Method and apparatus for determining fluid detection property, electronic device, and storage medium

Abstract

The application provides a method and device for determining fluid detection attributes, electronic equipment and a storage medium. The AVO pre-stack gather data is stacked through an azimuth angle and an incidence angle to obtain a stacked seismic data volume. Relative impedance data volumes corresponding to each azimuth angle are determined based on the stacked seismic data volume. Elliptical flattening corresponding to each incidence angle is determined based on the relative impedance data volumes corresponding to each azimuth angle. Each anisotropy strength frequency domain attribute is determined based on the elliptical flattening corresponding to each incidence angle. A gradient attribute of each anisotropy strength frequency domain attribute changing with the incidence angle is extracted to obtain fluid detection attributes of the target region, thereby improving the fluid detection accuracy of the target region.

Description

Technical Field

[0001] This application relates to the field of oil and gas geophysical exploration technology, and in particular to a method, apparatus, electronic device and storage medium for determining fluid detection properties. Background Technology

[0002] Predicting hydrocarbon reservoir fluids remains a challenging area that geophysical interpreters continue to work on. Currently, geophysical interpretation methods for detecting hydrocarbon content in reservoirs can be broadly categorized as follows: methods that qualitatively identify reservoir fluid characteristics based on rock physical analysis and pre-stack seismic inversion to obtain fluid-sensitive elastic parameters; gas-bearing detection methods based on AVO analysis; and fluid detection methods based on frequency attenuation characteristics. However, the method of qualitatively identifying reservoir fluid characteristics based on rock physical analysis and pre-stack seismic inversion has two shortcomings: first, the sensitivity of elastic parameters to fluids is far less than the influence of reservoir lithology and physical properties on elastic parameters. Therefore, when reservoir conditions themselves change drastically, the gas-bearing detection results exhibit significant ambiguity. Furthermore, this method, based on pre-stack elastic inversion, faces challenges in constructing a suitable low-frequency inversion model for reservoirs with rapid vertical and horizontal facies transitions. An inappropriate low-frequency model can lead to unreliable elastic parameter inversion results, affecting the accuracy of gas content detection. Gas content detection methods based on AVO analysis also suffer from two shortcomings: first, Poisson's ratio is not the optimal reservoir and fluid identification parameter for all reservoir types; second, AVO technology is also based on amplitude variations, and lithology and physical properties have a greater impact on amplitude variations, resulting in significant ambiguity in AVO-based gas content detection techniques. Fluid detection techniques based on frequency decay characteristics are limited by high-resolution time-frequency analysis methods, typically resulting in limited fluid detection resolution.

[0003] For fluid detection in complex, thin, narrow channel tight sandstone gas reservoirs and fractured reservoirs, the above methods are not well adapted because, like fractured reservoirs, complex, thin, narrow channels have certain spatial anisotropic characteristics. At the same time, the reservoir AVO characteristics are constantly changing in space due to the influence of the difference in reservoir tightness. Summary of the Invention

[0004] To address the aforementioned problems, this application provides a method, apparatus, electronic device, and storage medium for determining fluid detection properties, which can obtain the fluid detection properties of a target area, thereby improving the accuracy of fluid detection in the target area.

[0005] This application provides a method for determining fluid detection properties, including:

[0006] Acquire AVO pre-stack gather data for the target region;

[0007] The AVO pre-stack gather data are stacked based on the azimuth and incident angle to obtain the stacked seismic data volume.

[0008] Based on the superimposed seismic data volume, determine the relative impedance data volume corresponding to each azimuth angle;

[0009] Based on the relative impedance data volume corresponding to each azimuth angle, the elliptic flattening corresponding to each incident angle is determined.

[0010] The frequency domain properties of each anisotropic intensity are determined based on the elliptic flattening corresponding to each incident angle.

[0011] The gradient properties of the frequency domain properties of each anisotropic intensity as a function of the incident angle are extracted to obtain the fluid detection properties of the target region.

[0012] In some embodiments, determining the relative impedance data volume corresponding to each azimuth based on the stacked seismic data volume includes:

[0013] Well-seismic calibration is performed on the stacked seismic data volume corresponding to each azimuth angle;

[0014] Wavelets corresponding to each azimuth angle are extracted from the stacked seismic data volume after well-seismic calibration.

[0015] Impedance inversion is performed on the wavelets corresponding to each azimuth angle to determine the relative impedance volume data corresponding to each azimuth angle.

[0016] In some embodiments, determining the elliptic flattening corresponding to each incident angle based on the relative impedance data volume corresponding to each azimuth angle includes:

[0017] Ellipse fitting is performed based on the relative impedance data volume corresponding to each orientation and each incident angle to obtain the ellipse characteristic value corresponding to each incident angle.

[0018] The elliptic flattening corresponding to each incident angle is determined based on the elliptic eigenvalues ​​corresponding to each incident angle.

[0019] In some embodiments, the elliptic flattening is represented by four-dimensional data, and the determination of the frequency domain properties of each anisotropic intensity based on the elliptic flattening corresponding to each incident angle includes:

[0020] Time-frequency analysis is performed on the elliptic flattening corresponding to each incident angle to obtain five-dimensional data corresponding to each incident angle, wherein the five-dimensional data includes: frequency;

[0021] Based on the frequency of the five-dimensional data corresponding to each incident angle, determine the frequency domain energy corresponding to each incident angle.

[0022] The maximum frequency domain energy is determined based on the frequency domain energy corresponding to each incident angle.

[0023] The frequency domain properties of each anisotropic intensity are determined based on the maximum frequency domain energy.

[0024] In some embodiments, determining the frequency domain energy corresponding to each incident angle based on the frequency of the five-dimensional data corresponding to each incident angle includes:

[0025] The frequency domain energy corresponding to each incident angle is calculated using a first formula based on the frequencies of the five-dimensional data corresponding to each incident angle, wherein the first formula includes:

[0026]

[0027] Where E(f) is the frequency domain energy, A is the amplitude constant, and f b is the bandwidth factor, and f is the frequency.

[0028] In some embodiments, determining the frequency domain properties of each anisotropic intensity based on the maximum frequency domain energy includes:

[0029] Multiply the maximum frequency domain energy by the first ratio to obtain the first frequency domain energy;

[0030] Determine the first frequency domain energy to correspond to the first frequency and the second frequency;

[0031] Multiply the maximum frequency domain energy by the second ratio to obtain the second frequency domain energy;

[0032] Determine the third and fourth frequencies corresponding to the energy in the second frequency domain, wherein the first ratio and the second ratio are different;

[0033] The high-frequency attenuation gradient and the low-frequency attenuation gradient are determined based on the first frequency, the second frequency, the third frequency, and the fourth frequency;

[0034] The combined frequency attenuation gradient is obtained based on the high-frequency attenuation gradient and the low-frequency attenuation gradient, wherein the anisotropic intensity frequency domain attributes include: high-frequency attenuation gradient, low-frequency attenuation gradient, combined frequency attenuation gradient, maximum frequency domain energy, and the instantaneous dominant frequency corresponding to the maximum frequency domain energy.

[0035] In some embodiments, the first ratio is A%, the second ratio is B%, the first frequency is greater than the second frequency, the third frequency is greater than the fourth frequency, and determining the high-frequency attenuation gradient and the low-frequency attenuation gradient based on the first frequency, the second frequency, the third frequency, and the fourth frequency includes:

[0036] Calculate the spectral area corresponding to the first frequency and the second frequency respectively;

[0037] The high-frequency attenuation gradient is calculated based on the second formula, which is:

[0038]

[0039] Among them, G hf For high-frequency attenuation gradient, E max_A_h E is the spectral area corresponding to the first frequency. max_A_l f is the area of ​​the ground spectrum corresponding to the second frequency. A_h For the first frequency, f A_l The second frequency;

[0040] Calculate the spectral area corresponding to the third frequency and the fourth frequency respectively;

[0041] The low-frequency attenuation gradient is calculated based on the third formula, which is:

[0042]

[0043] Among them, G lf For low-frequency attenuation gradient, E max_B_h E represents the spectral area corresponding to the third frequency. max_B_l f is the spectral area corresponding to the fourth frequency. B_h For the third frequency, f B_l It is the fourth frequency.

[0044] In some embodiments, extracting the gradient properties of each anisotropic intensity frequency domain property as a function of the incident angle includes:

[0045] By fitting the frequency domain properties of each incident angle and each anisotropic intensity, the fitting equations of the frequency domain properties of each anisotropic intensity as a function of the incident angle are obtained.

[0046] Based on the fitted equation, the gradient properties of the frequency domain properties of each anisotropic intensity as a function of the incident angle are determined.

[0047] This application provides a device for determining fluid detection properties, comprising:

[0048] The acquisition module is used to acquire AVO pre-stack gather data for the target region;

[0049] The overlay module is used to overlay the AVO pre-stack gather data based on azimuth and incident angle to obtain a stacked seismic data volume;

[0050] The first determining module is used to determine the relative impedance data volume corresponding to each azimuth based on the superimposed seismic data volume;

[0051] The second determining module is used to determine the elliptic flattening corresponding to each incident angle based on the relative impedance data volume corresponding to each azimuth angle.

[0052] The third determination module is used to determine the frequency domain properties of each anisotropic intensity based on the elliptic flattening corresponding to each incident angle.

[0053] The extraction module is used to extract the gradient properties of the frequency domain properties of each anisotropic intensity as a function of the incident angle, so as to obtain the fluid detection properties of the target region.

[0054] This application provides an electronic device, including a memory and a processor. The memory stores a computer program, which, when executed by the processor, performs the method for determining fluid detection attributes.

[0055] This application provides a storage medium storing a computer program that can be executed by one or more processors and can be used to implement the method for determining fluid detection attributes described in any of the above claims.

[0056] This application provides a method, apparatus, electronic device, and storage medium for determining fluid detection attributes. The method involves superimposing AVO pre-stack gather data using azimuth and incident angles to obtain a superimposed seismic data volume; determining relative impedance data volumes corresponding to each azimuth based on the superimposed seismic data volume; determining the elliptic flattening corresponding to each incident angle based on the relative impedance data volumes corresponding to each azimuth; determining the frequency domain attributes of each anisotropic intensity based on the elliptic flattening corresponding to each incident angle; and extracting the gradient attributes of each anisotropic intensity frequency domain attribute as a function of the incident angle to obtain the fluid detection attributes of the target region, thereby improving the accuracy of fluid detection in the target region. Attached Figure Description

[0057] The present application will be described in more detail below based on embodiments and with reference to the accompanying drawings.

[0058] Figure 1 A schematic diagram illustrating the implementation process of a method for determining fluid detection properties provided in an embodiment of this application;

[0059] Figure 2 A flowchart illustrating another method for determining fluid detection properties provided in an embodiment of this application;

[0060] Figure 3 A schematic diagram of a small-angle well-crossing profile at 0-45° azimuth provided for an embodiment of this application;

[0061] Figure 4 This application provides a 135-180° azimuth high-angle well profile for embodiments of the present application;

[0062] Figure 5 This is a schematic diagram of the frequency domain peak energy attribute through the well under small-angle conditions in the embodiment.

[0063] Figure 6 This is a schematic diagram of the well profile of the high-frequency attenuation gradient attribute in the frequency domain under small-angle conditions in the embodiment.

[0064] Figure 7 A planar schematic diagram of the reservoir fluid properties corresponding to the high-frequency attenuation gradient attribute provided in the embodiments of this application;

[0065] Figure 8 This is a schematic diagram of the composition structure of the electronic device provided in the embodiments of this application.

[0066] In the accompanying drawings, the same parts are referred to by the same reference numerals, and the drawings are not drawn to scale. Detailed Implementation

[0067] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0068] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0069] If the application documents contain similar descriptions such as "first, second, third", the following explanation shall be added: In the following description, the terms "first, second, third" are used only to distinguish similar objects and do not represent a specific order of objects. It is understood that "first, second, third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0070] 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 application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0071] Before introducing the embodiments of this application, a brief overview of related technologies is provided. Predicting fluids in oil and gas-bearing reservoirs remains a challenging area that geophysical interpreters continuously strive to overcome. Currently, geophysical interpretation methods for detecting the oil and gas content of reservoirs can be broadly categorized as follows:

[0072] The first category is methods that qualitatively identify reservoir fluid characteristics by obtaining reservoir fluid-sensitive elastic parameters through pre-stack seismic inversion based on rock physical analysis. Reservoir rock physical analysis, as a bridge between reservoir characteristics and seismic attributes, is a seismic-oriented well analysis technique, a crucial foundational research work for reservoir prediction, and an important link in the feasibility analysis of reservoir and fluid prediction. With the help of rock physical analysis, the relationship between lithology and seismic attributes, the relationship between reservoir and seismic attributes, and the relationship between reservoir oil-bearing capacity and seismic attributes can be clarified. After identifying reservoir-sensitive elastic parameters through methods such as cross-plot analysis, the next step is to accurately obtain these parameters. Pre-stack simultaneous inversion is based on the Zoeppritz equation for reflection and transmission caused by plane waves incident on the reflection interface. Through approximation using the reflection coefficient equation and regularized inversion methods, different elastic parameters, including P-wave and S-wave velocities, densities, and Poisson's ratio, can be obtained, thereby achieving fluid detection. This type of method has two shortcomings: first, the sensitivity of elastic parameters to fluids is far less than the influence of reservoir lithology and physical properties on elastic parameters. Therefore, when reservoir conditions change drastically, the gas content detection results exhibit significant ambiguity. Furthermore, this method is based on pre-stack elastic inversion, which presents challenges in constructing a suitable low-frequency inversion model for reservoirs with rapid longitudinal and lateral facies changes. An inappropriate low-frequency model can lead to unreliable elastic parameter inversion results, thus affecting the accuracy of gas content detection.

[0073] The second category is gas-bearing detection methods based on AVO analysis. AVO technology establishes the relationship between reservoir fluid properties and AVO, applying AVO attribute parameters to detect the fluid-bearing properties of the reservoir. In practical applications, this involves using CDP gather data from seismic reflections to analyze the variation of reflected wave amplitude with shot-receiver distance at the reservoir interface, or calculating the variation parameters of reflected wave amplitude with its incident angle to estimate AVO attribute parameters (AVO intercept P and AVO slope G), Poisson's ratio, and fluid factor at the interface, further inferring the lithology and hydrocarbon-bearing properties of the reservoir. The theoretical basis of AVO technology is the difference in Poisson's ratio between different lithologies and different porous fluid media. This type of method also has two shortcomings: first, not all reservoir types have optimal Poisson's ratio parameters for reservoir and fluid identification; second, AVO technology is also based on amplitude variation, and lithology and physical properties have a greater impact on amplitude variation, so gas-bearing detection techniques based on AVO attributes also have significant ambiguity.

[0074] The third category is fluid detection techniques based on frequency attenuation characteristics. According to viscoelastic theory, the amplitude of seismic waves attenuates as the propagation distance increases. This is the theoretical basis for using frequency attenuation properties to predict the hydrocarbon content of formations. Frequency absorption attenuation refers to the loss of total energy of seismic waves propagating through underground geological bodies, and is an inherent property of the subsurface medium. Frequency attenuation property analysis converts seismic data from the time domain to the frequency domain, effectively detecting the fluidity of reservoirs by detecting the attenuation of high-frequency bands. This type of method is limited by high-resolution time-frequency analysis methods, and the resolution of fluid detection is usually relatively limited.

[0075] Fluid detection in complex, narrow-channel tight sandstone gas reservoirs and fractured reservoirs presents significant challenges. Like fractured reservoirs, complex, narrow-channel reservoirs exhibit spatial anisotropy. Furthermore, the AVO (Active Voorheological Value) characteristics of these reservoirs vary spatially due to differences in reservoir tightness. This makes existing methods inadequate for most applications, resulting in slow progress in fluid detection.

[0076] To address the problems existing in related technologies, this application provides a method for determining fluid detection properties. This method is applied to electronic devices, such as computers and mobile terminals. The functions implemented by the method for determining fluid detection properties provided in this application can be achieved by the processor of the electronic device calling program code, wherein the program code can be stored in a computer storage medium.

[0077] Example 1

[0078] This application provides a method for determining fluid detection properties. Figure 1 This is a schematic diagram illustrating the implementation process of a method for determining fluid detection properties provided in an embodiment of this application, as shown below. Figure 1 As shown, it includes the following steps:

[0079] Step S101: Obtain the AVO pre-stack gather data for the target region.

[0080] In this embodiment of the application, the target area can be a region with spatial anisotropic characteristics and where the AVO characteristics are constantly changing in space. For example, the target area can be a region with a thin and narrow channel tight sandstone gas reservoir or a fractured reservoir.

[0081] In this application embodiment, AVO pre-stack gather data can be obtained through input from an input device. In some embodiments, AVO pre-stack gather data can be obtained through the Internet.

[0082] Step S102: The AVO pre-stack gather data are stacked based on the azimuth and incident angle to obtain the stacked seismic data volume.

[0083] In this embodiment, there can be n azimuth angles and m incident angles. For example, n = 4, representing four azimuths, defined as n1 = 0, n2 = 45°, n3 = 90°, n4 = 135° respectively; m = 3, representing three angles, defined as m1 = 10°, m2 = 20°, m3 = 30° respectively. In this embodiment, the azimuth angles and incident angles can be configured.

[0084] In this embodiment, the superimposed seismic data volume includes m*n superimposed seismic data volumes, and each superimposed seismic data volume can be represented as: Seis m*n (x,y,t,azi n ,ang m ), where x represents the inline direction of the seismic data grid, y represents the xline direction of the seismic data grid, and t is the time of the time-domain seismic data. azi n It represents a total of n directions, ang m This represents dividing the incident angles into m.

[0085] Step S103: Determine the relative impedance data volume corresponding to each azimuth angle based on the superimposed seismic data volume.

[0086] In this embodiment of the application, well-seismic calibration can be performed on the stacked seismic data volume corresponding to each azimuth angle; wavelets corresponding to each azimuth angle can be extracted based on the stacked seismic data volume after well-seismic calibration; impedance inversion can be performed on the wavelets corresponding to each azimuth angle to determine the relative impedance volume data corresponding to each azimuth angle.

[0087] Continuing with the example above, taking the stacked seismic data corresponding to incident angle m1 as an example, the stacked seismic data corresponding to incident angle m1 is: A total of n azimuth angles of stacked seismic data are collected. Well-seismic calibration is performed on the stacked seismic data for each azimuth angle, and wavelets corresponding to each azimuth angle are extracted. Impedance inversion is then performed on the wavelets corresponding to each azimuth angle to obtain the relative impedance data for each azimuth angle. In this embodiment, the impedance inversion of the wavelets corresponding to each azimuth angle can be implemented using mature seismic inversion software such as Jason or NEWS. In this embodiment, the calibration of seismic attribute dimensions can be achieved through the above method. The relative impedance data volume of the n azimuth angles corresponding to the incident angle m1 can be represented as...

[0088] Step S104: Based on the relative impedance data volume corresponding to each azimuth angle, determine the elliptic flattening corresponding to each incident angle.

[0089] In this embodiment, the variation of the relative impedance data volume with the azimuth angle can be approximated as an ellipse in polar coordinates. Therefore, ellipse fitting can be performed based on the relative impedance data volume corresponding to each azimuth and each incident angle to obtain the ellipse feature value corresponding to each incident angle; the ellipse flattening corresponding to each incident angle can be determined based on the ellipse feature value corresponding to each incident angle.

[0090] Continuing with the example above, the relative impedance data volume based on the n azimuth angles corresponding to the incident angle m1 can be expressed as: based on An ellipse is fitted to the incident angle m1 to obtain ellipse feature values, which include: the length of the major axis, the length of the minor axis, and the angle between the major axis and the X-axis.

[0091] In this embodiment, the elliptic flattening can be calculated by dividing the major axis length by the minor axis length. In this embodiment, the elliptic flattening under the condition of incident angle m1 can be expressed as: Similarly, the elliptic flattening under other incident angle conditions can be calculated. LL.

[0092] Step S105: Determine the frequency domain properties of each anisotropic intensity based on the elliptic flattening corresponding to each incident angle.

[0093] Following the example above, the flattening of an ellipse can be represented by four-dimensional data. In this embodiment, step S105 can be implemented through the following steps:

[0094] Step S1051: Perform time-frequency analysis on the elliptic flattening corresponding to each incident angle to obtain five-dimensional data corresponding to each incident angle, wherein the five-dimensional data includes: frequency.

[0095] In this embodiment, time-frequency analysis represents a one-dimensional time signal as a two-dimensional function of time and frequency to reveal the frequency components contained in the signal and their characteristics of variation over time. Analyzing seismic signals using time-frequency analysis techniques can obtain important time-frequency domain information such as the time-spectrum while simultaneously acquiring instantaneous parameters such as instantaneous frequency, instantaneous phase, and instantaneous amplitude. This enables edge detection, attribute extraction, and fluid detection of seismic signals. Many time-frequency analysis methods are available, including STFT, Wigner-Ville distribution, S-transform, matched pursuit, and spectral inversion. A comprehensive analysis and comparison of the time-frequency analysis accuracy of different methods prioritizes matched pursuit and spectral inversion.

[0096] Continuing from the example above, based on time-frequency analysis, Rellipse can be... m (x,y,t,ang mExtending from four-dimensional to five-dimensional Rellipse m (x,y,t,ang m ,f), where f is the frequency.

[0097] Step S1052: Determine the frequency domain energy corresponding to each incident angle based on the frequency of the five-dimensional data corresponding to each incident angle.

[0098] In this embodiment of the application, the frequency domain energy corresponding to each incident angle can be calculated using a first calculation formula based on the frequency of the five-dimensional data corresponding to each incident angle. The first calculation formula includes:

[0099]

[0100] Where E(f) is the frequency domain energy, A is the amplitude constant, and f b is the bandwidth factor, and f is the frequency.

[0101] In this embodiment, the first calculation formula can be used to fit the asymmetric amplitude spectrum. By using the first calculation formula to determine the frequency domain energy corresponding to each incident angle, noise immunity can be improved, system errors can be reduced, and the accuracy of attenuation attribute extraction can be improved.

[0102] Step S1053: Determine the maximum frequency domain energy based on the frequency domain energy corresponding to each incident angle.

[0103] In this embodiment of the application, the maximum frequency domain energy E can be determined by analyzing the frequency domain energy corresponding to each incident angle. max .

[0104] Step S1054: Determine the frequency domain properties of each anisotropic intensity based on the maximum frequency domain energy.

[0105] In this embodiment of the application, the frequency domain properties of anisotropy intensity may include: high-frequency attenuation gradient, low-frequency attenuation gradient, combined frequency attenuation gradient, maximum frequency domain energy, and the instantaneous dominant frequency corresponding to the maximum frequency domain energy.

[0106] In this embodiment of the application, step S1054 can be implemented through the following steps:

[0107] Step S1: Multiply the maximum frequency domain energy by a first ratio to obtain the first frequency domain energy.

[0108] In this embodiment, the first ratio can be represented as A%, and the first frequency domain energy can be represented as: E max_A In this embodiment of the application, the first ratio can be configured; for example, the first ratio is 85%.

[0109] Step S2: Determine the first frequency domain energy corresponds to the first frequency and the second frequency.

[0110] By substituting the energy of the first frequency domain into the first calculation formula, two frequencies can be obtained, namely the first frequency and the second frequency.

[0111] In this embodiment of the application, the first frequency is greater than the second frequency.

[0112] Step S3: Multiply the maximum frequency domain energy by the second ratio to obtain the second frequency domain energy.

[0113] In this embodiment of the application, the first ratio can be expressed as B%, and the first frequency domain energy can be expressed as: E max_B .

[0114] Step S4: Determine the third and fourth frequencies corresponding to the energy in the second frequency domain, wherein the first ratio and the second ratio are different.

[0115] In this embodiment of the application, two frequencies can be obtained by substituting the energy of the second frequency domain into the first calculation formula, namely the third frequency and the fourth frequency.

[0116] In this embodiment of the application, the second ratio can be configured, for example, the second ratio is 55%.

[0117] Step S5: Determine the high-frequency attenuation gradient and the low-frequency attenuation gradient based on the first frequency, the second frequency, the third frequency, and the fourth frequency.

[0118] In this embodiment of the application, step S5 can be implemented through the following steps:

[0119] Step S51: Calculate the spectral area corresponding to the first frequency and the second frequency respectively.

[0120] In this embodiment of the application, the spectral area corresponding to the first frequency can be calculated by performing an integral operation based on the first frequency, and the spectral area corresponding to the second frequency can be calculated by performing an integral operation based on the second frequency.

[0121] Step S52: Calculate the high-frequency attenuation gradient based on the second calculation formula, wherein the second calculation formula is:

[0122]

[0123] Among them, G hf For high-frequency attenuation gradient, E max_A_h E is the spectral area corresponding to the first frequency. max_A_l f is the area of ​​the ground spectrum corresponding to the second frequency. A_h For the first frequency, f A_lThis is the second frequency.

[0124] Step S53: Calculate the corresponding spectral areas for the third frequency and the fourth frequency respectively.

[0125] In this embodiment of the application, the spectral area corresponding to the third frequency can be calculated by performing an integral operation based on the third frequency, and the spectral area corresponding to the fourth frequency can be calculated by performing an integral operation based on the fourth frequency.

[0126] Step S54: Calculate the low-frequency attenuation gradient based on the third formula, where the third formula is:

[0127]

[0128] Among them, G lf For low-frequency attenuation gradient, E max_B_h E represents the spectral area corresponding to the third frequency. max_B_l f is the spectral area corresponding to the fourth frequency. B_h For the third frequency, f B_l It is the fourth frequency.

[0129] Step S6: Obtain the combined frequency attenuation gradient based on the high-frequency attenuation gradient and the low-frequency attenuation gradient.

[0130] In this embodiment, the combined frequency attenuation gradient can be obtained by multiplying the high-frequency attenuation gradient and the low-frequency attenuation gradient. Continuing from the example above, G = G hf *G lf , where G is the combined frequency attenuation gradient.

[0131] The frequency domain properties of anisotropic intensity include: high-frequency attenuation gradient, low-frequency attenuation gradient, combined frequency attenuation gradient, maximum frequency domain energy, and the instantaneous dominant frequency corresponding to the maximum frequency domain energy. The maximum frequency domain energy can be the peak energy. Therefore, the frequency domain properties of anisotropic intensity corresponding to each incident angle can be expressed as:

[0132] Peak energy: E max (x,y,t,ang m );

[0133] Instantaneous clock speed: f h (x,y,t,ang m );

[0134] High-frequency attenuation gradient: G hf (x,y,t,ang m );

[0135] Low-frequency attenuation gradient: G lf (x,y,t,ang m );

[0136] And the combined frequency attenuation gradient: G(x,y,t,ang) m ).

[0137] Step S106: Extract the gradient properties of the frequency domain properties of each anisotropic intensity as a function of the incident angle to obtain the fluid detection properties of the target region.

[0138] In this embodiment, the frequency domain properties of each incident angle and each anisotropic intensity can be fitted to obtain the fitting equation of the frequency domain properties of each anisotropic intensity as a function of the incident angle; based on the fitting equation, the gradient properties of each anisotropic intensity frequency domain property as a function of the incident angle are determined.

[0139] Continuing from the example above, we analyze the frequency domain properties of anisotropic intensity as a function of the incident angle m, and extract the gradient properties of the frequency domain properties of anisotropic intensity as a function of the incident angle.

[0140] With E max (x,y,t,ang m Taking (e.g., using the least squares method, for each incident angle m1, m2, m3, L) The variation of L can be fitted linearly or logarithmically. Taking linear fitting as an example, the peak energy E max (x,y,t,ang m The variation of the incident angle m with the incident angle satisfies a linear fit, and the fitting equation can be expressed as: E max (x,y,t,ang m ) = g EVA (x,y,t)*ang m +b(x,y,t), where g EVA (x,y,t) represents the gradient property of the peak energy of the anisotropic intensity parameter in the frequency domain as a function of the incident angle. The gradient property of the peak energy as a function of the incident angle can indicate the fluid distribution characteristics under anisotropic conditions.

[0141] Similarly, g FVA (x,y,t) represents the gradient property of the anisotropic intensity parameter in the frequency domain as the instantaneous dominant frequency changes with the incident angle; g GhVA (x,y,t) represents the gradient property of the high-frequency attenuation gradient of the anisotropic intensity parameter in the frequency domain as a function of the incident angle; g GlVA (x,y,t) represents the gradient property of the low-frequency attenuation gradient of the anisotropic intensity parameter in the frequency domain as a function of the incident angle; g GVA (x,y,t) represents the gradient property of the combined frequency attenuation gradient of the anisotropic intensity parameters in the frequency domain as a function of the incident angle.

[0142] In the embodiments of this application, these gradient properties can characterize the distribution characteristics of fluids under anisotropic conditions.

[0143] In this embodiment, the sensitivity of these gradient attributes to fluid characterization varies for different geological conditions. By combining actual drilling analysis, the gradient attribute with the highest sensitivity can be selected as the fluid detection attribute for the target area, so as to detect fluid in the target area through the fluid detection attribute.

[0144] Example 2

[0145] Based on the foregoing embodiments, this application further provides a method for determining fluid detection properties. Figure 2 A flowchart illustrating another method for determining fluid detection properties provided in this application embodiment is shown below. Figure 2 As shown, the method includes:

[0146] Step S201: Wide azimuth amplitude preservation and AVO pre-stack gather data are stacked by azimuth and incident angle.

[0147] In this embodiment, based on wide-azimuth, amplitude-preserving, and AVO-preserving pre-stack gather data, azimuth- and incident-angle-based stacking is performed. It is assumed that the seismic data is stacked azimuth- and incident-angle-based to form Seis... m*n (x,y,t,azi n ,ang m A total of m*n stacked seismic data volumes are generated, where x represents the inline direction of the seismic data grid, y represents the xline direction of the seismic data grid, and t is the time of the time-domain seismic data. n This represents a total of n directions. For example, n=4, representing 4 directions, defined as n1=0, n2=45, n3=90, and n4=135 respectively. m The angle is divided into m incident angles. In this embodiment, m = 3, which means it is divided into 3 angles, defined as m1 = 10, m2 = 20, and m3 = 30 respectively. Figure 3 This is a schematic diagram of a small-angle well-crossing profile at an azimuth of 0-45° provided in an embodiment of this application. Figure 4 The 135-180° azimuth large-angle well profile provided in the embodiments of this application, in Figure 3 and Figure 4 In the diagram, the horizontal axis represents the track number, and the vertical axis represents time, such as... Figure 3 and Figure 4 It can be seen that data from different orientations and incident angles provide different characterizations of the reservoir, exhibiting certain anisotropic and AVO characteristics.

[0148] Step S202: Calculation of elliptic flattening under limited angle conditions.

[0149] Continuing with the example above, let's take a small angle (m1=10) stacked seismic data as an example. A total of four azimuth stacked datasets were used. Well-seismic calibration was performed on each azimuth stacked dataset, azimuth wavelets were extracted, and azimuth impedance inversion was conducted to obtain relative impedance data. This process can be implemented using mature seismic inversion software such as Jason and NEWS; the essence of this process is to calibrate the dimensions of seismic attributes. The relative impedance data volume corresponding to each azimuth is as follows:

[0150] The variation of impedance data with azimuth angle can be approximated as an ellipse in polar coordinates. For each CDP point in the reservoir, the relative impedance data corresponding to the n sub-azimuths under the incident angle m1 condition are... Ellipse fitting is performed, and three ellipse eigenvalues ​​are calculated: the length of the major axis, the length of the minor axis, and the angle between the major axis and the X-axis. Then, the ellipse flattening (major axis / minor axis) is obtained. Simultaneously, the ellipse flattening under the condition of a small angle m1 is recorded.

[0151] By analogy, the elliptic flattening under other incident angle conditions can be obtained. LL.

[0152] Step S203: Extraction of anisotropic intensity frequency domain attributes.

[0153] In this embodiment of the application, the extraction of anisotropic intensity frequency domain attributes can be achieved through the following steps:

[0154] Step S2031, for Rellipse m (x,y,t,ang m High-precision time-frequency analysis is performed.

[0155] There are many time-frequency analysis methods available, including STFT, Wigner-Ville distribution, S-transform, matched pursuit, and spectral inversion. Based on a comprehensive analysis and comparison of the time-frequency analysis accuracy of different methods, this embodiment adopts a time-frequency analysis method based on matched pursuit. Based on time-frequency analysis, we can... m (x,y,t,ang m Extending from four-dimensional to five-dimensional Rellipse m (x,y,t,ang m ,f).

[0156] Step S2032, calculate Rellipse m (x,y,t,ang m f) Frequency attribute.

[0157] Define Rellipse through calculation. m (x,y,t,ang m Let the frequency domain energy of f be E. Analyzing the relationship between E and frequency f, we can obtain the following parameters: a) Maximum frequency domain energy E max b) Instantaneous main frequency f h Defined as frequency energy with maximum E max c) The frequency of time; the corresponding maximum frequency domain energy E max The frequency energy E at 85% max_85 The corresponding frequency value at this time is f 85_h and f 85_l , and f 85_h >f 85_l Calculate the corresponding spectral area E max_85_h E max_85_l ;d) Corresponding to the maximum frequency domain energy E max The frequency energy E at 55% max_55 The corresponding frequency value at this time is f 55_h and f 55_l , and f 55_h >f 55_l Calculate the corresponding spectral area E max_55_h E max_55_l .

[0158] Further calculation of the high-frequency attenuation gradient:

[0159]

[0160] and low-frequency attenuation gradient:

[0161]

[0162] And the combined frequency attenuation gradient:

[0163] G = G hf *G lf

[0164] In this way, we obtain various properties of the anisotropic parameters in the frequency domain, including:

[0165] Peak energy: E max (x,y,t,ang m );

[0166] Instantaneous clock speed: f h (x,y,t,ang m );

[0167] High-frequency attenuation gradient: G hf (x,y,t,ang m );

[0168] Low-frequency attenuation gradient: G lf (x,y,t,ang m );

[0169] And the combined frequency attenuation gradient: G(x,y,t,ang) m ).

[0170] Figure 5 This is a schematic diagram of the frequency domain peak energy attribute through the well under small-angle conditions in the embodiment. Figure 6 This is a schematic diagram of the high-frequency attenuation gradient attribute in the frequency domain under small-angle conditions in the embodiment. Figure 5 and Figure 6 In the diagram, the horizontal axis represents the track number, and the vertical axis represents time.

[0171] Step S204: Extract the gradient properties of the frequency domain properties of each anisotropic intensity as a function of the incident angle.

[0172] For the different anisotropic intensity frequency domain properties in step S203, analyze their variation with the incident angle m, and extract the gradient properties of the anisotropic intensity frequency domain properties as a function of the incident angle.

[0173] With E max (x,y,t,ang m Taking (e.g., using the least squares method, for each incident angle m1, m2, m3, L) The variation of L can be fitted linearly or logarithmically. Taking linear fitting as an example, the peak energy E max (x,y,t,ang m The variation of the incident angle m with the linear fitting formula E max (x,y,t,ang m ) = g EVA (x,y,t)*ang m +b(x,y,t), g EVA (x,y,t) represents the gradient property of the peak energy of the anisotropic intensity parameter in the frequency domain as a function of the incident angle, which can usually indicate the characteristics of fluid distribution under anisotropic conditions.

[0174] Similarly, we can obtain:

[0175] g FVA (x,y,t) represents the gradient property of the anisotropic intensity parameter in the frequency domain as the instantaneous dominant frequency changes with the incident angle; g GhVA (x,y,t) represents the gradient property of the high-frequency attenuation gradient of the anisotropic intensity parameter in the frequency domain as a function of the incident angle; g GlVA(x,y,t) represents the gradient property of the low-frequency attenuation gradient of the anisotropic intensity parameter in the frequency domain as a function of the incident angle; g GVA (x,y,t) represents the gradient property of the combined frequency attenuation gradient of the anisotropic intensity parameters in the frequency domain as a function of the incident angle.

[0176] Step S205, gradient properties take priority.

[0177] In this embodiment, the sensitivity of these gradient attributes to fluid characterization varies for different locations. Based on actual drilling analysis, the azimuth anisotropic frequency-varying fluid factor that is most sensitive to the study area is ultimately selected. In this embodiment, the variation of high-frequency attenuation gradient attributes with angle, combined with actual drilling analysis, better reflects the reservoir fluid properties. Figure 7 This is a planar schematic diagram of the reservoir fluid properties corresponding to the high-frequency attenuation gradient attribute provided in the embodiments of this application, where the horizontal axis represents the line number and the vertical axis represents time.

[0178] The method for determining fluid detection attributes provided in this application addresses the challenge of fluid detection in complex, narrow-channel tight sandstone reservoirs, requiring comprehensive consideration of the influence of anisotropy and AVO variation characteristics. Therefore, based on wide-azimuth, amplitude-preserving, and AVO-preserving pre-stack data, it employs azimuth- and incident-angle-specific stacking, then calculates the anisotropic elliptic flattening under defined angle conditions. Furthermore, a high-precision time-frequency analysis method is used to extract the frequency domain attributes of the anisotropic intensity parameters. Finally, its gradient with angle variation is analyzed to obtain the fluid detection sensitive attributes. Detecting target areas using this fluid detection data improves fluid detection accuracy.

[0179] Example 3

[0180] Based on the foregoing embodiments, this application provides a device for determining fluid detection properties. The various modules and units included in the device can be implemented by a processor in a computer device; of course, they can also be implemented by specific logic circuits. In the implementation process, the processor can be a central processing unit (CPU), a microprocessor (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA), etc.

[0181] This application provides a device for determining fluid detection properties, the device comprising:

[0182] The acquisition module is used to acquire AVO pre-stack gather data for the target region;

[0183] The overlay module is used to overlay the AVO pre-stack gather data based on azimuth and incident angle to obtain a stacked seismic data volume;

[0184] The first determining module is used to determine the relative impedance data volume corresponding to each azimuth based on the superimposed seismic data volume;

[0185] The second determining module is used to determine the elliptic flattening corresponding to each incident angle based on the relative impedance data volume corresponding to each azimuth angle.

[0186] The third determination module is used to determine the frequency domain properties of each anisotropic intensity based on the elliptic flattening corresponding to each incident angle.

[0187] The extraction module is used to extract the gradient properties of the frequency domain properties of each anisotropic intensity as a function of the incident angle, so as to obtain the fluid detection properties of the target region.

[0188] In some embodiments, determining the relative impedance data volume corresponding to each azimuth based on the stacked seismic data volume includes:

[0189] Well-seismic calibration is performed on the stacked seismic data volume corresponding to each azimuth angle;

[0190] Wavelets corresponding to each azimuth angle are extracted from the stacked seismic data volume after well-seismic calibration.

[0191] Impedance inversion is performed on the wavelets corresponding to each azimuth angle to determine the relative impedance volume data corresponding to each azimuth angle.

[0192] In some embodiments, determining the elliptic flattening corresponding to each incident angle based on the relative impedance data volume corresponding to each azimuth angle includes:

[0193] Ellipse fitting is performed based on the relative impedance data volume corresponding to each orientation and each incident angle to obtain the ellipse characteristic value corresponding to each incident angle.

[0194] The elliptic flattening corresponding to each incident angle is determined based on the elliptic eigenvalues ​​corresponding to each incident angle.

[0195] In some embodiments, the elliptic flattening is represented by four-dimensional data, and the determination of the frequency domain properties of each anisotropic intensity based on the elliptic flattening corresponding to each incident angle includes:

[0196] Time-frequency analysis is performed on the elliptic flattening corresponding to each incident angle to obtain five-dimensional data corresponding to each incident angle, wherein the five-dimensional data includes: frequency;

[0197] Based on the frequency of the five-dimensional data corresponding to each incident angle, determine the frequency domain energy corresponding to each incident angle.

[0198] The maximum frequency domain energy is determined based on the frequency domain energy corresponding to each incident angle.

[0199] The frequency domain properties of each anisotropic intensity are determined based on the maximum frequency domain energy.

[0200] In some embodiments, determining the frequency domain energy corresponding to each incident angle based on the frequency of the five-dimensional data corresponding to each incident angle includes:

[0201] The frequency domain energy corresponding to each incident angle is calculated using a first formula based on the frequencies of the five-dimensional data corresponding to each incident angle, wherein the first formula includes:

[0202]

[0203] Where E(f) is the frequency domain energy, A is the amplitude constant, and f b is the bandwidth factor, and f is the frequency.

[0204] In some embodiments, determining the frequency domain properties of each anisotropic intensity based on the maximum frequency domain energy includes:

[0205] Multiply the maximum frequency domain energy by the first ratio to obtain the first frequency domain energy;

[0206] Determine the first frequency domain energy to correspond to the first frequency and the second frequency;

[0207] Multiply the maximum frequency domain energy by the second ratio to obtain the second frequency domain energy;

[0208] Determine the third and fourth frequencies corresponding to the energy in the second frequency domain, wherein the first ratio and the second ratio are different;

[0209] The high-frequency attenuation gradient and the low-frequency attenuation gradient are determined based on the first frequency, the second frequency, the third frequency, and the fourth frequency;

[0210] The combined frequency attenuation gradient is obtained based on the high-frequency attenuation gradient and the low-frequency attenuation gradient, wherein the anisotropic intensity frequency domain attributes include: high-frequency attenuation gradient, low-frequency attenuation gradient, combined frequency attenuation gradient, maximum frequency domain energy, and the instantaneous dominant frequency corresponding to the maximum frequency domain energy.

[0211] In some embodiments, the first ratio is A%, the second ratio is B%, the first frequency is greater than the second frequency, the third frequency is greater than the fourth frequency, and determining the high-frequency attenuation gradient and the low-frequency attenuation gradient based on the first frequency, the second frequency, the third frequency, and the fourth frequency includes:

[0212] Calculate the spectral area corresponding to the first frequency and the second frequency respectively;

[0213] The high-frequency attenuation gradient is calculated based on the second formula, which is:

[0214]

[0215] Among them, G hf For high-frequency attenuation gradient, E max_A_h E is the spectral area corresponding to the first frequency. max_A_l f is the area of ​​the ground spectrum corresponding to the second frequency. A_h For the first frequency, f A_l The second frequency;

[0216] Calculate the spectral area corresponding to the third frequency and the fourth frequency respectively;

[0217] The low-frequency attenuation gradient is calculated based on the third formula, which is:

[0218]

[0219] Among them, E max_B_h E represents the spectral area corresponding to the third frequency. max_B_l f is the spectral area corresponding to the fourth frequency. B_h For the third frequency, f B_l It is the fourth frequency.

[0220] In some embodiments, extracting the gradient properties of each anisotropic intensity frequency domain property as a function of the incident angle includes:

[0221] By fitting the frequency domain properties of each incident angle and each anisotropic intensity, the fitting equations of the frequency domain properties of each anisotropic intensity as a function of the incident angle are obtained.

[0222] Based on the fitted equation, the gradient properties of the frequency domain properties of each anisotropic intensity as a function of the incident angle are determined.

[0223] It should be noted that, in the embodiments of this application, if the above-described method for determining fluid detection attributes is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiments of this application, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), magnetic disks, or optical disks. Thus, the embodiments of this application are not limited to any specific hardware and software combination.

[0224] Accordingly, this application provides a storage medium storing a computer program thereon, characterized in that the computer program, when executed by a processor, implements the steps in the method for determining fluid detection attributes provided in the above embodiments.

[0225] Example 4

[0226] This application provides an electronic device; Figure 8 This is a schematic diagram of the composition structure of the electronic device provided in the embodiments of this application, such as... Figure 8 As shown, the electronic device 700 includes: a processor 701, at least one communication bus 702, a user interface 703, at least one external communication interface 704, and a memory 705. The communication bus 702 is configured to enable communication between these components. The user interface 703 may include a display screen, and the external communication interface 704 may include standard wired and wireless interfaces. The processor 701 is configured to execute a program stored in the memory for determining fluid detection attributes, to implement the steps in the method for determining fluid detection attributes provided in the above embodiment.

[0227] The descriptions of the display device and storage medium embodiments above are similar to those of the method embodiments above, and have similar beneficial effects. For technical details not disclosed in the computer device and storage medium embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0228] It should be noted that the descriptions of the storage medium and device embodiments above are similar to those of the method embodiments above, and have similar beneficial effects. For technical details not disclosed in the storage medium and device embodiments of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0229] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above-described processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the above-described embodiments are merely descriptive and do not represent the superiority or inferiority of the embodiments.

[0230] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0231] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0232] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0233] In addition, each functional unit in the various embodiments of this application can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0234] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0235] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a controller to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0236] The above description is merely an embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for determining fluid detection properties, characterized in that, include: Acquire AVO pre-stack gather data for the target region; The AVO pre-stack gather data are stacked based on the azimuth and incident angle to obtain the stacked seismic data volume. Based on the superimposed seismic data volume, determine the relative impedance data volume corresponding to each azimuth angle; Based on the relative impedance data volume corresponding to each azimuth angle, the elliptic flattening corresponding to each incident angle is determined. The frequency domain properties of each anisotropic intensity are determined based on the elliptic flattening corresponding to each incident angle. The elliptic flattening is represented by four-dimensional data, including: Time-frequency analysis is performed on the elliptic flattening corresponding to each incident angle to obtain five-dimensional data corresponding to each incident angle, wherein the five-dimensional data includes: frequency; Based on the frequency of the five-dimensional data corresponding to each incident angle, determine the frequency domain energy corresponding to each incident angle. The maximum frequency domain energy is determined based on the frequency domain energy corresponding to each incident angle. The frequency domain properties of each anisotropic intensity are determined based on the maximum frequency domain energy. The anisotropic intensity frequency domain attributes include: high-frequency attenuation gradient, low-frequency attenuation gradient, combined frequency attenuation gradient, maximum frequency domain energy, and the instantaneous dominant frequency corresponding to the maximum frequency domain energy. The gradient properties of the frequency domain properties of each anisotropic intensity as a function of the incident angle are extracted to obtain the fluid detection properties of the target region.

2. The method according to claim 1, characterized in that, The determination of the relative impedance data volume corresponding to each azimuth angle based on the superimposed seismic data volume includes: Well-seismic calibration is performed on the stacked seismic data volume corresponding to each azimuth angle; Wavelets corresponding to each azimuth angle are extracted from the stacked seismic data volume after well-seismic calibration. Impedance inversion is performed on the wavelets corresponding to each azimuth angle to determine the relative impedance volume data corresponding to each azimuth angle.

3. The method according to claim 1, characterized in that, The determination of the elliptic flattening corresponding to each incident angle based on the relative impedance data volume corresponding to each azimuth angle includes: Ellipse fitting is performed based on the relative impedance data volume corresponding to each azimuth angle and each incident angle to obtain the ellipse eigenvalues ​​corresponding to each incident angle. The elliptic flattening corresponding to each incident angle is determined based on the elliptic eigenvalues ​​corresponding to each incident angle.

4. The method according to claim 1, characterized in that, Based on the frequencies of the five-dimensional data corresponding to each incident angle, the frequency domain energy corresponding to each incident angle is determined, including: Based on the frequencies of the five-dimensional data corresponding to each incident angle, the frequency domain energy corresponding to each incident angle is calculated using a first calculation formula, wherein the first calculation formula includes: ； in, Here, A is the frequency domain energy, and A is the amplitude constant. For bandwidth factor, Let n be the frequency and n be the symmetry exponent.

5. The method according to claim 4, characterized in that, The determination of the frequency domain properties of each anisotropic intensity based on the maximum frequency domain energy includes: Multiply the maximum frequency domain energy by the first ratio to obtain the first frequency domain energy; Determine the first frequency domain energy to correspond to the first frequency and the second frequency; Multiply the maximum frequency domain energy by the second ratio to obtain the second frequency domain energy; Determine the second frequency domain energy to correspond to the third and fourth frequencies, wherein the first ratio and the second ratio are different; The high-frequency attenuation gradient and the low-frequency attenuation gradient are determined based on the first frequency, the second frequency, the third frequency, and the fourth frequency; The combined frequency attenuation gradient is obtained based on the high-frequency attenuation gradient and the low-frequency attenuation gradient.

6. The method according to claim 5, characterized in that, The first ratio is A%, the second ratio is B%, the first frequency is greater than the second frequency, the third frequency is greater than the fourth frequency, and the step of determining the high-frequency attenuation gradient and the low-frequency attenuation gradient based on the first frequency, the second frequency, the third frequency, and the fourth frequency includes: Calculate the spectral area corresponding to the first frequency and the second frequency respectively; The high-frequency attenuation gradient is calculated based on the second formula, which is: ； in, For high-frequency attenuation gradient, The area of ​​the spectrum corresponding to the first frequency. This represents the area of ​​the ground spectrum corresponding to the second frequency. For the first frequency, The second frequency; Calculate the spectral area corresponding to the third frequency and the fourth frequency respectively; The low-frequency attenuation gradient is calculated based on the third formula, which is: ; in, For low-frequency attenuation gradient, The spectral area corresponding to the third frequency. The spectral area corresponding to the fourth frequency. The third frequency, It is the fourth frequency.

7. The method according to claim 1, characterized in that, The extraction of the gradient properties of each anisotropic intensity frequency domain property as a function of the incident angle includes: By fitting the frequency domain properties of each incident angle and each anisotropic intensity, the fitting equations of the frequency domain properties of each anisotropic intensity as a function of the incident angle are obtained. Based on the fitted equation, the gradient properties of the frequency domain properties of each anisotropic intensity as a function of the incident angle are determined.

8. A device for determining fluid detection properties, characterized in that, include: The acquisition module is used to acquire AVO pre-stack gather data for the target region; The overlay module is used to overlay the AVO pre-stack gather data based on azimuth and incident angle to obtain a stacked seismic data volume; The first determining module is used to determine the relative impedance data volume corresponding to each azimuth based on the superimposed seismic data volume; The second determining module is used to determine the elliptic flattening corresponding to each incident angle based on the relative impedance data volume corresponding to each azimuth angle. The third determining module is used to determine the frequency domain attributes of each anisotropic intensity based on the elliptic flattening corresponding to each incident angle. The elliptic flattening is represented by four-dimensional data, including: Time-frequency analysis is performed on the elliptic flattening corresponding to each incident angle to obtain five-dimensional data corresponding to each incident angle, wherein the five-dimensional data includes: frequency; Based on the frequency of the five-dimensional data corresponding to each incident angle, determine the frequency domain energy corresponding to each incident angle. The maximum frequency domain energy is determined based on the frequency domain energy corresponding to each incident angle. The frequency domain properties of each anisotropic intensity are determined based on the maximum frequency domain energy. The anisotropic intensity frequency domain attributes include: high-frequency attenuation gradient, low-frequency attenuation gradient, combined frequency attenuation gradient, maximum frequency domain energy, and the instantaneous dominant frequency corresponding to the maximum frequency domain energy. The extraction module is used to extract the gradient properties of the frequency domain properties of each anisotropic intensity as a function of the incident angle, so as to obtain the fluid detection properties of the target region.

9. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program that, when executed by the processor, performs the method for determining fluid detection attributes as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The computer program stored in the storage medium can be executed by one or more processors and can be used to implement the method for determining fluid detection properties as described in any one of claims 1 to 7.

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