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Attenuation is often significant during seismic wave propagation in the subsurface, leading to the reduced resolution and narrower bandwidth of seismic images. Traditional corrections for such effects are inverse-Q filtering and deconvolution, which require a high signal-to-noise ratio (SNR) to avoid noise boost-up. Here, we propose a time-domain method offering advantages in the resolution and interpretational quality of the resulting images. Similar to wavelet transforms, the iterative time-domain deconvolution (ITD) represents the seismogram by a superposition of non-stationary source wavelets modeled in the appropriate attenuation model. Arbitrary frequency-dependent Q and velocity dispersion laws can be used and non-Q type attenuation can be caused by focusing, defocusing, scattering, effects of fine layering, and fluctuations of the wavefield. Compared to inverse-Q filtering and some deconvolution methods, the method does not boost high-frequency noise and is less sensitive to the accuracy of the Q model. We illustrate and compare this method to inverse-Q filtering by using several synthetic and real data examples. The tests include noise-contaminated data, inaccurate Q models, and variable source wavelets. The examples show that the ITD is a practical and effective tool for Q-compensation with a broad scope of potential applications, albeit with some defects. An important benefit of ITD that other methods may not possess could be the ability to utilize geological information, such as locations and sparseness of major reflectors or the presence of interpreted Q contrasts, which might be able to further improve the performance of ITD. [ABSTRACT FROM AUTHOR]

High-precision finite difference (FD) wavefield simulation is one of the key steps for the successful implementation of full-waveform inversion and reverse time migration. Most explicit FD schemes for solving seismic wave equations are not compact, which leads to difficulty and low efficiency in boundary condition treatment. Firstly, we review a family of tridiagonal compact FD (CFD) schemes of various orders and derive the corresponding optimization schemes by minimizing the error between the true and numerical wavenumber. Then, the optimized CFD (OCFD) schemes and a second-order central FD scheme are used to approximate the spatial and temporal derivatives of the 2D acoustic wave equation, respectively. The accuracy curves display that the CFD schemes are superior to the central FD schemes of the same order, and the OCFD schemes outperform the CFD schemes in certain wavenumber ranges. The dispersion analysis and a homogeneous model test indicate that increasing the upper limit of the integral function helps to reduce the spatial error but is not conducive to ensuring temporal accuracy. Furthermore, we examine the accuracy of the OCFD schemes in the wavefield modeling of complex structures using a Marmousi model. The results demonstrate that the OCFD4 schemes are capable of providing a more accurate wavefield than the CFD4 scheme when the upper limit of the integral function is 0.5π and 0.75π. [ABSTRACT FROM AUTHOR]

Elastic full waveform inversion (EFWI) is essential for obtaining high-resolution multi-parameter models. However, the conventional EFWI may suffer from severe cycle skipping without the low-frequency components in elastic seismic data. To solve this problem, we propose a multistage phase correction-based elastic full waveform inversion method in the frequency-wavenumber domain, which we call PC-EFWI for short. Specifically, the seismic data are first split using 2-D sliding windows; for each window, the seismic data are then transformed into the frequency-wavenumber domain for PC-EFWI misfit. In addition, we introduced a phase correction factor in the PC-EFWI misfit. In this way, it is possible to reduce phase differences between measured and synthetic data to mitigate cycle skipping by adjusting the phase correction factor in different scales. Numerical examples with the 2-D Marmousi model demonstrate that the frequency-wavenumber domain PC-EFWI with multistage strategy is an excellent way to reduce the risk of EFWI cycle skipping and build satisfactory start models for the conventional EFWI. [ABSTRACT FROM AUTHOR]