A natural gas reservoir detection method using amplitude-frequency modulation

Abstract

A method for detecting natural gas reservoirs using amplitude-frequency modulation is disclosed. The method comprises the following steps: acquiring seismic data; decomposing the seismic data using time-frequency analysis techniques to obtain a number of data subsets; performing wave impedance inversion on each of the data subsets using sparse pulse inversion techniques; calculating the mean square error function of the wave impedance for each frequency band; and performing amplitude-frequency modulation on the seismic data using the mean square error function. The present application provides a method for detecting natural gas reservoirs using amplitude-frequency modulation. This method uses a multi-scale inversion method based on time-frequency analysis to extract an indicator factor related to frequency dispersion. This factor is used to automatically modulate reflection intensity, thereby weakening the influence of other factors on reflection intensity, highlighting seismic reflection characteristics related to gas content, and enhancing the accuracy of geophysical detection of gas-bearing reservoirs.

Description

Technical Field

[0001] The invention belongs to the technical field of oil reservoir geophysical exploration and development, and in particular relates to a natural gas reservoir detection method using amplitude-frequency modulation. Background Art

[0002] Gas reservoir prediction is a classic research topic in geophysics. From early techniques such as bright spot and flat spot analysis to later techniques such as AVO analysis, elastic impedance inversion, full-wavefield elastic parameter inversion, and more recently, shale gas geophysical sweet spot analysis, geophysical methods have played a vital role in gas reservoir detection. Once gas is present in a formation, its velocity, density, and wave impedance decrease rapidly, increasing the wave impedance difference between the gas reservoir and the surrounding rock, and boosting the reflection intensity of the gas reservoir. Therefore, reflection intensity has become a key parameter in gas reservoir prediction and forms the theoretical basis for conventional gas reservoir prediction.

[0003] However, factors that alter formation reflection intensity include not only gas content but also local changes in sedimentary structure and formation physical properties, which can cause abnormal changes in reflection intensity. For example, there is often a large difference in wave impedance between coal seams and surrounding rocks, and their reflection intensity often exhibits characteristics similar to gas content.

[0004] Modern rock physics models and experimental analysis indicate that gas content not only reduces the propagation velocity of seismic waves but also causes them to exhibit significant dispersion characteristics within gas-bearing reservoirs. This means that the propagation velocity of seismic waves within gas-bearing reservoirs is related to frequency, with the velocity being a function of frequency, and the higher the frequency, the greater the velocity. Since wave impedance is equal to the product of seismic velocity and density, the dispersion of velocity also leads to the dispersion of wave impedance. Therefore, the dispersion of wave impedance can serve as an important indicator of gas-bearing reservoirs, but currently, corresponding detection methods are lacking. Summary of the Invention

[0005] In view of the above problems, the present invention provides an amplitude-frequency modulation natural gas reservoir detection method that overcomes the above problems or at least partially solves the above problems.

[0006] To solve the above technical problems, the present invention provides a natural gas reservoir detection method using amplitude-frequency modulation, the method comprising the following steps:

[0007] Acquisition of seismic data;

[0008] Decomposing the seismic data using a time-frequency analysis technique to obtain a plurality of data subsets;

[0009] Performing impedance inversion on each of the data subsets using a sparse pulse inversion technique;

[0010] Calculating the mean square error function of the wave impedance in each frequency band;

[0011] The seismic data is amplitude-frequency modulated using the mean square error function.

[0012] Preferably, the step of decomposing the seismic data using a time-frequency analysis technique to obtain a plurality of data subsets comprises the following steps:

[0013] acquiring the seismic data;

[0014] Calculating a spatial structure projection operator of the seismic data based on the seismic data;

[0015] The seismic data is decomposed into several data subsets with different frequency bands by using wavelet transform time-frequency analysis method.

[0016] Preferably, the performing wave impedance inversion on each of the data subsets using the sparse pulse inversion technique comprises the steps of:

[0017] Obtain seismic wavelets in each frequency band;

[0018] Constructing a corresponding wavelet matrix according to the seismic wavelet;

[0019] Obtain a transformation matrix that converts wave impedance into reflection coefficient;

[0020] Obtain the wave impedance inversion objective function;

[0021] obtaining a spatial structure projection operator of the seismic data;

[0022] The wave impedance of each frequency band is calculated according to the wavelet matrix, the conversion matrix, the wave impedance inversion objective function and the spatial structure projection operator.

[0023] Preferably, the expression of the wave impedance inversion objective function is:

[0024]

[0025] Among them, J(A i ) represents the objective function of the wave impedance inversion, W i represents the wavelet matrix composed of the seismic wavelet of the i-th frequency band, L represents the conversion matrix that converts wave impedance into reflection coefficient, A i Denotes the wave impedance, D i represents the data subset of the i-th frequency band, and P represents the spatial structure projection operator.

[0026] Preferably, the wave impedance is expressed as:

[0027] A i =(L T W i T Wi L+λP T P) -1 L T W i T D i ,

[0028] Among them, W i represents the wavelet matrix composed of the seismic wavelet of the i-th frequency band, L represents the conversion matrix that converts wave impedance into reflection coefficient, A i Denotes the wave impedance, D i represents the data subset of the i-th frequency band, P represents the spatial structure projection operator, and T represents the conjugate transpose.

[0029] Preferably, the calculating the mean square error function of the wave impedance of each frequency band comprises the steps of:

[0030] Obtaining the wave impedance of each frequency band;

[0031] Obtaining a relative change in each of the wave impedances;

[0032] Calculate the mean square error vector of all the relative changes.

[0033] Preferably, the expression of the relative change is:

[0034]

[0035] in, Represents the relative change, A i represents the wave impedance, and n represents the number of the frequency bands.

[0036] Preferably, the expression of the mean square error vector is:

[0037]

[0038] Wherein, σ represents the mean square error vector, represents the relative change, n represents the number of frequency bands,

[0039] Preferably, the use of the mean square error function to perform amplitude frequency modulation on the seismic data comprises the steps of:

[0040] acquiring the seismic data;

[0041] Applying Hilbert transform to the seismic data and obtaining the instantaneous amplitude of the seismic data;

[0042] Obtaining the mean square error function;

[0043] Calculating the frequency-varying modulation amplitude of the seismic data according to the instantaneous amplitude and the mean square error function;

[0044] The profile of the frequency-varying modulation amplitude is output and displayed.

[0045] Preferably, the frequency-variable modulation amplitude is expressed as:

[0046] D f =(1+σ)D s ,

[0047] Among them, D f represents the frequency-varying modulation amplitude, D s represents the instantaneous amplitude, and σ represents the mean square error function.

[0048] One or more technical solutions in the embodiments of the present invention have at least the following technical effects or advantages: The present application provides an amplitude-frequency modulation natural gas reservoir detection method, which extracts an indicator factor related to dispersion based on a multi-scale inversion method of time-frequency analysis, and uses this factor to automatically modulate the reflection intensity, thereby weakening the influence of other factors on the reflection intensity, highlighting the seismic reflection characteristics related to gas content, and enhancing the geophysical detection accuracy of gas-bearing reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0050] Figure 1 This is a flow chart of a natural gas reservoir detection method using amplitude-frequency modulation provided by an embodiment of the present invention;

[0051] Figure 2 A cross-sectional diagram of seismic data in an embodiment of the present invention;

[0052] Figure 3 is a spatial structure projection operator graph in an embodiment of the present invention;

[0053] Figure 4a This is a cross-sectional diagram of seismic data of the first frequency band in an embodiment of the present invention;

[0054] Figure 4b This is a cross-sectional diagram of seismic data of the second frequency band in an embodiment of the present invention;

[0055] Figure 4c This is a cross-sectional diagram of seismic data of the third frequency band in an embodiment of the present invention;

[0056] Figure 5a is an inversion impedance profile of seismic data of the first frequency band in an embodiment of the present invention;

[0057] Figure 5b is an inversion impedance profile of seismic data of the second frequency band in an embodiment of the present invention;

[0058] Figure 5c is an inversion impedance profile of seismic data of the third frequency band in an embodiment of the present invention;

[0059] Figure 6a is an instantaneous amplitude profile of seismic data in an embodiment of the present invention;

[0060] Figure 6b This is an amplitude profile diagram after frequency-variable modulation in an embodiment of the present invention. DETAILED DESCRIPTION

[0061] The present invention will be described in detail below in conjunction with specific embodiments and examples, and the advantages and various effects of the present invention will be more clearly presented. It should be understood by those skilled in the art that these specific embodiments and examples are for illustrating the present invention, rather than for limiting the present invention.

[0062] Throughout this specification, unless otherwise specified, the terms used herein should be understood as having the same meaning as commonly used in the art. Therefore, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. In the event of any conflict, the present specification shall take precedence.

[0063] Unless otherwise specified, various raw materials, reagents, instruments and equipment used in the present invention can be purchased from the market or prepared by existing methods.

[0064] like Figure 1 In an embodiment of the present application, the present invention provides an amplitude frequency modulation natural gas reservoir detection method, the method comprising the steps of:

[0065] S1: Acquire seismic data.

[0066] In the embodiments of the present application, seismic data can be acquired using a seismic instrument. Seismic data can include various types, such as amplitude and intensity. Below, seismic data from a block in the G oilfield in eastern my country is used as an example to implement the amplitude-frequency modulation natural gas reservoir detection method provided by the present invention. For ease of description, the seismic data is denoted as D.

[0067] S2: Decompose the seismic data using time-frequency analysis technology to obtain several data subsets.

[0068] In the embodiment of the present application, step S2 uses a time-frequency analysis technique to decompose the seismic data and obtain several data subsets, including the following steps:

[0069] acquiring the seismic data;

[0070] Calculating a spatial structure projection operator of the seismic data based on the seismic data;

[0071] The seismic data is decomposed into several data subsets with different frequency bands by using wavelet transform time-frequency analysis method.

[0072] In the embodiment of the present application, the corresponding spatial structure projection operator P is first calculated based on the seismic data D. Then, the wavelet transform time-frequency analysis method is used to decompose the seismic data D into three data subsets with different frequency bands, namely: D1, D2 and D3. The main frequencies corresponding to the three data subsets D1, D2 and D3 are 15Hz, 25Hz and 35Hz respectively, and the bandwidth is 10Hz. Figure 4a The seismic data D1 of the first frequency band is shown as Figure 4b The seismic data D2 of the second frequency band is shown as Figure 4c Shown is the seismic data D3 of the third frequency band.

[0073] In the embodiments of this application, the dispersion effect in seismic data is typically manifested as a change in velocity with frequency. Since wave impedance is a function of velocity and density, and dispersion caused by gas in the formation also has a certain impact on wave impedance, wave impedance also exhibits dispersion characteristics. Therefore, time-frequency analysis techniques are used to decompose the seismic data to obtain several data subsets with different frequency bands. This allows observation of the impact of dispersion on wave impedance within different frequency bands. Frequency-decomposition of wave impedance is used to characterize the frequency-dependent variation of wave impedance and extract indicator factors related to dispersion.

[0074] In the embodiment of the present application, the spatial structure projection operator can be obtained by solving the following least squares problem:

[0075]

[0076] Where d is the original seismic data, n and m are the lengths of the seismic data in time and space, respectively. It is the position of the seismic signal in time, ranging from 1:n. Ix represents the position of the seismic trace, ranging from 1:m. H is the spatial structure projection operator, a and b are the lengths of the projection operator in the longitudinal and transverse directions, respectively. Jt is the longitudinal position of the projection operator, ranging from -a:a. Jx represents the transverse position of the projection operator, ranging from -b:b. λ is the weighting operator. This equation is a typical least squares problem. Simply differentiate the above equation and set it to zero. Then, through linear operations, the projection operator can be obtained.

[0077] S3: Performing wave impedance inversion on each of the data subsets using a sparse pulse inversion technique.

[0078] In the embodiment of the present application, step S3 of performing impedance inversion on each of the data subsets using the sparse pulse inversion technique includes the following steps:

[0079] Obtain seismic wavelets in each frequency band;

[0080] Constructing a corresponding wavelet matrix according to the seismic wavelet;

[0081] Obtain a transformation matrix that converts wave impedance into reflection coefficient;

[0082] Obtain the wave impedance inversion objective function;

[0083] obtaining a spatial structure projection operator of the seismic data;

[0084] The wave impedance of each frequency band is calculated according to the wavelet matrix, the conversion matrix, the wave impedance inversion objective function and the spatial structure projection operator.

[0085] In the embodiment of the present application, the seismic wavelets of the corresponding frequency bands can be obtained according to the data subsets D1, D2 and D3 of the three different frequency bands, and the wavelet matrix W composed of the seismic wavelets of the corresponding frequency bands can be constructed. i (i=1, 2, 3), and then sequentially obtain the conversion matrix L for converting wave impedance into reflection coefficient, obtain the wave impedance inversion objective function, and obtain the spatial structure projection operator P of the seismic data, and calculate the wave impedance of each frequency band according to the wavelet matrix, the conversion matrix, the wave impedance inversion objective function, and the spatial structure projection operator.

[0086] In the embodiment of the present application, the expression of the wave impedance inversion objective function in step S3 is:

[0087]

[0088] Among them, J(A i ) represents the objective function of the wave impedance inversion, W i represents the wavelet matrix composed of the seismic wavelet of the i-th frequency band, L represents the conversion matrix that converts wave impedance into reflection coefficient, A i Denotes the wave impedance, D i represents the data subset of the i-th frequency band, and P represents the spatial structure projection operator.

[0089] In the embodiment of the present application, the expression of the wave impedance can be obtained according to the expression of the wave impedance inversion objective function:

[0090] A i =(LT W i T W i L+λP T P) -1 L T W i T D i ,

[0091] Among them, W i represents the wavelet matrix composed of the seismic wavelet of the i-th frequency band, L represents the conversion matrix that converts wave impedance into reflection coefficient, A i Denotes the wave impedance, D i represents the data subset of the i-th frequency band, P represents the spatial structure projection operator, and T represents the conjugate transpose.

[0092] In the embodiments of this application, Figure 5a The wave impedance A1 inverted from the seismic data D1 in the first frequency band is shown as follows: Figure 5b The figure shows the wave impedance A2 inverted from the seismic data D2 in the second frequency band. Figure 5c Shown is the wave impedance A3 inverted from the seismic data D3 in the third frequency band.

[0093] In the embodiment of the present application, sparse pulse inversion technology is used to perform wave impedance inversion on each of the data subsets. The focus is on utilizing the property of sparse pulse inversion technology to obtain more accurate high-resolution wave impedance profiles. Sparse pulse inversion technology can greatly improve the resolution of seismic data and provide a good data foundation for subsequent work.

[0094] In the embodiment of the present application, the corresponding wavelet matrix is ​​constructed according to the seismic wavelet using the following formula:

[0095]

[0096] In the embodiment of the present application, the conversion matrix for converting wave impedance into reflection coefficient is as follows:

[0097]

[0098] S4: Calculate the mean square error function of the wave impedance in each frequency band.

[0099] In the embodiment of the present application, calculating the mean square error function of the wave impedance of each frequency band in step S4 includes the following steps:

[0100] Obtaining the wave impedance of each frequency band;

[0101] Obtaining a relative change in each of the wave impedances;

[0102] Calculate the mean square error vector of all the relative changes.

[0103] In the embodiment of the present application, the wave impedances of the three frequency bands are first obtained, and the relative changes corresponding to the wave impedances of the three frequency bands are calculated, and then the mean square error vector of all the relative changes is calculated.

[0104] Specifically, calculating the mean square error (MSE) function of the wave impedance for each frequency band offers the following advantages: The mean square error, generally referred to as standard deviation, is a measure of the deviation of each data point from the mean, reflecting the degree of dispersion within a data set. By calculating the mean square error function of the wave impedance across different frequency bands, we can determine the differences in the dispersion effect of the wave impedance across different frequency bands. The dispersion effect of the wave impedance varies in strength across different frequency bands, potentially due to sudden changes in the formation or gas-bearing reservoirs. This difference, as a frequency-dependent attribute factor, is superimposed on the reflection amplitude, modulating the reflection amplitude to emphasize the strong attenuation caused by gas-bearing properties and mitigate the amplitude differences caused by non-gas-bearing properties.

[0105] In the embodiment of the present application, the expression of the relative change in step S4 is:

[0106]

[0107] in, Represents the relative change, A i represents the wave impedance, and n represents the number of the frequency bands.

[0108] Preferably, the expression of the mean square error vector is:

[0109]

[0110] Wherein, σ represents the mean square error vector, represents the relative change, n represents the number of frequency bands,

[0111] In the embodiment of the present application, the mean square error vector σ of the three data subsets D1, D2 and D3 is calculated according to the above steps:

[0112] S5: Performing amplitude-frequency modulation on the seismic data using the mean square error function.

[0113] In the embodiment of the present application, step S5 of performing amplitude-frequency modulation on the seismic data using the mean square error function includes the following steps:

[0114] acquiring the seismic data;

[0115] Applying Hilbert transform to the seismic data and obtaining the instantaneous amplitude of the seismic data;

[0116] Obtaining the mean square error function;

[0117] Calculating the frequency-varying modulation amplitude of the seismic data according to the instantaneous amplitude and the mean square error function;

[0118] The profile of the frequency-varying modulation amplitude is output and displayed.

[0119] In the embodiments of this application, Figure 6a is an instantaneous amplitude profile of seismic data D in an embodiment of the present invention, Figure 6b This is an amplitude profile diagram of seismic data D after frequency modulation in an embodiment of the present invention.

[0120] Specifically, the benefits of using the mean square error function to perform amplitude frequency modulation on the seismic data are as follows: first, the mean square error function of the wave impedance in different frequency bands is calculated. The strong attenuation caused by gas content in the formation will appear as a large variance value, which is used as a frequency-variant attribute indicator factor to modulate the reflection amplitude, thereby strengthening the amplitude anomaly caused by gas content and weakening the abnormal amplitude change caused by non-gas content. The same amplitude change caused by gas content and formation physical properties, which cannot be distinguished by the amplitude attribute used alone by conventional AVO technology, will be distinguished, highlighting the seismic reflection characteristics related to gas content and enhancing the characterization capability of seismic signals for gas-bearing reservoirs.

[0121] In the embodiment of the present application, the expression of the frequency-variable modulation amplitude is:

[0122] D f =(1+σ)D s ,

[0123] Among them, D f represents the frequency-varying modulation amplitude, D s represents the instantaneous amplitude, and σ represents the mean square error function.

[0124] Furthermore, by comparing and analyzing the instantaneous amplitude D of seismic data s Section (such as Figure 6a as shown) and the frequency-variable modulation amplitude D f Section (such as Figure 6b As shown in the figure), we can draw the following conclusions: the amplitude D of the frequency-variable modulation f Automatically modulate the reflection intensity to weaken the influence of other factors on the reflection intensity, highlight the seismic reflection characteristics related to gas content, and enhance the geophysical detection accuracy of gas reservoirs.

[0125] The present application provides an amplitude-frequency modulation natural gas reservoir detection method, which extracts an indicator factor related to dispersion based on a multi-scale inversion method of time-frequency analysis, and uses this factor to automatically modulate the reflection intensity, thereby weakening the influence of other factors on the reflection intensity, highlighting the seismic reflection characteristics related to gas content, and enhancing the geophysical detection accuracy of gas-bearing reservoirs.

[0126] It should be noted that, in this document, relational terms such as "first" and "second" are used solely to distinguish one entity or operation from another, and do not necessarily require or imply any actual relationship or order between these entities or operations. Furthermore, the terms "comprise," "include," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or device comprising a set of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. Without further limitation, an element defined by the phrase "comprising a..." does not preclude the presence of other identical elements in the process, method, article, or device comprising the recited element. The foregoing description is intended only to provide specific embodiments of the present application, intended to enable those skilled in the art to understand or implement the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to be accorded the broadest scope consistent with the principles and novel features of the present application.

[0127] In short, the above description is only a preferred embodiment of the technical solution of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention.

Claims

1. A natural gas reservoir detection method using amplitude-frequency modulation, characterized in that: The method comprises the steps of: Acquisition of seismic data; Decomposing the seismic data using a time-frequency analysis technique to obtain a plurality of data subsets; Performing impedance inversion on each of the data subsets using a sparse pulse inversion technique; Calculating the mean square error function of the wave impedance in each frequency band; Performing amplitude frequency modulation on the seismic data using the mean square error function; The step of performing impedance inversion on each of the data subsets using the sparse pulse inversion technique comprises the following steps: Obtain seismic wavelets in each frequency band; Constructing a corresponding wavelet matrix according to the seismic wavelet; Obtain a transformation matrix that converts wave impedance into reflection coefficient; Obtain the wave impedance inversion objective function; obtaining a spatial structure projection operator of the seismic data; Calculating the wave impedance of each frequency band according to the wavelet matrix, the conversion matrix, the wave impedance inversion objective function and the spatial structure projection operator; The expression of the wave impedance inversion objective function is: Among them, J(A i ) represents the objective function of the wave impedance inversion, W i represents the wavelet matrix composed of the seismic wavelet of the i-th frequency band, L represents the conversion matrix that converts wave impedance into reflection coefficient, A i Denotes the wave impedance, D i represents the data subset of the i-th frequency band, P represents the spatial structure projection operator, and λ represents the weight operator.

2. The method for detecting natural gas reservoirs by amplitude frequency modulation according to claim 1, characterized in that: Decomposing the seismic data using a time-frequency analysis technique to obtain a plurality of data subsets comprises the following steps: acquiring the seismic data; Calculating a spatial structure projection operator of the seismic data based on the seismic data; The seismic data is decomposed into several data subsets with different frequency bands by using wavelet transform time-frequency analysis method.

3. The method for detecting natural gas reservoirs by amplitude-frequency modulation according to claim 1, characterized in that: The expression of the wave impedance is: A i =(L T W i T W i L+λP T P) -1 L T W i T D i , Among them, W i represents the wavelet matrix composed of the seismic wavelet of the i-th frequency band, L represents the conversion matrix that converts wave impedance into reflection coefficient, A i Denotes the wave impedance, D i represents the data subset of the i-th frequency band, P represents the spatial structure projection operator, and T represents the conjugate transpose.

4. The method for detecting natural gas reservoirs by amplitude frequency modulation according to claim 1, characterized in that: The calculation of the mean square error function of the wave impedance of each frequency band comprises the steps of: Obtaining the wave impedance of each frequency band; Obtaining a relative change in each of the wave impedances; Calculate the mean square error vector of all the relative changes.

5. The method for detecting natural gas reservoirs by amplitude frequency modulation according to claim 4, characterized in that: The expression of the relative change is: in, Represents the relative change, A i represents the wave impedance, and n represents the number of the frequency bands.

6. The method for detecting natural gas reservoirs by amplitude frequency modulation according to claim 4, characterized in that: The expression of the mean square error vector is: Wherein, σ represents the mean square error vector, represents the relative change, n represents the number of frequency bands, 7. The amplitude frequency modulation natural gas reservoir detection method according to claim 1, characterized in that: The use of the mean square error function to perform amplitude frequency modulation on the seismic data comprises the steps of: acquiring the seismic data; Applying Hilbert transform to the seismic data and obtaining the instantaneous amplitude of the seismic data; Obtaining the mean square error function; Calculating the frequency-varying modulation amplitude of the seismic data according to the instantaneous amplitude and the mean square error function; The profile of the frequency-varying modulation amplitude is output and displayed.

8. The method for detecting natural gas reservoirs by amplitude-frequency modulation according to claim 7, characterized in that: The expression of the frequency-variable modulation amplitude is: D f =(1+σ)D s , Among them, D f represents the frequency-varying modulation amplitude, D s represents the instantaneous amplitude, and σ represents the mean square error function.

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