A Waste Road Identification Method Based on Singular Value Decomposition Technology

Abstract

The invention provides a waste channel identification method based on singular value decomposition technology, which belongs to the field of petroleum geophysical exploration. The method includes: (1) dividing the seismic data profile into three ranges, namely shallow range, middle range and deep range, wherein the shallow range includes the data before the first arrival, the middle range includes the data in the area where the first arrival is located, and the deep range includes the data in the area where the first arrival is located. The range includes the deep data after the first arrival; (2) for the data of each seismic trace, the attribute characteristics in the three ranges are obtained respectively, and the attribute characteristics include the average amplitude, dominant frequency, and number of zero-crossing points in the shallow range, The average amplitude, main frequency, number of zero-crossing points, and correlation coefficient in the middle range, the average amplitude, main frequency, number of zero-crossing points, and apparent attenuation factor in the deep range; (3) normalize each attribute feature, Obtaining an attribute matrix; (4) performing singular value decomposition on the attribute matrix, and calculating the Euclidean distance; (5) inputting a threshold.

Description

technical field [0001] The invention belongs to the field of petroleum geophysical exploration, and in particular relates to a waste road identification method based on singular value decomposition technology. Background technique [0002] In the process of seismic data processing, waste track detection and elimination are very important and cumbersome tasks in data processing. Usually, processors can only identify waste tracks based on characteristics such as amplitude value and video frequency. Manual judgment and manual elimination have the problems of low efficiency and inaccuracy, and it is difficult to meet the requirements of massive seismic data processing progress in high-density exploration. [0003] At present, some automatic or semi-automatic seismic channel editing algorithms and software, such as the software Promax, mainly use the individual processing modules in the software mechanically to distinguish abnormal channels through the main frequency, so the proc...

AI Technical Summary

Problems solved by technology

The impact of waste tracks on subsequent processing effects cannot be ignored, especially waste tracks with strong energy, which have adverse effects on multi-channel processing such as surface consistent processing amplitude compensation and pre-stack random noise attenuation: affecting the attenuation law of amplitude, resulting in The compensation coefficient is difficult to obtain accurately; the predictability of seismic reflection signals in the frequency domain is weakened, which limits the effective use of pre-stack random noise attenuation

[0006] Among the existing waste track identification technologies, 0mega, as the current mainstream processing software, can identify waste tracks such as industrial interference and empty guns during the filtering process, but it still cannot identify empty tracks mixed in normal data; in Promax In the process, manual operation can only be used to identify waste roads, which is time-consuming and labor-intensive

However, due to the great influence of waste tracks on the results of seismic data processing, it is imperative to deal with these waste tracks, and manual picking of waste tracks is far from meeting the current project schedule requirements

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