Linear denoising method based on multi-core processor

Abstract

The invention provides a linear denoising method based on a multi-core processor, which comprises the steps that: multi-shot earthquake data is read into a main node of the multi-core processor; the main node distributes a plurality of pieces of single-shot earthquake data in the multi-shot earthquake data to a plurality of sub-nodes of the multi-core processor; all the sub-nodes carry out lineardenoising to the single-shot earthquake data from the main node; and the main node collects the single-shot earthquake data which is linearly denoised from the sub-nodes, and outputs linearly denoised earthquake data. Wherein, when the sub-nodes carry out linear denoising, every time when the velocity of linear interference which is scanned from the single-shot earthquake data to be processed is consistent with any apparent velocity within a preset linear interference apparent velocity range, an optimized prediction filter operator is used for each frequency component in a frequency domain for prediction filtration along an X-direction after the same-phase shaft of the linear interference is flattened.

Description

Technical field [0001] The invention relates to a method for performing denoising processing on multi-shot seismic data, in particular to a method for parallelly performing linear denoising on multi-shot seismic data based on a multi-core processor. Background technique [0002] In recent years, with the development of oil and gas exploration, the scope of seismic exploration has become wider and deeper. Seismic exploration has gradually shifted from the east to the west, from plains to complex surface areas such as deserts, hills, and mountains. This kind of simple and easy-to-process work has basically come to an end, and the task left to geophysical prospectors is very arduous. In the seismic data collected in complex surface areas, the signal-to-noise ratio of the data is very low, and quite serious linear noise generally exists. In general, this kind of noise seriously interferes with the effective reflected signal and greatly reduces the signal-to-noise ratio of the seismic...

AI Technical Summary

Problems solved by technology

The disadvantage of this type of method is that it is slow, especially for 3D seismic data containing thousands or even tens of thousands of shots, the problem of processing speed is more serious, and it is difficult to meet the actual needs

[0005] The usual linear denoi

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