A cepstrum domain coal seam strong amplitude suppression method and device

Abstract

The present application belongs to the field of oil and gas exploration geophysics. The present application discloses a kind of coal seam strong amplitude suppression method in cepstrum domain. The method is converted to cepstrum domain by using the method of cepstrum analysis to seismic data, extracts second-order cepstrum coefficient, obtains second-order cepstrum coefficient data body, and then determines the maximum value in maximum value sequence as a mark point, combined with coal seam adaptive strong amplitude suppression of suppression factor setting. The present application provides a kind of coal seam strong amplitude suppression method in cepstrum domain, uses cepstrum operation to convert seismic data to cepstrum domain, which is beneficial to highlight weak information components, and uses second-order cepstrum coefficient to automatically detect the range of coal seam strong amplitude, which avoids the difficulties such as detecting coal seam thickness and estimating coal seam frequency in traditional coal seam strong amplitude suppression method. The present application provides a kind of device for coal seam strong amplitude suppression in cepstrum domain, including cepstrum processor, second-order cepstrum coefficient data body generator and coal seam suppression data generator. The method of coal seam strong amplitude suppression in cepstrum domain is realized.

Description

Technical Field

[0001] This invention relates to the field of geophysical processing methods for oil and gas exploration, specifically to a method and apparatus for suppressing strong amplitude of coal seams in the cepstral domain. Background Technology

[0002] Coal seams typically exhibit low-frequency, high-amplitude characteristics on seismic profiles, which can shield surrounding seismic reflections and mask weak signals from surrounding strata and reservoirs, thus affecting the detection of reservoirs in the area surrounding the coal seam. Traditional techniques for suppressing strong coal seam amplitudes mainly include extrapolating coal seam thickness from well logging data to seismic profiles, spectral decomposition, multi-wavelet decomposition and reconstruction, empirical mode decomposition-based strong amplitude suppression, and inverse Q-filtering. However, the technique of extrapolating coal seam thickness from well logging data to seismic profiles, which extrapolates the thickness of the coal seam and surrounding rock strata obtained at the well point, often cannot adapt to the complex and variable geological conditions outside the well point, exhibiting a "point-to-area" limitation. Spectral decomposition and multi-wavelet decomposition and reconstruction techniques require determining the frequency range of the coal seam to eliminate strong amplitude reflections; however, due to varying geological conditions in different areas of the work site, accurately estimating the frequency range of the coal seam is often difficult, thus only partially eliminating strong amplitude reflections. Strong amplitude suppression methods based on empirical mode decomposition (EMD) suffer from mode aliasing, leading to the suppression of some useful information while retaining some coal seam information. Inverse Q-filtering, a high-resolution processing method, improves seismic profile resolution through Q-compensation to separate the reflection information of coal seams and surrounding strata. However, suppressing noise amplification during Q-estimation and compensation in inverse Q-filtering remains a challenge.

[0003] The purpose of this invention is to solve the problems existing in the prior art by using a cepstral algorithm to detect the singularity characteristics of seismic wave amplitude caused by coal seams, thereby achieving adaptive suppression of strong amplitudes in coal seams. The method of suppressing strong amplitudes in coal seams using a cepstral algorithm is more sensitive to minute signal changes, does not require determining the frequency range of the coal seam, can adaptively detect the amplitude singularity characteristics caused by strong amplitudes in coal seams, and has stronger recognition and accuracy than conventional methods. Furthermore, it is fast and suitable for processing massive amounts of seismic data. Summary of the Invention

[0004] A method for suppressing strong amplitude in cepstral domain coal seams includes the following steps:

[0005] (1) Accurately identify the target layer of seismic data by comprehensively utilizing geological, well logging and synthetic seismic record data.

[0006] (2) For the target layer seismic data, the cepstral algorithm is used to convert the seismic data to the cepstral domain.

[0007] (3) Extract the second-order cepstral coefficient data volume from the seismic data in the cepstral domain frame by frame.

[0008] (4) Extract the maximum value of the second-order cepstral coefficient data volume one channel at a time, determine the two adjacent maximum values ​​in the maximum value sequence as marker points, and set the suppression factor to suppress the strong amplitude of the coal seam.

[0009] The core issue of this invention is to convert seismic data to the cepstral domain using a cepstral algorithm, extract second-order cepstral coefficient data from the cepstral domain seismic data, and use the positions of two adjacent maximum points in the second-order cepstral coefficient data as marker points, combined with the setting of a suppression factor, to achieve adaptive suppression of strong coal seam amplitude.

[0010] The specific implementation principle of this invention is as follows:

[0011] 1. Accurately identify the target layer of seismic data by comprehensively utilizing geological, well logging, and synthetic seismic record data.

[0012] 2. For seismic data of the target layer, the cepstral algorithm is used to convert the seismic data to the cepstral domain.

[0013] The target layer seismic data is recorded as follows: , This is a time variable. The time window length is set to... , Even numbers. For earthquake data. Fill in zeros one by one, in Leading zeros ( ) points, in Add zeros Points. Record the zero-padded seismic data as follows: .right Perform frame division, with each frame having a length of [length missing]. The frame shift is 1, and a Hamming window is added to each frame of signal. For each frame of signal with the window added... Calculate the cepstrum. The cepstrum calculation methods here can include Fourier transform-based cepstrum, wavelet packet transform-based cepstrum, and marginal spectrum-based cepstrum. The formula for calculating the cepstrum based on Fourier transform is as follows:

[0014] (1)

[0015] in, Indicates Fourier transform, This represents the inverse Fourier transform. For Logarithmic operations with base 0.

[0016] The cepstrum based on wavelet packet transform is:

[0017] (2)

[0018] in, This is a wavelet packet transform.

[0019] The cepstral based on the marginal spectrum is:

[0020] (3)

[0021] in, The marginal Hilbert transform is typically represented by calculating the time spectrum of the Hilbert-Huang transform. Time points earned:

[0022] (4)

[0023] in, , , . This indicates the operation of taking the real part. Indicates the first One intrinsic mode function. )express Hilbert transform, For frequency.

[0024] 3. For the cepstral domain seismic data, extract the second-order cepstral coefficient data volume frame by frame.

[0025] The second-order cepstral coefficient data of a seismic trace is defined as the set of points containing the second cepstral coefficient in each frame of the seismic trace. For seismic data in the cepstral domain... The second cepstral coefficient is extracted from each frame sequentially to generate the second-order cepstral coefficient data volume of the target layer seismic data. .

[0026] 4. For the second-order cepstral coefficient data volume, extract the maxima one by one, determine the positions of the two adjacent maxima in the maximum value sequence as marker points, and set the suppression factor to suppress the strong amplitude of the coal seam.

[0027] For second-order cepstral coefficient data volume Extract the maxima one by one, and let the position of the maximum value in the maximum value sequence be . Then the positions of the two maxima adjacent to the maximum value are: , .

[0028] Let the suppression factor be The calculation formula is as follows:

[0029] (5)

[0030] In the formula, This represents the number of sample points contained in each seismic trace. This represents the summation operation. This indicates finding the maximum value.

[0031] Seismic data after strong amplitude suppression of coal seams are

[0032] (6)

[0033] The cepstral domain coal seam strong amplitude suppression method of the present invention has the following characteristics, mainly manifested as follows:

[0034] (1) The cepstral operation was used to transform the seismic data into the cepstral domain, which is beneficial to highlighting the small and weak information components.

[0035] (2) The traditional coal seam strong amplitude suppression algorithm is extended to the cepstral domain, providing a supplementary algorithm to the traditional coal seam strong amplitude suppression algorithm.

[0036] (3) The second-order cepstral coefficient is used to automatically detect the strong amplitude range of the coal seam, avoiding the difficulties in detecting the coal seam thickness and estimating the coal seam frequency in the traditional strong amplitude suppression method. It is an adaptive high-resolution processing technology.

[0037] (4) The cepstral domain coal seam strong amplitude suppression method provided by the present invention has a fast running speed and is suitable for large-scale seismic signal processing.

[0038] This invention also provides a device for suppressing strong amplitude in cepstral domain coal seams, comprising a cepstral processor, a second-order cepstral coefficient data volume generator, and a coal seam suppression data generator. The cepstral processor performs cepstral operations, including Fourier transform, logarithm taking, and inverse Fourier transform. The spectrum obtained by the Fourier transform undergoes absolute value taking and adding "1". The second-order cepstral coefficient data volume generator performs channel-by-channel extraction of second-order cepstral coefficients from the cepstral data volume generated by the cepstral processor, generating a second-order cepstral coefficient data volume. The coal seam suppression data generator determines the positions of the two maxima adjacent to the maximum value of the second-order cepstral coefficient data volume channel-by-channel, and uses these two maxima positions combined with a suppression factor to achieve adaptive suppression of strong amplitude in coal seams, generating a coal seam suppression data volume. This device implements the aforementioned method for suppressing strong amplitude in cepstral domain coal seams and achieves the same effect. Attached Figure Description

[0039] Figure 1 This is a flowchart of a method for suppressing strong amplitude in cepstral domain coal seams.

[0040] Figure 2 This is a post-stack migration seismic profile of a gas field in the Ordos Basin.

[0041] Figure 3This is a diagram showing the volumetric results of the second-order cepstral coefficients.

[0042] Figure 4 This is a diagram showing the results of strong amplitude suppression in coal seams after processing with this technology;

[0043] Figure 5 This invention relates to a device for suppressing strong amplitude in cepstral domain coal seams. Detailed Implementation

[0044] (1) Figure 1 This is a method for suppressing strong amplitude in cepstral domain coal seams.

[0045] (2) Figure 2 This is a post-stack migration seismic profile of a gas field in the Ordos Basin. The image shows strong amplitude reflections occurring at the location of the coal seam (between 700ms and 800ms).

[0046] (3) Figure 3 This is a diagram showing the volumetric results of the second-order cepstral coefficients.

[0047] (4) Figure 4 This is a diagram showing the results of strong amplitude suppression of the coal seam after processing using this technique. As can be seen from the diagram, the strong amplitude reflection at the location of the coal seam has been suppressed, and the energy level remains at the same level as the surrounding seismic reflection signals. The weak reflection information around the coal seam has been enhanced.

[0048] (5) Figure 5 This invention relates to a device for suppressing strong amplitude vibrations in coal seams within the cepstral domain. It includes a cepstral processor, a second-order cepstral coefficient data generator, and a coal seam suppression data generator. Both the generator and processor comprise data processing and storage components, which communicate with each other via an internal bus. The data storage components of the generator and processor can be various types of memory, such as hard disks or USB flash drives, that store information using magnetic, electrical, optical, or other methods. The data processing components of the generator and processor can be microprocessors (MCUs) or programmable logic devices (FPGAs). The data processing components can invoke logic instructions from the data storage components to implement a cepstral domain method for suppressing strong amplitude vibrations in coal seams.

Claims

1. A cepstrum domain coal seam strong amplitude suppression method, characterized in that The following steps are adopted: (1) Accurately identify the target layer of seismic data by comprehensively utilizing geological, well logging and synthetic seismic record data; (2) For the target layer seismic data, the seismic data is converted to the cepstral domain using a cepstral algorithm, wherein the cepstral algorithm is one of the following: Fourier transform-based cepstral, wavelet packet transform-based cepstral, or marginal spectrum-based cepstral. The cepstral calculation formula based on Fourier transform is as follows: (1) wherein, denotes a Fourier transform, denotes an inverse Fourier transform, is a logarithm operation with base is a logarithm operation with base is a cepstrum domain seismic data, is a time variable, is a signal after zero padding, windowing and framing of target layer seismic data is a signal after zero padding, windowing and framing of target layer seismic data The cepstral calculation formula based on wavelet packet transform is as follows: (2) in, Wavelet packet transform; The cepstral calculation formula based on the marginal spectrum is as follows: (3) in, The marginal Hilbert transform is typically represented by calculating the time spectrum of the Hilbert-Huang transform. Time points earned: (4) in For frequency; (3) Extract the second-order cepstral coefficient data volume frame by frame from the cepstral domain seismic data; (4) Extract the maximum values ​​of the second-order cepstral coefficient data volume one channel at a time, determine the positions of the two adjacent maximum values ​​in the maximum value sequence as marker points, and set a suppression factor to suppress the strong amplitude of the coal seam; The method for determining the marker point is as follows: Let the position of the maximum value in the maximum value sequence be . Then the positions of the two maxima adjacent to the maximum value are: , ; Suppression factor The calculation formula is as follows: (5) In the formula, The number of sample points contained in each seismic trace. This represents the summation operation. This indicates finding the maximum value. Seismic data after strong amplitude suppression of coal seams are (6) This completes the strong amplitude suppression of the coal seam.

2. A technical device for suppressing strong amplitude in cepstral domain coal seams, implementing the method for suppressing strong amplitude in cepstral domain coal seams as described in claim 1, characterized in that, The system includes a cepstral processor, a second-order cepstral coefficient data volume generator, and a coal seam suppression data generator. The cepstral processor performs cepstral operations, including Fourier transform, logarithm taking, and inverse Fourier transform operations. The spectrum obtained by the Fourier transform is subjected to absolute value taking and adding "1" operations. The second-order cepstral coefficient data volume generator is used to perform channel-by-channel extraction of second-order cepstral coefficients from the cepstral data volume generated by the cepstral processor to generate the second-order cepstral coefficient data volume. The coal seam suppression data generator determines the positions of the two maxima adjacent to the maximum value of the second-order cepstral coefficient data volume channel by channel, and uses the two maxima positions combined with the suppression factor to achieve adaptive strong amplitude suppression of the coal seam, generating the coal seam suppression data volume.

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