Method, device, equipment and medium for identifying favorable areas

Abstract

The present application proposes a favorable zone identification method, device, equipment, and storage medium. The method includes: obtaining seismic data and well logging data of the study area; obtaining an amplitude plane distribution map of the target layer based on the seismic data; obtaining seismic wave impedance data of the target layer based on the seismic data; obtaining well logging wave impedance data, well logging porosity data, and well logging permeability data of the target layer based on the well logging data; obtaining a porosity plane distribution map of the target layer; obtaining a permeability plane distribution map of the target layer; obtaining wide-area apparent resistivity data of the target layer; obtaining a fluid identification plane map of the target layer; and superimposing the amplitude plane distribution map, porosity plane distribution map, permeability plane distribution map, and fluid identification plane map of the target layer to obtain favorable zone identification results for the target layer. The present application can identify favorable drilling zones during oil and gas field exploration using electromagnetic data, seismic data, and well logging data.

Description

Technical Field

[0001] The present application relates to the technical field of oil and gas exploration and development, and in particular to a method, device, equipment and medium for identifying a favorable zone. Background Art

[0002] Currently, geophysical technology development in oil and gas field exploration and development is primarily based on seismic data. Conventional seismic attribute analysis reveals sandstone thickness distribution or the planar distribution of reservoir physical properties. This only indicates the quality of reservoir physical properties, but cannot be linked to the oil and gas content in that area, making it impossible to accurately analyze the distribution of fluids within the reservoir. Relying solely on seismic attributes may reveal locations with good physical properties but low oil and gas content, making it impossible to accurately identify favorable drilling areas and optimize drilling locations, resulting in a low probability of drilling high-yield oil and gas wells. Summary of the Invention

[0003] This application aims to propose a favorable zone identification method, device, equipment and medium, which can achieve more accurate identification of favorable drilling areas during oil and gas field exploration by combining electromagnetic data, seismic data and logging data.

[0004] According to the first embodiment of the present application, the method for identifying a favorable zone includes:

[0005] Obtain seismic data and well logging data in the study area;

[0006] Obtaining an amplitude plane distribution diagram of a target layer according to the seismic data;

[0007] Acquiring seismic wave impedance data of the target layer according to the seismic data;

[0008] Acquiring logging wave impedance data, logging porosity data, and logging permeability data of the target layer based on the logging data;

[0009] Obtaining a porosity planar distribution diagram of the target layer according to the well logging wave impedance data, the well logging porosity data, and the seismic wave impedance data;

[0010] Obtaining a permeability planar distribution diagram of the target layer according to the well logging wave impedance data, the well logging permeability data, and the seismic wave impedance data;

[0011] Acquiring wide-area apparent resistivity data of the target layer;

[0012] Obtaining a fluid identification plan map of the target layer based on the wide-area apparent resistivity data;

[0013] The amplitude plane distribution map, the porosity plane distribution map, the permeability plane distribution map and the fluid identification plane map of the target layer are superimposed to obtain a favorable area identification result of the target layer.

[0014] According to some embodiments of the present application, obtaining the amplitude plane distribution map of the target layer based on the seismic data includes:

[0015] Extracting seismic attribute data of the target layer in the study area based on the seismic data;

[0016] An amplitude plane distribution diagram of the target layer is obtained according to the seismic attribute data, wherein the amplitude plane distribution diagram represents the sand body thickness distribution of the target layer.

[0017] According to some embodiments of the present application, obtaining the logging wave impedance data, the logging porosity data, and the logging permeability data of the target layer based on the logging data includes:

[0018] According to the logging data, three porosity curves are obtained; wherein the three porosity curves include an acoustic wave transit time curve, a density curve, and a neutron curve;

[0019] According to the three porosity curves, the well logging wave impedance data, the well logging porosity data and the well logging permeability data of the target layer are obtained.

[0020] According to some embodiments of the present application, obtaining the logging wave impedance data, the logging porosity data, and the logging permeability data of the target layer according to the three porosity curves includes:

[0021] Acquiring the logging wave impedance data according to the acoustic wave time difference curve and the density curve;

[0022] Acquiring the logging porosity data according to the acoustic wave time difference curve;

[0023] The well logging permeability data is obtained according to the neutron curve and the well logging porosity data.

[0024] According to some embodiments of the present application, obtaining a porosity planar distribution map of the target layer based on the well logging impedance data, the well logging porosity data, and the seismic impedance data includes:

[0025] Analyzing the correlation between the well logging porosity data and the well logging wave impedance data to obtain a first correlation coefficient;

[0026] When the first correlation coefficient is greater than or equal to a first threshold, analyzing the correlation between the well logging wave impedance data and the seismic wave impedance data to obtain a second correlation coefficient;

[0027] When the second correlation coefficient is greater than or equal to a first threshold, analyzing the correlation between the well logging porosity data and the seismic wave impedance data, and establishing a first correlation mathematical relationship between the well logging porosity data and the seismic wave impedance data;

[0028] According to the first related mathematical relationship, the logging porosity data is converted into three-dimensional volume data to obtain a porosity plane distribution map of the target layer;

[0029] The step of obtaining a permeability planar distribution diagram of the target layer based on the well logging wave impedance data, the well logging permeability data, and the seismic wave impedance data includes:

[0030] Analyzing the correlation between the well logging permeability data and the well logging wave impedance data to obtain a third correlation coefficient;

[0031] When the third correlation coefficient is greater than or equal to a first threshold, analyzing the correlation between the well logging wave impedance data and the seismic wave impedance data to obtain a fourth correlation coefficient;

[0032] When the fourth correlation coefficient is greater than or equal to the first threshold, analyzing the correlation between the well logging permeability data and the seismic wave impedance data, and establishing a second correlation mathematical relationship between the well logging permeability data and the seismic wave impedance data;

[0033] According to the second related mathematical relationship, the well logging permeability data is converted into three-dimensional volume data to obtain a permeability plane distribution diagram of the target layer.

[0034] According to some embodiments of the present application, obtaining a fluid identification plan map of the target layer based on the wide-area apparent resistivity data includes:

[0035] Encrypted acquisition of wide-area time-domain electromagnetic data of the target layer to obtain wide-area apparent resistivity data of the target layer;

[0036] Performing geological framework constrained inversion on the wide-area apparent resistivity data to obtain multiple inverted apparent resistivity distribution profiles of the target layer;

[0037] performing fluid identification and division on the plurality of inversion apparent resistivity distribution sections according to a fluid identification standard of the target layer to obtain a plurality of fluid identification results of the inversion apparent resistivity distribution sections;

[0038] According to the multiple inversion apparent resistivity distribution profile fluid identification results, the fluid plane identification result of the target layer is integrated to obtain the fluid identification plane map.

[0039] According to some embodiments of the present application, superimposing the amplitude plane distribution map, the porosity plane distribution map, the permeability plane distribution map, and the fluid identification plane map of the target layer to obtain a favorable zone identification result of the target layer includes:

[0040] Determine the scope of the study area and obtain boundary coordinates;

[0041] According to the boundary coordinates, the porosity plane distribution map and the permeability plane distribution map are superimposed by projection, and reservoir physical property classification is performed according to the reservoir physical property classification standard of the target layer to obtain the reservoir physical property plane distribution map of the target layer;

[0042] According to the boundary coordinates, the reservoir property plane distribution map and the amplitude plane distribution map are superimposed by projection, and the reservoir type is classified according to the reservoir type classification standard of the target layer to obtain the reservoir type plane distribution map of the target layer;

[0043] According to the boundary coordinates, the reservoir type planar distribution map and the fluid identification planar map are superimposed by projection, and favorable area division is performed according to the favorable area division standard of the target layer to obtain the favorable area identification result of the target layer.

[0044] According to the second aspect of the present application, the advantageous zone identification device includes:

[0045] The first acquisition module is used to obtain seismic data and well logging data of the study area;

[0046] A first plane map obtaining module is used to obtain an amplitude plane distribution map of a target layer based on the seismic data;

[0047] A second acquisition module is used to acquire seismic wave impedance data of the target layer based on the seismic data;

[0048] A third acquisition module is used to acquire the logging wave impedance data, the logging porosity data and the logging permeability data of the target layer according to the logging data;

[0049] A second plane map obtaining module is used to obtain a porosity plane distribution map of the target layer according to the well logging wave impedance data, the well logging porosity data and the seismic wave impedance data;

[0050] a third plane map obtaining module, configured to obtain a permeability plane distribution map of the target layer based on the well logging wave impedance data, the well logging permeability data, and the seismic wave impedance data;

[0051] a fourth acquisition module, configured to acquire wide-area apparent resistivity data of the target layer;

[0052] a fourth plane map obtaining module, configured to obtain a fluid identification plane map of the target layer based on the wide-area apparent resistivity data;

[0053] The identification result obtaining module is used to superimpose the amplitude plane distribution map, the porosity plane distribution map, the permeability plane distribution map and the fluid identification plane map of the target layer to obtain the favorable area identification result of the target layer.

[0054] According to an electronic device of an embodiment of the third aspect of the present application, the device includes a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the programs or instructions are executed by the processor, the steps of the advantageous zone identification method as described in any one of the embodiments of the first aspect are implemented.

[0055] According to the computer-readable storage medium of the fourth embodiment of the present application, computer-executable instructions are stored, and the computer-executable instructions are used to execute the advantageous zone identification method as described in the first embodiment above.

[0056] In the embodiment of the present application, seismic attributes are obtained by combining seismic data and well logging data for analysis, thereby realizing the identification of sand body thickness and porosity parameters, and then obtaining the sand body thickness distribution and the plane distribution of reservoir physical properties, which can identify and determine areas with good reservoir physical properties and large sand body thickness, and then use electromagnetic data to identify fluids, and then obtain the plane distribution of fluids, which can identify and determine oil and gas enrichment areas, and find the overlapping part of these two areas, that is, the drilling favorable area with large river sandstone thickness, good reservoir physical properties and oil and gas enrichment. The present application combines well logging data, electromagnetic data and seismic data to form a favorable area identification technology with deep fusion of "well electro-seismic", which can achieve more accurate identification of drilling favorable areas during oil and gas field exploration.

[0057] Other features and advantages of the present application will be set forth in the following description, and in part will be apparent from the description, or may be learned by practicing the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0059] Figure 1 is a flow chart of an embodiment of the advantageous zone identification method of the present application;

[0060] Figure 2 is a fluid identification standard chart of one embodiment of the advantageous zone identification method of the present application;

[0061] Figure 3 It is a reservoir property classification standard of an embodiment of the favorable zone identification method of the present application;

[0062] Figure 4 It is a reservoir type classification standard of an embodiment of the favorable zone identification method of the present application;

[0063] Figure 5 is a favorable area division standard of an embodiment of the favorable area identification method of the present application;

[0064] Figure 6 1 is a schematic diagram of the superposition process of the reservoir type plane distribution diagram of one embodiment of the favorable zone identification method of the present application;

[0065] Figure 7 1 is a schematic diagram of the superposition process of the favorable area plan layout diagram of one embodiment of the favorable area identification method of the present application;

[0066] Figure 8 is a schematic structural diagram of an embodiment of a favorable zone identification device of the present application;

[0067] Figure 9 It is a hardware structure diagram of an embodiment of the electronic device of the present application. DETAILED DESCRIPTION

[0068] The following describes in detail embodiments of the present application. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application and are not to be construed as limiting the present application.

[0069] In the description of this application, if there is a description of first, second, etc., it is only for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0070] In the description of this application, it should be understood that descriptions involving orientation, such as the orientation or positional relationship indicated by up, down, etc., are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on this application.

[0071] In the description of this application, it should be noted that, unless otherwise clearly defined, terms such as setting, installing, and connecting should be understood in a broad sense, and technical personnel in the relevant technical field can reasonably determine the specific meaning of the above terms in this application based on the specific content of the technical solution.

[0072] The technical solution of the present application will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described below are only part of the embodiments of the present application, not all of the embodiments.

[0073] Figure 1 This is a flow chart of the advantageous area identification method provided in the embodiment of this application. Figure 1 , further elaborating on the embodiments of this application.

[0074] The present invention provides a method for identifying a favorable area, which includes the following steps:

[0075] Step 101: Obtain seismic data and well logging data in the study area;

[0076] Step 102: Obtain an amplitude plane distribution diagram of the target layer based on the seismic data;

[0077] Step 103: Acquire seismic wave impedance data of the target layer based on the seismic data;

[0078] Step 104: Acquire the target layer's logging wave impedance data, logging porosity data, and logging permeability data based on the logging data;

[0079] Step 105: Obtain a porosity planar distribution diagram of the target layer based on the well logging impedance data, the well logging porosity data, and the seismic impedance data;

[0080] Step 106: Obtain a permeability planar distribution diagram of the target layer based on the well logging impedance data, the well logging permeability data, and the seismic impedance data;

[0081] Step 107: Acquire wide-area apparent resistivity data of the target layer;

[0082] Step 108: Obtain a fluid identification plan map of the target layer based on the wide-area apparent resistivity data;

[0083] Step 109 : Overlay the amplitude plane distribution map, the porosity plane distribution map, the permeability plane distribution map, and the fluid identification plane map of the target layer to obtain a favorable zone identification result of the target layer.

[0084] In the embodiment of the present application, seismic attributes are obtained by combining seismic data and well logging data analysis, thereby realizing the identification of sand body thickness and porosity parameters, and then obtaining the sand body thickness distribution and reservoir physical property plane distribution, which can identify and determine areas with good reservoir physical properties and large sand body thickness, and then use electromagnetic data to identify fluids, and then obtain the fluid plane distribution, which can identify and determine oil and gas enrichment areas, and find the overlapping part of these two areas, which is the drilling favorable area with large river sandstone thickness, good reservoir physical properties and oil and gas enrichment. The present application combines well logging data, electromagnetic data and seismic data to form a favorable area identification technology with deep fusion of "well electro-seismic", which can realize more accurate identification of drilling favorable areas during oil and gas field exploration. Furthermore, deploying well locations in favorable areas can effectively improve the success rate of drilling, increase the possibility of drilling high-yield oil and gas wells, and help to drill ideal wells with high daily production, high natural productivity, low development difficulty and low development cost in the research area.

[0085] The aforementioned seismic data may include seismic data acquired through seismic exploration and related seismic data interpretation results. Seismic data interpretation is the process of converting seismic data into geological information, including structural interpretation, stratigraphic interpretation, and lithologic interpretation. Seismic data plays a vital role in petroleum exploration, not only determining underground structural morphology and fault distribution, but also providing information on stratum lithology and reservoir thickness.

[0086] In some embodiments, after obtaining seismic data and well logging data in the study area, the method further includes performing preliminary processing on the seismic data.

[0087] The conventional steps and methods for preliminary processing of seismic data are as follows:

[0088] Preprocessing, including data input, observing system definition, trace editing, and true amplitude recovery;

[0089] Deconvolution is a frequency filtering process performed to eliminate the effects of ground filtering and receiving system filtering on seismic data. It can compress seismic wavelets, improve vertical resolution, and suppress interference such as multiple waves and short-period ringing, thereby improving the signal-to-noise ratio of seismic data.

[0090] Static correction: This step can eliminate the effects of surface elevation changes, weathering layer thickness and velocity changes, and excitation and receiving point depth changes on the reflected wave propagation time. This optimizes velocity analysis, improves stack imaging, increases the signal-to-noise ratio and resolution of seismic records, and accurately depicts the geometric morphology of various geological bodies.

[0091] Velocity analysis, including analysis of stacking velocity, root mean square velocity, average velocity and interval velocity;

[0092] Dynamic correction and stacking. The dynamic correction can eliminate the effect of shot offset on the travel time of the reflected wave, straighten the trajectory of the time-distance curve of the reflected wave at the common depth point, enhance the ability to suppress interference using stacking technology, and reduce the distortion of the reflected wave phase axis caused by the stacking process. The stacking method compresses multiple coverage data into a single coverage data, which can enhance the effective signal, suppress noise, and improve the signal-to-noise ratio of the seismic record.

[0093] Migration processing is the process of extending the surface records into the underground wave field through numerical calculation. In this process, the diffraction waves are converged, the reflected waves from the inclined interface are reset, the wave field interference is decomposed, the wavefront rotation phenomenon is eliminated, and the interface refraction, that is, the depth migration is corrected, so that the stratigraphic structure, fault distribution, breakpoints, pinch-out points, edges, anomalies and lithologic changes can be clearly imaged and accurately reset.

[0094] In some embodiments, after obtaining seismic data and well logging data of the study area, the method further includes performing preliminary processing on the well logging data.

[0095] The above preliminary processing of the logging data can be used to calculate the percentage of the thickness of the fine sandstone in the target layer to the total thickness of the target layer. The percentage of the thickness of the fine sandstone in the target layer to the total thickness of the target layer can represent the proportion of high-quality channel sandstone to the total sandstone, indicating the development of high-quality channel sandstone.

[0096] In some embodiments, obtaining an amplitude plane distribution map of a target layer based on seismic data includes:

[0097] Extract seismic attribute data of target layer in the study area based on seismic data;

[0098] According to the seismic attribute data, an amplitude plane distribution diagram of the target layer is obtained, wherein the amplitude plane distribution diagram represents the sand body thickness distribution of the target layer.

[0099] In this embodiment, seismic attribute data in the study area are extracted. Since the seismic attribute data are correlated with the thickness of fine sandstone, the corresponding seismic attribute plane distribution map can be obtained based on the seismic attribute data, and the thickness distribution of the sand body can be obtained based on this seismic attribute plane distribution map.

[0100] The seismic attribute data mentioned above has three common types of seismic attributes: amplitude, frequency and phase. In this application, the amplitude attribute data is used, so the amplitude plane distribution diagram of the target layer can be obtained.

[0101] The above-mentioned amplitude attribute data can adopt one of the categories of data. Specifically, in some cases, the root mean square amplitude can be used. Since the root mean square amplitude in the study area has the best correlation with the thickness percentage of fine sandstone in the target layer, the use of root mean square amplitude data can more accurately characterize the distribution of the target layer sand body.

[0102] In the preliminary processing of the above-mentioned logging data, the percentage data of the thickness of the fine sandstone in the target layer to the thickness of the entire target layer were statistically obtained. This percentage data can represent the proportion of high-quality channel sandstone to the total sandstone, indicating the development of high-quality channel sandstone. Therefore, in the study area, when the corresponding percentage data is highly correlated with the root mean square amplitude attribute obtained from seismic attributes, the root mean square amplitude attribute can be used to represent the thickness development of high-quality channel sandstone.

[0103] In some embodiments, obtaining logging wave impedance data, logging porosity data, and logging permeability data of a target layer based on well logging data includes:

[0104] According to the well logging data, three porosity curves are obtained; wherein the three porosity curves include the acoustic time difference curve, the density curve and the neutron curve;

[0105] According to the three-porosity curve, the logging wave impedance data, logging porosity data and logging permeability data of the target layer are obtained.

[0106] In this embodiment, a model needs to be established first to calculate the target layer logging porosity and logging permeability data. One or more of the three porosity curves, namely the acoustic wave time difference curve AC, the density curve DEN and the neutron curve CNL, can be selected to establish the model, and then the calculation is performed.

[0107] In some embodiments, obtaining the target layer's well logging impedance data, well logging porosity data, and well logging permeability data based on the three-porosity curve includes:

[0108] Obtain logging wave impedance data based on the acoustic wave time difference curve and density curve;

[0109] Obtain logging porosity data based on the acoustic time difference curve;

[0110] The logging permeability data is obtained based on the neutron curve and logging porosity data.

[0111] In this embodiment, the acoustic wave time difference curve AC among the three porosity curves is used to establish a relationship model between the logging porosity and the acoustic wave time difference curve AC, and then the logging porosity data of the target layer can be calculated; after obtaining the logging porosity data of the target layer, a relationship model between the logging porosity and the logging permeability is established, and then the logging permeability data of the target layer can be calculated.

[0112] The above wave impedance is generally defined as the product of density and velocity ρ i v i The above-mentioned acquisition of logging wave impedance data based on the acoustic wave time difference curve and density curve can be specifically constrained by the following mathematical expression:

[0113] ρ i v i =3.048×10 5 ×DEN i ×AC i

[0114] Among them, ρ i v i is the logging wave impedance of the ith formation, DEN i is the well logging density value of the i-th formation, in g / cm 3 , AC i is the acoustic time difference of the ith formation, in μs / ft.

[0115] The above method obtains the logging porosity data based on the acoustic transit time curve, that is, the acoustic transit time curve AC in the three porosity curves is used to establish a relationship model between the logging porosity and the acoustic transit time curve AC, which can be specifically constrained by the following mathematical expression:

[0116] φ=0.21654AC-36.265

[0117] Where, φ is the logging permeability, in %, and AC is the acoustic time difference curve.

[0118] The above-mentioned logging permeability data is obtained based on the neutron curve and logging porosity data, which can be specifically constrained by the following mathematical expression:

[0119]

[0120] Where K is the logging porosity in mD, φ is the logging permeability, and CNL is the neutron curve.

[0121] In some embodiments, seismic impedance data of the target layer is obtained based on seismic data. Post-stack inversion can be performed on the seismic data of the study area to obtain the seismic impedance data of the target layer, wherein the seismic impedance data is a three-dimensional volume data.

[0122] In some embodiments, obtaining a porosity planar distribution map of a target layer based on well logging impedance data, well logging porosity data, and seismic impedance data includes:

[0123] Analyze the correlation between the well logging porosity data and the well logging wave impedance data to obtain a first correlation coefficient;

[0124] When the first correlation coefficient is greater than or equal to the first threshold, analyzing the correlation between the well logging wave impedance data and the seismic wave impedance data to obtain a second correlation coefficient;

[0125] When the second correlation coefficient is greater than or equal to the first threshold, analyzing the correlation between the well logging porosity data and the seismic wave impedance data, and establishing a first correlation mathematical relationship between the well logging porosity data and the seismic wave impedance data;

[0126] According to the first related mathematical relationship, the well logging porosity data is converted into three-dimensional volume data to obtain the porosity plane distribution map of the target layer;

[0127] Based on the well logging impedance data, well logging permeability data and seismic impedance data, the permeability plane distribution map of the target layer is obtained, including:

[0128] Analyze the correlation between logging permeability data and logging wave impedance data to obtain the third correlation coefficient;

[0129] When the third correlation coefficient is greater than or equal to the first threshold, analyzing the correlation between the well logging wave impedance data and the seismic wave impedance data to obtain a fourth correlation coefficient;

[0130] When the fourth correlation coefficient is greater than or equal to the first threshold, analyzing the correlation between the well logging permeability data and the seismic wave impedance data, and establishing a second correlation mathematical relationship between the well logging permeability data and the seismic wave impedance data;

[0131] According to the second related mathematical relationship, the logging permeability data is converted into three-dimensional data to obtain the permeability plane distribution map of the target layer.

[0132] In this embodiment, by performing a linear correlation analysis between the well logging porosity data, well logging wave impedance data, and seismic wave impedance data of the target layer, when the positive correlation is high, a one-to-one mathematical relationship between the well logging porosity data and the seismic wave impedance data of the target layer can be established. Since the seismic wave impedance data is three-dimensional data, the well logging porosity data of the target layer can be expanded into three-dimensional data, thereby displaying the porosity distribution of the target layer on a plane and obtaining a porosity planar distribution map of the target layer. Similarly, by performing a linear correlation analysis between the well logging permeability data, well logging wave impedance data, and seismic wave impedance data of the target layer, when the positive correlation is high, a one-to-one mathematical relationship between the well logging permeability data and the seismic wave impedance data of the target layer can be established. Since the seismic wave impedance data is three-dimensional data, the well logging permeability data of the target layer can be expanded into three-dimensional data, thereby displaying the permeability distribution of the target layer on a plane and obtaining a permeability planar distribution map of the target layer.

[0133] In the above process, the correlation between the well logging porosity data and the well logging wave impedance data is first analyzed and a first correlation coefficient is obtained. When the first correlation coefficient is greater than or equal to the first threshold, it indicates that the correlation between the two is strong. Then, the next step is to analyze the correlation between the well logging wave impedance data and the seismic wave impedance data and obtain a second correlation coefficient. When the second correlation coefficient is greater than or equal to the first threshold, it indicates that the correlation between the two is strong. It can be known that there is a correlation between the well logging porosity data and the seismic wave impedance data. By establishing a one-to-one corresponding first correlation mathematical relationship between the two, the well logging porosity of the target layer is converted into three-dimensional data with spatial distribution, so that the distribution of the porosity of the target layer can be displayed on the plane, showing the high-value and low-value porosity areas, and obtaining the porosity plane distribution map of the target layer.

[0134] In the above process, the correlation between the well logging permeability data and the well logging wave impedance data is first analyzed and the third correlation coefficient is obtained. When the third correlation coefficient is greater than or equal to the first threshold, it indicates that the correlation between the two is strong. Then, the next step is to analyze the correlation between the well logging wave impedance data and the seismic wave impedance data and obtain the fourth correlation coefficient. When the fourth correlation coefficient is greater than or equal to the first threshold, it indicates that the correlation between the two is strong. It can be known that there is a correlation between the well logging permeability data and the seismic wave impedance data. By establishing a one-to-one corresponding second correlation mathematical relationship between the two, the well logging permeability of the target layer is converted into three-dimensional data with spatial distribution, so that the distribution of the permeability of the target layer can be displayed on the plane, and the permeability plane distribution map of the target layer can be obtained.

[0135] The first threshold can be set according to actual conditions. Specifically, the first threshold can be set to 0.8. When the correlation coefficient is greater than 0.8, it is considered that the correlation between the two data is strong.

[0136] In some embodiments, the wide-area apparent resistivity data of the target layer can be obtained based on the wide-area electromagnetic method to obtain the wide-area apparent resistivity data of the specified area. Specifically, the electromagnetic wave data of the specified area collected by the wide-area electromagnetic equipment can be used to obtain the wide-area apparent resistivity data of the specified area through Fourier transform, data denoising and calculation.

[0137] The wide-area electromagnetic equipment may include a wide-area high-power transmitter system and a wide-area high-precision receiver system.

[0138] The above wide-area apparent resistivity data can be calculated using the following formula:

[0139]

[0140] Where Ex is the x-component of the electric field of the wide-area electromagnetic device, MN is the distance between adjacent receiving points of the wide-area electromagnetic device, I is the magnitude of the harmonic current transmitted by the wide-area electromagnetic device, K is the device coefficient of the wide-area electromagnetic device observation device, and F(ikr) is the electromagnetic effect coefficient.

[0141] The above device coefficient K can be obtained by the following formula:

[0142] K=2πr 3 / (dL·MN)

[0143] Where dL is the distance of the electric dipole source of the wide-area electromagnetic device, and r is the transmitting and receiving distance of the wide-area electromagnetic device.

[0144] The above electromagnetic effect coefficient F(ikr) can be obtained by the following formula:

[0145]

[0146] in, is the azimuth, r is the receiving and transmitting distance of the wide-area electromagnetic equipment; k is the wave number, and i is the imaginary unit.

[0147] In some embodiments, obtaining a fluid identification plan map of a target layer based on wide-area apparent resistivity data includes:

[0148] Encrypted acquisition of wide-area time-domain electromagnetic data of the target layer to obtain wide-area apparent resistivity data of the target layer;

[0149] Perform geological framework-constrained inversion on wide-area apparent resistivity data to obtain multiple inverted apparent resistivity distribution profiles of the target layer;

[0150] According to the fluid identification standard of the target layer, multiple inversion apparent resistivity distribution sections are divided into fluid identification sections to obtain multiple fluid identification results of the inversion apparent resistivity distribution sections;

[0151] Based on the fluid identification results of multiple inverted apparent resistivity distribution profiles, the fluid plane identification results of the target layer are integrated to obtain a fluid identification plane map.

[0152] In this embodiment, spectrum encryption technology is used on the basis of wide-area electromagnetic method to encrypt the frequency points within the wide-area transmission frequency range of the target layer. By encrypting the target layer, the amount of data obtained is increased, and more reliable wide-area apparent resistivity data of the target layer is obtained. Therefore, the subsequent inversion results will be more reliable, and the vertical resolution will be effectively improved.

[0153] The above-mentioned geological framework constraint inversion is performed on the wide-area apparent resistivity data, wherein the layers can be divided according to the seismic data interpretation information in the seismic data, the geological framework can be constructed, and the geological framework constraint conditions can be obtained.

[0154] The above-mentioned fluid identification standard of the target layer is to identify and divide the target layer according to the wide-area apparent resistivity, such as Figure 2 As shown, the oil and gas layers, oil-water layers / gas-water layers, and water layers are divided. Based on multiple inverted apparent resistivity distribution profiles, the profile with the best inversion result among the multiple inverted apparent resistivity distribution profiles can be determined as the target inverted apparent resistivity distribution profile. Based on the target inverted apparent resistivity distribution profile, the fluid identification criteria for the target layer can be obtained.

[0155] The above-mentioned fluid identification results based on multiple inverted apparent resistivity distribution profiles are integrated to obtain the fluid plane identification results of the target layer and the fluid identification plane map. After completing the fluid identification work of the target layer in all profiles, the fluid identification results of all target layer profiles are combined to obtain the entire fluid identification data of the target layer, and then the fluid type and distribution range can be divided on the plane to obtain the fluid plane distribution map of the target layer in the study area, that is, the fluid identification plane map.

[0156] like Figure 6 and Figure 7 As shown, in some embodiments, the amplitude plane distribution map, the porosity plane distribution map, the permeability plane distribution map, and the fluid identification plane map of the target layer are superimposed to obtain a favorable zone identification result of the target layer, including:

[0157] Determine the scope of the study area and obtain the boundary coordinates;

[0158] Based on the boundary coordinates, the porosity plane distribution map and the permeability plane distribution map are superimposed by projection, and the reservoir physical property classification is performed according to the reservoir physical property classification standard of the target layer to obtain the reservoir physical property plane distribution map of the target layer;

[0159] Based on the boundary coordinates, the reservoir physical property plane distribution map and the amplitude plane distribution map are superimposed by projection, and the reservoir type is classified according to the reservoir type classification standard of the target layer to obtain the reservoir type plane distribution map of the target layer;

[0160] According to the boundary coordinates, the reservoir type plane distribution map and the fluid identification plane map are superimposed by projection, and the favorable area is divided according to the favorable area division standard of the target layer to obtain the favorable area identification result of the target layer.

[0161] In this embodiment, after the boundary range is determined, multiple different types of distribution maps are superimposed by projection, and all information can be displayed on one map. Different favorable area ranges are delineated according to corresponding division standards, and finally the favorable area identification result of the target layer can be obtained.

[0162] The CGCS2000 coordinate system can be used to determine the scope of the study area and obtain the boundary coordinates. Specifically, for example, if the study area is a quadrilateral, the coordinates of the four corners of the quadrilateral need to be determined.

[0163] For example, Figure 6 As shown in Figure 1, first superimpose the porosity plane distribution map b and permeability plane distribution map c of the target layer, and use the projection method to superimpose any map on the other map, and use the pre-defined reservoir physical property classification standard, such as Figure 3 As shown in the figure, the reservoir physical property range is delineated, and high-quality reservoirs, medium-quality reservoirs and poor-quality reservoirs are divided to obtain the reservoir physical property plane distribution map.

[0164] Secondly, if Figure 6 As shown in Figure 1, the reservoir physical property plane distribution map is superimposed with the amplitude plane distribution map a representing the thickness of the target layer sand body. The superposition method still adopts the projection method and uses the reservoir type classification standard, such as Figure 4 As shown in Figure 5, different reservoir types are circled and divided into Type I reservoirs, Type II reservoirs and Type III reservoirs, and the reservoir type plane distribution diagram d is obtained.

[0165] Finally, if Figure 7 As shown in the figure, the amplitude plane distribution map a is used as the reference of the boundary range, and the reservoir type plane distribution map d and the fluid identification plane map e are superimposed. The superposition method still adopts the projection method and uses the favorable area division standard, such as Figure 5 As shown in , the range of different favorable areas is delineated, and the optimal favorable area, suboptimal favorable area, medium favorable area and non-favorable area are divided, and finally the favorable area plane layout diagram f is obtained, so as to predict the favorable area and obtain the favorable area identification result. Figure 2 As shown in FIG5 , the fluid identification plane diagram e is divided into oil and gas layers, oil-water layers / gas-water layers, and water layers according to the fluid identification criteria. In the superimposed favorable area plane distribution diagram f, the area that is located in both the oil and gas layers and the Class I reservoir can be determined as the optimal favorable area.

[0166] It should be noted that if Figures 2 to 5 The various classification standards shown are for reference only, and the specific content can be adaptively adjusted according to the actual conditions of different regions.

[0167] The advantageous zone identification method provided in the embodiment of the present application may be executed by the advantageous zone identification device 200. In the embodiment of the present application, the advantageous zone identification device 200 executing the advantageous zone identification method is taken as an example to illustrate the advantageous zone identification device 200 provided in the embodiment of the present application.

[0168] See Figure 8 , is a schematic diagram of the structure of a favorable zone identification device 200 provided in an embodiment of the present application. Figure 8 As shown, the advantageous zone identification device 200 includes:

[0169] The first acquisition module 201 is used to acquire seismic data and well logging data of the study area;

[0170] A first plane map obtaining module 202 is used to obtain an amplitude plane distribution map of a target layer based on seismic data;

[0171] The second acquisition module 203 is used to obtain seismic wave impedance data of the target layer based on the seismic data;

[0172] The third acquisition module 204 is used to acquire the logging wave impedance data, the logging porosity data and the logging permeability data of the target layer according to the logging data;

[0173] The second plane map obtaining module 205 is used to obtain a porosity plane distribution map of the target layer based on the well logging wave impedance data, the well logging porosity data and the seismic wave impedance data;

[0174] The third plane map obtaining module 206 is used to obtain a permeability plane distribution map of the target layer based on the well logging wave impedance data, the well logging permeability data and the seismic wave impedance data;

[0175] The fourth acquisition module 207 is used to obtain wide-area apparent resistivity data of the target layer;

[0176] The fourth plane map obtaining module 208 is used to obtain a fluid identification plane map of the target layer based on the wide-area apparent resistivity data;

[0177] The identification result obtaining module 209 is used to superimpose the amplitude plane distribution map, the porosity plane distribution map, the permeability plane distribution map and the fluid identification plane map of the target layer to obtain the favorable area identification result of the target layer.

[0178] In some embodiments, the first plan view obtaining module 202 may be used to:

[0179] Extract seismic attribute data of target layer in the study area based on seismic data;

[0180] According to the seismic attribute data, an amplitude plane distribution diagram of the target layer is obtained, wherein the amplitude plane distribution diagram represents the sand body thickness distribution of the target layer.

[0181] In some implementations, the third acquisition module 204 may be configured to:

[0182] According to the well logging data, three porosity curves are obtained; wherein the three porosity curves include the acoustic time difference curve, the density curve and the neutron curve;

[0183] According to the three-porosity curve, the logging wave impedance data, logging porosity data and logging permeability data of the target layer are obtained.

[0184] In some implementations, the third acquisition module 204 may be configured to:

[0185] Obtain logging wave impedance data based on the acoustic wave time difference curve and density curve;

[0186] Obtain logging porosity data based on the acoustic time difference curve;

[0187] The logging permeability data is obtained based on the neutron curve and logging porosity data.

[0188] In some embodiments, the second plan view obtaining module 205 can be used to:

[0189] Analyze the correlation between the well logging porosity data and the well logging wave impedance data to obtain a first correlation coefficient;

[0190] When the first correlation coefficient is greater than or equal to the first threshold, analyzing the correlation between the well logging wave impedance data and the seismic wave impedance data to obtain a second correlation coefficient;

[0191] When the second correlation coefficient is greater than or equal to the first threshold, analyzing the correlation between the well logging porosity data and the seismic wave impedance data, and establishing a first correlation mathematical relationship between the well logging porosity data and the seismic wave impedance data;

[0192] According to the first related mathematical relationship, the well logging porosity data is converted into three-dimensional volume data to obtain the porosity plane distribution map of the target layer;

[0193] The third plane map obtaining module 206 can be used to:

[0194] Analyze the correlation between logging permeability data and logging wave impedance data to obtain the third correlation coefficient;

[0195] When the third correlation coefficient is greater than or equal to the first threshold, analyzing the correlation between the well logging wave impedance data and the seismic wave impedance data to obtain a fourth correlation coefficient;

[0196] When the fourth correlation coefficient is greater than or equal to the first threshold, analyzing the correlation between the well logging permeability data and the seismic wave impedance data, and establishing a second correlation mathematical relationship between the well logging permeability data and the seismic wave impedance data;

[0197] According to the second related mathematical relationship, the logging permeability data is converted into three-dimensional data to obtain the permeability plane distribution map of the target layer.

[0198] In some embodiments, the fourth plane map obtaining module 208 can be used to:

[0199] Encrypted acquisition of wide-area time-domain electromagnetic data of the target layer to obtain wide-area apparent resistivity data of the target layer;

[0200] Perform geological framework-constrained inversion on wide-area apparent resistivity data to obtain multiple inverted apparent resistivity distribution profiles of the target layer;

[0201] According to the fluid identification standard of the target layer, multiple inversion apparent resistivity distribution sections are divided into fluid identification sections to obtain multiple fluid identification results of the inversion apparent resistivity distribution sections;

[0202] Based on the fluid identification results of multiple inverted apparent resistivity distribution profiles, the fluid plane identification results of the target layer are integrated to obtain a fluid identification plane map.

[0203] In some implementations, the recognition result obtaining module 209 may be used to:

[0204] Determine the scope of the study area and obtain the boundary coordinates;

[0205] Based on the boundary coordinates, the porosity plane distribution map and the permeability plane distribution map are superimposed by projection, and the reservoir physical property classification is performed according to the reservoir physical property classification standard of the target layer to obtain the reservoir physical property plane distribution map of the target layer;

[0206] Based on the boundary coordinates, the reservoir physical property plane distribution map and the amplitude plane distribution map are superimposed by projection, and the reservoir type is classified according to the reservoir type classification standard of the target layer to obtain the reservoir type plane distribution map of the target layer;

[0207] According to the boundary coordinates, the reservoir type plane distribution map and the fluid identification plane map are superimposed by projection, and the favorable area is divided according to the favorable area division standard of the target layer to obtain the favorable area identification result of the target layer.

[0208] Since the favorable zone identification device 200 adopts all the technical solutions of the favorable zone identification method of the above embodiment, it has at least all the beneficial effects brought by the technical solutions of the above embodiment, which will not be described in detail here.

[0209] Figure 9 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application.

[0210] The electronic device may include a processor 301 and a memory 302 storing computer program instructions.

[0211] Specifically, the processor 301 may include a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0212] The memory 302 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 302 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 302 may include removable or non-removable (or fixed) media. Where appropriate, the memory 302 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 302 is a non-volatile solid-state memory.

[0213] In some embodiments, the memory 302 may include read-only memory (ROM), random access memory (RAM), magnetic disk storage media devices, optical storage media devices, flash memory devices, electrical, optical, or other physical / tangible memory storage devices. Thus, generally, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0214] The processor 301 reads and executes computer program instructions stored in the memory 302 to implement any one of the advantageous zone identification methods in the above embodiments.

[0215] In one example, the electronic device may further include a communication interface 303 and a bus 310. Figure 9 As shown, the processor 301 , the memory 302 , and the communication interface 303 are connected via a bus 310 and communicate with each other.

[0216] The communication interface 303 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0217] Bus 310 includes hardware, software or both, and the components of online data flow metering equipment are coupled to each other. For example, but not limitation, bus can include accelerated graphics port (AGP) or other graphics bus, enhanced industry standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industry standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations. In appropriate cases, bus 310 can include one or more buses. Although the present application embodiment describes and shows specific bus, the application considers any suitable bus or interconnection.

[0218] The electronic device can execute the advantageous zone identification method in the embodiment of the present application, thereby realizing the combination Figure 1 and Figure 8 Described is a method and apparatus for identifying advantageous zones.

[0219] In addition, in conjunction with the advantageous zone identification method in the above embodiments, embodiments of the present application may provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any of the advantageous zone identification methods in the above embodiments is implemented.

[0220] It should be understood that the present application is not limited to the specific configurations and processes described above and illustrated in the figures. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and illustrated as examples. However, the method process of the present application is not limited to the specific steps described and illustrated. Those skilled in the art can make various changes, modifications, and additions, or change the order of the steps after understanding the spirit of the present application.

[0221] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium that can store or transmit information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROMs, flash memories, erasable ROMs (EROMs), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0222] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps. In other words, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0223] Aspects of the present disclosure have been described above with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box 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 or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit. It is also understood that each box in the block diagram and / or flowchart and the combination of the boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0224] The above description is only a specific embodiment of the present application. Those skilled in the art will clearly understand that for the convenience and brevity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the scope of protection of the present application.

Claims

1. A method for identifying a favorable area, characterized in that: include: Obtain seismic data and well logging data in the study area; Obtaining an amplitude plane distribution diagram of a target layer according to the seismic data; Acquiring seismic wave impedance data of the target layer according to the seismic data; Acquiring logging wave impedance data, logging porosity data, and logging permeability data of the target layer based on the logging data; Obtaining a porosity planar distribution diagram of the target layer according to the well logging wave impedance data, the well logging porosity data, and the seismic wave impedance data; Obtaining a permeability planar distribution diagram of the target layer according to the well logging wave impedance data, the well logging permeability data, and the seismic wave impedance data; Acquiring wide-area apparent resistivity data of the target layer; Obtaining a fluid identification plan map of the target layer based on the wide-area apparent resistivity data; The amplitude plane distribution map, the porosity plane distribution map, the permeability plane distribution map and the fluid identification plane map of the target layer are superimposed to obtain a favorable area identification result of the target layer.

2. The advantageous zone identification method according to claim 1, characterized in that: Obtaining the amplitude plane distribution diagram of the target layer based on the seismic data includes: Extracting seismic attribute data of the target layer in the study area based on the seismic data; An amplitude plane distribution diagram of the target layer is obtained according to the seismic attribute data, wherein the amplitude plane distribution diagram represents the sand body thickness distribution of the target layer.

3. The advantageous zone identification method according to claim 1, characterized in that: The step of obtaining the well logging wave impedance data, well logging porosity data, and well logging permeability data of the target layer based on the well logging data includes: According to the logging data, three porosity curves are obtained; wherein the three porosity curves include an acoustic wave transit time curve, a density curve, and a neutron curve; According to the three porosity curves, the well logging wave impedance data, the well logging porosity data and the well logging permeability data of the target layer are obtained.

4. The advantageous zone identification method according to claim 3, characterized in that: The step of obtaining the well logging wave impedance data, well logging porosity data, and well logging permeability data of the target layer according to the three porosity curves includes: Acquiring the logging wave impedance data according to the acoustic wave time difference curve and the density curve; Acquiring the logging porosity data according to the acoustic wave time difference curve; The well logging permeability data is obtained according to the neutron curve and the well logging porosity data.

5. The advantageous zone identification method according to claim 1, characterized in that: The step of obtaining a porosity planar distribution diagram of the target layer based on the well logging wave impedance data, the well logging porosity data, and the seismic wave impedance data comprises: Analyzing the correlation between the well logging porosity data and the well logging wave impedance data to obtain a first correlation coefficient; When the first correlation coefficient is greater than or equal to a first threshold, analyzing the correlation between the well logging wave impedance data and the seismic wave impedance data to obtain a second correlation coefficient; When the second correlation coefficient is greater than or equal to a first threshold, analyzing the correlation between the well logging porosity data and the seismic wave impedance data, and establishing a first correlation mathematical relationship between the well logging porosity data and the seismic wave impedance data; According to the first related mathematical relationship, the logging porosity data is converted into three-dimensional volume data to obtain a porosity plane distribution map of the target layer; The step of obtaining a permeability planar distribution diagram of the target layer based on the well logging wave impedance data, the well logging permeability data, and the seismic wave impedance data includes: Analyzing the correlation between the well logging permeability data and the well logging wave impedance data to obtain a third correlation coefficient; When the third correlation coefficient is greater than or equal to a first threshold, analyzing the correlation between the well logging wave impedance data and the seismic wave impedance data to obtain a fourth correlation coefficient; When the fourth correlation coefficient is greater than or equal to the first threshold, analyzing the correlation between the well logging permeability data and the seismic wave impedance data, and establishing a second correlation mathematical relationship between the well logging permeability data and the seismic wave impedance data; According to the second related mathematical relationship, the well logging permeability data is converted into three-dimensional volume data to obtain a permeability plane distribution diagram of the target layer.

6. The advantageous zone identification method according to claim 1, characterized in that: The step of obtaining a fluid identification plan view of the target layer based on the wide-area apparent resistivity data includes: encrypting and collecting wide-area time-domain electromagnetic data of the target layer to obtain wide-area apparent resistivity data of the target layer; Performing geological framework constrained inversion on the wide-area apparent resistivity data to obtain multiple inverted apparent resistivity distribution profiles of the target layer; performing fluid identification and division on the plurality of inversion apparent resistivity distribution sections according to a fluid identification standard of the target layer to obtain a plurality of fluid identification results of the inversion apparent resistivity distribution sections; According to the multiple inversion apparent resistivity distribution profile fluid identification results, the fluid plane identification result of the target layer is integrated to obtain the fluid identification plane map.

7. The advantageous zone identification method according to claim 1, characterized in that: The superimposing the amplitude plane distribution map, the porosity plane distribution map, the permeability plane distribution map, and the fluid identification plane map of the target layer to obtain a favorable zone identification result of the target layer includes: Determine the scope of the study area and obtain boundary coordinates; According to the boundary coordinates, the porosity plane distribution map and the permeability plane distribution map are superimposed by projection, and reservoir physical property classification is performed according to the reservoir physical property classification standard of the target layer to obtain the reservoir physical property plane distribution map of the target layer; According to the boundary coordinates, the reservoir property plane distribution map and the amplitude plane distribution map are superimposed by projection, and the reservoir type is classified according to the reservoir type classification standard of the target layer to obtain the reservoir type plane distribution map of the target layer; According to the boundary coordinates, the reservoir type planar distribution map and the fluid identification planar map are superimposed by projection, and favorable area division is performed according to the favorable area division standard of the target layer to obtain the favorable area identification result of the target layer.

8. A favorable zone identification device, characterized in that: include: The first acquisition module is used to obtain seismic data and well logging data of the study area; A first plane map obtaining module is used to obtain an amplitude plane distribution map of a target layer according to the seismic data; A second acquisition module is used to acquire seismic wave impedance data of the target layer based on the seismic data; A third acquisition module is used to acquire the logging wave impedance data, the logging porosity data and the logging permeability data of the target layer according to the logging data; A second plane map obtaining module is used to obtain a porosity plane distribution map of the target layer according to the well logging wave impedance data, the well logging porosity data and the seismic wave impedance data; a third plane map obtaining module, configured to obtain a permeability plane distribution map of the target layer based on the well logging wave impedance data, the well logging permeability data, and the seismic wave impedance data; a fourth acquisition module, configured to acquire wide-area apparent resistivity data of the target layer; a fourth plane map obtaining module, configured to obtain a fluid identification plane map of the target layer based on the wide-area apparent resistivity data; The identification result obtaining module is used to superimpose the amplitude plane distribution map, the porosity plane distribution map, the permeability plane distribution map and the fluid identification plane map of the target layer to obtain the favorable area identification result of the target layer.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a program or instruction that can be run on the processor, and when the program or instruction is executed by the processor, the steps of the advantageous zone identification method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the advantageous zone identification method according to any one of claims 1 to 7.

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