Multi-wave time-frequency domain joint attribute construction method and device, equipment and medium

Abstract

The invention discloses a multi-wave time-frequency domain joint attribute construction method and device, equipment and a medium. The method comprises the following steps: determining odd components and even components of a multi-wave seismic signal; respectively performing phase decomposition on the odd component and the even component to obtain a first phase component and a second phase component; determining a first frequency domain seismic significance attribute and a first time domain seismic significance attribute of the first phase component, and determining a second frequency domain seismic significance attribute and a second time domain seismic significance attribute of the second phase component; determining a first time-frequency domain joint attribute according to the first frequency domain seismic saliency attribute and the first time domain seismic saliency attribute, and determining a second time-frequency domain joint attribute according to the second frequency domain seismic saliency attribute and the second time domain seismic saliency attribute, and predicting oil and gas reservoir information based on the first time-frequency domain joint attribute and the second time-frequency domain joint attribute. According to the technical scheme, the reliability of the multi-wave seismic attribute is improved by constructing the multi-wave time-frequency domain joint attribute.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of seismic exploration, and in particular to a multi-wave time-frequency domain joint attribute construction method, device, equipment and medium. BACKGROUND

[0002] Multi-wave seismic data is an important data resource for seismic exploration and oil and gas resource evaluation, which not only contains a large amount of characteristic information sensitive to oil and gas, but also has differences in response to oil and gas. However, there are many uncertainties in the interpretation process of seismic data, which makes it difficult to accurately predict oil and gas reservoir information (such as location and distribution).

[0003] In related technologies, seismic attributes are extracted based on seismic data obtained by single longitudinal wave exploration, and the prediction of oil and gas reservoir information is realized based on the extracted seismic attributes. However, the above-mentioned seismic attribute extraction method is severely dependent on longitudinal wave seismic data, and the information provided by single longitudinal wave seismic data is not comprehensive, which makes it impossible to accurately identify oil and gas reservoir information. SUMMARY

[0004] The present application provides a multi-wave time-frequency domain joint attribute construction method, device, equipment and medium, which fully considers the relationship between multi-wave seismic signal difference and reservoir oil and gas, improves the reliability of multi-wave seismic attribute by constructing multi-wave time-frequency domain joint attribute, and enhances the accuracy of oil and gas detection.

[0005] According to one aspect of the present application, a multi-wave time-frequency domain joint attribute construction method is provided, the method comprising:

[0006] obtaining a multi-wave seismic signal, determining the odd component and the even component of the multi-wave seismic signal;

[0007] phase decomposing the odd component to obtain a first phase component, and phase decomposing the even component to obtain a second phase component;

[0008] determining a first frequency domain seismic significance attribute and a first time domain seismic significance attribute of the first phase component, and determining a second frequency domain seismic significance attribute and a second time domain seismic significance attribute of the second phase component;

[0009] determining a first time-frequency domain joint attribute according to the first frequency domain seismic significance attribute and the first time domain seismic significance attribute, and determining a second time-frequency domain joint attribute according to the second frequency domain seismic significance attribute and the second time domain seismic significance attribute, to realize the prediction of oil and gas reservoir information based on the first time-frequency domain joint attribute and the second time-frequency domain joint attribute.

[0010] According to another aspect of the present application, a multi-wave time-frequency domain joint attribute construction device is provided, the device comprising:

[0011] The signal parity decomposition module is used to acquire multi-wave seismic signals and determine the odd and even components of the multi-wave seismic signals.

[0012] A signal phase decomposition module is used to perform phase decomposition on the odd components to obtain a first phase component, and to perform phase decomposition on the even components to obtain a second phase component.

[0013] The seismic saliency attribute determination module is used to determine the first frequency domain seismic saliency attribute and the first time domain seismic saliency attribute of the first phase component, and to determine the second frequency domain seismic saliency attribute and the second time domain seismic saliency attribute of the second phase component.

[0014] The time-frequency domain joint attribute determination module is used to determine a first time-frequency domain joint attribute based on the first frequency domain seismic significance attribute and the first time domain seismic significance attribute, and to determine a second time-frequency domain joint attribute based on the second frequency domain seismic significance attribute and the second time domain seismic significance attribute, so as to realize the prediction of oil and gas reservoir information based on the first time-frequency domain joint attribute and the second time-frequency domain joint attribute.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] At least one processor; and

[0017] A memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the multi-wavelength time-frequency domain joint attribute construction method according to any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the multi-wave time-frequency domain joint attribute construction method according to any embodiment of the present invention.

[0020] The technical solution of this invention first acquires multi-wave seismic signals and determines their odd and even components. Then, it performs phase decomposition on the odd components to obtain a first phase component, and on the even components to obtain a second phase component. Next, it determines the first frequency-domain and first time-domain seismic saliency attributes of the first phase component, and the second frequency-domain and second time-domain seismic saliency attributes of the second phase component. Finally, it determines a first time-frequency domain joint attribute based on the first frequency-domain and first time-domain seismic saliency attributes, and a second time-frequency domain joint attribute based on the second frequency-domain and second time-domain seismic saliency attributes, thereby enabling the prediction of oil and gas reservoir information based on these attributes. This technical solution fully considers the relationship between the differences in multi-wave seismic signals and reservoir oil and gas, and improves the reliability of multi-wave seismic attributes and enhances the accuracy of oil and gas detection by constructing multi-wave time-frequency domain joint attributes.

[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used 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 those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart of a multi-wave time-frequency domain joint attribute construction method provided in Embodiment 1 of the present invention;

[0024] Figure 2 This is a flowchart of a multi-wave time-frequency domain joint attribute construction method provided in Embodiment 2 of the present invention;

[0025] Figure 3a This is a schematic diagram of a complex geological model provided according to Embodiment 2 of the present invention;

[0026] Figure 3b This is a schematic diagram of a P-wave seismic record provided in Embodiment 2 of the present invention;

[0027] Figure 3c This is a schematic diagram of a converted wave seismic record according to Embodiment 2 of the present invention;

[0028] Figure 3d This is a schematic diagram of a negative 90-degree P-wave seismic record provided in Embodiment 2 of the present invention;

[0029] Figure 3e This is a schematic diagram of a negative 90-degree converted wave seismic record provided in Embodiment 2 of the present invention;

[0030] Figure 3f This is a schematic diagram of the significant properties of P-wave time-domain seismic activity provided in Embodiment 2 of the present invention;

[0031] Figure 3g This is a schematic diagram of the significant properties of converted wave time-domain seismic data according to Embodiment 2 of the present invention;

[0032] Figure 3h This is a schematic diagram of a significant characteristic of P-wave frequency domain seismic activity provided in Embodiment 2 of the present invention;

[0033] Figure 3i This is a schematic diagram of a significant characteristic of a converted wave frequency domain seismic event according to Embodiment 2 of the present invention;

[0034] Figure 3j This is a schematic diagram of the multi-wave time-frequency domain superposition attribute provided in Embodiment 2 of the present invention;

[0035] Figure 3k This is a schematic diagram of a multi-wave time-frequency domain fusion attribute provided in Embodiment 2 of the present invention;

[0036] Figure 4 This is a schematic diagram of wellbore data phase decomposition according to Embodiment 2 of the present invention;

[0037] Figure 5a This is a schematic diagram of an actual P-wave seismic record provided in Embodiment 2 of the present invention;

[0038] Figure 5b This is a schematic diagram of an actual converted wave seismic record provided in Embodiment 2 of the present invention;

[0039] Figure 5c This is a schematic diagram of an actual P-wave seismic record at -90 degrees according to Embodiment 2 of the present invention;

[0040] Figure 5d This is a schematic diagram of an actual converted wave seismic record at -90 degrees according to Embodiment 2 of the present invention;

[0041] Figure 5e This is a schematic diagram of the actual multi-wave time-frequency domain superposition properties provided in Embodiment 2 of the present invention;

[0042] Figure 5f This is a schematic diagram of actual multi-wave time-frequency domain fusion attributes provided in Embodiment 2 of the present invention;

[0043] Figure 6aThis is a schematic diagram of a slice of the original root mean square amplitude property of a longitudinal wave according to Embodiment 2 of the present invention;

[0044] Figure 6b This is a schematic diagram of a multi-wave time-frequency domain joint attribute slice provided in Embodiment 2 of the present invention;

[0045] Figure 7 This is a schematic diagram of a multi-wave time-frequency domain joint attribute construction device provided in Embodiment 3 of the present invention;

[0046] Figure 8 This is a schematic diagram of the structure of an electronic device that implements a multi-wave time-frequency domain joint attribute construction method according to an embodiment of the present invention. Detailed Implementation

[0047] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0048] It should be noted that the terms "first," "second," "target," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0049] Example 1

[0050] Figure 1 This is a flowchart of a method for constructing multi-wave time-frequency domain joint attributes according to Embodiment 1 of the present invention. This embodiment is applicable to the construction of multi-wave time-frequency domain joint attributes. This method can be executed by a multi-wave time-frequency domain joint attribute construction device, which can be implemented in hardware and / or software. This multi-wave time-frequency domain joint attribute construction device can be configured in an electronic device with data processing capabilities. Figure 1 As shown, the method includes:

[0051] S110: Acquire multi-wave seismic signals and determine the odd and even components of the multi-wave seismic signals.

[0052] Multi-wave seismic signals refer to seismic wave signals of various waveforms obtained based on multi-wave seismic exploration methods, specifically composed of multiple time-domain seismic traces. For example, these waveforms can include P-waves, S-waves, and converted waves. Compared to single-P-wave exploration methods, multi-wave seismic exploration can simultaneously preserve and extract P-wave and PS-wave reflection information, thus providing richer subsurface information. It plays a crucial role in fields such as structural imaging, lithology estimation, anisotropy analysis, fluid detection, and reservoir characterization.

[0053] In this embodiment, multi-wave seismic signals are first acquired, and the odd and even components of the multi-wave seismic signals are determined. Optionally, determining the odd and even components of the multi-wave seismic signals includes: determining the real and imaginary parts of the multi-wave seismic signals based on Hilbert transform; and performing odd-even decomposition on the real part of the multi-wave seismic signals to obtain the odd and even components of the multi-wave seismic signals.

[0054] Specifically, based on the Hilbert transform, the time-domain seismic trace signal X(t) can be decomposed into two parts: a real part and an imaginary part, expressed as X(t) = d(t) + iH(d(t)). Here, d(t) is the real part of X(t), H(d(t)) is the imaginary part of X(t), and H(d(t)) is the Hilbert transform of the signal d(t), which can be specifically expressed as... Furthermore, the instantaneous amplitude A(t) and instantaneous phase φ(t) of the time-domain seismic trace signal X(t) can be determined as follows: Then follow the formula The real part of a multi-wave seismic signal can be decomposed into odd and even components, where O i (t) and E i (t) represent the odd and even components, respectively. In this case, both the odd and even components of the multi-wave seismic signal can be represented by signals characterized by instantaneous amplitude and instantaneous phase.

[0055] S120, perform phase decomposition on the odd component to obtain the first phase component, and perform phase decomposition on the even component to obtain the second phase component.

[0056] In this embodiment, after determining the odd and even components of the multi-wave seismic signal, phase decomposition can be performed on the odd and even components to obtain a first phase component and a second phase component, respectively. Optionally, performing phase decomposition on the odd component to obtain the first phase component includes: determining a phase component extraction function based on the time-domain amplitude spectrum and time-domain phase spectrum of the odd component; and determining the first phase component corresponding to the odd component based on the phase component extraction function and a preset phase component range.

[0057] It should be noted that seismic trace signals can be described as a one-dimensional function that varies with time, recording the changes in amplitude. The amplitude spectrum A(f,t) is a two-dimensional function describing the change in amplitude with time and frequency. The phase spectrum θ(f,t) is a two-dimensional function describing the change in phase with time and frequency. Combining the amplitude and phase information A(f,t)*cosθ(f,t), a two-dimensional function of the reflection amplitude with respect to phase and time can be obtained, i.e. Wherein, at the starting frequency f1 and ending frequency f2 of the frequency band, X′(θ,t) is the phase component extraction function.

[0058] Specifically, when performing phase decomposition on odd components, the time-domain amplitude spectrum and time-domain phase spectrum are first determined based on the instantaneous amplitude and phase of the odd component, respectively. Then, the phase component extraction function is determined based on the product of the time-domain amplitude spectrum and the time-domain phase spectrum. Finally, the first phase component corresponding to the odd component is determined based on the phase component extraction function and a preset phase component range. The preset phase component range can refer to a range of phase components pre-set according to actual application requirements, and can be characterized by a phase interval based on the start and end phases. For example, the preset phase component range can be represented as [θ1, θ2], where θ1 and θ2 represent the start and end phases of the phase interval, respectively. Extracting any desired phase component within a specified frequency band can be based on the formula... The determination is then made. When performing phase decomposition on the dual components, the phase decomposition method described above can be used to obtain the second phase component corresponding to the dual components.

[0059] Therefore, seismic reflections with specific spectral characteristics can be enhanced or suppressed on the phase axis. Any pair of reflection coefficients can represent the sum of odd and even components. The reflection coefficients of even components have the same value and sign, while the reflection coefficients of odd components have the same value but opposite signs.

[0060] S130, determine the first frequency domain seismic significance attribute and the first time domain seismic significance attribute of the first phase component, and determine the second frequency domain seismic significance attribute and the second time domain seismic significance attribute of the second phase component.

[0061] In this embodiment, after performing phase decomposition on the odd and even components to obtain the first phase component and the second phase component, the first frequency domain seismic significance attribute and the first time domain seismic significance attribute of the first phase component can be further determined, as well as the second frequency domain seismic significance attribute and the second time domain seismic significance attribute of the second phase component.

[0062] In this embodiment, optionally, determining the first frequency domain seismic significance attribute of the first phase component includes: determining the frequency domain amplitude spectrum and frequency domain phase spectrum of the first phase component; determining the frequency domain amplitude spectrum difference of the first phase component based on the logarithm of the frequency domain amplitude spectrum; and determining the first frequency domain seismic significance attribute of the first phase component based on the frequency domain amplitude spectrum difference and the frequency domain phase spectrum.

[0063] Specifically, when determining the first frequency domain seismic significance attribute of the first phase component, the frequency domain display of the first phase component is first obtained by performing a two-dimensional Fourier transform on the first phase component. Then, based on the frequency domain display of the first phase component, the frequency domain amplitude spectrum and frequency domain phase spectrum of the first phase component are determined. For example, assuming the first phase component is represented as X(t,q), where t is time and q is the trace number, the frequency domain display of the first phase component can be represented as... in, This represents a two-dimensional Fourier transform. Then, based on the formula A(f,q)=|U(f,q)|, the frequency domain amplitude spectrum of the first phase component is calculated, and based on the formula P(f,q)=angle{U(f,q)}, the frequency domain phase spectrum of the first phase component is calculated. Furthermore, the frequency domain logarithmic amplitude spectrum of the first phase component can be calculated according to the formula L(f,q)=logU(f,q), and then based on mean filtering, it is calculated using the formula R(f,q)=L(f,q)-h. n *L(f,q) estimates the frequency domain amplitude spectral difference of the first phase component, h n The Gaussian window is used. Finally, based on the inverse Fourier transform, the first frequency domain seismic significance attribute of the first phase component is obtained, which can be expressed as: Where g(m,σ) is based on a Gaussian window h n A specific Gaussian low-pass filter is used, where m represents the filter size and σ represents the standard deviation. Similarly, the determination of the second frequency domain seismic significance attribute of the second phase component can refer to the process for determining the first frequency domain seismic significance attribute of the first phase component described above.

[0064] In this embodiment, optionally, determining the first time-domain seismic significance attribute of the first phase component includes: determining the time-domain significant amplitude attribute of the first phase component based on a Gaussian low-pass filter; determining the instantaneous frequency of the time-domain significant amplitude attribute and the control coefficient of the instantaneous frequency; and determining the first time-domain seismic significance attribute of the first phase component based on the time-domain significant amplitude attribute, the instantaneous frequency, and the control coefficient.

[0065] For example, assuming the first phase component is represented as X(t,q), where t is time and q is the trace number, then when determining the first time-domain seismic significance attribute of the first phase component X(t,q), it can first be determined using the formula HR=X(t,q)-H g*X(t,q) determines the temporal saliency amplitude property of the first phase component. Where H... g This is used to characterize a Gaussian low-pass filter, whose specific parameters differ from g(m,σ). Then, the concept of seismic wavelet construction is introduced, based on the formula... Determine the first time-domain seismic saliency attribute of the first phase component. Where, f m Let α be the instantaneous frequency of HR, and f m The control coefficients are shown. Therefore, the time-domain seismic significance attribute is positively correlated with both amplitude and frequency, effectively amplifying the differences in time-domain attributes among multiple waves. Similarly, the determination method for the second time-domain seismic significance attribute of the second phase component can refer to the process for determining the first time-domain seismic significance attribute of the first phase component described above.

[0066] S140, determine the first time-frequency domain joint attribute based on the first frequency domain seismic significance attribute and the first time domain seismic significance attribute, and determine the second time-frequency domain joint attribute based on the second frequency domain seismic significance attribute and the second time domain seismic significance attribute, so as to realize the prediction of oil and gas reservoir information based on the first time-frequency domain joint attribute and the second time-frequency domain joint attribute.

[0067] In this embodiment, after obtaining the first frequency domain seismic significance attribute and the first time domain seismic significance attribute, a first time-frequency domain joint attribute can be determined based on the first frequency domain seismic significance attribute and the first time domain seismic significance attribute. Simultaneously, after obtaining the second frequency domain seismic significance attribute and the second time domain seismic significance attribute, a second time-frequency domain joint attribute can be determined based on the second frequency domain seismic significance attribute and the second time domain seismic significance attribute, so as to achieve the prediction of oil and gas reservoir information based on the first time-frequency domain joint attribute and the second time-frequency domain joint attribute. Optionally, determining the first time-frequency domain joint attribute based on the first frequency domain seismic significance attribute and the first time domain seismic significance attribute includes: superimposing or fusing the first frequency domain seismic significance attribute and the first time domain seismic significance attribute to obtain the first time-frequency domain joint attribute.

[0068] Specifically, when determining the first time-frequency domain joint attribute, the first frequency domain seismic saliency attribute and the first time-domain seismic saliency attribute can be directly superimposed, or the first frequency domain seismic saliency attribute and the first time-domain seismic saliency attribute can be fused using RGB to obtain the first time-frequency domain joint attribute. Similarly, the second time-frequency domain joint attribute can be determined based on the superposition or fusion of the second frequency domain seismic saliency attribute and the second time-domain seismic saliency attribute. Based on the first time-frequency domain joint attribute and the second time-frequency domain joint attribute, oil and gas reservoir information can be predicted, where oil and gas reservoir information can include location and distribution information.

[0069] This invention proposes a multi-wave time-frequency combined seismic attribute based on multi-wave seismic data. It also establishes a link between multi-wave seismic attributes and reservoir fluids, expanding the attribute construction method based on multi-wave data and enhancing the stability and reliability of reservoir oil and gas detection. Compared with existing technologies, it has the following advantages: 1) This invention fully considers the differences in multi-wave seismic data to construct a new multi-wave time-frequency domain combined attribute. Conventional methods mainly predict reservoir fluid characteristics based on P-wave seismic attributes, resulting in strong ambiguity; 2) The attribute construction strategy designed in this invention based on phase decomposition theory introduces the phase information of multi-wave seismic data, improving the prediction accuracy of multi-wave attributes.

[0070] The technical solution of this invention first acquires multi-wave seismic signals and determines their odd and even components. Then, it performs phase decomposition on the odd components to obtain a first phase component, and on the even components to obtain a second phase component. Next, it determines the first frequency-domain and first time-domain seismic saliency attributes of the first phase component, and the second frequency-domain and second time-domain seismic saliency attributes of the second phase component. Finally, it determines a first time-frequency domain joint attribute based on the first frequency-domain and first time-domain seismic saliency attributes, and a second time-frequency domain joint attribute based on the second frequency-domain and second time-domain seismic saliency attributes, thereby enabling the prediction of oil and gas reservoir information based on these attributes. This technical solution fully considers the relationship between the differences in multi-wave seismic signals and reservoir oil and gas, and improves the reliability of multi-wave seismic attributes and enhances the accuracy of oil and gas detection by constructing multi-wave time-frequency domain joint attributes.

[0071] Example 2

[0072] Figure 2 This is a flowchart of a multi-wave time-frequency domain joint attribute construction method provided in Embodiment 2 of the present invention. This embodiment is based on the above embodiment and optimized. Specifically, the optimization is as follows: after performing phase decomposition on the odd components to obtain a first phase component and performing phase decomposition on the even components to obtain a second phase component, the method further includes: filtering the first phase component to obtain a first frequency-divided phase volume, and filtering the second phase component to obtain a second frequency-divided phase volume; correspondingly, determining the first frequency-domain seismic significance attribute and the first time-domain seismic significance attribute of the first phase component, and determining the second frequency-domain seismic significance attribute and the second time-domain seismic significance attribute of the second phase component, including: determining the first frequency-domain seismic significance attribute and the first time-domain seismic significance attribute of the first frequency-divided phase volume, and determining the second frequency-domain seismic significance attribute and the second time-domain seismic significance attribute of the second frequency-divided phase volume.

[0073] like Figure 2 As shown, the method in this embodiment specifically includes the following steps:

[0074] S210: Acquire multi-wave seismic signals and determine the odd and even components of the multi-wave seismic signals.

[0075] S220, perform phase decomposition on the odd component to obtain the first phase component, and perform phase decomposition on the even component to obtain the second phase component.

[0076] S230, the first phase component is filtered to obtain the first frequency-divided phase body, and the second phase component is filtered to obtain the second frequency-divided phase body.

[0077] It should be noted that the first and second phase components obtained through phase decomposition may contain noise, which will undoubtedly affect the accuracy of the time-frequency domain seismic saliency attributes, and consequently the accuracy of the time-frequency domain joint attributes. Therefore, in order to improve the time-frequency domain seismic saliency attributes, the first and second phase components need to be filtered to obtain the first and second frequency-divided phase volumes before determining the time-frequency domain seismic saliency attributes.

[0078] In this embodiment, optionally, filtering the first phase component to obtain the first frequency-divided phase body includes: determining the local maxima and local minima of the first phase component; obtaining the maxima envelope and minima envelope respectively through interpolation based on the local maxima and local minima; determining the mean envelope based on the maxima envelope and minimum envelope; determining the candidate oscillation mode based on the difference between the first phase component and the mean envelope; if the candidate oscillation mode meets the preset stopping criterion, then the candidate oscillation mode is determined as the target oscillation mode; otherwise, the candidate oscillation mode is used as the updated first phase component, and the above process of determining the candidate oscillation mode is repeated until the preset termination condition is met; and determining the first frequency-divided phase body corresponding to the first phase component based on the target oscillation mode.

[0079] In this embodiment, the corresponding frequency-division phase volume can be extracted after two-dimensional empirical mode decomposition filtering. The specific process is as follows: First, find the local maximum value I(I) of the first phase component I. max J max ) and local minimum I(I min J min Then, based on the local maxima and local minima, the maximum envelope E is obtained through interpolation. max (t) and the minimum envelope E min (t); then, the mean envelope is obtained by taking the average of the maximum and minimum envelopes. The candidate oscillation mode S = IM is obtained by subtracting the mean envelope from the first phase component. If the candidate oscillation mode meets the preset stopping criteria, the candidate oscillation mode is determined as the target oscillation mode. Otherwise, the candidate oscillation mode is used as the updated first phase component, i.e., I = S, and the above process of determining the candidate oscillation mode is repeated until the preset termination condition is met.

[0080] The preset stop criterion can be determined based on the standard deviation between two consecutive screening results. For example, the preset stop criterion can be set to a standard deviation less than a preset threshold. For two-dimensional signals, there are two commonly used methods for defining the standard deviation, which can be expressed as follows: and Where M and N are the height and width of the two-dimensional image, respectively; S k+1 and S k These are two consecutive oscillation modes obtained through a continuous screening process; ε is a small constant value to prevent the denominator from equaling zero. It is worth noting that SD2 is a more recommended calculation method because it effectively avoids the problem of a zero denominator due to the presence of zero pixels during the fitting process by adding a small constant to the denominator. When S calculated during the screening process meets the preset stopping criterion, S is recognized as a two-dimensional eigenmode decomposition. After obtaining all target oscillation modes through screening, each target oscillation mode can be used as the first frequency-divided phase body corresponding to the first phase component. Similarly, the filtering process for the second phase component can refer to the filtering process for the first phase component described above, thereby obtaining the second frequency-divided phase body corresponding to the second phase component.

[0081] S240, determine the first frequency domain seismic significance attribute and the first time domain seismic significance attribute of the first frequency-division phase volume, and determine the second frequency domain seismic significance attribute and the second time domain seismic significance attribute of the second frequency-division phase volume.

[0082] The specific implementation of S240 can refer to the relevant description of S130 in the above embodiment 1. The difference is that the first phase component and the second phase component are replaced with the first frequency divider phase body and the second frequency divider phase body, respectively.

[0083] S250, a first time-frequency domain joint attribute is determined based on the first frequency domain seismic significance attribute and the first time domain seismic significance attribute, and a second time-frequency domain joint attribute is determined based on the second frequency domain seismic significance attribute and the second time domain seismic significance attribute, so as to realize the prediction of oil and gas reservoir information based on the first time-frequency domain joint attribute and the second time-frequency domain joint attribute.

[0084] To verify the practicality of the method of this invention, the following section will calculate the joint attributes of multiple time-frequency domains based on a complex geological model designed by software simulation, compare and analyze the sensitivity of multiple attributes at reservoir development sites, and verify the predictive role of the joint attributes of multiple waves in complex reservoirs. See also Figure 3a This illustrates a schematic diagram of a complex geological model. Based on... Figure 3a The complex geological model in the model extracts multi-wave time-frequency domain features by decomposing the phase information of P-waves and converted waves, thereby enabling more accurate identification of fluids in thin reservoirs. Figure 3b and Figure 3c These are schematic diagrams of P-wave and converted-wave seismic records calculated based on complex geological models. (See also...) Figure 3d- Figure 3k As can be seen from the figure, multiple geological anomalies were designed in the complex geological model, of which only one is an oil and gas reservoir, while the rest are water-bearing reservoirs. This can effectively verify the predictive role of the attributes constructed in this invention for complex reservoirs. The detection of seismic significance attributes in the time and frequency domain provides a favorable basis for the description of deep oil and gas-bearing sandstones, thus laying a solid foundation for subsequent multi-wave attribute fusion.

[0085] Furthermore, this invention tested and analyzed actual single-well data. See also... Figure 4 This paper presents a comparative analysis of different phase components calculated from wellbore data in actual reservoirs. As shown in the figure, strong amplitude anomalies may appear in the odd-numbered phase components at the original weak amplitude locations. Especially in the case of thin gas-bearing sandstone layers (bright spots) with low impedance, amplitude anomalies corresponding to gas saturation appear in the single-phase components. Figure 4 The seismic responses of the -90°, 90°, 0°, and 180° phase components are presented. Phase decomposition reveals that the even-numbered phase components are similar to the original seismic response, while the hydrocarbon responses of the -90° and 90° phase components are significantly amplified. This implies that phase decomposition techniques can be used to extract phase components related to hydrocarbon content in rocks, thereby detecting and identifying potential hydrocarbon reservoirs. When thin layers of low-resistivity gas-bearing sandstone are present, the hydrocarbon response in the -90° phase component is enhanced, making it a bright spot or a significant anomalous response in the data.

[0086] To further verify the practicality and reliability of this invention, two practical data tests will be used for illustration below. See Figure 5a- Figure 5fThe method of this invention was applied to reservoir prediction in the F oilfield to verify its applicability to actual seismic data. The main target layers in this study area consist of superimposed channel sand bodies, primarily distributed around 1.11 seconds. These target layers exhibit low P-wave impedance and high converted wave impedance. The above description indicates that the study area possesses typical tight gas reservoir geological characteristics. During testing, phase decomposition and other methods were used to extract multi-wave seismic attribute characteristics, further identifying tight gas reservoirs. Furthermore, this study can further verify the applicability of the method in tight gas reservoir exploration and provides important guidance for the effective development of tight gas reservoirs in the Sichuan Basin. Figure 5a- Figure 5f The areas marked by the elliptical dashed lines in the image represent regions rich in gas content within the reservoir. Figure 5a and Figure 5b It is evident that it is difficult to identify the hydrocarbon content of sand bodies based solely on the differences in multi-wave amplitudes. In fact, compared with the P-wave record, the amplitude response of converted wave sand bodies is weakened. Figure 5c and Figure 5d This study demonstrates how seismic records based on phase decomposition, through comparison of P-wave and converted-wave records, can extract subsurface reservoir fluid characteristics from complex seismic records and identify reservoir anomalies. Figure 5e and Figure 5f It can be seen that, based on the time-frequency domain attribute differences between longitudinal waves and converted waves, reservoir fluids can be accurately detected, assisting in determining the well point location of horizontal wells, and better predicting reservoir oil and gas and identifying fluids, thus providing a strong guarantee for determining the target layer information.

[0087] Furthermore, this invention extracts root mean square amplitude slices along the layers from the obtained multi-wave time-frequency domain joint attributes and the actual P-wave seismic records, and conducts comparative analysis on them. Figure 6a and Figure 6b The images show root mean square amplitude slices based on P-wave seismic records and multi-wave time-frequency domain joint attributes, respectively. Compared with the root mean square attributes based on P-wave seismic records, the conventional method based on P-wave seismic records has achieved certain results. However, the method of this invention is clearly superior in the identified channel sand bodies, and the channel boundaries are delineated more accurately.

[0088] The above two practical data tests demonstrate that traditional seismic attribute extraction methods heavily rely on P-wave seismic data, and that multi-wave seismic data attribute extraction methods lack theoretical research. This invention expands the analytical capabilities of multi-wave seismic data, accurately extracts reflection information, and reduces the interpretive ambiguity of multi-component seismic data. Applying this method to theoretical model processing can distinguish the development location of effective reservoirs within the target area, effectively identifying favorable reservoirs, further demonstrating the reliability and practical application prospects of the method.

[0089] The technical solution of this invention involves performing phase decomposition on the odd components to obtain a first phase component, and performing phase decomposition on the even components to obtain a second phase component. Then, the first phase component is filtered to obtain a first frequency-divided phase volume, and the second phase component is filtered to obtain a second frequency-divided phase volume. A first frequency-domain seismic saliency attribute and a first time-domain seismic saliency attribute are determined for the first frequency-divided phase volume, as are a second frequency-domain seismic saliency attribute and a second time-domain seismic saliency attribute for the second frequency-divided phase volume. This technical solution, by filtering the first and second phase components, effectively reduces the impact of noise, thereby improving the accuracy of constructing time-frequency domain seismic saliency attributes. This improves the accuracy and reliability of constructing multi-wavelength time-frequency domain joint attributes, contributing to further enhancing the accuracy of oil and gas detection.

[0090] Example 3

[0091] Figure 7 This is a schematic diagram of a multi-wave time-frequency domain joint attribute construction device provided in Embodiment 3 of the present invention. This device can execute the multi-wave time-frequency domain joint attribute construction method provided in any embodiment of the present invention, and possesses the corresponding functional modules and beneficial effects of the method. For example... Figure 7 As shown, the device includes:

[0092] The signal parity decomposition module 310 is used to acquire multi-wave seismic signals and determine the odd and even components of the multi-wave seismic signals.

[0093] The signal phase decomposition module 320 is used to perform phase decomposition on the odd component to obtain a first phase component, and to perform phase decomposition on the even component to obtain a second phase component.

[0094] The seismic saliency attribute determination module 330 is used to determine the first frequency domain seismic saliency attribute and the first time domain seismic saliency attribute of the first phase component, and to determine the second frequency domain seismic saliency attribute and the second time domain seismic saliency attribute of the second phase component.

[0095] The time-frequency domain joint attribute determination module 340 is used to determine a first time-frequency domain joint attribute based on the first frequency domain seismic significance attribute and the first time domain seismic significance attribute, and to determine a second time-frequency domain joint attribute based on the second frequency domain seismic significance attribute and the second time domain seismic significance attribute, so as to realize the prediction of oil and gas reservoir information based on the first time-frequency domain joint attribute and the second time-frequency domain joint attribute.

[0096] Optionally, the signal parity decomposition module 310 is specifically used for:

[0097] The real and imaginary parts of the multi-wave seismic signal are determined based on the Hilbert transform;

[0098] The real part of the multi-wave seismic signal is decomposed into odd and even components to obtain the odd and even components of the multi-wave seismic signal.

[0099] Optionally, the signal phase decomposition module 320 is specifically used for:

[0100] The phase component extraction function is determined based on the time-domain amplitude spectrum and time-domain phase spectrum of the odd components;

[0101] The first phase component corresponding to the odd component is determined based on the phase component extraction function and the preset phase component range.

[0102] Optionally, the earthquake saliency attribute determination module 330 is used for:

[0103] Determine the frequency domain amplitude spectrum and frequency domain phase spectrum of the first phase component;

[0104] The frequency domain amplitude spectrum difference of the first phase component is determined based on the logarithm of the frequency domain amplitude spectrum;

[0105] The first frequency domain seismic significance attribute of the first phase component is determined based on the frequency domain amplitude spectrum difference and the frequency domain phase spectrum.

[0106] Optionally, the seismic saliency attribute determination module 330 is further configured to:

[0107] The temporal saliency amplitude property of the first phase component is determined based on a Gaussian low-pass filter;

[0108] Determine the instantaneous frequency of the time-domain saliency amplitude attribute and the control coefficient of the instantaneous frequency;

[0109] The first time-domain seismic significance attribute of the first phase component is determined based on the time-domain significance amplitude attribute, the instantaneous frequency, and the control coefficient.

[0110] Optionally, the time-frequency domain joint attribute determination module 340 is specifically used for:

[0111] The first frequency domain seismic significance attribute and the first time domain seismic significance attribute are superimposed or fused to obtain the first time-frequency domain joint attribute.

[0112] Optionally, the device further includes: a signal filtering and processing module, used for:

[0113] After performing phase decomposition on the odd components to obtain a first phase component and performing phase decomposition on the even components to obtain a second phase component, the first phase component is filtered to obtain a first frequency-divided phase body, and the second phase component is filtered to obtain a second frequency-divided phase body.

[0114] Accordingly, the earthquake saliency attribute determination module 330 is also used for:

[0115] The first frequency domain seismic significance attribute and the first time domain seismic significance attribute of the first frequency-division phase volume are determined, and the second frequency domain seismic significance attribute and the second time domain seismic significance attribute of the second frequency-division phase volume are determined.

[0116] Optionally, the signal filtering processing module is specifically used for:

[0117] Determine the local maxima and local minima of the first phase component;

[0118] Based on the local maxima and local minima, interpolation processing is used to obtain the maximum value envelope and the minimum value envelope, respectively;

[0119] The mean envelope is determined based on the maximum and minimum envelopes.

[0120] Candidate oscillation modes are determined based on the difference between the first phase component and the mean envelope surface;

[0121] If the candidate oscillation mode meets the preset stopping criteria, then the candidate oscillation mode is determined as the target oscillation mode;

[0122] Otherwise, the candidate oscillation mode is used as the updated first phase component, and the above process of determining the candidate oscillation mode is repeated until the preset termination condition is met.

[0123] The first frequency-divided phase body corresponding to the first phase component is determined based on the target oscillation mode.

[0124] The multi-wave time-frequency domain joint attribute construction device provided in this embodiment of the invention can execute the multi-wave time-frequency domain joint attribute construction method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0125] Example 4

[0126] Figure 8A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0127] like Figure 8 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0128] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0129] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the multi-wavelength time-frequency domain joint property construction method.

[0130] In some embodiments, the multi-wavelength time-frequency domain joint attribute construction method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the multi-wavelength time-frequency domain joint attribute construction method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to execute the multi-wavelength time-frequency domain joint attribute construction method by any other suitable means (e.g., by means of firmware).

[0131] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0132] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0133] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0134] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0135] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0136] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0137] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0138] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A multi-wave time-frequency domain joint attribute construction method, characterized in that, The method comprises: acquiring a multi-wave seismic signal, determining an odd component and an even component of the multi-wave seismic signal; phase decomposing the odd component to obtain a first phase component, and phase decomposing the even component to obtain a second phase component; determining a first frequency domain seismic significance attribute and a first time domain seismic significance attribute of the first phase component, and determining a second frequency domain seismic significance attribute and a second time domain seismic significance attribute of the second phase component; determining a first time-frequency domain joint attribute according to the first frequency domain seismic significance attribute and the first time domain seismic significance attribute, and determining a second time-frequency domain joint attribute according to the second frequency domain seismic significance attribute and the second time domain seismic significance attribute, so as to realize prediction of oil and gas reservoir information based on the first time-frequency domain joint attribute and the second time-frequency domain joint attribute.

2. The method of claim 1, wherein, The method comprises: determining an odd component and an even component of the multi-wave seismic signal, comprising: determining a real part and an imaginary part of the multi-wave seismic signal based on Hilbert transform; 3. The method of claim 1, wherein, performing odd-even decomposition on the real part of the multi-wave seismic signal to obtain the odd component and the even component of the multi-wave seismic signal. The method comprises: determining a first phase component by phase decomposing the odd component, comprising:

4. The method of claim 1, wherein, determining a phase component extraction function based on a time domain amplitude spectrum and a time domain phase spectrum of the odd component; determining the first phase component corresponding to the odd component based on the phase component extraction function and a preset phase component range. The method comprises: determining a first frequency domain seismic significance attribute of the first phase component, comprising:

5. The method of claim 1, wherein, determining a frequency domain amplitude spectrum and a frequency domain phase spectrum of the first phase component; determining a frequency domain amplitude spectrum difference of the first phase component based on a logarithm of the frequency domain amplitude spectrum; determining the first frequency domain seismic significance attribute of the first phase component based on the frequency domain amplitude spectrum difference and the frequency domain phase spectrum. The method comprises:

6. The method of claim 1, wherein, determining a first time domain seismic significance attribute of the first phase component, comprising: determining a time domain significance amplitude attribute of the first phase component based on a Gaussian low-pass filter; 7. The method according to any one of claims 1 to 6, characterized in that, determining an instantaneous frequency of the time domain significance amplitude attribute and a control coefficient of the instantaneous frequency; determining the first time domain seismic significance attribute of the first phase component according to the time domain significance amplitude attribute, the instantaneous frequency and the control coefficient. The method comprises: superimposing or fusing the first frequency domain seismic significance attribute and the first time domain seismic significance attribute to obtain a first time-frequency domain joint attribute. After phase decomposing the odd component to obtain a first phase component, and phase decomposing the even component to obtain a second phase component, the method further comprises: filtering the first phase component to obtain a first frequency phase body, and filtering the second phase component to obtain a second frequency phase body; correspondingly, the method comprises: determining a first frequency domain seismic significance attribute and a first time domain seismic significance attribute of the first phase component, and determining a second frequency domain seismic significance attribute and a second time domain seismic significance attribute of the second phase component, comprising: determine a first frequency domain seismic significance attribute and a first time domain seismic significance attribute of the first frequency division phase body, and determine a second frequency domain seismic significance attribute and a second time domain seismic significance attribute of the second frequency division phase body.

8. The method of claim 7, wherein, filtering the first phase component to obtain a first frequency division phase body, including: determining local maximum values and local minimum values of the first phase component; determining a mean value envelope surface according to the maximum value envelope surface and the minimum value envelope surface; determining a candidate oscillation mode according to a difference between the first phase component and the mean value envelope surface; if the candidate oscillation mode satisfies a preset stopping criterion, determining the candidate oscillation mode as a target oscillation mode; otherwise, taking the candidate oscillation mode as an updated first phase component, and repeatedly executing the process of determining the candidate oscillation mode until a preset termination condition is satisfied; determining a first frequency division phase body corresponding to the first phase component according to the target oscillation mode. The device includes:

9. A multi-wave time-frequency domain joint attribute construction device, characterized in that, a signal odd-even decomposition module configured to obtain a multi-wave seismic signal, and determine an odd component and an even component of the multi-wave seismic signal; a signal phase decomposition module configured to perform phase decomposition on the odd component to obtain a first phase component, and perform phase decomposition on the even component to obtain a second phase component; a seismic significance attribute determination module configured to determine a first frequency domain seismic significance attribute and a first time domain seismic significance attribute of the first phase component, and determine a second frequency domain seismic significance attribute and a second time domain seismic significance attribute of the second phase component; a time-frequency domain joint attribute determination module configured to determine a first time-frequency domain joint attribute according to the first frequency domain seismic significance attribute and the first time domain seismic significance attribute, and determine a second time-frequency domain joint attribute according to the second frequency domain seismic significance attribute and the second time domain seismic significance attribute, so as to realize prediction of oil and gas reservoir information based on the first time-frequency domain joint attribute and the second time-frequency domain joint attribute. The electronic device includes:

10. An electronic device, comprising: at least one processor; and a memory connected with the at least one processor in communication; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the multi-wave time-frequency domain joint attribute construction method in any one of claims 1-8. The computer readable storage medium stores computer instructions for enabling the processor to execute the multi-wave time-frequency domain joint attribute construction method in any one of claims 1-8 when executed.

11. A computer readable storage medium, characterized in that, ​

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