A discontinuity detection method for seismic data based on high-dimensional wavelet transform

Abstract

The invention relates to a high-dimensional wavelet transform-based method for discontinuity detection of seismic data. The method comprises the following steps: (1), collecting seismic data and carrying out pretreatment to obtain a three-dimensional seismic data volume; (2), carrying out Hilbert transform on each channel of the three-dimensional seismic data volume so as to obtain a three-dimensional phase cosine data volume; (3), carrying out partitioning on the three-dimensional phase cosine data volume and selecting searching scopes of scale, inclination and azimuth according to discontinuous scales and geographical objects; (4), carrying out three-dimensional continuous wavelet transform on each subblock of the three-dimensional phase cosine data volume; (5), giving discontinuity tolerances of the seismic data according to a three-dimensional continuous wavelet transform coefficient modulus of each the subblock of the three-dimensional phase cosine data volume so as to obtain a partitioning discontinuous data volume; (6), carrying out splicing on the generated partitioning discontinuous data volume to obtain a discontinuous data volume of the whole seismic data. According to the method provided in the invention, computation quantity is small and multiscale detection can be carried out on discontinuity of seismic data; therefore, the method can widely applied to the detection process of the seismic data.

Description

technical field [0001] The invention relates to a method for detecting seismic data in oil and gas exploration, in particular to a method for detecting discontinuity of seismic data based on high-dimensional wavelet transform. Background technique [0002] With the deepening and development of seismic exploration technology, oil and gas exploration has changed from conventional structural oil and gas reservoir exploration to subtle oil and gas reservoir exploration. The use of seismic data to detect formation dips, underground faults, fractures, lithological changes, and the edges of geological bodies is of great significance to the exploration of subtle oil and gas reservoirs. [0003] At present, the industry usually adopts 3D seismic prospecting technology, which generates a huge amount of data, even for post-stack data, the data amount is generally tens of GB (gigabytes). Therefore, when dealing with such a huge amount of data, the efficiency and speed of the technology...

AI Technical Summary

Problems solved by technology

Bouchereau first used 2DCWT to detect the discontinuous structure of seismic data in 1997. The wavelet used was two-dimensional Morlet wavelet, but the two-dimensional Morlet wavelet has poor spatial localization properties at low wave numbers, so it cannot be used on a large scale. Seismic data processing

In addition, 3D seismic data are often used in the industry at present, and 2D algorithms cannot make full use of the spatial correlation of 3D seismic data

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