Full-node data spectrum bluing frequency expanding method

Abstract

The invention provides a full-node data spectrum bluing frequency expanding method. The frequency expanding method comprises the following steps: S1, acquiring a full-node data pre-stack gather needing frequency expanding; s2, calculating a logging reflection coefficient frequency spectrum; s3, synthesizing a forward model gather; s4, carrying out frequency expansion processing by adopting a pre-stack spectral bluing method; and S5, outputting a pre-stack gather after blue frequency expansion of the full-node data spectrum. In an earthquake effective frequency band of full-node data, logging reflection coefficient spectrum bluing trend constraint is utilized, a frequency spectrum trend is calculated through a synthetic forward model, existing data frequency spectrum characteristics are optimized, earthquake vertical resolution is improved, false frequency is avoided, and meanwhile low-frequency information is protected; the processing result has a blue spectrum trend, so that the reflection coefficients of the seismic data and the logging data are the same and also have the blue spectrum trend.

Description

Technical Field

[0001] The present invention relates to the field of geophysical processing technology, and in particular to a method for blueing and expanding the spectrum of full-node data. Background Art

[0002] Full-node seismic is a new seismic technology. It is based on node self-collection and self-storage. Compared with traditional cable collection, it has incomparable technical advantages in arrangement and layout, belt channel capacity, construction efficiency, environmental adaptability, and achieving higher channel density. The new collection mode and data recording characteristics have brought a series of new challenges and changes to data processing. Conventional frequency extension methods can no longer meet the needs of fine processing of full-node seismic data.

[0003] Seismic frequency extension processing has always been a hot spot and difficulty in petroleum seismic data processing. There are two types of seismic frequency extension. The first is time domain frequency extension, which mainly includes anti-Q filtering, deconvolution, etc. The second is frequency domain frequency extension, which mainly includes spectrum blueing, spectrum whitening, spectrum inversion, etc. It is difficult to obtain a completely whitened spectrum in actual data processing; spectrum blueing frequency extension has been well applied. However, the current spectrum blueing frequency extension method does not consider the spectrum constraints of the well data in the full-node data work area, and the frequency extension effect is not obvious. At the same time, it is necessary to make better use of the rich logging data and geological data to carry out well-constrained amplitude-preserving spectrum blueing frequency extension processing to meet the subsequent fine reservoir prediction needs. Summary of the invention

[0004] In view of the above problems, the present invention is proposed to provide a method for blueing and expanding the data spectrum of a full node, which overcomes the above problems or at least partially solves the above problems.

[0005] According to one aspect of the present invention, a method for blue-banding a full-node data spectrum is provided, and the method comprises:

[0006] Step S1: Obtain pre-stack gathers of all-node data that need to be extended;

[0007] Step S2: Calculate the logging reflection coefficient spectrum;

[0008] Step S3: synthesizing forward model gathers;

[0009] Step S4: using the pre-stack spectrum blueing method to perform spectrum spreading processing;

[0010] Step S5: Output the pre-stack gathers after blueing and frequency spreading of the full-node data spectrum.

[0011] Optionally, the step S1: obtaining pre-stack gathers of full-node data requiring frequency spreading specifically includes:

[0012] Input the pre-stack gather data of the common imaging point in the time domain or depth domain of the full-node data that needs to be frequency-extended.

[0013] Optionally, the step S2: calculating the logging reflection coefficient spectrum specifically includes:

[0014] Convert the logging sound wave and density curve into the time domain, calculate the wave impedance and reflection coefficient, and then calculate the reflection coefficient spectrum;

[0015] Calculating a reflection coefficient spectrum trend according to the reflection coefficient spectrum;

[0016] The reflection coefficient spectrum shows a blue spectrum trend, with a stronger amplitude at the high-frequency end and a lower amplitude at the low-frequency end, which is a blue spectrum.

[0017] Optionally, the step S3: synthesizing the forward model gathers specifically includes:

[0018] The pre-stack AVO forward model gathers are used as constraint input, but VSP also has seismic wavelets, which can only be used as an intermediate processing constraint;

[0019] The objective function is the logging reflection coefficient, and the final goal is the convolution of the zero-phase broadband wavelet with the reflection coefficient.

[0020] Optionally, the step S3: synthesizing the forward model gathers further comprises:

[0021] The reflection coefficient is calculated according to the Zoeppritz equation and convolved with the seismic wavelet to obtain the pre-stack gathers of the synthetic forward model.

[0022] Optionally, the step S3: synthesizing the forward model gathers further comprises:

[0023] The spectrum trend is calculated from the forward model gathers. The spectrum of the forward model also shows a blue spectrum trend like the logging reflection coefficient.

[0024] Optionally, the step S4: using the pre-stack spectrum blueing method to perform spectrum spreading processing specifically includes:

[0025] The convolution model is expressed in the frequency domain as

[0026] A s (f) = A r (f)×A w (f) (1)

[0027] Among them, As(f) is the amplitude spectrum of the seismic gather, Ar(f) is the amplitude spectrum of the reflection coefficient, and Aw(f) is the amplitude spectrum of the seismic wavelet.

[0028] Optionally, in step S4, the reflection coefficient is divided into colored and white noise reflection coefficients, then formula (1) becomes

[0029] A s (f) = A rw (f)×A rb(f)×A w (f) (2)

[0030]

[0031] Among them, A rw (f) represents the white noise reflection coefficient, A rb (f) represents the colored reflectance.

[0032] Optionally, the formula (3) in step S4 is fitted using a first-order model of an autoregressive moving average model to perform color compensation processing on the reflection coefficient, and the formula is:

[0033]

[0034] Among them, F(i) represents the Z transform of the colored reflectance coefficient, and the parameters α and β respectively represent the key parameters of AR (autoregressive model) and MA (moving average model) that describe the characteristics of non-white noise, |α|<1, |β|<1.

[0035] Optionally, in step S4, it is assumed that the amplitude spectrum of the reflection coefficient is represented by R(iΔf), and the minimum value is obtained using the least squares algorithm. Formula (5) is:

[0036]

[0037] Optionally, in step S4, the blue spectrum feature fitted by formula (5) is used to calculate a blue filter operator to implement spectrum bluening and frequency extension processing;

[0038] The spectrum bluening and frequency extension processing uses the forward model to optimize the spectrum characteristics of existing data within the seismic effective frequency band. The processing result has a blue spectrum trend, making the reflection coefficient of seismic data and logging data also show a blue spectrum trend.

[0039] Optionally, the step S5: outputting the pre-stack gathers after spectral blueing and spectrum extension of all-node data specifically includes: outputting the pre-stack gather data of common imaging points in the time domain or depth domain of all-node data after spectral blueing and spectrum extension.

[0040] The present invention provides a method for blueing and spreading spectrum of full-node data, and the spreading method comprises: step S1: obtaining pre-stack gathers of full-node data that need to be spread; step S2: calculating the spectrum of logging reflection coefficient; step S3: synthesizing forward model gathers; step S4: spreading processing by pre-stack spectrum blueing method; step S5: outputting pre-stack gathers after blueing and spreading spectrum of full-node data. Within the seismic effective frequency band of full-node data, the blueing trend constraint of logging reflection coefficient spectrum is used, and the spectrum trend of the synthesized forward model is calculated to optimize the spectrum characteristics of existing data, improve the seismic vertical resolution, avoid the generation of false frequency, and protect low-frequency information at the same time; the processing result has a blue spectrum trend, so that the reflection coefficient of seismic data and logging data also presents a blue spectrum trend.

[0041] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0043] Figure 1 A flowchart of a method for blue-banding a full-node data spectrum provided by an embodiment of the present invention;

[0044] Figure 2 The pre-stack gather of the full-node data that needs to be frequency-spread in the embodiment of the present invention;

[0045] Figure 3 The pre-stack gather application effect of the full-node data spectrum blueing extension method in the embodiment of the present invention;

[0046] Figure 4 The pre-stack gathers of the synthetic forward model in the embodiment of the present invention;

[0047] Figure 5 The pre-stack angle gathers for which all-node data need to be extended in the embodiment of the present invention;

[0048] Figure 6 This is the application effect of the pre-stack angle gather after the blueing and frequency expansion of the full-node data spectrum in an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0050] The terms "comprises" and "having" and any variations thereof in the description embodiments, claims and drawings of the present invention are intended to cover non-exclusive inclusions, for example, including a series of steps or units.

[0051] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0052] like Figure 1 As shown, a method for blueing and expanding the spectrum of a full-node data spectrum includes:

[0053] Step S1: pre-stack gathers of all-node data that need to be extended;

[0054] Step S2: Calculate the logging reflection coefficient spectrum;

[0055] Step S3: synthesizing forward model gathers;

[0056] Step S4: using the pre-stack spectrum blueing method to perform spectrum spreading processing;

[0057] Step S5: Output the pre-stack gathers after blueing and frequency spreading of the full-node data spectrum.

[0058] In step S1: input the common imaging point pre-stack gather data in the time domain or depth domain of the full-node data that needs to be frequency-spread.

[0059] In step S2: the logging acoustic wave and density curve are converted into the time domain, and the wave impedance and reflection coefficient are calculated, and then the reflection coefficient spectrum is calculated; the reflection coefficient spectrum trend is calculated from the reflection coefficient spectrum. The reflection coefficient spectrum shows a "blue spectrum" trend, that is, the high frequency end has a strong amplitude and the low frequency end has a low amplitude, which is a blue spectrum.

[0060] In step S3: Traditional well constraint processing generally uses VSP data as constraint input. This method uses pre-stack AVO forward model gathers as constraint input, but VSP also has seismic wavelets, which can only be used as an intermediate processing constraint condition and cannot be used as the final objective function of seismic processing. Seismic data ultimately solves geological problems, so the final objective function should be the well logging reflection coefficient, but since seismic data has limited bandwidth, the final goal should be the convolution of the zero-phase broadband wavelet with the reflection coefficient.

[0061] In step S3: the reflection coefficient is calculated according to the Zoeppritz equation and then convolved with the seismic wavelet to obtain the pre-stack gathers of the synthetic forward model.

[0062] In step S3: the spectrum trend can be calculated from the forward model gathers. The spectrum of the forward model also shows a blue spectrum trend like the logging reflection coefficient.

[0063] In step S4: the convolution model is expressed in the frequency domain as

[0064] A s (f) = A r (f)×A w (f) (1)

[0065] Among them, As(f) is the amplitude spectrum of the seismic gather, Ar(f) is the amplitude spectrum of the reflection coefficient, and Aw(f) is the amplitude spectrum of the seismic wavelet.

[0066] In step S4: the reflection coefficient is divided into colored and white noise reflection coefficients, then formula (1) becomes

[0067] A s (f) = A rw (f)×A rb (f)×A w (f) (2)

[0068]

[0069] Among them, A rw (f) represents the white noise reflection coefficient, A rb (f) represents the colored reflectance.

[0070] In step S4: Formula (3) is fitted using the first-order model of the autoregressive moving average model, and the reflection coefficient is subjected to color compensation processing. The formula is:

[0071]

[0072] Among them, F(i) represents the Z transform of the colored reflectance coefficient, and the parameters α and β respectively represent the key parameters of AR (autoregressive model) and MA (moving average model) that describe the characteristics of non-white noise, |α|<1, |β|<1.

[0073] In step S4: Assuming that the amplitude spectrum of the reflection coefficient is represented by R(iΔf), the least squares algorithm is used to find the minimum value, and formula (5) is:

[0074]

[0075] In step S4: the blue spectrum characteristics fitted by formula (5) are used to calculate the blue filter operator to implement spectrum blueing and spectrum extension processing. The spectrum blueing and spectrum extension processing uses the forward model to optimize the spectrum characteristics of the existing data within the seismic effective frequency band, improve the seismic vertical resolution, avoid the generation of false frequencies, and protect the low-frequency information. The processing result has a blue spectrum trend, so that the reflection coefficients of the seismic data and the logging data also show a blue spectrum trend.

[0076] In step S5: output the pre-stack gather data of the common imaging point in the time domain or depth domain of the full-node data after spectrum blueing and frequency expansion.

[0077] Specific embodiment 1: Figure 2 It is the pre-stack gather of the full-node data that needs to be extended; Figure 3 This is the application effect of the pre-stack gather of the full-node data spectrum blueing extension method of the present invention; Figure 4 is the pre-stack gather of the synthetic forward model. Figure 3 It can be seen that the full-node data spectrum blueing extension method uses the logging reflection coefficient spectrum constraint within the seismic effective frequency band and calculates the spectrum trend through the synthetic forward model to optimize the existing data spectrum characteristics, improve the seismic vertical resolution, avoid the generation of false frequencies, and protect the low-frequency information.

[0078] Specific embodiment 2: Figure 5 It is the pre-stack angle gather that needs to be extended for all node data; Figure 6 This is the application effect of the pre-stack angle gather after the blueing and frequency expansion of the full-node data spectrum of the present invention. Figure 6 It can be seen that the blueing and frequency extension of the full-node data spectrum improves the resolution of thin layers, achieves the purpose of amplitude-preserving spectrum blueing and frequency extension, and is more conducive to the subsequent pre-stack AVO inversion.

[0079] Beneficial effect: The present invention provides a method for blueing and frequency extension of full-node data spectrum. The method utilizes the blueing trend constraint of logging reflection coefficient spectrum within the seismic effective frequency band of full-node data, calculates the spectrum trend through a synthetic forward model, optimizes the spectrum characteristics of existing data, improves the seismic vertical resolution, avoids the generation of false frequencies, and protects low-frequency information at the same time; the processing result has a blue spectrum trend, so that the reflection coefficient of the seismic data and the logging data also presents a blue spectrum trend.

[0080] The present invention provides a spectrum blueing extension method for full-node data logging spectrum constraints. Within the seismic effective frequency band of the full-node data, the blueing trend constraint of the logging reflection coefficient spectrum is utilized, and the spectrum trend is calculated by a synthetic forward model to optimize the spectrum characteristics of the existing data, improve the seismic vertical resolution, avoid the generation of false frequencies, and protect the low-frequency information at the same time.

[0081] The processing result of the present invention has a blue spectrum trend, so that the reflection coefficients of seismic data and well logging data also show a blue spectrum trend.

[0082] The above specific implementation methods further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific implementation methods of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for blue-banding the full-node data spectrum. It is characterized in that The spectrum spreading method comprises: Step S1: Obtain pre-stack gathers of all-node data that need to be extended; Step S2: Calculate the logging reflection coefficient spectrum; Step S3: synthesizing forward model gathers; Step S4: using the pre-stack spectrum blueing method to perform spectrum spreading processing; Step S5: Output the pre-stack gathers after blueing and frequency spreading of the full-node data spectrum.

2. According to claim 1, a method for blue-banding of a full-node data spectrum, It is characterized in that The step S1: obtaining the pre-stack gathers of the full-node data that needs to be frequency-spread specifically includes: Input the pre-stack gather data of the common imaging point in the time domain or depth domain of the full-node data that needs to be frequency-extended.

3. According to the method for blue-banding of the full-node data spectrum of claim 1, It is characterized in that The step S2: calculating the logging reflection coefficient spectrum specifically includes: Convert the logging sound wave and density curve into the time domain, calculate the wave impedance and reflection coefficient, and then calculate the reflection coefficient spectrum; Calculating a reflection coefficient spectrum trend according to the reflection coefficient spectrum; The reflection coefficient spectrum shows a blue spectrum trend, with a stronger amplitude at the high-frequency end and a lower amplitude at the low-frequency end, which is a blue spectrum.

4. According to claim 1, a method for blue-banding of a full-node data spectrum, It is characterized in that The step S3: synthesizing the forward model gathers specifically comprises: The pre-stack AVO forward model gathers are used as constraint input, but VSP also has seismic wavelets, which can only be used as an intermediate processing constraint; The objective function is the logging reflection coefficient, and the final goal is the convolution of the zero-phase broadband wavelet with the reflection coefficient.

5. According to claim 1, a method for blue-banding of a full-node data spectrum, It is characterized in that The step S3: synthesizing the forward model gathers further comprises: The reflection coefficient is calculated according to the Zoeppritz equation and convolved with the seismic wavelet to obtain the pre-stack gathers of the synthetic forward model.

6. A method for blue-banding a full-node data spectrum according to claim 1, It is characterized in that The step S3: synthesizing the forward model gathers further comprises: The spectrum trend is calculated from the forward model gathers. The spectrum of the forward model also shows a blue spectrum trend like the logging reflection coefficient.

7. According to claim 1, a method for blue-banding of a full-node data spectrum, It is characterized in that The step S4: using the pre-stack spectrum blueing method to perform spectrum spreading processing specifically includes: The convolution model is expressed in the frequency domain as A s (f)=A r (f)×A w (f) (1) Among them, As(f) is the amplitude spectrum of the seismic gather, Ar(f) is the amplitude spectrum of the reflection coefficient, and Aw(f) is the amplitude spectrum of the seismic wavelet.

8. According to claim 1, a method for blue-banding of a full-node data spectrum, It is characterized in that In step S4, the reflection coefficient is divided into colored and white noise reflection coefficients, and formula (1) becomes A s (f)=A rw (f)×A rb (f)×A w (f) (2) Among them, A rw (f) represents the white noise reflection coefficient, A rb (f) represents the colored reflectance.

9. A method for blue-banding a full-node data spectrum according to claim 8, It is characterized in that Formula (3) in step S4 is fitted using a first-order model of an autoregressive moving average model to perform color compensation processing on the reflection coefficient, and its formula is: Among them, F(i) represents the Z transform of the colored reflectance coefficient, and the parameters α and β respectively represent the key parameters of AR (autoregressive model) and MA (moving average model) that describe the characteristics of non-white noise, |α|<1, |β|<1.

10. A method for blue-banding a full-node data spectrum according to claim 1, It is characterized in that In step S4, it is assumed that the amplitude spectrum of the reflection coefficient is represented by R(iΔf), and the minimum value is obtained using the least squares algorithm. Formula (5) is:

11. A method for blue-banding a full-node data spectrum according to claim 10, It is characterized in that In step S4, the blue spectrum characteristics fitted by formula (5) are used to calculate the blue filter operator to implement spectrum bluening and frequency extension processing; The spectrum bluening and frequency extension processing uses the forward model to optimize the spectrum characteristics of existing data within the seismic effective frequency band. The processing result has a blue spectrum trend, making the reflection coefficient of seismic data and logging data also show a blue spectrum trend.

12. A method for blue-banding a full-node data spectrum according to claim 1, It is characterized in that The step S5: outputting the pre-stack gathers after spectral blueing and frequency extension of all-node data specifically includes: outputting the pre-stack gather data of common imaging points in the time domain or depth domain of the full-node data after spectral blueing and frequency extension.

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