Fracture-cavity body identification method and device based on carbonate reservoir

Abstract

The invention provides a fractured-vuggy body recognition method and device based on a carbonate reservoir. The fractured-vuggy body recognition method based on the carbonate reservoir comprises the steps that components, obtained in advance, of diffracted waves of a target work area in different directions are extracted; according to the components of the diffracted waves in the different directions, correspondingly solving sub-direction gradients of the diffracted waves in the different directions; and calculating gradient energy and gradient energy entropy of the diffracted wave according to the directional gradient so as to identify the fracture-cavity body of the target work area. In order to solve the problem that strong energy of conventional full-wave field data reflects weak energy diffracted waves of a fracture-covered cave body under event shielding in the prior art, diffracted wave data are directly adopted, and attributes with strong pertinence are extracted to identify the heterogeneous fracture-cave body, so that the identification capability of the fracture-cave body near a stratum interface is improved.

Description

Technical Field

[0001] The invention relates to the technical field of geophysical exploration of oil and gas fields, and in particular to a method and device for identifying fracture-cavity bodies based on carbonate reservoirs. Background Art

[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 "beaded" weak energy diffraction wave characteristics of different sizes and energies on the seismic profile, and are integrated with the strong energy reflection wave characteristics of the interface of a large set of formations to form a full-wavefield seismic profile, using seismic data and related attributes to characterize the boundaries of the fracture-cave bodies is one of the important tasks in predicting carbonate fracture-cave reservoirs.

[0003] In recent years, full-wavefield seismic attribute characterization methods have achieved good results in carbonate reservoir prediction, including the prediction of sweet spots in carbonate reservoirs using coherence, curvature, ant bodies, and amplitude change rate. However, due to the strong energy of the reflection event axis at the formation interface in conventional full-wavefield seismic data, it will shield the weak energy diffraction wave information generated by the heterogeneous fracture-cavity body in the underlying strata, resulting in insufficient recognition of fracture-cavity bodies, which cannot meet the current carbonate reservoirs, especially the qualitative identification of fractures and caves in heterogeneous reservoirs in carbonate rocks. Summary of the invention

[0004] One purpose of the present invention is to provide a fracture-cavity identification method based on carbonate reservoirs. This method combines the high resolution and low signal-to-noise ratio characteristics of diffraction wave data and the imaging advantages of diffraction waves on fracture-cavity reservoirs to propose a fracture-cavity identification method based on carbonate reservoirs. The method first extracts the components of the diffraction wave seismic data along three directions respectively; then, based on the properties of Gaussian function and convolution, the diffraction wave components are convolved with the first-order derivative of the Gaussian function respectively 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, thereby improving the fracture-cavity identification accuracy of carbonate reservoirs based on the gradient energy and gradient energy entropy of the diffraction wave.

[0005] Another object of the present invention is to provide a fracture-cavity body identification device based on carbonate reservoirs. Another object of the present invention is to provide a computer device, the computer device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the steps of the fracture-cavity body identification method based on carbonate reservoirs when executing the computer program. Another object of the present invention is to provide a readable medium, on which a computer program is stored, and when the computer program is executed by the processor, the steps of the fracture-cavity body identification method based on carbonate reservoirs are implemented.

[0006] In order to achieve the above objectives, the present invention discloses a method for identifying fractures and caves in carbonate reservoirs, comprising:

[0007] Extract the components of the diffraction waves of the target work area acquired in advance in different directions;

[0008] Obtaining the directional gradients of the diffraction wave in different directions according to the components of the diffraction wave in different directions;

[0009] The gradient energy and the gradient energy entropy of the diffraction wave are obtained according to the directional gradients to identify the fracture and cave body in the target work area.

[0010] In some embodiments of the present invention, the components of the diffraction wave in different directions include:

[0011] The diffraction wave includes a component in the survey line direction of the seismic data network of the target work area, a component in the seismic trace direction of the seismic data network, and a component in a direction perpendicular to the seismic data network.

[0012] In some embodiments of the present invention, obtaining the diffraction wave of the target working area includes the following steps:

[0013] The diffraction waves are separated from the three-dimensional seismic data volume of the target work area to obtain the diffraction waves.

[0014] In some embodiments of the present invention, the method for identifying fracture-cavity bodies in carbonate reservoirs further includes:

[0015] The derivatives of the components of the diffraction wave in different directions in different directions are obtained.

[0016] In some embodiments of the present invention, obtaining the directional gradients of the diffracted waves in different directions according to the components of the diffracted waves in different directions includes:

[0017] Obtaining one-dimensional Gaussian functions of the diffraction waves in different directions;

[0018] 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.

[0019] In some embodiments of the present invention, the method for identifying fracture-cavity bodies in carbonate reservoirs further includes:

[0020] fusing the directional gradients of the diffraction wave in different directions to obtain the gradient energy;

[0021] The gradient energy entropy of the diffraction wave is obtained according to the gradient energy.

[0022] In some embodiments of the present invention, obtaining the gradient energy and the gradient energy entropy of the diffraction wave according to the directional gradient to identify the fracture body in the target work area includes:

[0023] The contour and distribution pattern of the fracture body are characterized according to the gradient energy and the gradient energy entropy.

[0024] The present invention also discloses a fracture-cavity identification device based on carbonate reservoirs, comprising:

[0025] A diffraction wave component extraction module is used to extract components of the diffraction waves of the target work area acquired in advance in different directions;

[0026] A directional gradient obtaining module, used for obtaining the directional gradients of the diffraction wave in different directions according to the components of the diffraction wave in different directions;

[0027] The fracture 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 body in the target work area.

[0028] In some embodiments of the present invention, the components of the diffraction wave in different directions include:

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

[0030] In some embodiments of the present invention, the device for identifying fractures and caves in carbonate reservoirs further includes:

[0031] A diffraction wave acquisition module, used to acquire diffraction waves of a target work area;

[0032] The diffraction wave acquisition module comprises:

[0033] The diffraction wave acquisition unit is used to perform diffraction wave separation on the three-dimensional seismic data volume of the target work area to obtain the diffraction wave.

[0034] In some embodiments of the present invention, the device for identifying fractures and caves in carbonate reservoirs further includes:

[0035] The derivative obtaining module is used to obtain the derivatives of the components of the diffraction wave in different directions in different directions.

[0036] In some embodiments of the present invention, the directional gradient obtaining module includes:

[0037] A Gaussian function obtaining unit, used for obtaining the one-dimensional Gaussian function of the diffraction wave in different directions;

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

[0039] In some embodiments of the present invention, the device for identifying fractures and caves in carbonate reservoirs further includes:

[0040] A gradient energy obtaining module, used for fusing the directional gradients of the diffraction wave in different directions to obtain the gradient energy;

[0041] A gradient energy entropy obtaining module is used to obtain the gradient energy entropy of the diffraction wave according to the gradient energy.

[0042] In some embodiments of the present invention, the fracture body identification module includes:

[0043] A fracture body identification unit is used to characterize the fracture body contour and distribution law according to the gradient energy and the gradient energy entropy.

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

[0045] When the processor executes the program, the following method is implemented.

[0046] Extract the components of the diffraction waves of the target work area acquired in advance in different directions;

[0047] Obtaining the directional gradients of the diffraction wave in different directions according to the components of the diffraction wave in different directions;

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

[0049] In some embodiments of the present invention, the components of the diffraction wave in different directions include:

[0050] The diffraction wave includes a component in the survey line direction of the seismic data network of the target work area, a component in the seismic trace direction of the seismic data network, and a component in a direction perpendicular to the seismic data network.

[0051] In some embodiments of the present invention, obtaining the diffraction wave of the target working area includes the following steps:

[0052] The diffraction waves are separated from the three-dimensional seismic data volume of the target work area to obtain the diffraction waves.

[0053] In some embodiments of the present invention, the method for identifying fracture-cavity bodies in carbonate reservoirs further includes:

[0054] The derivatives of the components of the diffraction wave in different directions in different directions are obtained.

[0055] In some embodiments of the present invention, obtaining the directional gradients of the diffracted waves in different directions according to the components of the diffracted waves in different directions includes:

[0056] Obtaining one-dimensional Gaussian functions of the diffraction waves in different directions;

[0057] 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.

[0058] In some embodiments of the present invention, the method for identifying fracture-cavity bodies in carbonate reservoirs further includes:

[0059] fusing the directional gradients of the diffraction wave in different directions to obtain the gradient energy;

[0060] The gradient energy entropy of the diffraction wave is obtained according to the gradient energy.

[0061] In some embodiments of the present invention, obtaining the gradient energy and the gradient energy entropy of the diffraction wave according to the directional gradient to identify the fracture body in the target work area includes:

[0062] The contour and distribution pattern of the fracture body are characterized according to the gradient energy and the gradient energy entropy.

[0063] The present invention also discloses a computer readable medium having a computer program stored thereon.

[0064] When the program is executed by a processor, the following method is implemented.

[0065] Extract the components of the diffraction waves of the target work area acquired in advance in different directions;

[0066] Obtaining the directional gradients of the diffraction wave in different directions according to the components of the diffraction wave in different directions;

[0067] The gradient energy and the gradient energy entropy of the diffraction wave are obtained according to the directional gradients to identify the fracture and cave body in the target work area.

[0068] In some embodiments of the present invention, the components of the diffraction wave in different directions include:

[0069] The diffraction wave includes a component in the survey line direction of the seismic data network of the target work area, a component in the seismic trace direction of the seismic data network, and a component in a direction perpendicular to the seismic data network.

[0070] In some embodiments of the present invention, obtaining the diffraction wave of the target working area includes the following steps:

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

[0072] In some embodiments of the present invention, the method for identifying fracture-cavity bodies in carbonate reservoirs further includes:

[0073] The derivatives of the components of the diffraction wave in different directions in different directions are obtained.

[0074] In some embodiments of the present invention, obtaining the directional gradients of the diffracted waves in different directions according to the components of the diffracted waves in different directions includes:

[0075] Obtaining one-dimensional Gaussian functions of the diffraction waves in different directions;

[0076] 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.

[0077] In some embodiments of the present invention, the method for identifying fracture-cavity bodies in carbonate reservoirs further includes:

[0078] fusing the directional gradients of the diffraction wave in different directions to obtain the gradient energy;

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

[0080] In some embodiments of the present invention, obtaining the gradient energy and the gradient energy entropy of the diffraction wave according to the directional gradient to identify the fracture body in the target work area includes:

[0081] The contour and distribution pattern of the fracture body are characterized according to the gradient energy and the gradient energy entropy.

[0082] From the above description, it can be seen that the fracture-cave body identification method and device based on carbonate reservoirs provided by an embodiment of the present invention first extracts the components of the diffraction wave in different directions of the target work area obtained in advance; then, the directional gradients of the diffraction wave in different directions are calculated according to the components of the diffraction wave in different directions; finally, the gradient energy and gradient energy entropy of the diffraction wave are calculated according to the directional gradients to identify the fracture-cave body in the target work area.

[0083] Aiming at the problem of weak energy diffraction waves of covered fracture-cavity bodies under strong energy reflection event shielding of conventional full-wavefield data in the prior art, the present invention directly adopts diffraction wave data and extracts highly targeted attributes to identify heterogeneous fracture-cavity bodies, thereby improving the identification capability of fracture-cavity bodies near the stratum interface. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0085] Figure 1 A schematic diagram of a process of a fracture-cavity identification method based on a carbonate reservoir in the first embodiment of the present invention;

[0086] Figure 2 It is another schematic flow chart of the fracture-cavity identification method based on carbonate reservoir in the first embodiment of the present invention;

[0087] Figure 3 This is a third flow chart of the fracture-cavity identification method based on carbonate reservoir in the first embodiment of the present invention;

[0088] Figure 4 Schematic diagram of the process of step 200 in the fracture-cavity identification method based on carbonate reservoir in the first embodiment of the present invention;

[0089] Figure 5 This is a fourth flow chart of the fracture-cavity identification method based on carbonate reservoirs in the first embodiment of the present invention;

[0090] Figure 6 Schematic diagram of the process of step 300 in the fracture-cavity identification method based on carbonate reservoir in the first embodiment of the present invention;

[0091] Figure 7 It is a schematic diagram of the process of the fracture-cavity identification method based on carbonate reservoir in the second embodiment of the present invention;

[0092] Figure 8 A mind map of a fracture-cavity identification method based on a carbonate reservoir in Embodiment 2 of the present invention;

[0093] Fig. 9 It is the time domain full wave field seismic profile in the second embodiment of the present invention;

[0094] Fig.10 It is the time domain diffraction wave seismic profile in the second embodiment of the present invention;

[0095] Fig.11 It is the x-direction gradient profile of the time domain diffraction wave in the second embodiment of the present invention;

[0096] Fig.12 is the y-direction gradient profile of the time domain diffraction wave in the second embodiment of the present invention;

[0097] Fig.13 is the t-direction gradient profile of the time domain diffraction wave in the second embodiment of the present invention;

[0098] Fig.14 It is the time domain diffraction wave gradient energy profile in the second embodiment of the present invention;

[0099] Fig.15 It is the time domain diffraction wave gradient energy entropy profile in the second embodiment of the present invention;

[0100] Fig.16 It is the time domain diffraction wave gradient energy entropy plane in the second embodiment of the present invention;

[0101] Fig.17 This is a schematic diagram of the structure of a fracture-cavity identification device based on a carbonate reservoir in the third embodiment of the present invention;

[0102] Fig.18 It is a schematic diagram of the structure of an electronic device in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0103] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0104] It should be noted that the terms "including" and "having" in the specification and claims of the present application and the above-mentioned drawings and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. In the absence of conflict, the embodiments in the present application and the features in the embodiments may be combined with each other. 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, and processing of data in the technical solution of this application comply with the relevant provisions of laws and regulations.

[0106] Embodiment 1

[0107] In the existing technology, in conventional full-wavefield seismic data, the energy of the reflection event axis at the stratum interface is relatively strong, which will shield the weak energy diffraction wave information generated by the heterogeneous fracture-cavity body in the underlying stratum, resulting in insufficient recognition of the fracture-cavity body, and cannot meet the current problem of qualitative identification of fractures and caves in heterogeneous reservoirs. Based on this, Figure 1 As shown, the present invention provides a fracture-cavity identification method based on carbonate reservoirs, which comprises:

[0108] Step 100: extracting components of the diffraction waves of the target work area acquired in advance in different directions;

[0109] Diffraction waves refer to any inhomogeneous body in the ground that is smaller than or comparable to the wavelength of seismic waves, such as fault blocks and fault edges, which can be regarded as diffraction points. When seismic waves pass through diffraction points, they are the waves generated. According to Huygens' principle, during the propagation of seismic waves, when seismic waves encounter any irregular body on the interface, such as fault edges, stratum pinch points, and protrusions on unconformity surfaces, when seismic waves pass through these elastic discontinuities, they can be regarded as new sources of earthquakes, just like the diffraction phenomenon in optics. From this new source of earthquakes, a new disturbance is generated and propagates around the elastic space. This disturbance wave is called a diffraction wave.

[0110] Diffracted waves are divided into narrow diffracted waves and generalized diffracted waves. The basic viewpoint of physical seismology is that diffraction is the most basic, and the reflected wave is the sum of the diffracted waves generated by all small area elements on the reflection interface. This kind of diffraction is called generalized diffraction. Any inhomogeneous body in the ground that is smaller than or comparable to the wavelength of the seismic wave, such as fault blocks and fault edges, can be regarded as a diffraction point. The diffracted wave (diffracted wave) generated when the seismic wave passes through the diffraction point is a narrow diffraction, which is characterized by the seismic wave energy that seems to start from the diffraction point. It causes the tail of the reflected wave near the fault, which complicates the determination of the fault point. The diffracted wave has the following characteristics:

[0111] 1. The time-distance curve of the diffraction wave is a hyperbola, and its curvature is greater than that of the time-distance curve of the reflection wave;

[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 diffraction wave time-distance curve is always directly above the diffraction point, and the diffraction wave time-distance curve is tangent to the reflection wave time-distance curve;

[0113] 3. In the simple case of horizontal strata, the position of the minimum point of the diffraction wave phase axis indicates the position of the breakpoint; the minimum point of the diffraction wave is tangent to the reflected wave; in the case of inclined strata, the tangent point is not at the minimum point;

[0114] 4. When the section line intersects obliquely with the fault strike, the diffraction wave slows down;

[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: Obtaining the directional gradients of the diffraction wave in different directions according to the components of the diffraction wave in different directions;

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

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

[0119] Fractures and caves in carbonate rocks refer to the voids or cracks formed in carbonate rock formations. Carbonate rocks are mainly 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 caves can be tiny cracks, pores, pipes or caves, and their sizes can range from microns to meters. They can be formed by geological processes such as pressure release, dissolution, joint development, thermal expansion and contraction of rock layers. Fractures and caves in carbonate rocks are of great significance to the flow of water, storage and migration of oil and gas, and have a significant impact on the exploration and development of oil and gas.

[0120] From the above description, it can be seen that the fracture-cave body identification method based on carbonate reservoirs provided by an embodiment of the present invention first extracts the components of the diffraction wave in different directions of the target work area obtained in advance; then, the directional gradients of the diffraction wave in different directions are calculated according to the components of the diffraction wave in different directions; finally, the gradient energy and gradient energy entropy of the diffraction wave are calculated according to the directional gradients to identify the fracture-cave body in the target work area.

[0121] Aiming at the characteristic of low signal-to-noise ratio of diffraction wave, the present invention convolves the diffraction wave components with the first-order derivative of Gaussian function respectively based on the properties of Gaussian function and convolution, so that the diffraction wave components in three directions can be filtered to suppress noise and the diffraction wave gradients in the corresponding directions can be obtained. On the other hand, aiming at the problem of high resolution of diffraction wave and relatively scattered data, the present invention focuses and fuses the directional gradients of diffraction wave into gradient energy, calculates and obtains the corresponding diffraction wave gradient energy entropy, thereby improving the recognition accuracy of fractures and caves in carbonate reservoirs.

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

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

[0124] As you can understand, the seismic network generates seismic waves by sending controlled seismic sources (such as source vehicles, explosives, seismic machines, etc.) and records them on sensors. The seismic data recorded by the sensors will be processed and analyzed to obtain information such as underground geological structure, location, morphology and properties of oil and gas reservoirs. 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. The underground geological structure and reservoir distribution can be inferred by analyzing the characteristics of reflected and refracted waves.

[0126] Oil and gas reservoirs: Oil and gas reservoirs usually have different seismic attributes, and seismic data analysis can be used to identify and describe the characteristics of the reservoirs, including porosity, saturation, elastic parameters, etc.

[0127] Oil and gas distribution: Seismic networks can provide information on the approximate location, boundaries, and extension of underground oil and gas layers, helping explorers determine the potential production and development plans of oil and gas fields.

[0128] In some embodiments of the present invention, see Figure 2 , the fracture-cavity identification method based on carbonate reservoirs also includes:

[0129] Step 90: performing diffraction wave separation on the three-dimensional seismic data volume of the target work area to obtain the diffraction wave.

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

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

[0132] In some embodiments of the present invention, see Figure 3 , the fracture-cavity identification method based on carbonate reservoirs also includes:

[0133] Step 80: Obtain the derivatives of the components of the diffraction wave in different directions in different directions.

[0134] In some embodiments of the present invention, see Figure 4 , step 200 comprises:

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

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

[0137]

[0138]

[0139]

[0140] In the above formula, σ is the variance, which determines the fatness or thinness of the Gaussian normal distribution. The larger the variance, the fatter and shorter the normal distribution is, and the stronger the filtering effect on seismic data noise is. It is preferably a value between 0.1 and 3.0.

[0141] Step 202: deriving directional gradients of the diffracted wave in different directions according to the derivatives of the components of the diffracted wave in different directions and the one-dimensional Gaussian function in the corresponding direction.

[0142] While obtaining the derivatives of the diffraction wave seismic data along three directions, they are convolved with a one-dimensional Gaussian function to perform Gaussian smoothing filtering, and the derivatives after filtering in three directions, namely, the directional gradients, can be obtained.

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

[0144]

[0145]

[0146]

[0147] Next, the gradients (first-order derivatives) of the diffraction wave seismic data D(x, y, t) along the three directions are set to d x (x,y,t),d y (x,y,t) and d t (x, y, t), and convolve them with a one-dimensional Gaussian function for Gaussian smoothing filtering, and the gradient dG after filtering in three directions can be obtainedx (x,y,t),dG y (x,y,t) and dG t (x,y,t), which is the gradient vector volume.

[0148] According to the properties of convolution, the convolution of the derivative of a certain directional component of the seismic data with the Gaussian function is equal to the convolution of a certain directional component of the seismic data with the first-order 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 invention, see Figure 5 , the fracture-cavity identification method based on carbonate reservoirs also includes:

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

[0154] According to the gradient dG after filtering in three directions x (x,y,t),dG y (x,y,t) and dG t (x,y,t), and fused to get the diffraction wave gradient energy E.

[0155]

[0156] Step 500: Obtaining the gradient energy entropy of the diffraction wave according to the gradient energy.

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

[0158]

[0159] In some embodiments of the present invention, see Figure 6 , step 300 comprises:

[0160] Step 301: Describe the contour and distribution pattern of the fracture body according to the gradient energy and the gradient energy entropy.

[0161] According to the diffraction wave gradient energy E and gradient energy entropy H obtained by the above steps, the fracture-cavity body of the carbonate reservoir is identified and predicted, that is, the outline of the fracture-cavity body and its plane distribution law are described.

[0162] In view of the shortcomings of conventional full-wavefield seismic data, the present invention combines the high resolution and low signal-to-noise ratio characteristics of diffraction wave data and the imaging advantages of diffraction waves on fracture-cavity reservoirs, and proposes a fracture-cavity identification method based on carbonate reservoirs. The method first extracts the components of the diffraction wave seismic data along three directions respectively; then, based on the properties of Gaussian function and convolution, the diffraction wave components are convolved with the first-order derivative of the Gaussian function respectively 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, thereby improving the fracture-cavity identification accuracy of carbonate reservoirs based on the gradient energy and gradient energy entropy of the diffraction wave.

[0163] The present invention filters the directional components of diffraction wave data based on Gaussian functions to suppress part of the noise, obtains the gradient parameters of the diffraction wave in the directions, focuses and fuses them into diffraction wave gradient energy, and forms a diffraction wave gradient energy entropy attribute extraction method, thereby improving the fracture and cave attribute recognition accuracy of carbonate reservoirs and providing strong technical support for oil and gas geophysical exploration of heterogeneous geological anomalies in the study area.

[0164] Embodiment 2

[0165] In order to further illustrate the solution, the present invention also takes a certain block as an example to provide a specific application example of the fracture-cavity identification method based on carbonate reservoirs.

[0166] In order to make full use of the high-resolution detail information of diffraction wave data and improve the accuracy of fracture and cave identification in carbonate reservoirs, a fracture and cave body identification method based on carbonate reservoirs and a specific implementation process are proposed in a specific application example of the present invention. Specifically, see Figure 7 as well as Figure 8 , including the following steps:

[0167] S1: Acquire the radio wave 3D seismic data volume.

[0168] Perform diffraction wave separation on the full-wavefield three-dimensional seismic data volume of the target work area to obtain a diffraction wave three-dimensional seismic data volume; specifically, perform diffraction wave separation on a full-wavefield three-dimensional seismic data volume S(x, y, t) of a time length T to obtain a diffraction wave three-dimensional seismic data volume D(x, y, t), where t = 0, 1, 2, L, T;

[0169] See also Fig. 9 , which shows the full-wavefield seismic data S profile with a time domain range of 3s-4s and a duration of T=1s. From the profile, it can be seen that within the time range of 3.3s-3.6s, the fracture-cavity body in the carbonate reservoir exhibits a "beaded" diffraction wave seismic response characteristic, with strong heterogeneity. Fig.10 The cross-section of the diffraction wave data D obtained using the relevant mature diffraction wave separation method is shown. The diffraction wave has high resolution and rich detail information, which can better characterize the detailed characteristics of the fracture-cavity 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, which are D x (x,y,t),D y (x,y,t) and D t (x,y,t).

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

[0173] The one-dimensional Gaussian functions in the x, y and t directions are set to G(x), G(y) and G(t) respectively, and the variance σ of the Gaussian functions in the three directions is all 1.

[0174]

[0175]

[0176]

[0177] Among them, σ is the variance, which determines the fatness or thinness of the Gaussian normal distribution. The larger the variance, the fatter and shorter the normal distribution is, and the stronger the filtering effect on seismic data noise is. It is generally taken as a value between 0.1 and 3.0.

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

[0179] Derivative of a one-dimensional Gaussian function, the first-order derivatives in the corresponding directions are g(x), g(y), and g(t):

[0180]

[0181]

[0182]

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

[0184] While obtaining the derivatives of the diffraction wave seismic data in three directions, they are convolved with a one-dimensional Gaussian function for Gaussian smoothing filtering, and the derivatives after filtering in three directions can be obtained, namely, the directional gradients

[0185] Specifically, the gradients (first-order derivatives) of the diffraction wave seismic data D(x, y, t) along the three directions are set to d x (x,y,t),d y (x,y,t) and d t (x, y, t), respectively, convolve with a one-dimensional Gaussian function for Gaussian smoothing filtering, and the gradient dG after filtering in three directions can be obtained x (x,y,t),dG y (x,y,t) and dG t (x, y, t), that is, the gradient vector volume. According to the properties of convolution, the convolution of the derivative of a certain direction component of seismic data with the Gaussian function is equal to the convolution of a certain direction component of seismic data with the first-order 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 is understandable that, according to the nature of convolution, the convolution of the derivative of a certain direction component of seismic data with the Gaussian function is equal to the convolution of a certain direction component of seismic data with the first-order derivative of the Gaussian function. x , D y and D t Convolving with the one-dimensional Gaussian function derivative, we can get the diffraction wave gradient dG after filtering noise suppression in three directions. x , dG y and dG t ,like Figures 11 to 13 As shown, the signal-to-noise ratio of the diffraction wave gradient profiles in three directions is improved.

[0190] S6: According to the directional gradient vectors in three directions, the diffraction wave gradient energy E is obtained by fusion.

[0191] According to the gradient dG after filtering in three directions x (x,y,t),dG y (x,y,t) and dG t (x,y,t), and fused to get the diffraction wave gradient energy E.

[0192]

[0193] The diffraction wave gradient dG after suppressing the filtering noise in three directions x , dG y and dG t The diffraction wave gradient energy E is obtained by fusion, and the profile is as follows Fig.14 shown.

[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, and the profile is as follows Fig.15 As shown in the figure, the diffraction wave energy is focused on the section, which can effectively depict the three-dimensional morphology of the fracture cavity.

[0198] S8: Using the two attributes of diffraction wave gradient energy E and gradient energy entropy H, the fracture-cavity bodies in carbonate reservoirs are identified and predicted.

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

[0200] According to the plane diagram of the diffraction wave gradient energy entropy H ( Fig.16 ), the fracture-cave bodies of carbonate reservoirs are identified and predicted, which can better describe the contours of fracture-cave bodies of carbonate reservoirs in this block in detail, as well as the distribution patterns on the plane, which is more consistent with the actual drilling results.

[0201] From the above description, it can be seen that the fracture-cave body identification method based on carbonate reservoirs provided by an embodiment of the present invention first extracts the components of the diffraction wave in different directions of the target work area obtained in advance; then, the directional gradients of the diffraction wave in different directions are calculated according to the components of the diffraction wave in different directions; finally, the gradient energy and gradient energy entropy of the diffraction wave are calculated according to the directional gradients to identify the fracture-cave body in the target work area.

[0202] The present invention suppresses the noise of diffraction wave data based on Gaussian function to realize the extraction of diffraction wave gradient energy entropy attribute. Specifically, the diffraction wave directional component is first extracted, then the diffraction wave component filtering and gradient are obtained, and finally the diffraction wave gradient energy entropy attribute is extracted. The diffraction wave gradient energy entropy attribute extraction process is used to realize the fusion of diffraction wave component gradient and the function of gradient energy entropy attribute extraction.

[0203] As the effective oil and gas storage space of carbonate reservoirs, fractures and caves show diffraction wave characteristics. Conventional full-wavefield seismic data has the following characteristics: the energy of the reflection phase axis at the formation interface is relatively strong, which will shield the weak energy diffraction wave information generated by the heterogeneous fracture and cave bodies in the underlying strata, resulting in insufficient recognition of fracture and cave bodies, and cannot meet the current problem of qualitative identification of fractures and caves in heterogeneous reservoirs. To this end, the present invention aims at the shortcomings of conventional full-wavefield seismic data, combines the high resolution and low signal-to-noise ratio characteristics of diffraction wave data, and the imaging advantages of diffraction waves for fracture and cave reservoirs, and proposes a fracture and cave body identification method based on carbonate reservoirs. The method first extracts the components of the diffraction wave seismic data along three directions respectively; then, based on the properties of Gaussian function and convolution, the diffraction wave components are convolved with the first-order derivative of the Gaussian function respectively to obtain the diffraction wave gradient after filtering in three directions; finally, the diffraction wave direction gradient is focused and fused into gradient energy, and the corresponding diffraction wave gradient energy entropy is calculated, thereby improving the recognition accuracy of fractures and caves in carbonate reservoirs.

[0204] Embodiment 3

[0205] Based on the same principle, this embodiment also discloses a fracture-cavity identification device based on carbonate reservoirs, such as Fig.17 As shown, the device comprises:

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

[0207] A directional gradient obtaining module 20, used for obtaining the directional gradients of the diffracted wave in different directions according to the components of the diffracted wave in different directions;

[0208] The fracture body identification module 30 is used to obtain the gradient energy and gradient energy entropy of the diffraction wave according to the directional gradient to identify the fracture body in the target work area.

[0209] In some embodiments of the present invention, the components of the diffraction wave in different directions include:

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

[0211] In some embodiments of the present invention, the device for identifying fractures and caves in carbonate reservoirs further includes:

[0212] A diffraction wave acquisition module, used to acquire diffraction waves of a target work area;

[0213] The diffraction wave acquisition module comprises:

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

[0215] In some embodiments of the present invention, the device for identifying fractures and caves in carbonate reservoirs further includes:

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

[0217] In some embodiments of the present invention, the directional gradient obtaining module includes:

[0218] A Gaussian function obtaining unit, used for obtaining the one-dimensional Gaussian function of the diffraction wave in different directions;

[0219] The directional gradient obtaining unit is used to obtain the directional gradients of the diffracted wave in different directions according to the derivatives of the components of the radiation wave in different directions in different directions and the one-dimensional Gaussian function in the corresponding direction.

[0220] In some embodiments of the present invention, the device for identifying fractures and caves in carbonate reservoirs further includes:

[0221] A gradient energy obtaining module, used for fusing the directional gradients of the diffraction wave in different directions to obtain the gradient energy;

[0222] A gradient energy entropy obtaining module is used to obtain the gradient energy entropy of the diffraction wave according to the gradient energy.

[0223] In some embodiments of the present invention, the fracture body identification module includes:

[0224] A fracture body identification unit is used to characterize the fracture body contour and distribution law according to the gradient energy and the gradient energy entropy.

[0225] From the above description, it can be seen that the fracture-cave body identification device based on carbonate reservoirs provided by an embodiment of the present invention first extracts the components of the diffraction wave in different directions of the target work area obtained in advance; then, the directional gradients of the diffraction wave in different directions are calculated according to the components of the diffraction wave in different directions; finally, the gradient energy and gradient energy entropy of the diffraction wave are calculated according to the directional gradients to identify the fracture-cave body in the target work area.

[0226] The present invention utilizes the characteristics of high resolution and low signal-to-noise ratio of diffraction wave seismic data, filters the directional components of the diffraction wave data based on a Gaussian function to suppress part of the noise, obtains the gradient parameters of the diffraction wave in the direction, focuses and fuses them into diffraction wave gradient energy, and forms a diffraction wave gradient energy entropy attribute extraction method, thereby improving the fracture and cave attribute recognition accuracy of carbonate reservoirs.

[0227] Embodiment 4

[0228] The embodiment of the present application also provides a specific implementation of an electronic device capable of implementing all steps in the fracture-cavity identification method based on carbonate reservoirs in the above embodiment, see Fig.18 , electronic equipment specifically includes the following:

[0229] Processor (processor) 1201, memory (memory) 1202, communication interface (CommunicationsInterface) 1203 and bus 1204;

[0230] The processor 1201, the memory 1202, and the communication interface 1203 communicate with each other via the bus 1204; the communication interface 1203 is used to realize information transmission between related devices such as server-side devices, computing units, and client devices.

[0231] The processor 1201 is used to call the computer program in the memory 1202. When the processor executes the computer program, all the steps in the method for identifying fracture-cavity bodies based on carbonate reservoirs in the above embodiment are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0232] Extract the components of the diffraction waves of the target work area acquired in advance in different directions;

[0233] Obtaining the directional gradients of the diffraction wave in different directions according to the components of the diffraction wave in different directions;

[0234] The gradient energy and the gradient energy entropy of the diffraction wave are obtained according to the directional gradients to identify the fracture and cave body in the target work area.

[0235] In some embodiments of the present invention, the components of the diffraction wave in different directions include:

[0236] The diffraction wave includes a component in the survey line direction of the seismic data network of the target work area, a component in the seismic trace direction of the seismic data network, and a component in a direction perpendicular to the seismic data network.

[0237] In some embodiments of the present invention, obtaining the diffraction wave of the target working area includes the following steps:

[0238] The diffraction waves are separated from the three-dimensional seismic data volume of the target work area to obtain the diffraction waves.

[0239] In some embodiments of the present invention, the method for identifying fracture-cavity bodies in carbonate reservoirs further includes:

[0240] The derivatives of the components of the diffraction wave in different directions in different directions are obtained.

[0241] In some embodiments of the present invention, obtaining the directional gradients of the diffracted waves in different directions according to the components of the diffracted waves in different directions includes:

[0242] Obtaining one-dimensional Gaussian functions of the diffraction waves in different directions;

[0243] 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.

[0244] In some embodiments of the present invention, the method for identifying fracture-cavity bodies in carbonate reservoirs further includes:

[0245] fusing the directional gradients of the diffraction wave in different directions to obtain the gradient energy;

[0246] The gradient energy entropy of the diffraction wave is obtained according to the gradient energy.

[0247] In some embodiments of the present invention, obtaining the gradient energy and the gradient energy entropy of the diffraction wave according to the directional gradient to identify the fracture body in the target work area includes:

[0248] The contour and distribution pattern of the fracture body are characterized according to the gradient energy and the gradient energy entropy.

[0249] The present invention also discloses a fracture-cavity identification device based on carbonate reservoirs, comprising:

[0250] A diffraction wave component extraction module is used to extract components of the diffraction waves of the target work area acquired in advance in different directions;

[0251] A directional gradient obtaining module, used for obtaining the directional gradients of the diffraction wave in different directions according to the components of the diffraction wave in different directions;

[0252] The fracture 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 body in the target work area.

[0253] In some embodiments of the present invention, the components of the diffraction wave in different directions include:

[0254] The diffraction wave includes a component in the survey line direction of the seismic data network of the target work area, a component in the seismic trace direction of the seismic data network, and a component in a direction perpendicular to the seismic data network.

[0255] Embodiment 5

[0256] The embodiments of the present application also provide a computer-readable storage medium capable of implementing all the steps of the fracture-cavity identification method based on carbonate reservoirs in the above embodiments. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, all the steps of the fracture-cavity identification method based on carbonate reservoirs in the above embodiments are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0257] Extract the components of the diffraction waves of the target work area acquired in advance in different directions;

[0258] Obtaining the directional gradients of the diffraction wave in different directions according to the components of the diffraction wave in different directions;

[0259] The gradient energy and the gradient energy entropy of the diffraction wave are obtained according to the directional gradients to identify the fracture and cave body in the target work area.

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

[0261] The diffraction wave includes a component in the survey line direction of the seismic data network of the target work area, a component in the seismic trace direction of the seismic data network, and a component in a direction perpendicular to the seismic data network.

[0262] In some embodiments of the present invention, obtaining the diffraction wave of the target working area includes the following steps:

[0263] The diffraction waves are separated from the three-dimensional seismic data volume of the target work area to obtain the diffraction waves.

[0264] In some embodiments of the present invention, the method for identifying fracture-cavity bodies in carbonate reservoirs further includes:

[0265] The derivatives of the components of the diffraction wave in different directions in different directions are obtained.

[0266] In some embodiments of the present invention, obtaining the directional gradients of the diffracted waves in different directions according to the components of the diffracted waves in different directions includes:

[0267] Obtaining one-dimensional Gaussian functions of the diffraction waves in different directions;

[0268] 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.

[0269] In some embodiments of the present invention, the method for identifying fracture-cavity bodies in carbonate reservoirs further includes:

[0270] fusing the directional gradients of the diffraction wave in different directions to obtain the gradient energy;

[0271] The gradient energy entropy of the diffraction wave is obtained according to the gradient energy.

[0272] In some embodiments of the present invention, obtaining the gradient energy and the gradient energy entropy of the diffraction wave according to the directional gradient to identify the fracture body in the target work area includes:

[0273] The contour and distribution pattern of the fracture body are characterized according to the gradient energy and the gradient energy entropy.

[0274] The present invention also discloses a fracture-cavity identification device based on carbonate reservoirs, comprising:

[0275] A diffraction wave component extraction module is used to extract components of the diffraction waves of the target work area acquired in advance in different directions;

[0276] A directional gradient obtaining module, used for obtaining the directional gradients of the diffraction wave in different directions according to the components of the diffraction wave in different directions;

[0277] The fracture 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 body in the target work area.

[0278] In some embodiments of the present invention, the components of the diffraction wave in different directions include:

[0279] The diffraction wave includes a component in the survey line direction of the seismic data network of the target work area, a component in the seismic trace direction of the seismic data network, and a component in a direction perpendicular to the seismic data network.

[0280] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the hardware + program embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0281] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0282] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0283] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0284] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0285] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0286] The present invention uses specific embodiments to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

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 diffraction wave in different directions according to the components of the diffraction wave in different directions; The gradient energy and the gradient energy entropy of the diffraction wave are obtained according to the directional gradients to identify the fracture and cave body in the target work area.

2. The method for identifying fractures and caves in carbonate reservoirs 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 network of the target work area, a component in the seismic trace direction of the seismic data network, and a component in a direction perpendicular to the seismic data network.

3. The method for identifying fractures and caves in carbonate reservoirs according to claim 1, characterized in that: The acquisition of the diffraction waves of the target work area includes the following steps: The diffraction waves are separated from the three-dimensional seismic data volume of the target work area to obtain the diffraction waves.

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 method for identifying fractures and caves in carbonate reservoirs 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 method for identifying fracture-cavity bodies in carbonate reservoirs according to claim 1, characterized in that: Obtaining the gradient energy and the gradient energy entropy of the diffraction wave according to the directional gradient to identify the fracture-cavity body in the target work area, including: The contour and distribution pattern of the fracture body are characterized according to the gradient energy and the gradient energy entropy.

8. A device for identifying fractures and caves based on carbonate reservoirs, characterized in that: include: A diffraction wave component extraction module is used to extract components of the diffraction waves of the target work area acquired in advance in different directions; A directional gradient obtaining module, used for obtaining the directional gradients of the diffraction wave in different directions according to the components of the diffraction wave in different directions; The fracture 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 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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