Multi-component earthquake data vector mean value filtering method

A technique of seismic data and mean value filtering, which is applied in seismic signal processing and other directions, can solve the problem of easily destroying the vector relationship between multi-component seismic data components, and achieve the goal of keeping special vector features undistorted, suppressing pulse random noise and Gaussian random noise Effect

Active Publication Date: 2015-11-25
INST OF GEOCHEM CHINESE ACADEMY OF SCI
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Problems solved by technology

[0005] The main purpose of the present invention is to provide a vector mean filtering method for multi-component seismic data, to solve the proble

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  • Multi-component earthquake data vector mean value filtering method
  • Multi-component earthquake data vector mean value filtering method
  • Multi-component earthquake data vector mean value filtering method

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Embodiment Construction

[0025] The main idea of ​​the present invention is to search out the local trajectory of the seismic wave event in multiple linear trajectories and curved trajectories based on the vector distance between the adjacent channel multi-component seismic vector signal segments, and then add a window along the local trajectory of the seismic event Select field points, and based on multivariate data statistical sorting theory, carry out vector mean filtering processing on multiple vector signal sampling points selected along the local trajectory of the event, so as to solve the problem of effective signals near the local extremum of the inclined event and seismic wave by a simple rectangular filter window. In addition to the problem of damage, it can effectively suppress pulse random noise and Gaussian random noise, and can well keep the special vector characteristics of multi-component seismic signals without distortion.

[0026] In order to make the purpose, technical solution and a...

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Abstract

The invention discloses a multi-component earthquake data vector mean value filtering method, comprising steps of processing the multi-component earthquake data before superstition, using multi-component data on each sampling point to constitute a vector, determining the length N of a filtering window on a horizontal direction and the length on the time direction, searching the local optimal track of the current filtering point on a same-phase axis through the distance between the vectorend curves of the adjacent channel vector data, taking the current filtering point as a center, choosing N vector signal points on the optimal local tracks, performing boundary sequencing on the N vector signals to obtain a boundary mid-value vector, calculating the distance between the vector signal point and the boundary mid-value and the mean value, choosing the vector signal point which is positioned the in the middle portion after sequencing, and performing averaging on the vector signals positioned in the middle to obtain the average value. The invention solves the problem that the prior art is likely to damage the vector relation between the multi-component earthquake components when suppressing the random noise.

Description

technical field [0001] The invention relates to the technical field of seismic data filtering, in particular to a vector mean filtering method for multi-component seismic data. Background technique [0002] In the exploration of fossil energy such as oil, natural gas, coal, and coalbed methane, seismic exploration technology based on explosive sources (artificial sources) is one of the key technologies to obtain underground structure and lithology information and identify the existence of oil and gas and other energy sources. Conventional seismic exploration technology mainly uses the excitation and propagation of longitudinal waves and the reception of single-component seismic signals to achieve the purpose of exploring underground elastic wave field anomalies. With the deepening of oil and gas exploration and development, the oil and gas exploration targets are becoming more and more complex, and the corresponding exploration technology level is also improving. In the past...

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Application Information

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IPC IPC(8): G01V1/36
Inventor 汪超王赟
Owner INST OF GEOCHEM CHINESE ACADEMY OF SCI
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