Fluid identification method, device, equipment and storage medium

Abstract

The present application proposes a fluid identification method, apparatus, equipment, and storage medium. The method includes: obtaining geological information data of the area to be identified, establishing multiple well-connected stratigraphic grid profiles, and calibrating the layers; obtaining first wide-area apparent resistivity data of all layers in the area to be identified, and second wide-area apparent resistivity data of the target layer in the area to be identified, and replacing the data of the target layer in the first wide-area apparent resistivity data with the second wide-area apparent resistivity data to obtain an electrical comprehensive data body; performing joint constrained inversion based on the multiple well-connected stratigraphic grid profiles and the electrical comprehensive data body to obtain multiple inverted apparent resistivity distribution profiles, and determining the target inverted apparent resistivity distribution profile to obtain a wide-area fluid identification standard, and performing fluid identification division on the multiple inverted apparent resistivity distribution profiles, thereby obtaining a fluid plane identification result for the area to be identified. The present application can achieve high-precision fluid identification of the target layer in the area to be identified through well logging data and electromagnetic 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 fluid identification method, device, equipment and storage medium. Background Art

[0002] Currently, the research and development of geophysical technologies for oil and gas field exploration and development primarily relies on seismic data acquired through seismic methods. However, there are relatively few existing technologies for fluid identification during oil and gas field exploration and development. Typically, fluid identification is achieved using a combination of seismic data, well logging data, and electrical data. Because these technologies require the collection of three types of information, data processing is difficult and slow. Especially in mature oil and gas exploration and development areas, the fluid identification process is significantly affected by the quality of seismic data. Seismic data can also lead to inaccurate stratigraphic structures, numerous constraints, and slow processing speeds, resulting in significant application limitations. Summary of the Invention

[0003] The present application aims to propose a fluid identification method, device, equipment and storage medium, which realizes fluid identification of the target layer in the identification area through logging data and electromagnetic data, while improving the speed and accuracy of fluid identification.

[0004] The fluid identification method according to the first embodiment of the present application includes:

[0005] Obtaining geological information of the area to be identified, the geological information including lithologic data, well logging data, oil and gas testing data, stratification data, and completion data;

[0006] According to the lithologic data and the well logging data, multiple well-connected stratigraphic grid sections are established and horizon positions are calibrated;

[0007] Based on the wide-area electromagnetic method, first wide-area apparent resistivity data of all layers in the area to be identified are obtained;

[0008] Based on the spectrum encryption technology and the wide-area electromagnetic method, second wide-area apparent resistivity data of the target layer in the area to be identified is obtained;

[0009] replacing the data of the target layer in the first wide-area apparent resistivity data with the second wide-area apparent resistivity data to obtain an electrical comprehensive data volume;

[0010] Performing joint constrained inversion based on the multiple well-connected stratigraphic grid sections and the comprehensive electrical data volume to obtain multiple inverted apparent resistivity distribution sections;

[0011] Determining a target inversion apparent resistivity distribution profile based on the multiple inversion apparent resistivity distribution profiles, wherein the target inversion apparent resistivity distribution profile is a profile with the best inversion result among the multiple inversion apparent resistivity distribution profiles;

[0012] Obtaining a wide-area fluid identification standard based on the well logging data, the oil and gas testing data, and the target inversion apparent resistivity distribution profile, wherein the wide-area fluid identification standard identifies and divides the fluid in the to-be-identified area based on the wide-area apparent resistivity;

[0013] performing fluid identification and division on the plurality of inverted apparent resistivity distribution profiles according to the wide-area fluid identification standard to obtain fluid identification results of the plurality of inverted apparent resistivity distribution profiles;

[0014] According to the multiple inverted apparent resistivity distribution profile fluid identification results, a fluid plane identification result of the target layer in the area to be identified is obtained.

[0015] According to some embodiments of the present application, obtaining the second wide-area apparent resistivity data of the target layer in the area to be identified based on spectrum encryption technology and wide-area electromagnetic method includes:

[0016] Obtaining the top and bottom depths of the target layer according to the well logging data;

[0017] Based on the skin depth formula, the wide-area transmission frequency range of the target layer is obtained according to the top and bottom depths of the target layer;

[0018] Based on spectrum encryption technology, frequency encryption is performed within the wide-area transmission frequency range of the target layer;

[0019] Based on the wide-area electromagnetic method, obtaining second electromagnetic wave data of the target layer collected by wide-area electromagnetic equipment in an encrypted manner;

[0020] Second wide-area apparent resistivity data of the target layer is obtained according to the second electromagnetic wave data.

[0021] According to some embodiments of the present application, obtaining first wide-area apparent resistivity data of all layers in the area to be identified based on a wide-area electromagnetic method includes:

[0022] Based on the wide-area electromagnetic method, obtaining first electromagnetic wave data of the area to be identified collected by the wide-area electromagnetic equipment;

[0023] First wide-area apparent resistivity data of all layers in the area to be identified is obtained based on the first electromagnetic wave data.

[0024] According to some embodiments of the present application, after obtaining first wide-area apparent resistivity data of all layers in the area to be identified based on the first electromagnetic wave data, the method further includes:

[0025] The first wide-area apparent resistivity data is subjected to layer correction based on the well logging data, so that the first wide-area apparent resistivity data matches the lithology data, layering data and completion data of the area to be identified.

[0026] According to some embodiments of the present application, performing joint constrained inversion based on the multiple well-connected formation grid sections and the electrical comprehensive data volume to obtain multiple inverted apparent resistivity distribution sections includes:

[0027] Establishing a geoelectrical model based on the multiple well-connected stratigraphic grid sections and the electrical comprehensive data volume;

[0028] Based on multiple inversion constraints, the geoelectric model is jointly inverted to obtain multiple inversion apparent resistivity distribution profiles.

[0029] According to some embodiments of the present application, the well logging data includes well logging resistivity;

[0030] The wide-area fluid identification standard is obtained based on the well logging data, the oil and gas test data and the target inversion apparent resistivity distribution profile, including:

[0031] Obtaining a first fluid identification standard for the area to be identified based on the well logging data and the oil and gas testing data; wherein the first fluid identification standard identifies and divides the fluids in the area to be identified based on the well logging resistivity;

[0032] The wide-area fluid identification standard is obtained according to the target inversion apparent resistivity distribution profile and the first fluid identification standard.

[0033] According to some embodiments of the present application, obtaining a fluid plane identification result of the target layer in the area to be identified based on the multiple inverted apparent resistivity distribution profile fluid identification results includes:

[0034] According to the fluid identification results of the multiple inverted apparent resistivity distribution profiles, the fluid types and distribution ranges are divided on a plane to obtain a fluid plane distribution map of the target layer in the area to be identified;

[0035] The fluid types include gas layer, gas-water layer, gas-bearing layer, and dry layer.

[0036] A fluid identification device according to an embodiment of the second aspect of the present application includes:

[0037] The first acquisition module is used to acquire geological information of the area to be identified, wherein the geological information includes lithology data, well logging data, oil and gas testing data, stratification data and completion data;

[0038] An establishment module is used to establish multiple well-connected stratigraphic grid sections and calibrate horizons based on the lithologic data and the well logging data;

[0039] A second acquisition module is configured to obtain first wide-area apparent resistivity data of all layers in the area to be identified based on a wide-area electromagnetic method;

[0040] A third acquisition module is configured to obtain second wide-area apparent resistivity data of the target layer in the area to be identified based on spectrum encryption technology and the wide-area electromagnetic method;

[0041] a replacement module, configured to replace the data of the target layer in the first wide-area apparent resistivity data with the second wide-area apparent resistivity data to obtain an electrical comprehensive data body;

[0042] an inversion module, configured to perform a joint constrained inversion based on the plurality of well-connected formation grid sections and the electrical comprehensive data volume to obtain a plurality of inverted apparent resistivity distribution sections;

[0043] a determination module, configured to determine a target inversion apparent resistivity distribution profile based on the plurality of inversion apparent resistivity distribution profiles, wherein the target inversion apparent resistivity distribution profile is a profile with the best inversion result among the plurality of inversion apparent resistivity distribution profiles;

[0044] a standard acquisition module, configured to obtain a wide-area fluid identification standard based on the well logging data, the oil and gas test data, and the target inversion apparent resistivity distribution profile, wherein the wide-area fluid identification standard identifies and divides the fluid in the to-be-identified area based on the wide-area apparent resistivity;

[0045] a first identification module configured to perform fluid identification and division on the plurality of inverted apparent resistivity distribution profiles according to the wide-area fluid identification standard, and obtain fluid identification results of the plurality of inverted apparent resistivity distribution profiles;

[0046] The second identification module is configured to obtain a fluid plane identification result of the target layer in the area to be identified based on the multiple inverted apparent resistivity distribution profile fluid identification results.

[0047] 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 fluid identification method as described in any one of the embodiments of the first aspect are implemented.

[0048] 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 fluid identification method as described in the first embodiment above.

[0049] In the embodiment of the present application, the low-precision stratigraphic framework established by seismic data is abandoned, and the geological framework is established by using real geological data such as well logging data, which has high reliability, higher accuracy and fast data processing speed; in the process of acquiring electromagnetic data, the wide-area apparent resistivity data of the target layer in the area to be identified is acquired by encrypting the acquisition, thereby increasing the amount of acquired data of the target layer and improving the resolution of the underground structure of the deeper target layer; the acquired well-connected stratigraphic grid profile and the acquired electrical comprehensive data body are jointly constrained inverted, and combined with real geological data such as well logging data and electromagnetic data, a more accurate inversion result can be obtained, while avoiding the problems of huge data, slow processing speed and high multi-solution in the process of using seismic data. In mature oil and gas exploration and development areas with rich and accurate well logging data, the present application can realize fluid identification of the target layer in the area to be identified by well logging data and electromagnetic data, avoiding the problem of low accuracy of the stratigraphic framework established by seismic data, while improving the speed and accuracy of fluid identification, effectively filling the gap in rapid fluid identification in highly mature oil and gas development areas.

[0050] 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

[0051] 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:

[0052] Figure 1 is a flow chart of an embodiment of the fluid identification method of the present application;

[0053] Figure 2 This is a well logging comprehensive classification evaluation standard chart of an embodiment of the fluid identification method of the present application;

[0054] Figure 3 is a wide-area fluid identification standard chart of one embodiment of the fluid identification method of the present application;

[0055] Figure 4 is a schematic structural diagram of an embodiment of a fluid identification device of the present application;

[0056] Figure 5 It is a hardware structure diagram of an embodiment of the electronic device of the present application. DETAILED DESCRIPTION

[0057] 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.

[0058] 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.

[0059] 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.

[0060] 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.

[0061] 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.

[0062] To facilitate a better understanding of the solutions of the embodiments of the present application, the relevant technologies are first introduced below.

[0063] In the field of oil and gas exploration and development, target reservoirs often contain fluids of varying properties, such as oil, natural gas, formation water, and artificially injected fracturing fluids. These multiple fluids coexist within the reservoir, forming vertical layers and horizontal blocks due to the influence of gravity or artificial development measures. When deploying oil and gas exploration and production wells, it is crucial to select locations within oil and gas-rich areas to maximize drilling success rates.

[0064] The resistivity of oil, gas, and water in a reservoir varies significantly, forming the theoretical basis for this fluid identification method. Generally, oil and natural gas are essentially non-conductive, exhibiting high to very high resistance. Formation water and artificially injected water-based fracturing fluids are conductors, exhibiting low to very low resistance. The resistivity of formations devoid of oil, gas, or water typically falls somewhere in between these two.

[0065] Seismic exploration is typically used for exploring unknown areas, providing rich and reliable data. However, it is difficult and costly to conduct, making it inadequate in mature oil and gas exploration and development areas. Furthermore, mature areas boast densely drilled wells, providing abundant geological information such as well logging and logging, enabling a clear understanding of stratigraphic architecture and structural development. Geological information obtained through drilling provides firsthand insights into the subsurface, resulting in the most accurate and reliable stratigraphic architecture.

[0066] Figure 1 This is a flow chart of the fluid identification method according to the embodiment of the present application. Figure 1 , further elaborating on the embodiments of this application.

[0067] The present invention provides a method for fluid identification, which includes the following steps:

[0068] Step 101: Acquire geological information of the area to be identified, including lithologic data, well logging data, oil and gas testing data, stratification data, and completion data;

[0069] Step 102: Based on the lithologic data and well logging data, multiple well-connected stratigraphic grid sections are established and the horizons are calibrated;

[0070] Step 103: obtaining first wide-area apparent resistivity data of all layers in the area to be identified based on the wide-area electromagnetic method;

[0071] Step 104: obtaining second wide-area apparent resistivity data of the target layer in the area to be identified based on spectrum encryption technology and wide-area electromagnetic method;

[0072] Step 105: Replace the data of the target layer in the first wide-area apparent resistivity data with the second wide-area apparent resistivity data to obtain an electrical comprehensive data volume;

[0073] Step 106: performing joint constrained inversion based on the multiple well-connected stratigraphic grid sections and the electrical comprehensive data volume to obtain multiple inverted apparent resistivity distribution sections;

[0074] Step 107: determining a target inverted apparent resistivity distribution profile based on the multiple inverted apparent resistivity distribution profiles, wherein the target inverted apparent resistivity distribution profile is the profile with the best inversion result among the multiple inverted apparent resistivity distribution profiles;

[0075] Step 108: Obtain a wide-area fluid identification standard based on the well logging data, oil and gas test data, and the target inverted apparent resistivity distribution profile, wherein the wide-area fluid identification standard identifies and divides the fluids in the to-be-identified area based on the wide-area apparent resistivity.

[0076] Step 109: performing fluid identification and division on the multiple inverted apparent resistivity distribution profiles according to the wide-area fluid identification standard to obtain multiple fluid identification results of the inverted apparent resistivity distribution profiles;

[0077] Step 110: Obtain a fluid plane identification result of a target layer in the area to be identified based on the multiple inverted apparent resistivity distribution profile fluid identification results.

[0078] In the embodiment of the present application, the low-precision stratigraphic framework established by seismic data is abandoned, and the geological framework is established by using real geological data such as well logging data, which has high reliability, higher accuracy and fast data processing speed; in the process of acquiring electromagnetic data, the wide-area apparent resistivity data of the target layer in the area to be identified is acquired by encrypting the acquisition, thereby increasing the amount of acquired data of the target layer and improving the resolution of the underground structure of the deeper target layer; the acquired well-connected stratigraphic grid profile and the acquired electrical comprehensive data body are jointly constrained inverted, and combined with real geological data such as well logging data and electromagnetic data, a more accurate inversion result can be obtained, while avoiding the problems of huge data, slow processing speed and high multi-solution in the process of using seismic data. In mature oil and gas exploration and development areas with rich and accurate well logging data, the present application can realize fluid identification of the target layer in the area to be identified by well logging data and electromagnetic data, avoiding the problem of low accuracy of the stratigraphic framework established by seismic data, while improving the speed and accuracy of fluid identification, effectively filling the gap in rapid fluid identification in highly mature oil and gas development areas.

[0079] In some embodiments, geological information data of the area to be identified is obtained, and the geological information data includes lithology data, well logging data, oil and gas testing data, stratification data, and completion data;

[0080] The aforementioned area to be identified may be a research area within an area where oil and gas exploration and development are relatively mature.

[0081] The above-mentioned geological information data can be relevant data of drilled wells located in the area to be identified; wherein, the above-mentioned drilled wells are not limited to oil wells, gas wells and water wells, and each well can be evenly distributed in the study area; the above-mentioned relevant data of drilled wells should include but are not limited to well data such as lithological data, stratification data, logging data, mud logging data, oil and gas testing data and completion data.

[0082] The above-mentioned lithologic data include data that directly reflect lithology and data that indirectly reflect lithology. The data that directly reflect lithology include drilling cores and logging cuttings, while the data that indirectly reflect lithology include gamma logging, compensated density logging, natural potential logging, photoelectric effect cross-section index logging, sonic logging and other logging data.

[0083] For example, in the aforementioned lithologic data, the data directly reflecting the lithologic characteristics can be used to determine the lithologic characteristics first. In wells where direct lithologic data is unavailable, the data indirectly reflecting the lithologic characteristics can be used to identify the lithologic characteristics. In some cases, both direct and indirect lithologic data can be collected, allowing for cross-correlation and more accurate data.

[0084] The above-mentioned stratification data include the stratification results data at the oil field site, logging depth data, the above-mentioned core data and geological background data.

[0085] For example, the stratification results data provided by the oil field site can be used in the above-mentioned stratification data; if such results data are not available, the geological background data can be used to obtain the geological development background in the study area, including tectonic movements and sedimentary environments. At the same time, the lithologic data can be used to subdivide the layers of each well, and the lithologic data and logging depth data can be matched one-to-one to obtain the stratification results data.

[0086] The above-mentioned logging data include specific logging data such as resistivity logging, gamma logging, density logging, spontaneous potential logging, neutron logging, photoelectric effect cross-section index logging, acoustic transit time logging, and nuclear magnetic resonance logging. All logging data have corresponding depth data.

[0087] The above-mentioned resistivity logging can be used to determine the resistivity value of the target layer, which can reflect the oil and gas content. Specifically, the higher the oil and gas content, the greater the resistivity, and vice versa. If it contains water, the resistivity value is lower than that without water; the above-mentioned gamma logging can be used to measure lithology, and can more accurately distinguish the lithology changes at the top and bottom of the target layer, thereby accurately determining the top and bottom depths of the target layer; the above-mentioned density logging can be used to measure the density of the target layer, which can assist in judging the fluid. Among them, the fluids mainly include oil, gas and water, which have obvious differences in density; the above-mentioned neutron logging is quite sensitive to the oil and gas content of the target layer. This is because the difference in the deceleration ability of oil layers and gas layers for neutrons is very obvious. Therefore, neutron logging can be used to judge the oil and gas content of the target layer; the above-mentioned acoustic time difference logging can be used to judge the lithology, porosity and pore fluid properties of the formation; the above-mentioned nuclear magnetic resonance logging can use thermal relaxation time to distinguish oil and water and judge the fluid properties.

[0088] The above-mentioned logging data include cuttings logging, gas logging and fluorescence logging.

[0089] The above-mentioned oil and gas testing data include the property identification results of various fluids such as oil, gas and water.

[0090] The above completion data include regional structural overview and structural development history, stratigraphic sequence encountered, stratification basis, stratigraphic electrical characteristics and rock-electrical combination characteristics, and the situation of oil, gas and water layers encountered.

[0091] The regional structural overview and structural development history in the above-mentioned completion data can serve as the basis for the subsequent establishment of well-connected profiles and the vertical and planar analysis of fluid identification. The stratigraphic sequence encountered in the above-mentioned completion data refers to the general term for various layered rocks formed during the development of the earth's crust, including sedimentary, volcanic and metamorphic layered rocks. Analysis of the stratigraphic sequence of a single well is the basis for establishing a single-well stratification framework profile and a well-connected framework profile. The stratification in the above-mentioned completion data is based on comparable marker layer characteristics, paleontological data and rock-electrical combination characteristics.

[0092] In some embodiments, based on lithologic data and well logging data, multiple well-connected stratigraphic grid sections are established and horizons are calibrated, including:

[0093] Establish a single well stratigraphic framework profile based on lithologic data and well logging data;

[0094] Then, multiple wells are selected and a well-connected stratigraphic grid section is established based on their single-well stratigraphic grid sections.

[0095] The above-mentioned single-well stratigraphic framework profile mainly includes the following information: natural gamma ray logging (GR, unit API), shale content (SH, unit %), acoustic transit time logging (AC, unit us / ft), resistivity logging (M2RX / M2R6, unit Ω·m), total hydrocarbon content (unit %), porosity logging (POR, unit %), etc.

[0096] As mentioned above, multiple wells are selected and a connected stratigraphic grid section is established based on their single-well stratigraphic grid sections. When selecting wells, attention should be paid to the section direction reflecting the structural characteristics of the area to be identified as much as possible. The selected well locations should include major oil and gas production wells and water injection wells.

[0097] In some embodiments, the apparent resistivity data of a specified area is obtained based on the wide-area electromagnetic method. The electromagnetic wave data of the specified area is collected by wide-area electromagnetic equipment, and the apparent resistivity data of the specified area is obtained through Fourier transform, data denoising, calculation and other measures.

[0098] The wide-area electromagnetic equipment may include a wide-area high-power transmitter and a wide-area high-precision receiver.

[0099] The above apparent resistivity data can be calculated using the following formula:

[0100]

[0101] 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 observation device of the wide-area electromagnetic device, and F(ikr) is the electromagnetic effect coefficient.

[0102] The above device coefficient K can be obtained by the following formula:

[0103] K=2πr 3 / (dL·MN)

[0104] 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.

[0105] The above electromagnetic effect coefficient F(ikr) can be obtained by the following formula:

[0106]

[0107] 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.

[0108] In some embodiments, based on spectrum encryption technology and wide-area electromagnetic method, obtaining second wide-area apparent resistivity data of the target layer in the area to be identified includes:

[0109] Obtain the top and bottom depths of the target layer based on well logging data;

[0110] Based on the skin depth formula, the wide-area emission frequency range of the target layer is obtained according to the top and bottom depths of the target layer;

[0111] Based on spectrum encryption technology, frequency points are encrypted within the wide-area transmission frequency range of the target layer;

[0112] Based on the wide-area electromagnetic method, the second electromagnetic wave data of the target layer collected by the wide-area electromagnetic equipment is obtained;

[0113] Second wide-area apparent resistivity data of the target layer is obtained according to the second electromagnetic wave data.

[0114] In this implementation, encrypted acquisition of the target layer increases the amount of data acquired, resulting in more reliable second-wide-area apparent resistivity data for the target layer. This, in turn, makes subsequent inversion results more reliable, effectively improving vertical resolution. Specifically, when the target layer is deep, without frequency encryption, the signal frequencies corresponding to the target layer depth are typically 1-3. With spectrum encryption, this can be increased to 10-30, doubling the number, significantly improving vertical resolution.

[0115] The above skin depth formula is as follows:

[0116]

[0117] Where D is the detection depth, in meters; ρ is the apparent resistivity, in Ω·m, representing the combined resistivity from the surface to a certain depth, i.e., the combined resistivity of multiple layers; and f is the transmitted signal frequency, in Hz. The transmission frequency of wide-area electromagnetic equipment can range from 0.0020 Hz to 15728.6 Hz, and the transmission frequency can be adjusted based on actual conditions. Generally, higher frequencies result in shallower detection depths, while higher frequencies result in deeper detection depths.

[0118] Specifically, the top and bottom depths of the target layer are obtained from the logging data, and the emission frequency is converted according to the skin depth formula to obtain the wide-area emission frequency range of the target layer. Subsequently, based on the above-mentioned top and bottom frequency ranges of the target layer, spectrum encryption technology is used to encrypt and collect wide-area pseudo-random signal data for the target layer. After Fourier transform, data denoising and calculation, the wide-area apparent resistivity of the target layer is obtained.

[0119] In some embodiments, obtaining first wide-area apparent resistivity data of all layers in the area to be identified based on a wide-area electromagnetic method includes:

[0120] Based on the wide-area electromagnetic method, first electromagnetic wave data of the area to be identified is obtained by the wide-area electromagnetic equipment;

[0121] First wide-area apparent resistivity data of all layers in the area to be identified are obtained based on the first electromagnetic wave data.

[0122] In this embodiment, electromagnetic wave data of the area to be identified is collected by wide-area electromagnetic equipment, thereby obtaining first wide-area apparent resistivity data of all layers in the area to be identified.

[0123] In some embodiments, first wide-area apparent resistivity data of all layers in the area to be identified is obtained based on the first electromagnetic wave data, and then the method further includes:

[0124] According to the well logging data, the first wide-area apparent resistivity data is subjected to layer correction so that the first wide-area apparent resistivity data matches the lithology data, layering data and completion data of the area to be identified.

[0125] The above-mentioned stratum correction can be achieved by obtaining information such as the target layer's logging resistivity, lithology, top and bottom depths, and oil and gas content based on the information given by the various logging curves included in the logging data, and making a comprehensive judgment to achieve stratum correction of the first wide-area apparent resistivity data.

[0126] In this embodiment, the wide-area apparent resistivity is corrected for the horizon using the logging resistivity and logging depth, which can reduce the error between the wide-area apparent resistivity and the horizon in the profile, so that the apparent resistivity has a good matching relationship with the lithology and depth, further improving the accuracy and reliability of the first wide-area apparent resistivity data.

[0127] Generally speaking, for strata of different lithologies, their resistivity usually has a large difference. The resistivity of mudstone is generally less than 200Ω·m, the resistivity of sandstone is 10-1000Ω·m, the resistivity of limestone or dolomite is 150-9000Ω·m, and the resistivity of anhydrite is 10 4 -10 6 Ω·m, the resistivity of granite can reach 10 5 Ω·m.

[0128] If the formation contains fluids (oil, gas, and water), the formation resistivity will fluctuate greatly. Taking a common sandstone reservoir as an example, if it contains oil or gas, its resistivity can exceed 10 6 Ω·m, and with the difference in oil and gas content and accumulation location, the depth of color can be used in the profile to intuitively reflect the accumulation shape and location of oil and gas; if the sandstone reservoir contains formation water or water-based fracturing fluid, the resistivity will decrease due to the increase in ion concentration in the water body. In this case, the resistivity of the sandstone reservoir is generally lower than 50Ω·m, which can also be intuitively reflected by the depth of color in the apparent resistivity profile.

[0129] Generally speaking, if a formation contains no fluid, the top and bottom boundaries of the apparent resistivity can be roughly demarcated by lithology. By simultaneously determining the top and bottom depths of the formation using well logging resistivity, a relatively accurate apparent resistivity profile can be obtained. If certain formations contain fluid, the type, location, depth, and extension of the fluid within that layer will be reflected through the type, location, depth, and extension of the color. Therefore, matching wide-area apparent resistivity data with lithologic data, stratification data, and completion data ensures its accuracy and reliability.

[0130] In some embodiments, after performing horizon correction on the first wide-area apparent resistivity data, the method further includes:

[0131] Performing linear fitting on the acquired first wide-area apparent resistivity data, and performing correlation analysis with the well logging resistivity in the well logging data, to obtain a correlation coefficient between the first wide-area apparent resistivity data and the well logging resistivity;

[0132] The square of the above correlation coefficient, that is, the value of the determination coefficient is judged: when the determination coefficient is within the preset range, it can be judged that the correlation between the first wide-area apparent resistivity data and the logging resistivity is good, the first wide-area apparent resistivity data is relatively accurate, and can be used for subsequent inversion steps without further horizon correction; when the determination coefficient is not within the preset range, it can be judged that the correlation between the first wide-area apparent resistivity data and the logging resistivity is general, the first wide-area apparent resistivity data has errors, and cannot be directly used in subsequent inversion steps, and horizon correction needs to be continued; it should be noted that the first wide-area apparent resistivity data after the horizon correction is completed again still needs to undergo the above-mentioned correlation analysis with the logging resistivity until the determination coefficient is within the preset range.

[0133] For example, when the wide-area apparent resistivity data is highly correlated with the resistivity logging data (M2RX / M2R6, unit Ω·m), the calculated determination coefficient R 2>0.8, which reflects that the wide-area apparent resistivity data collected on the ground has good reliability and can maintain a high degree of similarity with the logging resistivity measured close to the rock formation, which can be used as the basis for fluid identification.

[0134] In some embodiments, the data of the target layer in the first wide-area apparent resistivity data is replaced with the second wide-area apparent resistivity data to obtain an electrical comprehensive data volume.

[0135] The exploration principle of wide-area electromagnetic (WAM) is that high-frequency signals measure at shallow depths, resulting in strong signals and high frequency transmissions, while low-frequency signals measure at greater depths, resulting in weak signals and low frequency transmissions. Directly using the first wide-area apparent resistivity data for inversion will result in low identification accuracy for fluids within the target layer. At greater depths, without frequency encryption of the target layer, the signal frequencies corresponding to the target layer depth are generally 1-3, but after encryption, they can be increased to 10-30. Therefore, after intensified acquisition of the target layer, the vertical resolution is doubled, resulting in a qualitative improvement and more reliable inversion results. Therefore, by replacing the target layer data in the first wide-area apparent resistivity data with the second wide-area apparent resistivity data, the top and bottom boundaries of previously inaccurately identified gas-bearing zones can now be more accurately identified after inversion. This is crucial for oilfields and impacts subsequent well placement and development measures.

[0136] In some embodiments, a joint constrained inversion is performed based on multiple well-connected formation grid sections and electrical comprehensive data volumes to obtain multiple inverted apparent resistivity distribution profiles, including:

[0137] Establish a geoelectrical model based on multiple well-connected stratigraphic grid sections and electrical comprehensive data volumes;

[0138] Based on multiple inversion constraints, the geoelectric model is jointly inverted to obtain multiple inverted apparent resistivity distribution profiles.

[0139] In this embodiment, a geological framework established based on real geological data such as well logging and mud recording and a comprehensive electrical data body obtained by wide-area electromagnetic method are integrated, and multiple inversion constraints are used to minimize the multi-solution of the inversion results and improve the reliability of the inversion results.

[0140] The above-mentioned inversion constraints include three types of constraints: resistivity constraint, geometric parameter (i.e., formation thickness or depth) constraint, and mixed constraint of rock physical properties and geometric parameters; and two types of constraint methods: tight constraint and wide constraint.

[0141] Specifically, at resistivity logging locations, resistivity constraints can be applied based on known logging resistivity; at locations where specific geometric parameters are known, geometric parameter constraints can be applied; when only partial geometric parameters are obtained and some data are missing, mixed constraints of rock properties and geometric parameters can be applied based on the partial geometric parameters obtained and rock property-related data.

[0142] Specifically, tight constraints are imposed on parameters that have been determined by recording and logging data, including logging resistivity, depth or layer thickness parameters. This is mainly for tight constraints on drilling positions; wide constraints, that is, interval constraints, are used to give a possible range of variation for parameters that cannot be accurately determined by existing data, including resistivity or layer thickness, and automatically determine the value of the parameter through constrained inversion. This is usually mainly for wide constraints in the inter-well area.

[0143] Condition constraints can usually be applied before inversion, where multiple constraints are independent of each other and have an impact on the inversion results; multiple constraints are applied simultaneously, and multiple inversions are performed by adjusting the constraints one by one to obtain multiple inversion apparent resistivity distribution profiles.

[0144] In some embodiments, determining a target inverted apparent resistivity distribution profile based on a plurality of inverted apparent resistivity distribution profiles includes:

[0145] According to the logging resistivity, the error status of multiple inverted apparent resistivity distribution profiles is obtained;

[0146] According to the error conditions of multiple inverted apparent resistivity distribution profiles, the target inverted apparent resistivity distribution profile is determined.

[0147] Specifically, an error range will be set for the inversion result before inversion. If the error between the inversion result and the actual measured resistivity is less than 5%, it is usually considered to be reliable. The inverted apparent resistivity distribution profile with the smallest error rate or that meets the standard can be selected as the target inversion apparent resistivity distribution profile.

[0148] In some embodiments, the well logging data includes well resistivity;

[0149] Based on well logging data, oil and gas testing data and target inversion apparent resistivity distribution profile, wide-area fluid identification standards are obtained, including:

[0150] Based on the well logging data and the oil and gas testing data, a first fluid identification standard for the area to be identified is obtained; wherein the first fluid identification standard identifies and divides the fluids in the area to be identified based on the well logging resistivity;

[0151] According to the target inversion apparent resistivity distribution profile and the first fluid identification criterion, the wide-area fluid identification criterion is obtained.

[0152] The first fluid identification standard of the area to be identified is obtained based on the logging data and oil and gas test data. The logging data of the selected wells in the study area can be screened to select natural gamma ray logging (GR, unit API), neutron logging (CNL, unit %), density logging (DEN, unit g / cm 3 ), resistivity logging (RT, unit Ω·m) and other information, after comparison with geological knowledge, the first fluid identification standard is established, that is, the comprehensive classification and evaluation standard of logging, such as Figure 2 The specific values ​​need to be determined based on the specific data conditions of the region.

[0153] Based on the target inversion apparent resistivity distribution profile and the first fluid identification standard, the wide-area fluid identification standard is obtained. The range of the above logging data can be verified based on the actual oil and gas test results and the gas and water production of the target layer. Then, based on the logging resistivity of the target layer of each well, a wide-area fluid identification standard that conforms to the actual geological conditions and production conditions of the study area is established, such as Figure 3 The specific values ​​need to be determined based on the specific data conditions of the region.

[0154] In some embodiments, according to the wide-area fluid identification standard, multiple inverted apparent resistivity distribution sections are divided for fluid identification to obtain multiple inverted apparent resistivity distribution section fluid identification results. Alternatively, the wide-area fluid identification standard may be used to perform fluid identification on multiple inverted apparent resistivity distribution sections for the target layer to obtain fluid identification results for multiple sections of the target layer.

[0155] In some embodiments, obtaining a fluid plane identification result of a target layer in a to-be-identified area based on multiple inverted apparent resistivity distribution profile fluid identification results includes:

[0156] Based on the fluid identification results of multiple inverted apparent resistivity distribution profiles, the fluid types and distribution ranges are divided on the plane to obtain the fluid plane distribution map of the target layer in the area to be identified;

[0157] Among them, fluid types include gas layer, gas-water layer, gas-bearing layer, and dry layer.

[0158] In this embodiment, the fluid identification results of multiple sections of the target layer are obtained after fluid identification of other sections using the wide-area fluid identification standard. The multiple section identification results are combined to form the planar fluid identification results of the target layer, and finally the oil, gas and water distribution areas are divided on the plane.

[0159] After completing the target layer fluid identification work in all sections, the fluid identification results of all target layer sections can be combined to obtain the entire target layer fluid identification data, and then the fluid type and distribution range can be divided on the plane to obtain the target layer fluid plane distribution map in the study area.

[0160] In some embodiments, based on the layer fluid plane distribution map, the regions in the map can be divided into favorable areas, medium areas, and unfavorable areas according to the gas content.

[0161] In this embodiment, favorable areas are areas with high gas content that are comprehensively judged based on the results of wide-area fluid identification, with reference to the geological background and the difficulty of development. They are an important reference for the next step of well deployment; the gas content in the medium area is relatively reduced, the enrichment level is weakened, and the continuity is poor, but it can still be used as a valuable development area; the unfavorable area is a reservoir with low gas content and high water content, and basically has no economic development value.

[0162] The fluid identification method provided in the embodiment of the present application may be performed by the fluid identification device 200. In the embodiment of the present application, the fluid identification device 200 performing the fluid identification method is taken as an example to illustrate the fluid identification device 200 provided in the embodiment of the present application.

[0163] See Figure 4 , is a schematic diagram of the structure of a fluid identification device 200 provided in an embodiment of the present application. Figure 4 As shown, the fluid identification device 200 includes:

[0164] The first acquisition module 201 is used to acquire geological information of the area to be identified, wherein the geological information includes lithology data, well logging data, oil and gas testing data, stratification data and completion data;

[0165] Establishing module 202, for establishing multiple well-connected stratigraphic grid sections and calibrating horizons based on lithologic data and well logging data;

[0166] The second acquisition module 203 is used to obtain first wide-area apparent resistivity data of all layers in the area to be identified based on the wide-area electromagnetic method;

[0167] The third acquisition module 204 is configured to obtain second wide-area apparent resistivity data of the target layer in the area to be identified based on spectrum encryption technology and wide-area electromagnetic method;

[0168] A replacement module 205 is configured to replace the data of the target layer in the first wide-area apparent resistivity data with the second wide-area apparent resistivity data to obtain an electrical comprehensive data volume;

[0169] Inversion module 206, for performing joint constrained inversion based on multiple well-connected stratigraphic grid sections and electrical comprehensive data volumes to obtain multiple inverted apparent resistivity distribution sections;

[0170] A determination module 207 is configured to determine a target inversion apparent resistivity distribution profile based on the multiple inversion apparent resistivity distribution profiles, wherein the target inversion apparent resistivity distribution profile is the profile with the best inversion result among the multiple inversion apparent resistivity distribution profiles;

[0171] The standard acquisition module 208 is used to obtain a wide-area fluid identification standard based on the well logging data, the oil and gas test data, and the target inversion apparent resistivity distribution profile, wherein the wide-area fluid identification standard identifies and divides the fluids in the identification area according to the wide-area apparent resistivity;

[0172] A first identification module 209 is configured to perform fluid identification and division on multiple inverted apparent resistivity distribution profiles according to a wide-area fluid identification standard, thereby obtaining multiple fluid identification results for the inverted apparent resistivity distribution profiles;

[0173] The second identification module 210 is configured to obtain a fluid plane identification result of a target layer in a to-be-identified area based on a plurality of inverted apparent resistivity distribution profile fluid identification results.

[0174] In some implementations, the third acquisition module 204 may be configured to:

[0175] Obtain the top and bottom depths of the target layer based on well logging data;

[0176] Based on the skin depth formula, the wide-area emission frequency range of the target layer is obtained according to the top and bottom depths of the target layer;

[0177] Based on spectrum encryption technology, frequency points are encrypted within the wide-area transmission frequency range of the target layer;

[0178] Based on the wide-area electromagnetic method, the second electromagnetic wave data of the target layer collected by the wide-area electromagnetic equipment is obtained;

[0179] Second wide-area apparent resistivity data of the target layer is obtained according to the second electromagnetic wave data.

[0180] In some implementations, the second acquisition module 203 may be configured to:

[0181] Based on the wide-area electromagnetic method, first electromagnetic wave data of the area to be identified is obtained by the wide-area electromagnetic equipment;

[0182] First wide-area apparent resistivity data of all layers in the area to be identified are obtained based on the first electromagnetic wave data.

[0183] In some implementations, the second acquisition module 203 may also be used to:

[0184] According to the well logging data, the first wide-area apparent resistivity data is subjected to layer correction so that the first wide-area apparent resistivity data matches the lithology data, layering data and completion data of the area to be identified.

[0185] In some embodiments, the inversion module 206 can be used to:

[0186] Establish a geoelectrical model based on multiple well-connected stratigraphic grid sections and electrical comprehensive data volumes;

[0187] Based on multiple inversion constraints, the geoelectric model is jointly inverted to obtain multiple inverted apparent resistivity distribution profiles.

[0188] In some embodiments, the well logging data includes well resistivity;

[0189] The standard acquisition module 208 can be used to:

[0190] Based on the well logging data and the oil and gas testing data, a first fluid identification standard for the area to be identified is obtained; wherein the first fluid identification standard identifies and divides the fluids in the area to be identified based on the well logging resistivity;

[0191] According to the target inversion apparent resistivity distribution profile and the first fluid identification criterion, the wide-area fluid identification criterion is obtained.

[0192] In some embodiments, the second identification module 210 may be configured to:

[0193] Based on the fluid identification results of multiple inverted apparent resistivity distribution profiles, the fluid types and distribution ranges are divided on the plane to obtain the fluid plane distribution map of the target layer in the area to be identified;

[0194] Among them, fluid types include gas layer, gas-water layer, gas-bearing layer, and dry layer.

[0195] Since the fluid identification device 200 adopts all the technical solutions of the fluid 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.

[0196] Figure 5 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application.

[0197] The electronic device may include a processor 301 and a memory 302 storing computer program instructions.

[0198] 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.

[0199] 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.

[0200] 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.

[0201] The processor 301 reads and executes computer program instructions stored in the memory 302 to implement any one of the fluid identification methods in the above embodiments.

[0202] In one example, the electronic device may further include a communication interface 303 and a bus 310. Figure 5 As shown, the processor 301 , the memory 302 , and the communication interface 303 are connected via a bus 310 and communicate with each other.

[0203] 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.

[0204] 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.

[0205] The electronic device can execute the fluid identification method in the embodiment of the present application, thereby realizing the combination Figure 1 and Figure 4 A fluid identification method and apparatus are described.

[0206] In addition, in conjunction with the fluid 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 fluid identification methods in the above embodiments is implemented.

[0207] 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.

[0208] 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.

[0209] 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.

[0210] 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.

[0211] 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 fluid identification method, characterized in that: include: Obtaining geological information of the area to be identified, the geological information including lithologic data, well logging data, oil and gas testing data, stratification data, and completion data; According to the lithologic data and the well logging data, multiple well-connected stratigraphic grid sections are established and horizon positions are calibrated; Based on the wide-area electromagnetic method, first wide-area apparent resistivity data of all layers in the area to be identified are obtained; Based on the spectrum encryption technology and the wide-area electromagnetic method, second wide-area apparent resistivity data of the target layer in the area to be identified is obtained; replacing the data of the target layer in the first wide-area apparent resistivity data with the second wide-area apparent resistivity data to obtain an electrical comprehensive data volume; Performing joint constrained inversion based on the multiple well-connected stratigraphic grid sections and the comprehensive electrical data volume to obtain multiple inverted apparent resistivity distribution sections; Determining a target inversion apparent resistivity distribution profile based on the multiple inversion apparent resistivity distribution profiles, wherein the target inversion apparent resistivity distribution profile is a profile with the best inversion result among the multiple inversion apparent resistivity distribution profiles; Obtaining a wide-area fluid identification standard based on the well logging data, the oil and gas testing data, and the target inversion apparent resistivity distribution profile, wherein the wide-area fluid identification standard identifies and divides the fluid in the to-be-identified area based on the wide-area apparent resistivity; performing fluid identification and division on the plurality of inverted apparent resistivity distribution profiles according to the wide-area fluid identification standard to obtain fluid identification results of the plurality of inverted apparent resistivity distribution profiles; According to the multiple inverted apparent resistivity distribution profile fluid identification results, a fluid plane identification result of the target layer in the area to be identified is obtained.

2. The fluid identification method according to claim 1, characterized in that: The second wide-area apparent resistivity data of the target layer in the area to be identified is obtained based on the spectrum encryption technology and the wide-area electromagnetic method, including: Obtaining the top and bottom depths of the target layer according to the well logging data; Based on the skin depth formula, the wide-area transmission frequency range of the target layer is obtained according to the top and bottom depths of the target layer; Based on spectrum encryption technology, frequency encryption is performed within the wide-area transmission frequency range of the target layer; Based on the wide-area electromagnetic method, obtaining second electromagnetic wave data of the target layer collected by wide-area electromagnetic equipment in an encrypted manner; Second wide-area apparent resistivity data of the target layer is obtained according to the second electromagnetic wave data.

3. The fluid identification method according to claim 1, characterized in that: The first wide-area apparent resistivity data of all layers in the area to be identified is obtained based on the wide-area electromagnetic method, including: Based on the wide-area electromagnetic method, first electromagnetic wave data of the area to be identified is acquired by a wide-area electromagnetic device; First wide-area apparent resistivity data of all layers in the area to be identified is obtained based on the first electromagnetic wave data.

4. The fluid identification method according to claim 3, characterized in that: After obtaining first wide-area apparent resistivity data of all layers in the area to be identified based on the first electromagnetic wave data, the method further includes: The first wide-area apparent resistivity data is subjected to layer correction according to the well logging data, so that the first wide-area apparent resistivity data matches the lithology data, the layering data and the completion data of the area to be identified respectively.

5. The fluid identification method according to claim 3, characterized in that: The method of performing joint constrained inversion based on the multiple well-connected formation grid sections and the electrical comprehensive data volume to obtain multiple inverted apparent resistivity distribution sections includes: Establishing a geoelectrical model based on the multiple well-connected stratigraphic grid sections and the electrical comprehensive data volume; Based on multiple inversion constraints, the geoelectric model is jointly inverted to obtain multiple inversion apparent resistivity distribution profiles.

6. The fluid identification method according to claim 1, characterized in that: The well logging data includes well logging resistivity; The wide-area fluid identification standard is obtained based on the well logging data, the oil and gas test data and the target inversion apparent resistivity distribution profile, including: Obtaining a first fluid identification standard for the area to be identified based on the well logging data and the oil and gas testing data; wherein the first fluid identification standard identifies and divides the fluids in the area to be identified based on the well logging resistivity; The wide-area fluid identification standard is obtained according to the target inversion apparent resistivity distribution profile and the first fluid identification standard.

7. The fluid identification method according to claim 1, characterized in that: The step of obtaining a fluid plane identification result of the target layer in the to-be-identified area based on the multiple inverted apparent resistivity distribution profile fluid identification results includes: According to the fluid identification results of the multiple inverted apparent resistivity distribution profiles, the fluid types and distribution ranges are divided on a plane to obtain a fluid plane distribution map of the target layer in the area to be identified; The fluid types include gas layer, gas-water layer, gas-bearing layer, and dry layer.

8. A fluid identification device, characterized in that: include: The first acquisition module is used to acquire geological information of the area to be identified, wherein the geological information includes lithology data, well logging data, oil and gas testing data, stratification data and completion data; An establishment module is used to establish multiple well-connected stratigraphic grid sections and calibrate horizons based on the lithologic data and the well logging data; A second acquisition module is configured to obtain first wide-area apparent resistivity data of all layers in the area to be identified based on a wide-area electromagnetic method; A third acquisition module is configured to obtain second wide-area apparent resistivity data of the target layer in the area to be identified based on spectrum encryption technology and the wide-area electromagnetic method; a replacement module, configured to replace the data of the target layer in the first wide-area apparent resistivity data with the second wide-area apparent resistivity data to obtain an electrical comprehensive data body; an inversion module, configured to perform a joint constrained inversion based on the plurality of well-connected formation grid sections and the electrical comprehensive data volume to obtain a plurality of inverted apparent resistivity distribution sections; a determination module, configured to determine a target inversion apparent resistivity distribution profile based on the plurality of inversion apparent resistivity distribution profiles, wherein the target inversion apparent resistivity distribution profile is a profile with the best inversion result among the plurality of inversion apparent resistivity distribution profiles; a standard acquisition module, configured to obtain a wide-area fluid identification standard based on the well logging data, the oil and gas test data, and the target inversion apparent resistivity distribution profile, wherein the wide-area fluid identification standard identifies and divides the fluid in the to-be-identified area based on the wide-area apparent resistivity; a first identification module configured to perform fluid identification and division on the plurality of inverted apparent resistivity distribution profiles according to the wide-area fluid identification standard, and obtain fluid identification results of the plurality of inverted apparent resistivity distribution profiles; The second identification module is configured to obtain a fluid plane identification result of the target layer in the area to be identified based on the multiple inverted apparent resistivity distribution profile fluid identification results.

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 fluid 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 fluid identification method according to any one of claims 1 to 7.

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