Method for step-by-step identification of broken solution and related device

Abstract

The invention discloses a method and a related device for step-by-step identification of a broken solution. The method comprises the following steps: depicting an external boundary of a fault solution through seismic facies identification; describing a fault-karst fracture-cavity system through fracture prediction; and representing the pore structure in the broken solution through porosity inversion. By means of the method, macroscopic-to-concrete and qualitative-to-quantitative broken solution prediction is achieved, and the method is a new thought and a new method for step-by-step control and step-by-step dissection. According to the method provided by the invention, the dessert reservoir can be accurately searched and identified, the exploration and development investment is saved, and the single well yield is improved.

Description

Technical Field

[0001] The invention relates to the field of carbonate reservoir prediction in the petroleum industry, and in particular to a method for step-by-step identification of fault-karst bodies and related devices. Background Art

[0002] Carbonate rocks are relatively dense, especially limestones with poor pores. Generally, it is difficult to form effective reservoirs, but a series of fault zones formed after multiple tectonic actions are prone to forming reservoirs. The main reason is that under the exposure and erosion caused by tectonic uplift, surface water seeps down along the faults or local hydrothermal fluids rise, causing the fractures and cracks in these fracture zones to be dissolved and transformed to form carbonate fracture-cavity reservoirs. These reservoirs are controlled by faults and are distributed along the faults in both the vertical and horizontal directions. Under the sealing of the overburden and the shielding of the lateral dense limestone, karst reservoirs with various forms are formed, which are called "fault-karst bodies".

[0003] Due to differences in tectonic activities, sedimentary backgrounds and scales of karst development, the morphological characteristics and distribution of fault-karst bodies in different regions vary, resulting in low accuracy in the identification, prediction and characterization of fault-karst bodies, which restricts the efficient development of complex oil and gas fields. Summary of the invention

[0004] In view of the above problems, the object of the present invention is to provide a method and related device for step-by-step identification of disintegrated bodies.

[0005] In a first aspect, an embodiment of the present invention provides a method for step-by-step identification of a disintegration body, comprising the following steps:

[0006] Through seismic facies identification, the external boundary of the fault-karst body is characterized;

[0007] Through fracture prediction, describe the fault-karst fracture-cavity system;

[0008] The pore structure inside the fault solution is characterized by porosity inversion.

[0009] In one embodiment, characterizing the external boundary of the fault-karst body by identifying seismic phases includes:

[0010] Determine the distribution area of ​​beach-facies reservoirs through seismic attribute analysis;

[0011] Determine the karst development area through karst paleo-geomorphological restoration and karst paleo-fault analysis;

[0012] The beach phase reservoir distribution area and the karst development area are superimposed to determine the karst reservoir development area, and the structural tensor technology is used in the karst reservoir development area to characterize the external boundary of the fault-karst body.

[0013] In one embodiment, determining the distribution area of ​​the beach phase reservoir includes:

[0014] Through well seismic calibration, the seismic response characteristics of the reservoir are determined. Combined with the logging information, the seismic attributes reflecting the seismic response characteristics are selected according to the seismic response characteristics. The distribution of the beach phase reservoir is determined by combining the selected seismic attributes with the logging information.

[0015] In one embodiment, determining the seismic response characteristics of the reservoir includes:

[0016] The channel integration and / or 90° phase conversion technology is used to enhance the response characteristics of the reservoir on the seismic data, and the seismic response characteristics of the enhanced reservoir on the seismic data are determined to be medium-intensity peak reflection.

[0017] In one embodiment, the determining of the karst development area comprises:

[0018] Determine favorable karst development areas by carrying out paleo-geomorphological restoration, and characterize the distribution of karst paleo-faults by using fault prediction technology;

[0019] The karst favorable development area and the distribution of the karst ancient faults are superimposed to determine the karst development area.

[0020] In one embodiment, the description of the fault-karst fracture-cavity system by fracture prediction includes:

[0021] Combined with drilling information, the optimal fracture prediction technology is used to describe the vertical and horizontal distribution of fractures and holes in the fault-karst body.

[0022] In one embodiment, characterizing the internal pore structure of the fault-karst body by porosity inversion includes:

[0023] Conduct post-stack wave impedance inversion on reservoir seismic data to obtain wave impedance inversion data volume;

[0024] According to the relationship between wave impedance and porosity, the wave impedance inversion data volume is converted into a porosity data volume;

[0025] Extracting, from the porosity data volume, a porosity data volume having a porosity greater than a preset lower limit threshold;

[0026] The extracted porosity data volume is fused with the structure tensor data volume to characterize the internal pore structure of the fault-solid body.

[0027] In a second aspect, an embodiment of the present invention provides a device for step-by-step identification of a disintegrated body, comprising:

[0028] The characterization module is used to characterize the external boundary of the fault-karst body through seismic phase identification;

[0029] Description module, used to describe fault-karst fracture-cavity system through fracture prediction;

[0030] The characterization module is used to characterize the pore structure inside the fault solution through porosity inversion.

[0031] In a third aspect, an embodiment of the present invention provides a computing device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the aforementioned method of step-by-step identification of disintegrating bodies when executing the program.

[0032] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the aforementioned method for step-by-step identification of disintegrated bodies is implemented.

[0033] The beneficial effects of the above technical solution provided by the embodiment of the present invention include at least:

[0034] The above-mentioned fault-karst body step-by-step identification method and related device provided by the embodiment of the present invention qualitatively determine the outer boundary of the fault-karst body through seismic phase identification; qualitatively describe the fracture-cavity system inside the fault-karst body through fracture prediction; and quantitatively characterize the internal pore structure of the fault-karst body through porosity inversion. It realizes the prediction of fault-karst body from macroscopic to specific, from qualitative to quantitative, and is a new idea and method of step-by-step control and step-by-step dissection.

[0035] Furthermore, the method for step-by-step identification of fault-karst bodies provided in the embodiment of the present invention comprehensively considers various factors such as geology, well logging, and seismicity, and selects the best method in each level of the method according to the actual working conditions to predict, describe, and characterize the fault-karst body reservoir. Compared with the method of predicting fault-karst bodies based on fault identification in the prior art, the disadvantage that a relatively single method cannot accurately predict fault-karst body reservoirs is solved. The method provided by the present invention can accurately find and identify sweet spot reservoirs, save exploration and development investment, and increase the production of single wells.

[0036] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0038] Figure 1 It is a flow chart of the method for step-by-step identification of disintegration bodies in an embodiment of the present invention;

[0039] Figure 2 This is a seismic response characteristic diagram of the Permian Maokou Formation reservoir in an embodiment of the present invention;

[0040] Figure 3 This is a distribution diagram of the beach phase reservoir of the Permian Maokou Formation in the embodiment of the present invention;

[0041] Figure 4 This is a distribution diagram of karst development areas and faults during the sedimentary period of the Permian Maokou Formation in an embodiment of the present invention;

[0042] Figure 5 This is a distribution diagram of the external boundary of the Permian Maokou Formation fault-karst body in an embodiment of the present invention;

[0043] Figure 6 This is a distribution diagram of fractures and holes in the fault-karst body of the Permian Maokou Formation in an embodiment of the present invention;

[0044] Figure 7 This is a fusion diagram of the porosity data and structure tensor data of the moxi151-moxi39 wells in an embodiment of the present invention;

[0045] Figure 8 This is a flowchart of the carbonate rock fault-karst body step-by-step identification technology in an embodiment of the present invention;

[0046] Fig. 9 It is a schematic diagram of the structure of the device for step-by-step identification of disintegrated bodies in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] This embodiment provides a method for step-by-step identification of a dissolution body. Although the drawings show exemplary embodiments of the present disclosure, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. Specifically, the following steps are included:

[0048] The embodiment of the present invention provides a method for step-by-step identification of a disintegration body, referring to Figure 1 As shown, the method comprises the following steps:

[0049] S11. Characterize the external boundary of the fault-karst body through seismic phase identification;

[0050] S12. Describe the fault-karst fracture-cavity system through fracture prediction;

[0051] S13. Characterize the pore structure inside the fault solution through porosity inversion.

[0052] In one embodiment, in the above step S11, the external boundary of the fault-karst body is characterized by seismic phase identification, which can be achieved by the following steps in sequence:

[0053] (1) Determine the distribution area of ​​beach-facies reservoirs through seismic attribute analysis;

[0054] (2) Determine the karst development area through restoration of karst paleo-geomorphology and analysis of karst paleo-faults;

[0055] (3) The distribution area of ​​the beach phase reservoir and the karst development area are superimposed to determine the karst reservoir development area, and the structural tensor technology is used in the karst reservoir development area to characterize the external boundary of the fault-karst body.

[0056] In step S11 (1), in order to determine the distribution area of ​​the beach-facies reservoir, the seismic response characteristics of the reservoir are first analyzed through well seismic calibration; then, based on the seismic response characteristics of the reservoir, the seismic attributes are optimized and combined with the logging information to determine the distribution area of ​​the beach-facies reservoir.

[0057] For example, the response characteristics of the reservoir on the seismic data may be represented by using weak peak reflection and / or medium intensity peak reflection, but the present invention is not limited to the above-mentioned way of representing seismic response characteristics.

[0058] For example, the maximum peak amplitude attribute may be selected as the optimal seismic attribute, but the present invention is not limited to the above preferred seismic attribute manner.

[0059] For example, four geological models are established, including the development location, number of development layers, thickness of the reservoir, and physical property differences. Through forward simulation, the seismic response characteristics of the reservoir, i.e., weak wave crest reflection, can be obtained on the seismic profile. Due to the low resolution of seismic data, some thin reservoirs do not respond on the seismic data. In order to make the response characteristics of the reservoir on the seismic data clearer, the seismic response characteristics of the reservoir, i.e., medium-intensity wave crest reflection, can be obtained on the seismic profile through trace integration and / or 90° phase conversion technology. The embodiments of the present invention are not limited to the above-mentioned method of obtaining weak wave crest reflection and medium-intensity wave crest reflection.

[0060] In step S11, in order to determine the karst development area, paleo-geomorphological restoration is first carried out to determine the favorable development area of ​​karst action; then, combined with drilling information, the best fracture prediction technology is selected to characterize the distribution of karst paleo-fractures; finally, the favorable karst development area and the distribution of karst paleo-fractures obtained respectively are superimposed to determine the karst development area.

[0061] When carrying out paleo-geomorphological restoration to determine favorable development areas of karstification, different methods such as the impression method, the residual stratigraphic thickness method or the sequence stratigraphy method may be used. The embodiments of the present invention do not limit the specific method used.

[0062] When carrying out the step of characterizing the distribution of ancient karst faults, different fault prediction technologies can be preferably used, such as fault enhancement based on coherent attributes, fault identification based on spectral decomposition, high-resolution fault automatic identification, etc., and the embodiments of the present invention do not impose any restrictions on this.

[0063] On the basis of (1) and (2) of step S11, the respectively determined beach phase reservoir distribution area and karst development area are superimposed to determine the karst reservoir development area; in the karst reservoir development area, the structural tensor technology is further used to characterize the outer boundary of the fault-karst body.

[0064] In step S12, the internal structure of the fault-karst body, that is, the distribution of fractures and pores in the vertical and horizontal directions, is qualitatively described by using the optimal fracture prediction technology in combination with the drilling information.

[0065] Among the preferred fracture prediction technologies, fracture prediction technologies such as coherence attributes, curvature attributes, frequency division edge detection, or amplitude azimuth decomposition can be used. The drilling information can be combined to select the optimal fracture prediction technology to achieve a qualitative description of the internal structure of the fault carve. The specific implementation methods of each fracture prediction technology can refer to the prior art.

[0066] In step S13, in order to quantitatively characterize the pore structure inside the fault-solid body, the fault-solid body boundary determined in step S11 is used as a constraint condition to carry out reservoir porosity inversion. For example, this can be achieved by sequentially performing the following steps:

[0067] (1) Perform post-stack impedance inversion on reservoir seismic data to obtain an impedance inversion data volume;

[0068] (2) According to the relationship between wave impedance and porosity, the wave impedance inversion data volume is converted into a porosity data volume;

[0069] (3) From the porosity data volume, extract the porosity data volume that is greater than a preset lower porosity threshold; fuse the extracted porosity data volume with the structure tensor data volume to complete the quantitative characterization of the pore structure inside the fault-karst body.

[0070] When performing post-stack wave impedance inversion in the above step S13 (1), geostatistical inversion or waveform indication inversion or other methods may be used, but the present invention does not limit this.

[0071] The porosity lower limit threshold value preset in the above step S13 (3) is determined according to the actual working condition analysis. For example, the lower limit threshold value may be equal to 2%, but this is not limited in the embodiment of the present invention.

[0072] The embodiment of the present invention proposes a method for step-by-step identification of fault-karst bodies, firstly qualitatively determining the external boundary of the fault-karst body; then qualitatively describing the fracture-cavity system inside the fault-karst body; and finally quantitatively characterizing the internal pore structure of the fault-karst body. By comprehensively utilizing geological, logging and seismic data, a new method for fault-karst body prediction is realized, which is step-by-step controlled and dissected from macroscopic to specific, from qualitative to quantitative.

[0073] The above-mentioned method of step-by-step identification of dissolution bodies is illustrated by a specific example.

[0074] Taking the Permian Maokou Formation reservoir in a certain area of ​​a basin in the west as an example, the dolomite reservoir of the Maokou Formation in this area is mainly located in the Mao 2nd section of the middle part of the Maokou Formation. The granular beach phase is the material basis for the formation of the reservoir, and the weathering karst and faults formed by sedimentation are the key to the formation of favorable reservoirs. The scale, stage and karst stage of the fault are the main influencing factors for the development of fault-karst bodies. The fault-karst bodies are mainly distributed in deep and large fault zones and their secondary fault zone dissolution surfaces. The fracture-cavern type fault-karst bodies formed on the dissolution surface of the secondary fault zone have the largest relative scale, the largest storage space, the best matching relationship between faults and caves, and the best reservoir performance. The method provided by the present invention is used to realize the step-by-step identification of the fault-karst reservoirs in the area, which can be completed in three steps in total.

[0075] The first step is to characterize the outer boundary of the fault-karst body through seismic phase identification. This step can be divided into three steps 1.1 to 1.3 to complete the characterization of the outer boundary of the fault-karst body in sequence.

[0076] 1.1. Determine the distribution of beach-phase reservoirs through seismic attribute analysis. The specific approach is: determine the seismic response characteristics of the reservoir through well-seismic calibration. For example, four geological models of reservoir development location, number of development layers, reservoir thickness and reservoir physical property differences can be established, and then the seismic response characteristics of the reservoir - weak peak reflection - can be determined through forward simulation. Due to the defect of low resolution of seismic data, some thin reservoirs have no response or unclear response in seismic data. Therefore, in this embodiment, the 90° phase conversion technology is used to obtain a new response characteristic of the reservoir - medium-intensity peak reflection, so that the response characteristics of the reservoir on the seismic data are clearer. For example, the moxi39 dolomite beach-phase reservoir of the Permian Maokou Formation in the region is taken as the research object, and the corresponding seismic response characteristics are obtained by the above method, such as Figure 2 Shown, including Figure 2 The weak peak reflection in the middle and upper figure and Figure 2 The iso-intensity peak reflection in the middle and lower figures. The location of the moxi39 beach phase reservoir of the Permian Maokou Formation in this area is shown in Figure 3 as shown in .

[0077] from Figure 2 Comparing the above figure with the figure below, it can be seen that in the conventional seismic profile of the moxi39 well, the location where the reservoir is developed is a weak peak reflection in a wide and gentle trough reflection, and the seismic response characteristics of the medium-intensity peak reflection that should be theoretically not obvious. Since the dolomite reservoir of the Maokou Formation is relatively thin, the standard 0° phase conventional seismic data is not ideal for thin layer interpretation. Therefore, by performing the 90° phase conversion technology, a very clear seismic response characteristic of medium-intensity peak reflection at the reservoir development location can be obtained. The present invention does not limit the above-mentioned method of obtaining the seismic response characteristics and the specific representation method of the seismic response characteristics.

[0078] Next, based on the medium-intensity crest seismic response characteristics of the reservoir, experiments were conducted using amplitude seismic attributes (such as root mean square amplitude, maximum peak amplitude, maximum trough amplitude, amplitude energy, amplitude slope, absolute amplitude integral, etc.) to select sensitive seismic attributes that match the reservoir in actual drilling. On this basis, using the development location of the dolomite reservoir explained in the logging information, the time window size for sensitive seismic attribute extraction is continuously corrected, and the plan view that best matches the actual drilling is selected to determine the distribution of the beach-phase reservoir. For example, the seismic attribute selected in this example is the maximum peak amplitude attribute. By analyzing the maximum peak amplitude attribute, the distribution map of the beach-phase reservoir of the Permian Maokou Formation in this area is obtained as shown below. Figure 3 As shown. Figure 3 Among them, the area with the maximum peak amplitude attribute greater than 3400db is the area where the beach phase reservoir is developed.

[0079] The present invention does not limit the above-selected specific seismic attributes.

[0080] 1.2. Determine the karst development zone through karst paleo-geomorphology restoration and karst paleo-fault analysis. The specific approach is: first, carry out paleo-geomorphology restoration to determine the favorable development zone of karst action. For example, the paleo-geomorphology restoration can be carried out by using the impression method, residual stratigraphic thickness method or sequence stratigraphy method; then, combined with the drilling information, the best fracture prediction technology is selected to characterize the fracture distribution during the karst period. For example, the preferred fracture prediction technology may include fracture enhancement based on coherent attributes, fracture identification based on spectral decomposition and high-resolution fracture automatic identification; finally, the obtained karst paleo-geomorphology and karst paleo-fault are superimposed to determine the karst development zone. The karst development zone and fracture distribution map of the Permian Maokou Formation sedimentary period obtained in this example are shown in the figure. Figure 4 As shown. Figure 4 In the figure, the area with high paleo-geomorphology (relatively darker color) is the karst development area during the sedimentary period. The karst paleo-geomorphology and paleo-fault distribution in this area can be clearly seen from the figure. The present invention does not limit the method of carrying out paleo-geomorphology restoration and depicting the fault distribution during the karst period.

[0081] 1.3, using the structural tensor technique to depict the external boundary of the fault-karst body. The specific method includes: superimposing the beach phase reservoir distribution area and the karst development area determined in the first and second steps to obtain the karst reservoir development area; then using the structural tensor technique in the karst reservoir development area to depict the external boundary of the fault-karst body. The distribution of the external boundary of the fault-karst body obtained by the structural tensor technique is shown in Figure 1. Figure 5 shown.

[0082] The implementation steps of the structural tensor analysis technology are as follows: (1) Seismic data preprocessing: Perform a full three-dimensional multi-window dip scan on the seismic data to obtain the dip data volume and the azimuth data volume, and use the dip data volume and the azimuth data volume as constraints for filtering to obtain new three-dimensional seismic data; (2) Obtaining gradients: Obtaining the first-order partial derivatives of the preprocessed three-dimensional seismic data in the vertical, inline and crossline directions to obtain the gradient vector of each data sample position corresponding to the preprocessed three-dimensional seismic data; (3) Constructing a structural tensor matrix: Multiplying the gradient with its transpose to form a third-order square matrix, and smoothing each element in the square matrix to obtain the average structural tensor matrix within a certain scale range; (4) Calculating structural tensor data: Decomposing the structural tensor eigenvalues ​​at each data sample point to obtain the anisotropic parameters and directional characteristics that characterize the image structure, and calculating the structural tensor data by optimizing the three eigenvalues ​​and their different combinations; (5) Extracting sensitive attributes: Using statistical optimization and other methods to extract sensitive attributes from the structural tensor data, the boundary of the fault-karst body can be obtained.

[0083] The second step is to describe the fracture-cavity system of the fault-karst body through fracture prediction. After completing the first step of characterizing the external boundary of the fault-karst body, the internal fracture-cavity system of the fault-karst body is qualitatively described next. The fracture-cavity system of the fault-karst body is mainly the vertical and horizontal distribution of internal fractures and holes. Combined with drilling information, the description of the fracture-cavity system of the fault-karst body is achieved by optimizing the best fracture prediction technology. For example, the optional fracture prediction technologies include coherence attributes, curvature attributes, frequency division edge detection or amplitude azimuth decomposition and other technologies. In this example, based on the fracture prediction technology of the maximum positive curvature attribute of the structure-guided filter, the distribution map of fractures and holes in the fault-karst body is obtained as shown in the figure. Figure 6 The embodiment of the present invention does not limit the preferred actual crack prediction technology.

[0084] The third step is to characterize the internal structure of the fault-karst body through porosity inversion. The differences in the internal structure of the fault-karst body are mainly reflected in the degree of development of internal fractures and caves. The reservoir porosity inversion is carried out with the fault-karst body boundary determined by the structural tensor attributes in the first step as a constraint condition. The specific implementation method can be completed through the following steps 3.1 to 3.3.

[0085] 3.1, perform post-stack wave impedance inversion on reservoir seismic data to obtain wave impedance inversion data volume. The method for performing post-stack wave impedance inversion can adopt a geostatistical inversion method or a waveform indication inversion method. In this example, the waveform indication inversion method is adopted, but the embodiment of the present invention does not limit the specific post-stack wave impedance inversion method.

[0086] 3.2, according to the relationship between wave impedance and porosity, the wave impedance inversion data volume is converted into a porosity data volume. First, the wave impedance is calculated using the acoustic wave curves and density curves of the reservoir development sections of all wells in the study area; secondly, the neutron curve or porosity curve of the reservoir section is corrected using the core analysis data of the reservoir section to calculate the porosity; then, a quantitative relationship between wave impedance and porosity is established; finally, according to this quantitative relationship, the wave impedance inversion data volume is converted into a porosity data volume.

[0087] 3.3, the porosity is selected as the reservoir lower limit threshold, so all the porosity data volumes greater than 2% are extracted and fused with the structure tensor data volume to achieve the characterization of the pore structure inside the fault-karst body. For example, after the porosity data volume exceeding the threshold value of the moxi151-moxi39 wells in this area is fused with the structure tensor data, the characterization diagram of the pore structure inside the fault-karst body is obtained as follows Figure 7 As shown. Figure 7 The variation of the porosity inside the fault-karst body can be seen in the figure: the darker color area has a smaller porosity and undeveloped fractures and holes; the lighter color area has a larger porosity and more developed fractures and holes. In the embodiment of the present invention, the preset lower limit of the porosity is not limited.

[0088] In summary, the implementation process in the embodiment of the present invention can be summarized as follows: Figure 8 The flowchart of the technical process for step-by-step identification of carbonate fault-karst bodies is shown.

[0089] Based on the same inventive concept, an embodiment of the present invention also provides a device for step-by-step identification of broken dissolution bodies. Since the principle of the problem solved by the device is similar to that of the aforementioned method for step-by-step identification of broken dissolution bodies, the implementation of the device can refer to the implementation of the aforementioned method, and the repeated parts will not be repeated.

[0090] The embodiment of the present invention provides a device for step-by-step identification of a disintegrated body, referring to Fig. 9 As shown, including:

[0091] A characterization module 91 is used to characterize the outer boundary of the fault-karst body through seismic phase identification;

[0092] A description module 92 is used to describe the fault-karst fracture-cavity system through fracture prediction;

[0093] The characterization module 93 is used to characterize the pore structure inside the fault solution through porosity inversion.

[0094] An embodiment of the present invention provides a computing device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the aforementioned method for step-by-step identification of disintegrated bodies when executing the program.

[0095] An embodiment of the present invention provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the method for step-by-step identification of disintegration bodies as described above is implemented.

[0096] Obviously, those skilled in the art can make various changes to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these changes.

Claims

1. A method for step-by-step identification of disintegration bodies, characterized in that: include: Through seismic facies identification, the external boundary of the fault-karst body is characterized; Through fracture prediction, describe the fault-karst fracture-cavity system; The pore structure inside the fault solution is characterized by porosity inversion.

2. The method according to claim 1, characterized in that The identification of seismic phases and the characterization of the external boundary of the fault-karst body include: Determine the distribution area of ​​beach-facies reservoirs through seismic attribute analysis; Determine the karst development area through karst paleo-geomorphological restoration and karst paleo-fault analysis; The beach phase reservoir distribution area and the karst development area are superimposed to determine the karst reservoir development area, and the structural tensor technology is used in the karst reservoir development area to characterize the external boundary of the fault-karst body.

3. The method according to claim 2, characterized in that The determining of the distribution area of ​​the beach facies reservoir comprises: Through well seismic calibration, the seismic response characteristics of the reservoir are determined. Combined with the logging information, the seismic attributes reflecting the seismic response characteristics are selected according to the seismic response characteristics. The distribution area of ​​the beach phase reservoir is determined by combining the selected seismic attributes with the logging information.

4. The method according to claim 3, characterized in that The determining of the seismic response characteristics of the reservoir comprises: The channel integration and / or 90° phase conversion technology is used to enhance the response characteristics of the reservoir on the seismic data, and the seismic response characteristics of the enhanced reservoir on the seismic data are determined to be medium-intensity peak reflections.

5. The method according to claim 2, characterized in that Determining the karst development area includes: Determine favorable karst development areas by carrying out paleo-geomorphological restoration, and characterize the distribution of karst paleo-faults by using fault prediction technology; The karst favorable development area and the distribution of the karst ancient faults are superimposed to determine the karst development area.

6. The method according to claim 1, characterized in that The description of the fault-karst fracture-cavity system through fracture prediction includes: Combined with drilling information, the optimal fracture prediction technology is used to describe the vertical and horizontal distribution of fractures and holes in the fault-karst body.

7. The method according to claim 1, characterized in that The porosity inversion is used to characterize the internal pore structure of the fault-karst body, including: Conduct post-stack wave impedance inversion on reservoir seismic data to obtain wave impedance inversion data volume; According to the relationship between wave impedance and porosity, the wave impedance inversion data volume is converted into a porosity data volume; Extracting, from the porosity data volume, a porosity data volume having a porosity greater than a preset lower limit threshold; The extracted porosity data volume is fused with the structure tensor data volume to characterize the internal pore structure of the fault-solid body.

8. A device for simulating the multi-stage oil and gas accumulation process, characterized in that: include: The characterization module is used to characterize the external boundary of the fault-karst body through seismic phase identification; Description module, used to describe fault-karst fracture-cavity system through fracture prediction; The characterization module is used to characterize the pore structure inside the fault solution through porosity inversion.

9. A computing device, characterized in that include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for step-by-step identification of a disintegrating body as described in any one of claims 1 to 8 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for step-by-step identification of a disintegration body according to any one of claims 1 to 8 is implemented.

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