Method and device for identifying fracture-cavity bodies based on carbonate reservoirs

Abstract

The application provides a carbonate reservoir-based fracture-cave body identification method and device, and the carbonate reservoir-based fracture-cave body identification method comprises the following steps: extracting diffracted waves of different directions of a target work area obtained in advance; calculating directional gradients of the diffracted waves in different directions according to the diffracted waves of different directions; calculating gradient energy and gradient energy entropy of the diffracted waves according to the directional gradients, so as to identify the fracture-cave body of the target work area. The application directly uses diffracted wave data and extracts strong attributes for identifying the non-homogeneous fracture-cave body, thereby improving the identification ability of the fracture-cave body near the stratigraphic boundary.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of oil and gas field geophysical exploration technology, and particularly relates to a fracture-cave body identification method and device based on a carbonate reservoir. BACKGROUND

[0002] At present, the fracture-cave bodies in the reservoirs of major carbonate oil and gas fields are important oil and gas storage spaces and exploration and development targets. Since the fracture-cave bodies appear as weak energy diffracted wave features of "beads" of different sizes and energies on a seismic profile, and are fused with strong energy reflected wave features of a large set of stratigraphic interfaces to form a full wave field seismic profile, it is one of the important works for carbonate fracture-cave reservoir prediction to use seismic data and related attributes to depict the fracture-cave body boundaries.

[0003] In recent years, the full wave field seismic attribute depiction method has achieved good results in carbonate reservoir prediction, including using coherence, curvature, ant body and amplitude variation rate to predict sweet spots in carbonate reservoirs. However, due to the strong energy of the reflection phase axis at the stratigraphic interface in conventional full wave field seismic data, the weak energy diffracted wave information generated by the underlying heterogeneous fracture-cave bodies is shielded, resulting in insufficient identification ability of the fracture-cave bodies, which cannot meet the current needs of qualitative identification of fracture-caves in carbonate reservoirs, especially in heterogeneous reservoirs. SUMMARY

[0004] One purpose of the present application is to provide a fracture-cave body identification method based on a carbonate reservoir. The method is combined with the high resolution, low signal-to-noise ratio characteristics of diffracted wave data and the imaging advantages of diffracted wave on fracture-cave reservoirs to improve the identification accuracy of carbonate reservoir fracture-caves. The method first extracts diffracted wave seismic data components along three directions; then based on the properties of the Gaussian function and convolution, the diffracted wave components are respectively convolved with the first-order derivative of the Gaussian function to obtain the diffracted wave gradient after filtering in three directions; finally, the diffracted wave directional gradient is focused and fused into gradient energy, and the corresponding diffracted wave gradient energy entropy is calculated, so as to improve the identification accuracy of carbonate reservoir fracture-caves based on the gradient energy and gradient energy entropy of diffracted wave.

[0005] Another purpose of the present application is to provide a fracture-cave body identification device based on a carbonate reservoir. Still another purpose of the present application is to provide a computer device including a memory and a processor, the memory storing a computer program, and the processor implementing the steps of the above-mentioned fracture-cave body identification method based on a carbonate reservoir when executing the computer program. Still another purpose of the present application is to provide a readable medium having a computer program stored thereon, the computer program being executed by the processor to implement the steps of the above-mentioned fracture-cave body identification method based on a carbonate reservoir.

[0006] To achieve the above object, the application discloses a fracture-cave body identification method based on a carbonate reservoir, comprising:

[0007] Extracting components of diffracted waves in different directions of a target work area obtained in advance;

[0008] Correspondingly calculating directional gradients of the diffracted waves in different directions according to the components of the diffracted waves in different directions;

[0009] Calculating gradient energy and gradient energy entropy of the diffracted waves according to the directional gradients to identify fracture-cave bodies of the target work area.

[0010] In some embodiments of the application, the components of the diffracted waves in different directions include:

[0011] Components of the diffracted waves in line directions of a seismic data network of the target work area, components of the diffracted waves in seismic trace directions of the seismic data network, and components of the diffracted waves in directions perpendicular to the seismic data network.

[0012] In some embodiments of the application, the diffracted waves of the target work area obtained include the following steps:

[0013] Performing diffracted wave separation on a three-dimensional seismic data volume of the target work area to obtain the diffracted waves.

[0014] In some embodiments of the application, the fracture-cave body identification method based on the carbonate reservoir further includes:

[0015] Calculating derivatives of the components of the diffracted waves in different directions in different directions.

[0016] In some embodiments of the application, the corresponding calculation of the directional gradients of the diffracted waves in different directions according to the components of the diffracted waves in different directions includes:

[0017] Calculating one-dimensional Gaussian functions of the diffracted waves in the different directions;

[0018] Calculating the directional gradients of the diffracted waves in different directions according to the derivatives of the components of the diffracted waves in different directions and the one-dimensional Gaussian functions of the corresponding directions.

[0019] In some embodiments of the application, the fracture-cave body identification method based on the carbonate reservoir further includes:

[0020] Fusing the directional gradients of the diffracted waves in different directions to calculate the gradient energy;

[0021] Calculating the gradient energy entropy of the diffracted waves according to the gradient energy.

[0022] In some embodiments of the present application, gradient energy and gradient energy entropy of the diffracted wave are calculated according to the directional gradient to identify the fracture-vug body of the target work area, comprising:

[0023] The fracture-vug body profile and distribution rule are described according to the gradient energy and the gradient energy entropy.

[0024] The present application further discloses a fracture-vug body identification device based on a carbonate reservoir, comprising:

[0025] A diffracted wave component extraction module is configured to extract components of the diffracted wave of the target work area in different directions;

[0026] A directional gradient calculation module is configured to calculate directional gradients of the diffracted wave in different directions according to the components of the diffracted wave in different directions;

[0027] A fracture-vug body identification module is configured to calculate gradient energy and gradient energy entropy of the diffracted wave according to the directional gradient to identify the fracture-vug body of the target work area.

[0028] In some embodiments of the present application, the components of the diffracted wave in different directions comprise:

[0029] The component of the diffracted wave in the line direction of the seismic data network of the target work area, the component of the seismic data network in the seismic trace direction, and the component in the direction perpendicular to the seismic data network.

[0030] In some embodiments of the present application, the fracture-vug body identification device based on the carbonate reservoir further comprises:

[0031] A diffracted wave acquisition module is configured to acquire the diffracted wave of the target work area;

[0032] The diffracted wave acquisition module comprises:

[0033] A diffracted wave acquisition unit is configured to separate the diffracted wave from the three-dimensional seismic data volume of the target work area to acquire the diffracted wave.

[0034] In some embodiments of the present application, the fracture-vug body identification device based on the carbonate reservoir further comprises:

[0035] A derivative calculation module is configured to calculate derivatives of the components of the diffracted wave in different directions in different directions.

[0036] In some embodiments of the present application, the directional gradient calculation module comprises:

[0037] A Gaussian function calculation unit is configured to calculate one-dimensional Gaussian functions of the diffracted wave in the different directions;

[0038] The directional gradient obtaining unit is configured to obtain directional gradients of the diffracted wave in different directions according to derivatives of the components of the wave in different directions and one-dimensional Gaussian functions corresponding to the directions.

[0039] In some embodiments of the present application, the fracture-cave body identification device based on carbonate reservoirs further comprises:

[0040] The gradient energy obtaining module is configured to fuse the directional gradients of the diffracted wave in different directions to obtain the gradient energy.

[0041] The gradient energy entropy obtaining module is configured to obtain the gradient energy entropy of the diffracted wave according to the gradient energy.

[0042] In some embodiments of the present application, the fracture-cave body identification module comprises:

[0043] The fracture-cave body identification unit is configured to describe the fracture-cave body profile and distribution law according to the gradient energy and the gradient energy entropy.

[0044] The present application further discloses a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor,

[0045] The processor implements the following method when executing the program.

[0046] The components of the diffracted wave in different directions of a target work area are extracted in advance;

[0047] The directional gradients of the diffracted wave in different directions are obtained according to the components of the diffracted wave in different directions;

[0048] The gradient energy and the gradient energy entropy of the diffracted wave are obtained according to the directional gradients to identify the fracture-cave body of the target work area.

[0049] In some embodiments of the present application, the components of the diffracted wave in different directions comprise:

[0050] The components of the diffracted wave in the line direction of a seismic data network of the target work area, the components of the diffracted wave in the seismic trace direction of the seismic data network and the components of the diffracted wave in the direction perpendicular to the seismic data network.

[0051] In some embodiments of the present application, the diffracted wave of the target work area obtained comprises the following steps:

[0052] The diffracted wave is obtained by performing diffracted wave separation on a three-dimensional seismic data body of the target work area.

[0053] In some embodiments of the present application, the fracture-cave body identification method based on carbonate reservoirs further comprises:

[0054] Derivatives of the components of the diffracted wave in different directions are calculated.

[0055] In some embodiments of the present application, the directional gradients of the diffracted wave in different directions are calculated according to the components of the diffracted wave in different directions, comprising:

[0056] A one-dimensional Gaussian function of the diffracted wave in the different directions is calculated.

[0057] The directional gradients of the diffracted wave in different directions are calculated according to the derivatives of the components of the diffracted wave in different directions and the one-dimensional Gaussian function of the corresponding direction.

[0058] In some embodiments of the present application, the method for identifying fracture-cave bodies based on carbonate reservoirs further comprises:

[0059] The directional gradients of the diffracted wave in different directions are fused to calculate the gradient energy.

[0060] The gradient energy entropy of the diffracted wave is calculated according to the gradient energy.

[0061] In some embodiments of the present application, the gradient energy and the gradient energy entropy of the diffracted wave are calculated according to the directional gradients to identify the fracture-cave bodies in the target work area, comprising:

[0062] The fracture-cave body profile and distribution rule are described according to the gradient energy and the gradient energy entropy.

[0063] The present application further discloses a computer readable medium, which has a computer program stored thereon,

[0064] The program is executed by a processor to implement the following method.

[0065] The components of the diffracted wave in different directions of a target work area previously acquired are extracted.

[0066] The directional gradients of the diffracted wave in different directions are calculated according to the components of the diffracted wave in different directions.

[0067] The gradient energy and the gradient energy entropy of the diffracted wave are calculated according to the directional gradients to identify the fracture-cave bodies in the target work area.

[0068] In some embodiments of the present application, the components of the diffracted wave in different directions comprise:

[0069] The components of the diffracted wave in the line direction of a seismic data network in the target work area, the components of the diffracted wave in the seismic trace direction of the seismic data network and the components of the diffracted wave in the direction perpendicular to the seismic data network.

[0070] In some embodiments of the present application, the diffraction wave of the target work area is obtained by the following steps:

[0071] The diffraction wave of the target work area is separated from the three-dimensional seismic data volume to obtain the diffraction wave.

[0072] In some embodiments of the present application, the method for identifying the fracture-cave body based on the carbonate reservoir further comprises:

[0073] Derivatives of the components of the diffraction wave in different directions are calculated.

[0074] In some embodiments of the present application, the directional gradient of the diffraction wave in different directions is calculated according to the components of the diffraction wave in different directions, comprising:

[0075] A one-dimensional Gaussian function of the diffraction wave in the different directions is calculated.

[0076] The directional gradient of the diffraction wave in different directions is calculated according to the derivatives of the components of the diffraction wave in different directions and the one-dimensional Gaussian function of the corresponding direction.

[0077] In some embodiments of the present application, the method for identifying the fracture-cave body based on the carbonate reservoir further comprises:

[0078] The directional gradients of the diffraction wave in different directions are fused to calculate the gradient energy.

[0079] The gradient energy entropy of the diffraction wave is calculated according to the gradient energy.

[0080] In some embodiments of the present application, the gradient energy and the gradient energy entropy of the diffraction wave are calculated according to the directional gradients to identify the fracture-cave body of the target work area, comprising:

[0081] The fracture-cave body profile and distribution rule are described according to the gradient energy and the gradient energy entropy.

[0082] As can be seen from the above description, the method and device for identifying the fracture-cave body based on the carbonate reservoir provided by the embodiments of the present application first extract the components of the diffraction wave in different directions of the target work area obtained in advance; then, the directional gradient of the diffraction wave in different directions is calculated according to the components of the diffraction wave in different directions; finally, the gradient energy and the gradient energy entropy of the diffraction wave are calculated according to the directional gradient to identify the fracture-cave body of the target work area.

[0083] The present application directly uses the diffraction wave data and extracts the targeted attribute to identify the heterogeneous fracture-cave body, thereby improving the identification ability of the fracture-cave body near the stratigraphic boundary. BRIEF DESCRIPTION OF DRAWINGS

[0084] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without any creative effort based on these drawings.

[0085] Figure 1 A flowchart of the fracture-cave body identification method based on carbonate reservoirs in embodiment one of the present application;

[0086] Figure 2 Another flowchart of the fracture-cave body identification method based on carbonate reservoirs in embodiment one of the present application;

[0087] Figure 3 A third flowchart of the fracture-cave body identification method based on carbonate reservoirs in embodiment one of the present application;

[0088] Figure 4 A flowchart of step 200 in the fracture-cave body identification method based on carbonate reservoirs in embodiment one of the present application;

[0089] Figure 5 A fourth flowchart of the fracture-cave body identification method based on carbonate reservoirs in embodiment one of the present application;

[0090] Figure 6 A flowchart of step 300 in the fracture-cave body identification method based on carbonate reservoirs in embodiment one of the present application;

[0091] Figure 7 A flowchart of the fracture-cave body identification method based on carbonate reservoirs in embodiment two of the present application;

[0092] Figure 8 A mind map of the fracture-cave body identification method based on carbonate reservoirs in embodiment two of the present application;

[0093] Figure 9 A time-domain full-wavefield seismic profile in embodiment two of the present application;

[0094] Figure 10 A time-domain diffraction wave seismic profile in embodiment two of the present application;

[0095] Figure 11 A time-domain diffraction wave x-direction gradient profile in embodiment two of the present application;

[0096] Figure 12 A time-domain diffraction wave y-direction gradient profile in embodiment two of the present application;

[0097] Figure 13 Time domain diffraction wave t direction gradient profile in the second embodiment of the present application;

[0098] Figure 14 Time domain diffraction wave gradient energy profile in the second embodiment of the present application;

[0099] Figure 15 Time domain diffraction wave gradient energy entropy profile in the second embodiment of the present application;

[0100] Figure 16 Time domain diffraction wave gradient energy entropy plane in the second embodiment of the present application;

[0101] Figure 17 Structure schematic diagram of the fracture-cave body identification device based on carbonate reservoir in the third embodiment of the present application;

[0102] Figure 18 Structure schematic diagram of the electronic device in the fourth embodiment of the present application. DETAILED DESCRIPTION

[0103] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0104] It should be noted that the terms "comprising" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device comprising a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to the process, method, product or device. The embodiments in the present application and the features in the embodiments can be combined with each other without conflict. The present application will be described in detail below with reference to the drawings and in combination with the embodiments.

[0105] The acquisition, storage, use, processing and the like of data in the technical solutions of the present application all comply with the relevant provisions of laws and regulations.

[0106] Embodiment one

[0107] In the prior art, the energy of the reflection phase axis at the stratigraphic interface of the conventional full wave field seismic data is strong, which can shield the weak energy diffraction wave information generated by the non-homogeneous fracture and hole body in the underlying stratum, resulting in insufficient identification ability of the fracture and hole body, and cannot meet the current problem of qualitative identification of non-homogeneous reservoir fractures and holes. Figure 1 Based on this, as shown in the present application, a fracture and hole body identification method based on a carbonate reservoir is provided, which comprises:

[0108] Step 100: Extracting the components of the diffraction wave in different directions of the pre-acquired target work area;

[0109] Diffracted wave refers to any small or comparable inhomogeneous body to seismic wave wavelength, such as fault block, fault edge, which can be regarded as a diffraction point, and the wave generated when the seismic wave passes through the diffraction point. According to Huygens principle, during the propagation of seismic wave, any irregular body on the interface, such as fault edge point, stratum pinch-out point, protrusion point on unconformable surface, etc., when the seismic wave passes through these elastic discontinuous points, it is also the same as the diffraction phenomenon in optics, and this discontinuous point can be regarded as a new source, from which a new disturbance is generated and propagates to the elastic space. This disturbance wave is called diffraction wave.

[0110] Diffracted wave is divided into narrow sense diffraction wave and broad sense diffraction wave. The basic view of physical seismology believes that diffraction is the most basic, and reflected wave is the sum of diffraction waves generated by all small area elements on the reflection interface, which is called broad sense diffraction. Any small or comparable inhomogeneous body to seismic wave wavelength, such as fault block, fault edge, can be regarded as a diffraction point, and the diffracted wave (diffracted wave) generated when the seismic wave passes through the diffraction point is narrow sense diffraction, which is characterized by the fact that the seismic wave energy seems to be from the diffraction point, which causes the tail of the reflected wave near the fault, and makes the determination of the fault point complex. The diffracted wave has the following characteristics:

[0111] 1. The time-distance curve of the diffracted wave is a hyperbola, and the bending degree is larger than that of the reflected wave time-distance curve;

[0112] 2. The minimum point of the time-distance curve is directly above the diffraction point, and the diffraction line is generated by the diffraction point. The minimum point of the diffracted wave time-distance curve is directly above the diffraction point, and the diffracted wave time-distance curve is tangent to the reflected wave time-distance curve;

[0113] 3. In the simple case of stratum level, the minimum point position of the diffracted wave phase axis indicates the fault point position; the minimum point of the diffracted wave is tangent to the reflected wave; in the case of stratum inclination, the tangent point is not at the minimum point;

[0114] 4. When the profile line is oblique to the fault trend, the diffracted wave is slow;

[0115] 5. When the energy of diffraction waves is strong, it sometimes seriously masks and interferes with the reflected waves in seismic records. It can be eliminated through combination, multiple coverage and superposition.

[0116] Step 200: deriving directional gradients of the diffracted wave in different directions according to the components of the diffracted wave in different directions;

[0117] Preferably, the different directions in step 200 include x, y and z directions in the seismic network, and the z direction is also called t (time) direction.

[0118] Step 300: Calculating the gradient energy and gradient energy entropy of the diffraction wave according to the directional gradient to identify the fracture-cavity body in the target work area;

[0119] Fractures and vugs in carbonate rocks refer to voids or cracks formed within carbonate rock formations. Carbonate rocks are primarily composed of carbonate minerals, such as calcite and dolomite. Due to the high solubility and breakability of carbonate rocks, various fissures and voids are formed when subjected to geomechanical and hydrogeological processes. These fractures and vugs can be tiny cracks, pores, conduits, or caves, ranging in size from microns to meters. They can be formed by geological processes such as pressure release, dissolution, joint development, and thermal expansion and contraction of the rock layer. Fractures and vugs in carbonate rocks are of great significance to water flow, oil and gas storage, and migration, and have a significant impact on oil and gas exploration and development.

[0120] As can be seen from the above description, the method for identifying fractures and caves in carbonate reservoirs provided by an embodiment of the present invention first extracts the components of the diffraction waves in different directions of the target work area obtained in advance; then, the directional gradients of the diffraction waves in different directions are calculated based on the components of the diffraction waves in different directions; finally, the gradient energy and gradient energy entropy of the diffraction waves are calculated based on the directional gradients to identify the fractures and caves in the target work area.

[0121] In view of the low signal-to-noise ratio of diffraction waves, the present invention, based on the properties of Gaussian functions and convolution, convolves the diffraction wave components with the first-order derivative of the Gaussian function respectively. This can filter the diffraction wave components in three directions to suppress noise while obtaining the diffraction wave gradients in the corresponding directions. On the other hand, to address the problem of high resolution of diffraction waves and relatively scattered data, the present invention focuses and fuses the directional gradients of the diffraction waves into gradient energy, and calculates the corresponding diffraction wave gradient energy entropy, thereby improving the accuracy of carbonate reservoir fracture and cavity identification.

[0122] In some embodiments of the present invention, the components of the diffracted waves in different directions in step 100 include:

[0123] The component of the diffracted wave in the line direction (x direction) of the seismic data network of the target work area, the component of the seismic data network in the seismic trace direction (y direction), and the component in the direction perpendicular to the seismic data network (z direction, i.e., the depth direction).

[0124] It can be understood that the seismic network generates seismic waves by sending a controlled seismic source (such as a seismic source vehicle, explosives, a seismic machine, etc.) and records on a sensor. The seismic data recorded by the sensor is processed and analyzed to obtain information about the underground geological structure, the location, shape and properties of the oil and gas reservoir, etc. Specifically, the following information can be obtained through the seismic network:

[0125] Underground geological structure: Seismic waves will be reflected and refracted between different rock layers and media, and the characteristics of the reflected and refracted waves can be analyzed to infer the underground geological structure and reservoir distribution.

[0126] Oil and gas reservoir: Oil and gas reservoirs usually have different seismic properties, and the characteristics of the reservoir, including porosity, saturation, and elastic parameters, can be identified and described through seismic data analysis.

[0127] Oil and gas distribution: The seismic network can provide information about the approximate location, boundary and extent of the underground oil and gas layer, helping exploration personnel determine the potential yield and development plan of the oil and gas field.

[0128] In some embodiments of the present application, referring to Figure 2 The method for identifying fracture-vug bodies based on carbonate reservoirs further comprises:

[0129] Step 90: Diffracted wave separation is performed on the three-dimensional seismic data volume of the target work area to obtain the diffracted wave.

[0130] Specifically, diffracted wave separation is performed on the full-wavefield three-dimensional seismic data volume of the target work area to obtain a diffracted wave three-dimensional seismic data volume.

[0131] Further, diffracted wave separation is performed on a full-wavefield three-dimensional seismic data volume S(x, y, t) with a time length T to obtain a diffracted wave three-dimensional seismic data volume D(x, y, t), where t = 0, 1, 2, L, T;

[0132] In some embodiments of the present application, referring to Figure 3 The method for identifying fracture-vug bodies based on carbonate reservoirs further comprises:

[0133] Step 80: Derivatives of the diffracted wave components in different directions are obtained.

[0134] In some embodiments of the present application, referring to Figure 4 Step 200 comprises:

[0135] Step 201: obtaining one-dimensional Gaussian functions of the diffraction wave in different directions;

[0136] According to step 100, first, the components of the diffraction wave seismic data D(x, y, t) along the x, y and t directions are extracted, respectively, as D x (x, y, t), D y (x, y, t) and D t (x, y, t). Then, for step 201, one-dimensional Gaussian functions in the x, y and t directions are respectively set based on the Gaussian function definition, specifically: one-dimensional Gaussian functions in the x, y and t directions are respectively set as G(x), G(y) and G(t).

[0137]

[0138]

[0139]

[0140] In the above formula, σ is the variance, which determines the fatness of the Gaussian normal distribution, the larger the variance, the relatively fat and short the normal distribution, the stronger the filtering effect on the noise of the seismic data, and a value between 0.1 and 3.0 is preferably selected;

[0141] Step 202: obtaining directional gradients of the diffraction wave in different directions according to derivatives of the wave in different directions and one-dimensional Gaussian functions in corresponding directions.

[0142] While obtaining the derivatives of the diffraction wave seismic data along the three directions respectively, Gaussian smoothing filtering processing is performed by convolution with the one-dimensional Gaussian functions respectively, and the derivatives after filtering in the three directions, i.e. directional gradients, can be obtained.

[0143] Specifically, first, the derivative of the one-dimensional Gaussian function is obtained, and the first-order derivatives of the one-dimensional Gaussian function in the corresponding directions are respectively g(x), g(y) and g(t).

[0144]

[0145]

[0146]

[0147] Then, the gradients (first-order derivatives) of the diffraction wave seismic data D(x, y, t) along the three directions are respectively set as d x (x, y, t), d y (x, y, t) and d t (x, y, t), and Gaussian smoothing filtering processing is performed by convolution with the one-dimensional Gaussian functions respectively, and the gradients dGx (x,y,t), dG y (x,y,t) and dG t (x,y,t), i.e. the gradient vector field.

[0148] According to the property of convolution, the derivative of a certain direction component of seismic data and a Gaussian function is equal to the convolution of the certain direction component of seismic data and the first derivative of the Gaussian function.

[0149] dG x (x,y,t) = d x (x,y,t)*G(x) = D x (x,y,t)*g(x)

[0150] dG y (x,y,t) = d y (x,y,t)*G(y) = D y (x,y,t)*g(y)

[0151] dG t (x,y,t) = d t (x,y,t)*G t (t) = D t (x,y,t)*g(t)

[0152] In some embodiments of the present application, referring to Figure 5 , the method for identifying the fracture-cavity of the carbonate reservoir further comprises:

[0153] Step 400: fusing the directional gradients of the diffracted wave in different directions to obtain the gradient energy;

[0154] According to the gradient dG x (x,y,t), dG y (x,y,t) and dG t (x,y,t), the gradient energy E of the diffracted wave is fused.

[0155]

[0156] Step 500: obtaining the gradient energy entropy of the diffracted wave according to the gradient energy.

[0157] According to the following formula, the gradient energy entropy H of the diffracted wave can be calculated.

[0158]

[0159] In some embodiments of the present application, referring to Figure 6 , the step 300 comprises:

[0160] Step 301: according to the gradient energy and the gradient energy entropy, the fracture-cave body profile and distribution law are depicted.

[0161] According to the diffraction wave gradient energy E and the gradient energy entropy H obtained by the above steps, the fracture-cave body of the carbonate reservoir is identified and predicted, that is, the fracture-cave body profile and the planar distribution law thereof are depicted.

[0162] The present application aims at the deficiency of conventional full-wave field seismic data, combines the high resolution, low signal-to-noise ratio characteristics of diffraction wave data, and the imaging advantage of diffraction wave to fracture-cave reservoir, and proposes a fracture-cave body identification method based on carbonate reservoir. The method first extracts diffraction wave seismic data components along three directions respectively; then based on the properties of Gaussian function and convolution, the diffraction wave components are respectively convolved with the first-order derivative of Gaussian function to obtain the diffraction wave gradient after filtering in three directions; finally, the diffraction wave gradient in different directions is focused and fused into gradient energy, and the corresponding diffraction wave gradient energy entropy is calculated, so as to improve the fracture-cave identification accuracy of carbonate reservoir based on the gradient energy and the gradient energy entropy of diffraction wave.

[0163] The present application filters the diffraction wave data directional components based on Gaussian function to suppress part of noise, and obtains the gradient parameters of diffraction wave directional components, focuses and fuses into diffraction wave gradient energy, forms an extraction method based on diffraction wave gradient energy entropy attribute, so as to improve the fracture-cave attribute identification accuracy of carbonate reservoir, and provides strong technical support for oil and gas geophysical exploration of non-homogeneous geological anomaly body in the study area.

[0164] Embodiment two

[0165] In order to further illustrate the scheme, the present application also provides a specific application example of the fracture-cave body identification method based on carbonate reservoir.

[0166] In order to fully utilize the high resolution detail information of diffraction wave data and improve the fracture-cave identification accuracy of carbonate reservoir, the present application provides a specific application example of the fracture-cave body identification method based on carbonate reservoir and the specific process of implementation, specifically, referring to Figure 7 and Figure 8 , comprising the following steps:

[0167] S1: obtaining diffraction wave three-dimensional seismic data body.

[0168] The diffraction wave three-dimensional seismic data body is obtained by separating the diffraction wave from the full-wave field three-dimensional seismic data body of the target work area; specifically, the diffraction wave three-dimensional seismic data body D(x,y,t) is obtained by separating the diffraction wave from the full-wave field three-dimensional seismic data body S(x,y,t) with a time length T, wherein t=0,1,2,L,T;

[0169] Referring toFigure 9 The full wavefield seismic data S profile with the time domain range of 3s-4s and the length of T=1s is shown, and from the profile, it can be seen that in the time range of 3.3s-3.6s, the fracture-vug body in the carbonate reservoir shows the "bead" shaped diffraction wave seismic response characteristics, and has strong heterogeneity. Figure 10 The profile of diffraction wave data D obtained by using the related mature diffraction wave separation method is shown, the diffraction wave has high resolution and rich detail information, and can better depict the detail characteristics of the fracture-vug body development.

[0170] S2: Extract the components of the diffraction wave along the x, y and t directions, respectively.

[0171] Extract the components of the diffraction wave seismic data D(x, y, t) along the x, y and t directions, respectively, D x (x, y, t), D y (x, y, t) and D t (x, y, t).

[0172] S3: Generate one-dimensional Gaussian functions in x, y and t directions, respectively;

[0173] Set the one-dimensional Gaussian functions in x, y and t directions as G(x), G(y) and G(t) respectively, and the Gaussian function variance σ in the three directions is all taken as 1.

[0174]

[0175]

[0176]

[0177] Wherein, σ is the variance, which determines the fatness of the Gaussian normal distribution, the greater the variance, the relatively fat and short of the normal distribution, the stronger the filtering effect on the seismic data noise, and generally takes a value between 0.1-3.0;

[0178] S4: Calculate the first derivative of the one-dimensional Gaussian function in three directions, respectively;

[0179] Derive the one-dimensional Gaussian function, and the first derivative of the corresponding direction is g(x), g(y) and g(t) respectively:

[0180]

[0181]

[0182]

[0183] S5: Calculate the directional gradient in three directions, respectively.

[0184] In the process of obtaining the derivatives of the diffracted wave seismic data along three directions, Gaussian smoothing filtering processing is performed by respectively convolving with a one-dimensional Gaussian function, to obtain the derivatives after filtering in three directions, i.e., directional gradients

[0185] Specifically, the gradients (first derivatives) of the diffracted wave seismic data D(x, y, t) along three directions are respectively set as d x (x, y, t), d y (x, y, t) and d t (x, y, t), Gaussian smoothing filtering processing is performed by respectively convolving with a one-dimensional Gaussian function, to obtain the gradients dG x (x, y, t), dG y (x, y, t) and dG t (x, y, t), i.e., a gradient vector.According to the properties of convolution, the derivative of a directional component of seismic data and a Gaussian function is equal to the convolution of the directional component of seismic data and the first derivative of the Gaussian function.

[0186] dG x (x, y, t) = d x (x, y, t) * G(x) = D x (x, y, t) * g(x)

[0187] dG y (x, y, t) = d y (x, y, t) * G(y) = D y (x, y, t) * g(y)

[0188] dG t (x, y, t) = d t (x, y, t) * G t (t) = D t (x, y, t) * g(t)

[0189] It can be understood that, according to the properties of convolution, the derivative of a directional component of seismic data and a Gaussian function is equal to the convolution of the directional component of seismic data and the first derivative of the Gaussian function. Therefore, the diffracted wave components D x , D y and D t are respectively convolved with a one-dimensional Gaussian function derivative, to obtain the gradients dG x , dG y and dG t of the diffracted wave after filtering noise suppression, as shown in FIG. 6, the signal-to-noise ratio of the diffracted wave gradient profile in three directions is improved. Figures 11 to 13

[0190] S6: According to the directional gradient vectors in three directions, the diffracted wave gradient energy E is fused.

[0191] Gradient dG after filtering in three directions x (x,y,t), dG y (x,y,t) and dG t (x,y,t), and the fusion of diffraction wave gradient energy E.

[0192]

[0193] Diffraction wave gradient dG after filtering noise in three directions x , dG y and dG t The fusion of diffraction wave gradient energy E, the profile is shown in Figure 14 .

[0194] S7: According to the diffraction wave gradient energy E, the corresponding gradient energy entropy H can be calculated.

[0195] According to the definition of entropy, the diffraction wave gradient energy entropy H can be calculated.

[0196]

[0197] According to the diffraction wave gradient energy E, the diffraction wave gradient energy entropy H is calculated, the profile is shown in Figure 15 , the diffraction wave energy is focused on the profile, which can effectively depict the three-dimensional morphology of the fracture-vug body.

[0198] S8: Using the diffraction wave gradient energy E and the gradient energy entropy H, the fracture-vug body of the carbonate reservoir is identified and predicted.

[0199] Through steps S1 to S7, the diffraction wave gradient energy E and the gradient energy entropy H are obtained to identify and predict the fracture-vug body of the carbonate reservoir.

[0200] According to the plan view of the diffraction wave gradient energy entropy H Figure 16 ), the fracture-vug body of the carbonate reservoir is identified and predicted, which can better depict the outline of the fracture-vug body of the carbonate reservoir in the block and the distribution rule on the plane, and is more consistent with the actual drilling results.

[0201] From the above description, the fracture-vug body identification method based on the carbonate reservoir provided by the embodiment of the application first extracts the diffraction wave components in different directions of the target work area obtained in advance; then, the directional gradient of the diffraction wave in different directions is calculated according to the diffraction wave components in different directions; finally, the gradient energy and the gradient energy entropy of the diffraction wave are calculated according to the directional gradient to identify the fracture-vug body of the target work area.

[0202] The application is based on Gaussian function to suppress noise of diffraction wave data, and realizes extraction of diffraction wave gradient energy entropy attribute. Specifically, first, diffraction wave directional components are extracted, then, diffraction wave component filtering and gradient are calculated, and finally, diffraction wave gradient energy entropy attribute is extracted. The diffraction wave gradient energy entropy attribute extraction process is used to realize functions of diffraction wave component gradient fusion and gradient energy entropy attribute extraction.

[0203] As an effective oil and gas reservoir space of carbonate reservoir, the fracture-cavity shows diffraction wave characteristics. Conventional full wave field seismic data has the following characteristics: the energy of reflection phase axis at the formation boundary is strong, which can shield the weak energy diffraction wave information generated by the heterogeneous fracture-cavity in the underlying formation, resulting in insufficient identification ability of the fracture-cavity, which cannot meet the current problem of qualitative identification of heterogeneous reservoir fracture-cavity. Therefore, the application proposes a fracture-cavity identification method based on carbonate reservoir in view of the shortcomings of conventional full wave field seismic data, in combination with the characteristics of high resolution and low signal-to-noise ratio of diffraction wave data, and the imaging advantage of diffraction wave to fracture-cavity reservoir. The method first extracts diffraction wave seismic data components along three directions respectively; then, based on the properties of Gaussian function and convolution, the diffraction wave components are respectively convolved with the first derivative of Gaussian function to obtain the diffraction wave gradient after filtering in three directions; finally, the diffraction wave directional gradient is focused and fused into gradient energy, and the corresponding diffraction wave gradient energy entropy is calculated, so as to improve the identification accuracy of carbonate reservoir fracture-cavity.

[0204] Embodiment three

[0205] Based on the same principle, the embodiment also discloses a fracture-cavity identification device based on carbonate reservoir, as shown in the figure, the device comprises: Figure 17

[0206] The diffraction wave component extraction module 10 is used to extract the components of the diffraction wave of the target work area in different directions.

[0207] The directional gradient calculation module 20 is used to calculate the directional gradient of the diffraction wave in different directions according to the components of the diffraction wave in different directions.

[0208] The fracture-cavity identification module 30 is used to calculate the gradient energy and gradient energy entropy of the diffraction wave according to the directional gradient, so as to identify the fracture-cavity of the target work area.

[0209] In some embodiments of the application, the components of the diffraction wave in different directions comprise:

[0210] The component of the diffraction wave in the line direction of the seismic data network of the target work area, the component of the seismic data network in the seismic trace direction, and the component in the direction perpendicular to the seismic data network.

[0211] ​In some embodiments of the present application, the fracture-cave body identification device based on the carbonate reservoir further comprises:

[0212] The diffraction wave acquisition module is configured to acquire diffraction waves of the target work area.

[0213] The diffraction wave acquisition module comprises:

[0214] The diffraction wave acquisition unit is configured to perform diffraction wave separation on the three-dimensional seismic data volume of the target work area to acquire the diffraction waves.

[0215] In some embodiments of the present application, the fracture-cave body identification device based on the carbonate reservoir further comprises:

[0216] The derivative obtaining module is configured to obtain derivatives of the components of the diffraction waves in different directions.

[0217] In some embodiments of the present application, the directional gradient obtaining module comprises:

[0218] The Gaussian function obtaining unit is configured to obtain one-dimensional Gaussian functions of the diffraction waves in the different directions.

[0219] The directional gradient obtaining unit is configured to obtain directional gradients of the diffraction waves in different directions according to the derivatives of the components of the diffraction waves in different directions and the one-dimensional Gaussian functions of the corresponding directions.

[0220] In some embodiments of the present application, the fracture-cave body identification device based on the carbonate reservoir further comprises:

[0221] The gradient energy obtaining module is configured to fuse the directional gradients of the diffraction waves in different directions to obtain the gradient energy.

[0222] The gradient energy entropy obtaining module is configured to obtain the gradient energy entropy of the diffraction waves according to the gradient energy.

[0223] In some embodiments of the present application, the fracture-cave body identification module comprises:

[0224] The fracture-cave body identification unit is configured to depict the fracture-cave body profile and distribution law according to the gradient energy and the gradient energy entropy.

[0225] As can be seen from the above description, the fracture-cave body identification device based on the carbonate reservoir provided by the embodiments of the present application first extracts the components of the diffraction waves in different directions of the target work area acquired in advance; then, the directional gradients of the diffraction waves in different directions are obtained according to the components of the diffraction waves in different directions; finally, the gradient energy and the gradient energy entropy of the diffraction waves are obtained according to the directional gradients to identify the fracture-cave body of the target work area.

[0226] The application utilizes the characteristics of high resolution and low signal-to-noise ratio of diffracted wave seismic data, filters the directional components of diffracted wave data based on Gaussian function to suppress part of noise, and obtains the gradient parameters of diffracted wave directional components, focuses and fuses into diffracted wave gradient energy, forms a diffracted wave gradient energy entropy attribute extraction method, so as to improve the fracture-cave attribute identification precision of carbonate reservoirs.

[0227] Embodiment four

[0228] The embodiment of the application also provides a specific implementation of an electronic device capable of realizing all steps in the fracture-cave body identification method based on carbonate reservoirs in the above-mentioned embodiments, referring to Figure 18 , the electronic device specifically includes the following contents:

[0229] The processor (processor) 1201, the memory (memory) 1202, the communication interface (Communications Interface) 1203 and the bus 1204;

[0230] The processor 1201, the memory 1202, the communication interface 1203 and the bus 1204 complete the communication among each other; the communication interface 1203 is used for realizing the information transmission between the server-side device, the computing unit and the client-side device and other related devices.

[0231] The processor 1201 is used for calling the computer program in the memory 1202, and the processor realizes all steps in the fracture-cave body identification method based on carbonate reservoirs in the above-mentioned embodiments when executing the computer program, for example, the processor realizes the following steps when executing the computer program:

[0232] Extracting the components of diffracted wave in different directions of the target work area acquired in advance;

[0233] According to the directional gradient of the diffracted wave in different directions, the directional gradient of the diffracted wave in different directions is obtained;

[0234] According to the directional gradient, the gradient energy and the gradient energy entropy of the diffracted wave are obtained to identify the fracture-cave body of the target work area.

[0235] In some embodiments of the application, the components of the diffracted wave in different directions include:

[0236] The component of the diffracted wave in the line direction of the seismic data measuring network of the target work area, the component of the seismic data measuring network in the seismic trace direction and the component in the direction perpendicular to the seismic data measuring network.

[0237] In some embodiments of the application, the diffracted wave of the target work area obtained includes the following steps:

[0238] Diffracted wave separation is performed on the three-dimensional seismic data volume of the target work area to obtain the diffracted wave.

[0239] In some embodiments of the present application, the method for identifying fracture-vug bodies based on carbonate reservoirs further comprises:

[0240] Derivatives of the diffracted wave components in different directions are calculated.

[0241] In some embodiments of the present application, the directional gradient of the diffracted wave in different directions is calculated according to the diffracted wave components in different directions, comprising:

[0242] A one-dimensional Gaussian function of the diffracted wave in different directions is calculated.

[0243] The directional gradient of the diffracted wave in different directions is calculated according to the derivatives of the diffracted wave components in different directions and the one-dimensional Gaussian function of the corresponding direction.

[0244] In some embodiments of the present application, the method for identifying fracture-vug bodies based on carbonate reservoirs further comprises:

[0245] The directional gradients of the diffracted wave in different directions are fused to calculate the gradient energy.

[0246] The gradient energy entropy of the diffracted wave is calculated according to the gradient energy.

[0247] In some embodiments of the present application, the gradient energy and the gradient energy entropy of the diffracted wave are calculated according to the directional gradients to identify the fracture-vug bodies of the target work area, comprising:

[0248] The fracture-vug body profile and distribution rule are described according to the gradient energy and the gradient energy entropy.

[0249] The present application also discloses a device for identifying fracture-vug bodies based on carbonate reservoirs, comprising:

[0250] The diffracted wave component extraction module is configured to extract the components of the diffracted wave in different directions of the target work area obtained in advance.

[0251] The directional gradient calculation module is configured to calculate the directional gradient of the diffracted wave in different directions according to the diffracted wave components in different directions.

[0252] The fracture-vug body identification module is configured to calculate the gradient energy and the gradient energy entropy of the diffracted wave according to the directional gradients to identify the fracture-vug bodies of the target work area.

[0253] In some embodiments of the present application, the diffracted wave components in different directions comprise:

[0254] A component of the diffracted wave in a line direction of a seismic data grid of the target work area, a component of the diffracted wave in a seismic trace direction of the seismic data grid, and a component of the diffracted wave in a direction perpendicular to the seismic data grid.

[0255] Embodiment five

[0256] Embodiments of the present application also provide a computer readable storage medium capable of implementing all steps of the above-mentioned carbonate reservoir-based fracture-cavity identification method, and the computer readable storage medium stores a computer program which, when executed by a processor, implements all steps of the above-mentioned carbonate reservoir-based fracture-cavity identification method, for example, the following steps are implemented when the processor executes the computer program:

[0257] extracting components of the diffracted wave in different directions of a target work area obtained in advance;

[0258] correspondingly calculating directional gradients of the diffracted wave in different directions according to the components of the diffracted wave in different directions;

[0259] calculating gradient energy and gradient energy entropy of the diffracted wave according to the directional gradients to identify a fracture-cavity of the target work area.

[0260] In some embodiments of the present application, the components of the diffracted wave in different directions include:

[0261] A component of the diffracted wave in a line direction of a seismic data grid of the target work area, a component of the diffracted wave in a seismic trace direction of the seismic data grid, and a component of the diffracted wave in a direction perpendicular to the seismic data grid.

[0262] In some embodiments of the present application, obtaining the diffracted wave of the target work area includes the following steps:

[0263] performing diffracted wave separation on a three-dimensional seismic data volume of the target work area to obtain the diffracted wave.

[0264] In some embodiments of the present application, the carbonate reservoir-based fracture-cavity identification method further includes:

[0265] calculating derivatives of the components of the diffracted wave in different directions in different directions.

[0266] In some embodiments of the present application, the corresponding calculation of the directional gradients of the diffracted wave in different directions according to the components of the diffracted wave in different directions includes:

[0267] calculating a one-dimensional Gaussian function of the diffracted wave in the different directions;

[0268] Derivatives of the diffracted wave in different directions are calculated according to derivatives of the diffracted wave in different directions and one-dimensional Gaussian functions corresponding to the directions.

[0269] In some embodiments of the present application, the method for identifying fracture-vug bodies based on carbonate reservoirs further comprises:

[0270] The directional gradient of the diffracted wave in different directions is fused to calculate the gradient energy.

[0271] The gradient energy entropy of the diffracted wave is calculated according to the gradient energy.

[0272] In some embodiments of the present application, the gradient energy and the gradient energy entropy of the diffracted wave are calculated according to the directional gradient to identify the fracture-vug bodies in the target work area, which comprises:

[0273] The fracture-vug body profile and distribution rule are described according to the gradient energy and the gradient energy entropy.

[0274] The present application further discloses a device for identifying fracture-vug bodies based on carbonate reservoirs, which comprises:

[0275] The diffracted wave component extraction module is configured to extract the components of the diffracted wave in different directions of the target work area obtained in advance.

[0276] The directional gradient calculation module is configured to calculate the directional gradient of the diffracted wave in different directions according to the components of the diffracted wave in different directions.

[0277] The fracture-vug body identification module is configured to calculate the gradient energy and the gradient energy entropy of the diffracted wave according to the directional gradient to identify the fracture-vug bodies in the target work area.

[0278] In some embodiments of the present application, the components of the diffracted wave in different directions comprise:

[0279] The components of the diffracted wave in the line direction of the seismic data network of the target work area, the seismic trace direction of the seismic data network and the direction perpendicular to the seismic data network.

[0280] Each of the embodiments in the present application is described in a progressive manner, and the same or similar parts of each embodiment can be referred to each other, and each embodiment mainly describes the difference from other embodiments. Especially, for the hardware+program type embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the related parts can be referred to the part of the method embodiment.

[0281] The above-described embodiments of the application are described in connection with the pertinent figures. Other embodiments are within the scope and spirit of the claims. In some instances, the actions or steps can be performed in an order different from the order described in the embodiments. Further, the processes depicted in the figures do not necessarily require the particular order shown, or sequential order, to achieve the desired results. In certain implementations, multitasking and parallel processing can be advantageous.

[0282] Those skilled in the art will appreciate that embodiments of the application can be devised for a method, a system, or a computer program product. Accordingly, the present application can be embodied in the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) embodying computer readable program code.

[0283] The present application is described in reference to the flowchart illustrations and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0284] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0285] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0286] The principles and implementation manners of the present application are described by using specific examples in the present application. The above examples are only used to help understand the method of the present application and its core idea. Meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation manners and application ranges will be changed. In summary, the content of the present description should not be understood as a limitation of the present application.

Claims

1. A fracture-cavity identification method based on carbonate reservoirs, characterized in that: include: Extract the components of the diffraction waves of the target work area acquired in advance in different directions; Obtaining the directional gradients of the diffracted wave in different directions according to the components of the diffracted wave in different directions; The gradient energy and gradient energy entropy of the diffraction wave are calculated according to the directional gradient to identify the fracture and cavity body in the target working area.

2. The fracture-cavity identification method based on carbonate reservoir according to claim 1, characterized in that: The components of the diffraction wave in different directions include: The diffraction wave includes a component in the survey line direction of the seismic data survey network of the target work area, a component in the seismic trace direction of the seismic data survey network, and a component in the direction perpendicular to the seismic data survey network.

3. The fracture-cavity identification method based on carbonate reservoir according to claim 1, characterized in that: Obtaining the diffraction waves of the target work area includes the following steps: Diffraction wave separation is performed on the three-dimensional seismic data volume of the target work area to obtain the diffraction wave.

4. The method for identifying fractures and caves in carbonate reservoirs according to claim 1, characterized in that: Also includes: The derivatives of the components of the diffraction wave in different directions in different directions are obtained.

5. The fracture-cavity identification method based on carbonate reservoir according to claim 4, characterized in that: Obtaining the directional gradients of the diffracted waves in different directions according to the components of the diffracted waves in different directions, including: Obtaining one-dimensional Gaussian functions of the diffraction waves in different directions; The directional gradients of the diffracted waves in different directions are obtained according to the derivatives of the components of the diffracted waves in different directions and the one-dimensional Gaussian functions in the corresponding directions.

6. The method for identifying fractures and caves in carbonate reservoirs according to claim 1, characterized in that: Also includes: fusing the directional gradients of the diffraction wave in different directions to obtain the gradient energy; The gradient energy entropy of the diffraction wave is obtained according to the gradient energy.

7. The fracture-cavity identification method based on carbonate reservoir according to claim 1, characterized in that: Obtaining the gradient energy and gradient energy entropy of the diffraction wave according to the directional gradient to identify the fracture-cavity body in the target working area includes: The fracture body contour and distribution law are characterized according to the gradient energy and the gradient energy entropy.

8. A device for identifying fractures and caves in carbonate reservoirs, characterized in that: include: A diffraction wave component extraction module is used to extract the components of the diffraction waves of the target work area acquired in advance in different directions; A directional gradient obtaining module, configured to obtain the directional gradients of the diffracted wave in different directions according to the components of the diffracted wave in different directions; The fracture-hole body identification module is used to obtain the gradient energy and gradient energy entropy of the diffraction wave according to the directional gradient to identify the fracture-hole body in the target work area.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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