CN112558158A - Seismic data bidirectional frequency extension method and system based on logging curve - Google Patents
Seismic data bidirectional frequency extension method and system based on logging curve Download PDFInfo
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Abstract
The invention discloses a seismic data bidirectional frequency extension method and a system based on a logging curve, which comprises the following steps: acquiring a synthetic record calibration result of logging acoustic impedance data and seismic data; comparing the synthetic record calibration result with a preset calibration value, and if the synthetic record calibration result is greater than or equal to the preset calibration value, respectively acquiring frequency spectrum information of the seismic data and frequency spectrum information of the logging acoustic impedance data; respectively acquiring first logging sound wave impedance data and second logging sound wave impedance data based on frequency spectrum information of the seismic data and the logging sound wave impedance data; establishing a nonlinear relation model of the seismic data and the first logging acoustic impedance data; and acquiring the seismic data of the second logging acoustic impedance data after frequency broadening. The invention is based on the nonlinear relation between the logging acoustic impedance data and the seismic data, and carries out bidirectional frequency extension processing on the seismic data based on the logging acoustic impedance data, and the reliability of frequency extension results is high.
Description
Technical Field
The invention belongs to the field of petroleum exploration, and particularly relates to a seismic data bidirectional frequency extension method and system based on a logging curve.
Background
The existing seismic data frequency band widening technology is mainly based on a signal analysis method to perform frequency band widening on the basis of seismic data, but the frequency broadening result is easy to have high uncertainty. Therefore, a seismic data band widening method that improves reliability of frequency broadening results is particularly needed.
Disclosure of Invention
The invention aims to provide a seismic data bidirectional frequency extension method and system based on a logging curve, which can improve the reliability of frequency extension results.
According to one aspect of the invention, a log-based seismic data bidirectional frequency broadening method is provided, which comprises the following steps: acquiring a synthetic record calibration result of logging acoustic impedance data and seismic data; comparing the synthetic record calibration result with a preset calibration value, and if the synthetic record calibration result is greater than or equal to the preset calibration value, respectively acquiring frequency spectrum information of the seismic data and frequency spectrum information of the logging acoustic impedance data; respectively acquiring first logging sound wave impedance data and second logging sound wave impedance data based on the frequency spectrum information of the seismic data and the logging sound wave impedance data; establishing a nonlinear relation model of the seismic data and the first logging acoustic impedance data; and acquiring the seismic data after the frequency extension of the second logging sound wave impedance data based on the nonlinear relation model of the seismic data and the first logging sound wave impedance data and the second logging sound wave impedance data.
Preferably, the fourier transform is performed on the seismic data to obtain spectral information of the seismic data.
Preferably, the logging acoustic impedance data is resampled, and the resampled logging acoustic impedance data is subjected to fourier transform to obtain frequency spectrum information of the logging acoustic impedance data.
Preferably, the acquiring the first logging acoustic impedance data and the second logging acoustic impedance data based on the spectrum information of the seismic data and the logging acoustic impedance data includes: acquiring an effective frequency band of the seismic data based on the frequency spectrum information of the seismic data, and filtering the logging acoustic impedance data in the effective frequency band to acquire first logging acoustic impedance data; and acquiring a total frequency band of the seismic data based on the frequency spectrum information of the seismic data, and filtering the logging acoustic wave impedance data in the total frequency band to acquire second logging acoustic wave impedance data.
Preferably, a nonlinear relation model of the seismic data and the first logging acoustic impedance data is established through a neural network algorithm.
According to another aspect of the invention, a log-based seismic data bidirectional frequency broadening system is provided, the system comprising: a memory storing computer-executable instructions; a processor executing computer executable instructions in the memory to perform the steps of: acquiring a synthetic record calibration result of logging acoustic impedance data and seismic data; comparing the synthetic record calibration result with a preset calibration value, and if the synthetic record calibration result is greater than or equal to the preset calibration value, respectively acquiring frequency spectrum information of the seismic data and frequency spectrum information of the logging acoustic impedance data; respectively acquiring first logging sound wave impedance data and second logging sound wave impedance data based on the frequency spectrum information of the seismic data and the logging sound wave impedance data; establishing a nonlinear relation model of the seismic data and the first logging acoustic impedance data; and acquiring the seismic data after the frequency extension of the second logging sound wave impedance data based on the nonlinear relation model of the seismic data and the first logging sound wave impedance data and the second logging sound wave impedance data.
Preferably, the fourier transform is performed on the seismic data to obtain spectral information of the seismic data.
Preferably, the logging acoustic impedance data is resampled, and the resampled logging acoustic impedance data is subjected to fourier transform to obtain frequency spectrum information of the logging acoustic impedance data.
Preferably, the acquiring the first logging acoustic impedance data and the second logging acoustic impedance data based on the spectrum information of the seismic data and the logging acoustic impedance data includes: acquiring an effective frequency band of the seismic data based on the frequency spectrum information of the seismic data, and filtering the logging acoustic impedance data in the effective frequency band to acquire first logging acoustic impedance data; and acquiring a total frequency band of the seismic data based on the frequency spectrum information of the seismic data, and filtering the logging acoustic wave impedance data in the total frequency band to acquire second logging acoustic wave impedance data.
Preferably, a nonlinear relation model of the seismic data and the first logging acoustic impedance data is established through a neural network algorithm.
The invention has the beneficial effects that: the method is based on the nonlinear relation between the logging acoustic impedance data and the seismic data, and the two-way frequency extension processing of the seismic data is carried out based on the logging acoustic impedance data, so that the frequency band range of the seismic data is improved, and the reliability of frequency extension results is high.
The present invention has other features and advantages which will be apparent from or are set forth in detail in the accompanying drawings and the following detailed description, which are incorporated herein, and which together serve to explain certain principles of the invention.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent by describing in more detail exemplary embodiments thereof with reference to the attached drawings, in which like reference numerals generally represent like parts throughout.
FIG. 1 shows a flow diagram of a log-based method for bi-directional frequency broadening of seismic data, according to an embodiment of the invention.
FIG. 2 illustrates a synthetic record calibration chart for a log-based seismic data bi-directional frequency broadening method according to an embodiment of the present invention.
FIG. 3 illustrates a seismic data profile of a log-based seismic data bi-directional frequency broadening method according to an embodiment of the present invention.
FIG. 4 illustrates a graph of seismic data spectral information for a log-based seismic data bi-directional frequency broadening method, according to an embodiment of the present invention.
FIG. 5 is a graph of spectral information of log acoustic impedance data for a log-based seismic data two-way frequency extension method according to an embodiment of the invention.
FIG. 6 illustrates a cross-sectional view of bi-directional frequency-extended seismic data for a log-based bi-directional frequency-extension method of seismic data, in accordance with an embodiment of the present invention.
Detailed Description
Preferred embodiments of the present invention will be described in more detail below. While the following describes preferred embodiments of the present invention, it should be understood that the present invention may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
The invention discloses a seismic data bidirectional frequency broadening method based on a logging curve, which comprises the following steps: acquiring a synthetic record calibration result of logging acoustic impedance data and seismic data; comparing the synthetic record calibration result with a preset calibration value, and if the synthetic record calibration result is greater than or equal to the preset calibration value, respectively acquiring frequency spectrum information of the seismic data and frequency spectrum information of the logging acoustic impedance data; respectively acquiring first logging sound wave impedance data and second logging sound wave impedance data based on frequency spectrum information of the seismic data and the logging sound wave impedance data; establishing a nonlinear relation model of the seismic data and the first logging acoustic impedance data; and acquiring the seismic data of the second logging acoustic impedance data after frequency extension based on the nonlinear relation model of the seismic data and the first logging acoustic impedance data and the second logging acoustic impedance data.
Specifically, synthetic record calibration is carried out, synthetic record calibration results of logging acoustic impedance data and seismic data are obtained, and a compressed logging curve can be properly stretched to obtain synthetic record calibration results with high correlation. The high calibration correlation degree of the synthetic record represents the similarity degree of the logging data and the seismic data in the same frequency band, and the higher the similarity degree is, the higher the precision of bidirectional frequency extension is. And only when the calibration result of the synthetic record is greater than or equal to the preset calibration value, executing the subsequent steps to realize bidirectional frequency broadening.
When the synthetic record calibration result is larger than or equal to a preset calibration value, respectively acquiring frequency spectrum information of the seismic data and frequency spectrum information of the logging sound wave impedance data, respectively acquiring first logging sound wave impedance data and second logging sound wave impedance data based on the frequency spectrum information of the seismic data and the logging sound wave impedance data, establishing a nonlinear relation model of the seismic data and the first logging sound wave impedance data, and further acquiring the seismic data after frequency extension of the second logging sound wave impedance data based on the nonlinear relation model of the seismic data and the first logging sound wave impedance data.
According to the illustrative embodiment, the seismic data bidirectional frequency extension method based on the logging curve is based on the nonlinear relation between the logging acoustic impedance data and the seismic data, the seismic data bidirectional frequency extension processing is carried out based on the logging acoustic impedance data, the frequency band range of the seismic data is improved, the reliability of frequency extension results is high, and the method has great popularization and application values in a lamella development area.
Preferably, the Fourier transform is performed on the seismic data to obtain the frequency spectrum information of the seismic data.
As a preferred scheme, the logging acoustic impedance data are resampled, and the resampled logging acoustic impedance data are subjected to Fourier transform to obtain frequency spectrum information of the logging acoustic impedance data.
As a preferred scheme, the acquiring the first logging acoustic impedance data and the second logging acoustic impedance data based on the spectrum information of the seismic data and the logging acoustic impedance data includes: acquiring an effective frequency band of the seismic data based on the frequency spectrum information of the seismic data, and filtering the logging acoustic impedance data in the effective frequency band to obtain first logging acoustic impedance data; and acquiring a total frequency band of the seismic data based on the frequency spectrum information of the seismic data, and filtering the logging acoustic impedance data in the total frequency band to obtain second logging acoustic impedance data.
Specifically, the low-frequency information and the high-frequency information missing from the seismic data can be known through the seismic data spectrum information, so that the main frequency band concentration range of the seismic data, namely the effective frequency band, is determined, and the first logging acoustic impedance data obtained by filtering the logging acoustic impedance data in the effective frequency band range is determined. And the total frequency band of the seismic data, namely the frequency band range for finally carrying out bidirectional frequency extension, can be known according to the frequency spectrum information of the seismic data, and the logging acoustic wave impedance data is filtered in the total frequency band to obtain second logging acoustic wave impedance data.
As a preferred scheme, a nonlinear relation model of the seismic data and the first logging sound wave impedance data is established through a neural network algorithm.
Specifically, the neural network algorithm establishes a nonlinear relation model of the seismic data and the first logging acoustic impedance data based on a training sample of the neural network, and the establishment of the training sample of the neural network is the prior art and is not described herein again. The training sample of the neural network has a data input end and a data output end, the first logging sound wave impedance data is input at the data input end, the seismic data is input at the data output end, the training sample of the neural network obtains the input data and the output data to form a nonlinear relation between the input data and the output data, a nonlinear relation model between the seismic data and the first logging sound wave impedance data is established, and the nonlinear relation model between the seismic data and the first logging sound wave impedance data is stored. Applying this relationship to the entire logging band can achieve frequency-extending results. And inputting second logging acoustic impedance data at the data input end of a training sample of the neural network, and generating data which corresponds to the input data and is obtained through a nonlinear relation by using a stored nonlinear relation model of the seismic data and the first logging acoustic impedance data, namely the seismic data after frequency extension of the second logging acoustic impedance data at the data output end.
According to the invention, the seismic data bidirectional frequency extension system based on the logging curve comprises: a memory storing computer-executable instructions; a processor executing computer executable instructions in the memory to perform the steps of: acquiring a synthetic record calibration result of logging acoustic impedance data and seismic data; comparing the synthetic record calibration result with a preset calibration value, and if the synthetic record calibration result is greater than or equal to the preset calibration value, respectively acquiring frequency spectrum information of the seismic data and frequency spectrum information of the logging acoustic impedance data; respectively acquiring first logging sound wave impedance data and second logging sound wave impedance data based on frequency spectrum information of the seismic data and the logging sound wave impedance data; establishing a nonlinear relation model of the seismic data and the first logging acoustic impedance data; and acquiring the seismic data of the second logging acoustic impedance data after frequency extension based on the nonlinear relation model of the seismic data and the first logging acoustic impedance data and the second logging acoustic impedance data.
Specifically, synthetic record calibration is carried out, synthetic record calibration results of logging acoustic impedance data and seismic data are obtained, and a compressed logging curve can be properly stretched to obtain synthetic record calibration results with high correlation. The high calibration correlation degree of the synthetic record represents the similarity degree of the logging data and the seismic data in the same frequency band, and the higher the similarity degree is, the higher the precision of bidirectional frequency extension is. And only when the calibration result of the synthetic record is greater than or equal to the preset calibration value, executing the subsequent steps to realize bidirectional frequency broadening.
When the synthetic record calibration result is larger than or equal to a preset calibration value, respectively acquiring frequency spectrum information of the seismic data and frequency spectrum information of the logging sound wave impedance data, respectively acquiring first logging sound wave impedance data and second logging sound wave impedance data based on the frequency spectrum information of the seismic data and the logging sound wave impedance data, establishing a nonlinear relation model of the seismic data and the first logging sound wave impedance data, and further acquiring the seismic data after frequency extension of the second logging sound wave impedance data based on the nonlinear relation model of the seismic data and the first logging sound wave impedance data.
According to the illustrative embodiment, the seismic data bidirectional frequency extension method based on the logging curve is based on the nonlinear relation between the logging acoustic impedance data and the seismic data, the seismic data bidirectional frequency extension processing is carried out based on the logging acoustic impedance data, the frequency band range of the seismic data is improved, the reliability of frequency extension results is high, and the method has great popularization and application values in a lamella development area.
Preferably, the Fourier transform is performed on the seismic data to obtain the frequency spectrum information of the seismic data.
As a preferred scheme, the logging acoustic impedance data are resampled, and the resampled logging acoustic impedance data are subjected to Fourier transform to obtain frequency spectrum information of the logging acoustic impedance data.
As a preferred scheme, the acquiring the first logging acoustic impedance data and the second logging acoustic impedance data based on the spectrum information of the seismic data and the logging acoustic impedance data includes: acquiring an effective frequency band of the seismic data based on the frequency spectrum information of the seismic data, and filtering the logging acoustic impedance data in the effective frequency band to obtain first logging acoustic impedance data; and acquiring a total frequency band of the seismic data based on the frequency spectrum information of the seismic data, and filtering the logging acoustic impedance data in the total frequency band to obtain second logging acoustic impedance data.
Specifically, the low-frequency information and the high-frequency information missing from the seismic data can be known through the seismic data spectrum information, so that the main frequency band concentration range of the seismic data, namely the effective frequency band, is determined, and the first logging acoustic impedance data obtained by filtering the logging acoustic impedance data in the effective frequency band range is determined. And the total frequency band of the seismic data, namely the frequency band range for finally carrying out bidirectional frequency extension, can be known according to the frequency spectrum information of the seismic data, and the logging acoustic wave impedance data is filtered in the total frequency band to obtain second logging acoustic wave impedance data.
As a preferred scheme, a nonlinear relation model of the seismic data and the first logging sound wave impedance data is established through a neural network algorithm.
Specifically, the neural network algorithm establishes a nonlinear relation model of the seismic data and the first logging acoustic impedance data based on a training sample of the neural network, and the establishment of the training sample of the neural network is the prior art and is not described herein again. The training sample of the neural network has a data input end and a data output end, the first logging sound wave impedance data is input at the data input end, the seismic data is input at the data output end, the training sample of the neural network obtains the input data and the output data to form a nonlinear relation between the input data and the output data, a nonlinear relation model between the seismic data and the first logging sound wave impedance data is established, and the nonlinear relation model between the seismic data and the first logging sound wave impedance data is stored. Applying this relationship to the entire logging band can achieve frequency-extending results. And inputting second logging acoustic impedance data at the data input end of a training sample of the neural network, and generating data which corresponds to the input data and is obtained through a nonlinear relation by using a stored nonlinear relation model of the seismic data and the first logging acoustic impedance data, namely the seismic data after frequency extension of the second logging acoustic impedance data at the data output end.
Examples
FIG. 1 shows a flow diagram of a log-based method for bi-directional frequency broadening of seismic data, according to an embodiment of the invention. FIG. 2 illustrates a synthetic record calibration chart for a log-based seismic data bi-directional frequency broadening method according to an embodiment of the present invention. FIG. 3 illustrates a seismic data profile of a log-based seismic data bi-directional frequency broadening method according to an embodiment of the present invention. FIG. 4 illustrates a graph of seismic data spectral information for a log-based seismic data bi-directional frequency broadening method, according to an embodiment of the present invention. FIG. 5 is a graph of spectral information of log acoustic impedance data for a log-based seismic data two-way frequency extension method according to an embodiment of the invention. FIG. 6 illustrates a cross-sectional view of bi-directional frequency-extended seismic data for a log-based bi-directional frequency-extension method of seismic data, in accordance with an embodiment of the present invention.
As shown in fig. 1, a method for bi-directional frequency broadening of seismic data based on a log includes:
s102: acquiring a synthetic record calibration result of logging acoustic impedance data and seismic data;
specifically, the synthetic log calibration is carried out, and the compression logging curve can be properly stretched to obtain a synthetic log calibration result with higher correlation. The high calibration correlation degree of the synthetic record represents the similarity degree of the logging data and the seismic data in the same frequency band, and the higher the similarity degree is, the higher the precision of bidirectional frequency extension is. As shown in FIG. 2, the correlation degree in the time range of 2.7-3.25s in the calibration chart of the synthetic record of the work area well reaches 85%, so the accuracy of the spread frequency range of the seismic data in the 2.7-3.25s is higher.
S104: comparing the synthetic record calibration result with a preset calibration value, and if the synthetic record calibration result is greater than or equal to the preset calibration value, respectively acquiring frequency spectrum information of the seismic data and frequency spectrum information of the logging acoustic impedance data;
performing Fourier transform on the seismic data to obtain frequency spectrum information of the seismic data;
specifically, as shown in fig. 3, the seismic data having a sampling interval of 1ms is subjected to fourier transform to obtain spectral information, and a spectral information map is shown in fig. 4.
Resampling the logging acoustic impedance data, and carrying out Fourier transform on the resampled logging acoustic impedance data to obtain frequency spectrum information of the logging acoustic impedance data;
specifically, the logging acoustic impedance data is resampled to make the sampling interval of the data be 1ms, which is the same as that of the seismic data, and then the resampled logging acoustic impedance data is subjected to fourier transform to obtain frequency spectrum information, and a frequency spectrum information chart is shown in fig. 5.
S106: respectively acquiring first logging sound wave impedance data and second logging sound wave impedance data based on frequency spectrum information of the seismic data and the logging sound wave impedance data;
the method for acquiring the first logging acoustic impedance data and the second logging acoustic impedance data based on the frequency spectrum information of the seismic data and the logging acoustic impedance data comprises the following steps: acquiring an effective frequency band of the seismic data based on the frequency spectrum information of the seismic data, and filtering the logging acoustic impedance data in the effective frequency band to obtain first logging acoustic impedance data; acquiring a total frequency band of the seismic data based on the frequency spectrum information of the seismic data, and filtering the logging acoustic impedance data in the total frequency band to obtain second logging acoustic impedance data;
specifically, the seismic data lack 0-8HZ low-frequency information and 52-80HZ high-frequency information through seismic data spectrum information, the main frequency band of the seismic data is concentrated in 8-52HZ, namely the effective frequency band is 8-52HZ, and the logging acoustic impedance data are filtered on the basis of the effective frequency band, so that first logging acoustic impedance data with the frequency band range of 8-52HZ are obtained. And the total frequency band of the seismic data is 0-80HZ according to the frequency spectrum information of the seismic data, namely the frequency band range of the finally bidirectional frequency broadening is 0-80HZ, and the frequency band range is the second logging acoustic impedance data of 0-80 HZ.
S108: establishing a nonlinear relation model of the seismic data and the first logging acoustic impedance data;
a nonlinear relation model of seismic data and first logging acoustic impedance data is established through a neural network algorithm.
S110: and acquiring the seismic data of the second logging acoustic impedance data after frequency extension based on the nonlinear relation model of the seismic data and the first logging acoustic impedance data and the second logging acoustic impedance data.
Specifically, the nonlinear relation model of the seismic data obtained by the neural network algorithm and the first logging acoustic impedance data is used for calculating and obtaining the seismic data with the frequency band range of 0-80HZ, namely the seismic data after bidirectional frequency extension, on the basis of the second logging acoustic impedance data with the frequency band range of 0-80HZ, and the section view of the seismic data after bidirectional frequency extension is shown in fig. 6.
Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.
Claims (10)
1. A seismic data bidirectional frequency broadening method based on a well log is characterized by comprising the following steps:
acquiring a synthetic record calibration result of logging acoustic impedance data and seismic data;
comparing the synthetic record calibration result with a preset calibration value, and if the synthetic record calibration result is greater than or equal to the preset calibration value, respectively acquiring frequency spectrum information of the seismic data and frequency spectrum information of the logging acoustic impedance data;
respectively acquiring first logging sound wave impedance data and second logging sound wave impedance data based on the frequency spectrum information of the seismic data and the logging sound wave impedance data;
establishing a nonlinear relation model of the seismic data and the first logging acoustic impedance data;
and acquiring the seismic data after the frequency extension of the second logging sound wave impedance data based on the nonlinear relation model of the seismic data and the first logging sound wave impedance data and the second logging sound wave impedance data.
2. The log-based seismic data bi-directional frequency broadening method as claimed in claim 1, wherein fourier transform is performed on the seismic data to obtain spectral information of the seismic data.
3. The log-based seismic data bi-directional frequency broadening method as claimed in claim 1, wherein the log acoustic impedance data is re-sampled, and the re-sampled log acoustic impedance data is fourier transformed to obtain the frequency spectrum information of the log acoustic impedance data.
4. The log-based seismic data bi-directional frequency broadening method as claimed in claim 1, wherein said obtaining first and second log acoustic impedance data based on the spectral information and the log acoustic impedance data of the seismic data comprises:
acquiring an effective frequency band of the seismic data based on the frequency spectrum information of the seismic data, and filtering the logging acoustic impedance data in the effective frequency band to acquire first logging acoustic impedance data;
and acquiring a total frequency band of the seismic data based on the frequency spectrum information of the seismic data, and filtering the logging acoustic wave impedance data in the total frequency band to acquire second logging acoustic wave impedance data.
5. The log-based seismic data bi-directional frequency broadening method as claimed in claim 1, wherein a non-linear relationship model of said seismic data and said first log acoustic impedance data is established through a neural network algorithm.
6. A log-based seismic data bi-directional frequency broadening system, comprising:
a memory storing computer-executable instructions;
a processor executing computer executable instructions in the memory to perform the steps of:
acquiring a synthetic record calibration result of logging acoustic impedance data and seismic data;
comparing the synthetic record calibration result with a preset calibration value, and if the synthetic record calibration result is greater than or equal to the preset calibration value, respectively acquiring frequency spectrum information of the seismic data and frequency spectrum information of the logging acoustic impedance data;
respectively acquiring first logging sound wave impedance data and second logging sound wave impedance data based on the frequency spectrum information of the seismic data and the logging sound wave impedance data;
establishing a nonlinear relation model of the seismic data and the first logging acoustic impedance data;
and acquiring the seismic data after the frequency extension of the second logging sound wave impedance data based on the nonlinear relation model of the seismic data and the first logging sound wave impedance data and the second logging sound wave impedance data.
7. The log-based seismic data bi-directional frequency broadening system of claim 6, wherein Fourier transforming said seismic data obtains spectral information of said seismic data.
8. The log-based seismic data bi-directional frequency broadening system of claim 6, wherein the log acoustic impedance data is re-sampled and a fourier transform of the re-sampled log acoustic impedance data is performed to obtain spectral information of the log acoustic impedance data.
9. The log-based seismic data bi-directional frequency broadening system of claim 6, wherein said obtaining first and second log acoustic impedance data based on spectral information and log acoustic impedance data of said seismic data comprises:
acquiring an effective frequency band of the seismic data based on the frequency spectrum information of the seismic data, and filtering the logging acoustic impedance data in the effective frequency band to acquire first logging acoustic impedance data;
and acquiring a total frequency band of the seismic data based on the frequency spectrum information of the seismic data, and filtering the logging acoustic wave impedance data in the total frequency band to acquire second logging acoustic wave impedance data.
10. The log-based seismic data bi-directional frequency broadening system of claim 6, wherein a non-linear relationship model of said seismic data and said first log acoustic impedance data is established via a neural network algorithm.
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