Simultaneous-source shooting can help reduce the acquisition time cost, but at the expense of introducing strong interference (blending noise) into the acquired seismic data. It has been demonstrated previously that the deblending problem can be considered as an inversion process. In this letter, we propose a new iterative approach to solve this inversion problem. In the proposed approach, a new coherency-promoting constraint, called structuring median filtering (SMF), is proposed and used to regularize the estimated model in each iteration. The SMF processes the signal by the interactions of the input signal and another given small section of signal, namely, the structuring element. The SMF is more robust than other coherency-promoting filtering such as the median filtering and mathematical morphological filtering. Numerical experiments demonstrate that the iterative deblending based on the SMF constraint obtains a better performance and a faster convergence than the low-rank and compressed sensing constraint-based deblending approaches.

Exploration Geophysics is published by CSIRO PUBLISHING on behalf of the Australian Society of Exploration Geophysicists. Papers published report the results of significant case histories and relevant original research in geophysics, with emphasis on the Australian and similar environments.

The Radon transform (RT) has been widely used in seismic data processing. In this paper, we develop a sparse time-variant anisotropic Radon transform (ART) to regularize and interpolate the prestack seismic data. By introducing the anelliptical parameter η, the ART has a more accurate integral path than other widely used RTs, which produces a better energy-focused Radon panel in the case of a vertical transverse isotropy VTI medium or seismic gather with a large moveout. To promote the sparsity of the Radon panel, the RT is realized as a l ₁–l ₂ norm inversion problem, and the fast iterative shrinkage thresholding algorithm is imposed to solve this sparsity-constrained inversion problem. Compared with the time-invariant parabolic RT in the mixed frequency-time domain and time-variant hyperbolic RT, the reconstructed result of the ART has the best performance and the least reconstruction error in a general synthetic VTI medium. Another field marine example further demonstrates that the ART is effective and robust for prestack seismic data regularization.

Least-squares reverse time migration (LSRTM) aims to produce a high-quality migration image of complex geological structures. However, the weaker deep seismic reflections are often masked by the overlying strata in migration images. Therefore, it is difficult for the LSRTM to image the deeper structures. This letter proposes a phase-amplitude LSRTM (PA-LSRTM) in the time-frequency domain to improve the migration image of deep seismic reflections and subsalt structures. The PA-LSRTM is formulated as an inverse problem that minimizes the time-frequency phase-amplitude difference between the predicted and observed data. The seismic data was initially transformed into the time-frequency domain to establish a PA-LSRTM misfit. An amplitude factor was then introduced in the time-frequency misfit to weaken the weights of amplitude components. In this case, it emphasized the similarity of phase components. Furthermore, the sparsity promotion method was combined with a simultaneous source technique to increase the computational efficiency and reduce the crosstalk noise. The PA-LSRTM with sparsity promotion (SPA-LSRTM) misfit can finally be solved using a Fast Iterative Shrinkage-Thresholding Algorithm (FISTA). The numerical and marine field data tests demonstrate that the SPA-LSRTM can effectively produce a high-resolution image of deep structures.

The seismic exploration method could explore deep metal ore bodies (depth > 1000 m). However, it is difficult to describe the geometry of the complex metal ore body accurately. Seismic full waveform inversion is a relatively new method to achieve accurate imaging of subsurface structures, but its success requires better initial models and low-frequency data. The seismic data acquired in the metal mine area is usually difficult to meet the requirements of full waveform inversion. The passive seismic data usually contains good low frequency information. In this paper, we use both passive and active seismic datasets to improve the full waveform inversion results in the metal mining area. The results show that the multisource seismic full waveform inversion could obtain a suitable result for high-resolution seismic imaging of metal ore bodies.