By redistributing some of the data compression process to the GPU’s, we were able to reduce the run time overhead by 10% of the conventional RTM.
In this abstract, we describe how to improve time domain full waveform inversion using source wavelet convolution, windowed back propagation and source side illumination. Instead of estimating the source wavelet from field data, a user defined source wavelet can be convolved to field data. This convolution makes waveform matching between modeled and field data easier. Increasing time window applied to residual enables top down velocity update and reduces the possibility of being stuck at a local minimum. The balance of gradient value can be improved by the illumination compensation using the square of source side wavefield. Well balanced gradient helps FWI restore the absolute value of velocity. We apply this method to estimate migration velocities using 2D and 3D synthetic and real data examples.