Multi-component seismic data filtering method based on vector mixing distance sorting

Abstract

The invention discloses a multi-component seismic data filtering method based on vector mixing distance sorting, which is suitable for random noise suppression of multi-component seismic data. The above mentioned method comprises steps that the multi-component seismic channel data is acquired to form vector seismic channel data; a filtering time window length L is predetermined, and by taking a current filtering point as the center of the filtering time window length, L vectors are acquired from the vector seismic channel data, and L is a positive integer greater than zero; according to the L vectors, first crowding distances are acquired; the normalization processing of the L vectors is carried out to acquire second crowding distances; by adding together the first crowding distances and the second crowding distances, mixing crowding distances are acquired, and the sorting of the mixing crowding distances is carried out, and the vector corresponding to the minimum mixing crowding distance is the final value of the current filtering point. The problem of the prior art of inability of removing random noises at the same time of effectively maintaining the multi-component seismic data vector characteristics is solved.

Description

technical field [0001] The invention relates to the technical field of seismic exploration, in particular to a multi-component seismic data filtering method based on vector mixing distance sorting. Background technique [0002] Multi-component seismic data simultaneously records the movement of particles in the vertical and horizontal directions, and is a complete record of the seismic wave vector field. The vector data not only provides the travel time (velocity), amplitude and frequency information of the longitudinal wave and the shear wave, but also provides the relative amplitude relationship between the components of the same wave, as well as the amplitude difference and travel time difference of different waves. The unique information of these vector wave fields can describe the structure, lithology, fluid saturation, pore pressure, fractures and other characteristics of the subsurface medium in more detail and accurately. However, due to the limitations of current m...

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