Instantaneous polarization filtering focused on suppression of surface waves

Abstract

The different characteristics of polarization of body and Rayleigh waves make it possible to separate these two types of waves by their characteristics and suppress the latter. The moving time-window analysis often is used in polarization filtering but it is difficult to determine a suitable time-window length, resulting in some problems, such as complex eigenvalues and non-convergence. For overcoming these disadvantages, in this paper, we introduce the concept of complex-trace analysis and conduct de-noise processing to suppress undesirable surface waves by instantaneous polarization analysis in the case of horizontal and vertical component seismic recordings from the Hauinan coal mine. The performance of the method is illustrated by examples with synthetic and field data and its effectiveness to remove surface waves from multi-component seismic data is demonstrated.

Surface-Wave Extraction Based on Morphological Diversity of Seismic Events

“…However, it may be difficult to extract surface waves in some cases dispersive energy of higher-mode surface waves also overlaps with that of reflections in the f-v domain and then original surface-wave dispersive energy is distorted. Because the frequencies and velocities of PS-waves are close to those of higher-mode surface waves [16].…”

“…Methods of surface-wave suppression are based on single-component processing or multicomponent processing. Methods of single-component processing include f-k filtering, empirical mode decomposition and other transform methods [4,[13][14][15] while methods of multicomponent processing are polarization filtering and vector median filtering which preserve the vector characteristics and the spectral bandwidth of reflections [16,17].…”

Noise Attenuation Based on Wave Vector Characteristics

“…However, some noise, such as ground roll, always shares a similar frequency band with shear waves. To overcome this problem, polarization-filtering methods in the time-frequency domain are employed rather than those in a real time-series to separate noise and body waves [5,11,[19][20][21][22][23][24]. However, body waves are still hard to distinguish only using instantaneous polarization attributes when significant random noise and extra non-ground-roll related coherent noise occur on all three components [25].…”

Surface-Wave Extraction Based on Morphological Diversity of Seismic Events

“…Methods of surface-wave suppression are based on single-component processing or multicomponent processing. Methods of single-component processing include f-k filtering, curvelet transform, and other transform methods [13][14][15], while methods of multicomponent processing are polarization filtering and vector median filtering, which preserve the vector characteristics and the spectral bandwidth of reflections [16,17]. By a hybrid linear-hyperbolic Radon transform, Trad et al [18] separate surface waves successfully in a signal model that consists of both surface waves with linear events and reflections with hyperbolic events.…”

“…Using high-resolution LRT, Hu et al [19] transform raw data into the frequency-velocity (f-v) domain to implement surface-wave separation. However, dispersive energy of higher-mode surface waves may overlap with that of reflections in the f-v domain, because the frequencies and velocities of PS-waves are close to those of higher-mode surface waves [16]. So, it may be difficult to extract surface waves from X-component seismic data.In this paper, we propose a method of surface-wave extraction to overcome the influence of reflections on surface-wave dispersive energy.…”