To eliminate crosstalk within the imaging results of elastic reverse time migration (ERTM), we can separate the coupled P- and S-waves from the forward source wavefield and the backpropagated receiver wavefield. The P- and S-wave decoupling method retains the original phase, amplitude, and physical meaning in the separated wavefields. Thus, it is a vital wavefield separation method in ERTM. However, because these decomposed wavefields are vectors, we could consider how to retrieve scalar images that reveal the real reflectivity of the subsurface. For this purpose, we derive a scalar P-wave equation from the velocity-stress relationship for PP imaging. The phase and amplitude of this scalar P-wave are consistent with the scalarized P-wave. Therefore, this scalar P-wave can be exploited to perform PP imaging directly, with the imaging result retaining the amplitude characteristics. For PS imaging, it is difficult to calculate a dynamic preserved scalar S-wave. However, we have developed a scalar PS imaging method that divides the PS image into energy and sign components according to the geometric relationship between the wavefield vibration and propagation directions. The energy is calculated through the amplitude crosscorrelation of the forward P-wave and backpropagated S-wave from the receivers. The sign is obtained from the dot product of the forward P-wave vector and the backpropagated S-wave vector. These PP and PS imaging methods are suitable for 2D and 3D isotropic media and maintain the correct amplitude information while eliminating polarity-reversal phenomena. Several numerical models are used to verify the robustness and effectiveness of our method.

The arrival time of a microseismic event is an important piece of information for microseismic monitoring. The accuracy and efficiency of arrival time identification is affected by many factors, such as the low signal-to-noise ratio (SNR) of the records, the vast amount of real-time monitoring records, and the abnormal situations of monitoring equipment. In order to eliminate the interference of these factors, we propose a method based on phase-only correlation (POC) to estimate the relative arrival times of microseismic events. The proposed method includes three main steps: (1) The SNR of the records is improved via time-frequency transform, which is used to obtain the time-frequency representation of each trace of a microseismic event. (2) The POC functions of all pairs of time-frequency representations are calculated. The peak value of the POC function indicates the similarity of the traces, and the peak position in the time lag axis indicates the relative arrival times between the traces. (3) Using the peak values as weighting coefficients of the linear equations, consistency processing is used to exclude any abnormal situations and obtain the optimal relative arrival times. We used synthetic data and field data to validate the proposed method. Comparing with Akaike information criterion (AIC) and cross-correlation, the proposed method is more robust at estimating the relative arrival time and excluding the influence of abnormal situations.

Description of fluid properties, natural fractures, and stress conditions is significant for seismic characterization of unconventional fractured reservoirs. For the first two aspects, traditional methods to solid-liquid decoupling by low-frequency anisotropic Gassmann fluid substitution equation fall short in two aspects: 1) neglecting the combined effects of fractures and pore fluid, and 2) disregarding the influence of fracture inclination on the seismic anisotropy. To address the above two issues simultaneously, this article derives a novel PP-wave reflection coefficient incorporating fluid bulk modulus, vertical effective stress correlation parameter, fracture density, and coupled anisotropic fluid indicator (CFI) in the tilted transverse isotropy (TTI) medium. The derived TTI-saturated stiffnesses with CFI are revealed to provide the improved accuracy regarding physical property parameters (porosity, fluid fillings, and matrix mineral content) and fracture parameters (including fracture density and inclination). To invert the above key parameters from offset vector tile (OVT) domain seismic data, the stepwise seismic inversion strategy based on Lp quasi-norm sparsity constraints is employed. Synthesized azimuthal seismic data with varying signal-to-noise ratios (SNR) validate the feasibility and robustness of the proposed inversion method. Ultimately, the innovative method exhibits compelling effectiveness when applied to fractured shale gas-bearing reservoirs in the Sichuan Basin, China.

Elastic reverse time migration (ERTM) uses multicomponent seismic data to image not only PP but also PS waves. The incorporation of PS imaging substantially mitigates the multisolution problem of inversion and interpretation. However, in ERTM, the PP image is affected by backscattering artifacts when the scattering angle is 180° or close to 180°. When the migration velocity model is inaccurate, false images may appear in regions with large velocity gradients in the PP and PS images. Deprimary ERTM (DpERTM) addresses this issue by decomposing the wavefield into up- and downgoing wavefields and subsequently crosscorrelates the downgoing-source and the upgoing-receiver wavefields to eliminate false images and low-frequency noise. However, the prismatic and turning waves used for imaging steeply dipping structures are weakened. Based on this analysis, we develop a method of flank-preserving DpERTM that introduces prismatic and turning waves information into the composite wavefield through a specific directional wavefield decomposition method based on the Hilbert transform. Subsequently, we construct the elastic wave dual-composite crosscorrelation imaging condition using composite downgoing-source and composite upgoing-receiver wavefields, which significantly enhances imaging of steeply dipping structures. Several numerical examples are evaluated to demonstrate that our method effectively suppresses low-frequency noise and eliminates false images caused by large velocity gradients while preserving steeply dipping structures.

During the multi-component seismic exploration, P- and S-waves can be recorded, enabling us to obtain more information about the subsurface media. In the interpretation and processing of most multi-component seismic data, accurate separation of P- and S-waves in forward simulation and wavefield extrapolation is essential, such as elastic reverse time migration and elastic full-waveform inversion. We decouple the elastic wavefield based on the first-order velocity-stress elastic wave decoupling equation. However, this method produces obvious separation artifacts due to the non-zero spatial derivative of the elastic parameters at the geological interfaces, which can affect later seismic processing and interpretation. To address this issue, an adaptive median filtering method is proposed to remove these artifacts. First, calculate the velocity change rate and identify the interfaces where the artifacts occur. Utilizing threshold to filter velocity change rates in order to determine the position of interfaces where artifacts occur. Then, the window calculation function based on the wavelength of seismic is used to obtain the median filtering window used for processing. Finally, it applies adaptive median filtering to remove the separated artifacts while preserving the valid information of the wavefields. This method preserves the effective wavefields and effectively removes separation artifacts. Through numerical simulations, it is verified that the adaptive median filtering method can effectively and completely remove the separation artifacts occurring at all interfaces.

Presents corrections to the paper, (Corrections to “Seismic Inversion of Anisotropic and Isotropic Fluid Indicators and Fracture Density in the TTI Medium”).