Fluid identification method, device and equipment and storage medium

Abstract

The invention provides a fluid identification method, device and equipment and a storage medium, and the method comprises the steps: obtaining the geological information data of a to-be-identified region, building a plurality of well-connecting stratigraphic framework profiles, and calibrating the horizon; obtaining first wide-area apparent resistivity data of all layers in the to-be-identified area and second wide-area apparent resistivity data of a target layer in the to-be-identified area, 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 volume; carrying out joint constraint inversion according to the multiple well-connected stratigraphic framework profiles and the electrical comprehensive data volume to obtain multiple inversion apparent resistivity distribution profiles, determining a target inversion apparent resistivity distribution profile, obtaining a wide-area fluid identification standard, carrying out fluid identification division on the multiple inversion apparent resistivity distribution profiles, and carrying out fluid identification division on the wide-area fluid identification standard. And further obtaining a fluid plane identification result of the to-be-identified area. According to the invention, high-precision fluid identification of the target layer in the to-be-identified area can be realized through the logging data and the 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] At present, the research and development of geophysical technology in the process of oil and gas field exploration and development is mainly based on the seismic data obtained by seismic methods. As for the problem of fluid identification in the process of oil and gas field exploration and development, there are few existing technical means. Generally, seismic data, logging data and electrical data are used to jointly realize fluid identification. Since this technical means needs to collect three kinds of information, data processing is difficult and the processing speed is slow. Especially in mature oil and gas exploration and development areas, the fluid identification process is greatly affected by the quality of seismic data. There are problems such as low accuracy of the stratigraphic structure established by seismic data, many restrictions, and slow processing speed, and there are great limitations in its application. 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, and improves the speed and accuracy of fluid identification.

[0004] According to the first aspect of the present application, the fluid identification method includes:

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

[0006] According to the lithology data and the well logging data, multiple well-connected stratigraphic grid sections are established and the horizons are marked;

[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 body;

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

[0011] Determining a target inversion apparent resistivity distribution profile according to 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] According to the well logging data, the oil and gas test data and the target inversion apparent resistivity distribution profile, a wide-area fluid identification standard is obtained, wherein the wide-area fluid identification standard identifies and divides the fluid in the to-be-identified area according to the wide-area apparent resistivity;

[0013] According to the wide-area fluid identification standard, the multiple inversion apparent resistivity distribution sections are divided into fluid identification sections to obtain multiple inversion apparent resistivity distribution section fluid identification results;

[0014] According to the multiple inversion apparent resistivity distribution profile fluid identification results, the 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 the spectrum encryption technology and the wide-area electromagnetic method includes:

[0016] According to the logging data, obtaining the top and bottom depths of the target layer;

[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 points are encrypted within the wide-area transmission frequency range of the target layer;

[0019] Based on the wide-area electromagnetic method, obtaining the second electromagnetic wave data of the target layer collected by the 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 the wide-area electromagnetic method includes:

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

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

[0024] According to some embodiments of the present application, the first wide-area apparent resistivity data of all layers in the area to be identified is obtained according to the first electromagnetic wave data, and then the method further includes:

[0025] According to the 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 respectively.

[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 inversion apparent resistivity distribution sections includes:

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

[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 testing data and the target inversion apparent resistivity distribution profile, including:

[0031] According to the well logging data and the oil and gas testing data, a first fluid identification standard of the to-be-identified area is obtained; wherein the first fluid identification standard identifies and divides the fluid in the to-be-identified area according to 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 inversion apparent resistivity distribution profile fluid identification results includes:

[0034] According to the fluid identification results of the multiple inversion 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] Among them, the fluid types include gas layer, gas-water layer, gas-containing layer, and dry layer.

[0036] According to the second aspect of the present application, a fluid identification device 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 the horizons according to the lithological data and the logging data;

[0039] A second acquisition module is used 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 used 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, used for performing joint constrained inversion according to the multiple well-connected formation grid sections and the electrical comprehensive data volume to obtain multiple inversion apparent resistivity distribution sections;

[0043] A determination module, configured to determine a target inversion apparent resistivity distribution profile according to 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, 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 fluid in the to-be-identified area based on the wide-area apparent resistivity;

[0045] A first identification module is used to perform fluid identification and division on the multiple inversion apparent resistivity distribution profiles according to the wide-area fluid identification standard to obtain multiple inversion apparent resistivity distribution profile fluid identification results;

[0046] The second identification module is used to obtain the fluid plane identification result of the target layer in the area to be identified according to the multiple inversion 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 aspect 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 aspect 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 encrypted, the amount of data collected by the target layer is increased, and the resolution of the underground structure of the deeper target layer is improved; 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 the fluid identification of the target layer in the area to be identified through 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 of rapid fluid identification in highly mature areas of oil and gas development.

[0050] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent from the description, or may be understood 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 schematic flow chart of an embodiment of the fluid identification method of the present application;

[0053] Figure 2 It is a well logging comprehensive classification evaluation standard chart of one 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 schematic diagram of the hardware structure of an embodiment of the electronic device of the present application. DETAILED DESCRIPTION

[0057] The embodiments of the present application are described in detail below, and 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 cannot be understood 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 the present application, it should be understood that the descriptions involving orientation, such as the orientation or positional relationship indicated as up, down, etc., are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0060] In the description of this application, it should be noted that, unless otherwise clearly defined, terms such as setting, installing, connecting, etc. should be understood in a broad sense, and technicians 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, the target reservoir often contains fluids of different properties, such as oil, natural gas, formation water and artificially injected fracturing fluid. Multiple fluids coexist in the reservoir, and due to the influence of gravity or artificial development measures, they will be layered vertically and aggregated in blocks in the plane. When deploying oil and gas exploration and production wells, it is necessary to select sites in oil and gas rich areas as much as possible to increase the success rate of drilling.

[0064] The resistivity of oil, gas and water in the reservoir is very different, which is the theoretical basis for fluid identification in this method. In general, oil and natural gas are basically non-conductive, showing high resistance to very high resistance; formation water and artificially injected water-based fracturing fluid are conductors, showing low resistance to very low resistance; and the resistivity of formations without oil, gas and water is usually between the above two.

[0065] Seismic exploration is usually used for exploration in unknown areas. It has rich and reliable data, but it is difficult to operate and has high costs. In mature oil and gas exploration and development areas, seismic exploration is no longer applicable. At the same time, there are many wells in mature areas, and there is a wealth of geological information such as logging, which makes it easy to clearly understand the stratigraphic structure and structural development. The geological information obtained from drilling is the first-hand data reflecting the real underground situation, and the stratigraphic structure established by this is the most accurate and reliable.

[0066] Figure 1 This is a flow chart of the fluid identification method of the embodiment provided in this application. Figure 1 , the embodiments of the present application are further described.

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

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

[0069] Step 102: Establish multiple well-connected stratigraphic grid sections and calibrate the horizons based on the lithology data and logging data;

[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, 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;

[0073] Step 106, performing joint constrained inversion based on multiple well-connected formation grid profiles and electrical comprehensive data volumes to obtain multiple inverted apparent resistivity distribution profiles;

[0074] Step 107, determining a target inversion apparent resistivity distribution profile according to 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;

[0075] Step 108, 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;

[0076] Step 109, performing fluid identification and division on multiple inversion apparent resistivity distribution profiles according to the wide-area fluid identification standard, and obtaining multiple inversion apparent resistivity distribution profile fluid identification results;

[0077] Step 110: Obtain a fluid plane identification result of a target layer in the area to be identified based on 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 encrypted, the amount of data collected by the target layer is increased, and the resolution of the underground structure of the deeper target layer is improved; 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 the fluid identification of the target layer in the area to be identified through 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 of rapid fluid identification in highly mature areas of oil and gas development.

[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 above-mentioned area to be identified may be a research area in 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 lithological data, stratification data, logging data, logging data, oil and gas testing data and completion data and other well data.

[0082] The above-mentioned lithological data include data that directly reflect the lithology and data that indirectly reflect the lithology. The data that directly reflect the lithology include drilling core sampling and logging cuttings, and the data that indirectly reflect the 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, among the above lithology data, the data that directly reflects the lithology can be used to determine the lithology first; in the case of wells without direct lithology data, the data that indirectly reflects the lithology can be used to identify the lithology. In some cases, both the data that directly reflects the lithology and the data that indirectly reflects the lithology are collected, and they can be verified with each other to obtain more accurate data.

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

[0085] For example, among the above-mentioned stratification data, the stratification results data given at the oil field site can be used; 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, and at the same time, the lithological data can be used to subdivide the layers of each well, and the lithological data and logging depth data can be matched one by one to obtain the stratification results data.

[0086] The above logging data include specific data of resistivity logging, gamma logging, density logging, natural potential logging, neutron logging, photoelectric effect cross-section index logging, acoustic time difference logging, nuclear magnetic resonance logging, etc. 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, and can assist in determining the fluid, among which 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, because the difference in the deceleration ability of oil layers and gas layers for neutrons is very obvious, so neutron logging can be used to determine the oil and gas content of the target layer; the above-mentioned acoustic time difference logging can be used to determine the lithology, porosity and pore fluid properties of the formation; the above-mentioned nuclear magnetic resonance logging can use thermal relaxation time to distinguish between oil and water and determine the fluid properties.

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

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

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

[0091] The regional structural overview and structural development history in the above completion data can serve as the basis for the subsequent establishment of well-connected profiles, vertical analysis of fluid identification and planar analysis; the stratigraphic sequence encountered in the above completion data refers to the general term for various layered rocks formed in the process of crustal development, including sedimentary, volcanogenic 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 basis in the above completion data is the comparable marker layer characteristics, paleontological data and rock-electric combination characteristics.

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

[0093] Establish a single well stratigraphic framework profile based on lithology 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 time difference logging (AC, unit us / ft), resistivity logging (M2RX / M2R6, unit Ω·m), logging total hydrocarbon content (unit %), porosity logging (POR, unit %), etc.

[0096] In the above, multiple wells are selected and a connected stratigraphic framework section is established based on the stratigraphic framework sections of their single wells. 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 a wide-area electromagnetic device, 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 mentioned above may include a wide-area high-power transmitter and a wide-area high-precision receiver.

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

[0100]

[0101] Among them, 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 sent 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] Among them, dL is the distance of the electric dipole source of the wide-area electromagnetic device, and r is the transmission and reception 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, second wide-area apparent resistivity data of the target layer in the area to be identified is obtained, including:

[0109] Obtain the top and bottom depths of the target layer based on 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] The second wide-area apparent resistivity data of the target layer is obtained according to the second electromagnetic wave data.

[0114] In this embodiment, by encrypting the target layer for acquisition, the amount of data obtained is increased, and more reliable second wide-area apparent resistivity data of the target layer is obtained, so that the subsequent inversion results will be more reliable, and the vertical resolution is effectively improved. Specifically, when the depth of the target layer is large, the frequency point encryption of the target layer is not performed, and the signal frequency corresponding to the depth of the target layer is generally 1-3. After the spectrum encryption, it can reach 10-30, which doubles the order of magnitude, and the vertical resolution is qualitatively improved.

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

[0116]

[0117] Where D is the detection depth, m; ρ is the apparent resistivity, Ω·m, which represents the comprehensive resistivity of multiple layers from the surface to a certain depth; f represents the transmission signal frequency, Hz. The transmission frequency range of wide-area electromagnetic equipment can be 0.0020Hz to 15728.6Hz, and the transmission frequency can be adjusted according to actual conditions. Generally, the higher the frequency, the shallower the detection depth, and the higher the frequency, the deeper the detection depth.

[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 top and bottom frequency ranges of the target layer, the 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, based on the wide-area electromagnetic method, obtaining first wide-area apparent resistivity data of all layers in the area to be identified includes:

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

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

[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 according to the first electromagnetic wave data, and then the method further includes:

[0124] According to the 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, the layering data and the completion data of the area to be identified respectively.

[0125] The above-mentioned stratigraphic correction can be performed based on the information given by each logging curve included in the logging data, to obtain the logging resistivity, lithology, top and bottom depths, oil and gas content and other information of the target layer and make a comprehensive judgment to achieve stratigraphic correction of the first wide-area apparent resistivity data.

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

[0127] Generally speaking, for strata of different lithologies, their resistivity is usually quite different. 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 fluid (oil, gas, water), the formation resistivity will fluctuate greatly. Taking the 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 position, the depth of color can be used in the profile to intuitively reflect the accumulation form and position 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] In general, if there is no fluid in the formation, the top and bottom boundaries of the apparent resistivity can be roughly divided by lithology, and the top and bottom depths of the formation can be determined by logging resistivity, so that a more accurate apparent resistivity profile can be obtained. If there is fluid in some formations, the type, location, depth and extension of the color in the layer will reflect the type, distribution, content and extension of the fluid. Therefore, matching the wide-area apparent resistivity data with lithology data, stratification data and completion data can ensure 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 well logging resistivity is good, the first wide-area apparent resistivity data is relatively accurate, and can be used in subsequent inversion steps without further layer 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 well logging resistivity is general, the first wide-area apparent resistivity data has errors, and cannot be directly used in subsequent inversion steps, and further layer correction is required; it should be noted that the first wide-area apparent resistivity data after completing the layer correction again still needs to undergo the above-mentioned correlation analysis with the well 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 data obtained from resistivity logging (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 have 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 method is that high-frequency signal has shallow measurement depth, strong signal and high frequency of transmitted signal; low-frequency signal has deep measurement depth, weak signal and low frequency of transmitted signal. If the first wide-area apparent resistivity data is directly used for inversion, the recognition accuracy of the fluid in the target layer is not high. When the depth is large, the frequency points of the target layer are not encrypted. The signal frequency corresponding to the depth of the target layer is generally 1-3, and it can be 10-30 after encryption. Therefore, after the encrypted acquisition of the target layer, the order of magnitude is doubled, the vertical resolution is qualitatively improved, and the inversion result is more reliable. Therefore, after replacing the data of the target layer in the first wide-area apparent resistivity data with the second wide-area apparent resistivity data, the gas-bearing area that was previously not accurately identified can be more accurately identified after inversion. It is very important for oil fields and is related to subsequent well site deployment 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 inversion apparent resistivity distribution sections, including:

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

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

[0139] In this embodiment, the geological framework established based on real geological data such as well logging and mud recording and the electrical comprehensive data body obtained based on the 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 constraint conditions include three types of constraint: 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 the resistivity logging location, resistivity constraints can be performed based on the known logging resistivity; at the location where specific geometric parameters are known, geometric parameter constraints can be performed; when only part of the geometric parameters are obtained and some data are missing, mixed constraints on rock properties and geometric parameters can be performed based on the obtained partial geometric parameters 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 locations; wide constraints, i.e. 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. The value of the parameter is automatically determined through constrained inversion. This is usually mainly for wide constraints in the inter-well area.

[0143] Usually, conditional constraints can be performed before inversion, where multiple constraint conditions are independent of each other and have an impact on the inversion results; multiple constraint conditions are performed simultaneously, and the constraint conditions are adjusted one by one to perform multiple inversions to obtain multiple inversion apparent resistivity distribution profiles.

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

[0145] According to the logging resistivity, the error conditions of multiple inversion apparent resistivity distribution profiles are 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, before inversion, an error range will be set for the inversion result. If the error between the inversion result and the actual measured resistivity is less than 5%, it is usually considered to be credible. The inverted apparent resistivity distribution profile with the smallest error rate or that meets the standard can be selected as the target inverted apparent resistivity distribution profile.

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

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

[0150] According to the well logging data and the oil and gas testing data, a first fluid identification standard of the area to be identified is obtained; wherein the first fluid identification standard identifies and divides the fluid in the area to be identified according to the well logging resistivity;

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

[0152] According to the logging data and oil and gas test data, the first fluid identification standard of the area to be identified can be obtained, which can be used to screen the logging data of the selected wells in the study area, and select natural gamma 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 As shown, the specific values ​​need to be determined based on the specific data conditions of the area.

[0153] The above-mentioned wide-area fluid identification standard is obtained based on the target inversion apparent resistivity distribution profile and the first fluid identification standard. According to the actual oil and gas test results, the gas and water production conditions of the target layer are used to verify the range of the above-mentioned logging data. 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 As shown, the specific values ​​need to be determined based on the specific data conditions of the area.

[0154] In some embodiments, according to the wide-area fluid identification standard, multiple inversion apparent resistivity distribution sections are divided for fluid identification to obtain multiple inversion apparent resistivity distribution section fluid identification results. It can be that the wide-area fluid identification standard is used to identify the fluid of the target layer on multiple inversion apparent resistivity distribution sections to obtain fluid identification results of multiple sections of the target layer.

[0155] In some embodiments, the fluid plane identification result of the target layer in the area to be identified is obtained according to the multiple inversion apparent resistivity distribution profile fluid identification results, including:

[0156] Based on the fluid identification results of multiple inversion 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 result of the target layer, and finally the oil, gas and water distribution areas are divided on the plane.

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

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

[0161] In this implementation, the favorable area is an area with a high gas content that is comprehensively determined based on the results of wide-area fluid identification, with reference to the geological background and the difficulty of development. It is 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 executed by the fluid identification device 200. In the embodiment of the present application, the fluid identification device 200 executing 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 also 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 data of the area to be identified, and the geological information data 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 the horizons according to the lithology data and the 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 used to obtain the second wide-area apparent resistivity data of the target layer in the area to be identified based on the spectrum encryption technology and the wide-area electromagnetic method;

[0168] A replacement module 205 is used 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;

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

[0170] A determination module 207 is used to determine a target inversion apparent resistivity distribution profile according to 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;

[0171] The standard acquisition module 208 is used to obtain the wide-area fluid identification standard according to 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 identification area according to the wide-area apparent resistivity;

[0172] The first identification module 209 is used to perform fluid identification and division on multiple inversion apparent resistivity distribution profiles according to the wide-area fluid identification standard to obtain multiple inversion apparent resistivity distribution profile fluid identification results;

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

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

[0175] Obtain the top and bottom depths of the target layer based on 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] The 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 used to:

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

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

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

[0184] According to the 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, the layering data and the completion data of the area to be identified respectively.

[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 bodies;

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

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

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

[0190] According to the well logging data and the oil and gas testing data, a first fluid identification standard of the area to be identified is obtained; wherein the first fluid identification standard identifies and divides the fluid in the area to be identified according to the well logging resistivity;

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

[0192] In some implementations, the second identification module 210 may be used to:

[0193] Based on the fluid identification results of multiple inversion 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. In appropriate cases, the memory 302 may include a removable or non-removable (or fixed) medium. In appropriate cases, 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 a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Thus, in general, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) 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 implements any one of the fluid identification methods in the above embodiments by reading and executing computer program instructions stored in the memory 302 .

[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 parts of online data flow billing equipment are coupled to each other. For example, but not limitation, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front-end bus (FSB), hypertransport (HT) interconnection, industrial 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 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the present 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 combination with the fluid identification method in the above embodiments, the present application embodiment can provide a computer storage medium to implement. The computer storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any one of the fluid identification methods in the above embodiments is implemented.

[0207] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between 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, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, 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 capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), 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, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0210] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment 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 can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0211] The above is only a specific implementation of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity 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 protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A fluid identification method, characterized in that: include: Obtaining geological information of the area to be identified, the geological information including lithology data, well logging data, oil and gas testing data, stratification data and completion data; According to the lithology data and the well logging data, multiple well-connected stratigraphic grid sections are established and the horizons are marked; 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 body; Performing joint constrained inversion according to the multiple well-connected formation grid sections and the electrical comprehensive data volume to obtain multiple inverted apparent resistivity distribution sections; Determining a target inversion apparent resistivity distribution profile according to 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; According to the well logging data, the oil and gas test data and the target inversion apparent resistivity distribution profile, a wide-area fluid identification standard is obtained, wherein the wide-area fluid identification standard identifies and divides the fluid in the to-be-identified area according to the wide-area apparent resistivity; According to the wide-area fluid identification standard, the multiple inversion apparent resistivity distribution sections are divided into fluid identification sections to obtain multiple inversion apparent resistivity distribution section fluid identification results; According to the multiple inversion apparent resistivity distribution profile fluid identification results, the 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 to-be-identified area is obtained based on the spectrum encryption technology and the wide-area electromagnetic method, including: According to the well logging data, obtaining the top and bottom depths of the target layer; 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 points are encrypted within the wide area transmission frequency range of the target layer; Based on the wide-area electromagnetic method, obtaining the second electromagnetic wave data of the target layer collected by the wide-area electromagnetic equipment in an encrypted manner; The 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 to-be-identified area are obtained based on the wide-area electromagnetic method, including: Based on the wide area electromagnetic method, obtaining the first electromagnetic wave data of the area to be identified collected by the wide area electromagnetic equipment; The first wide-area apparent resistivity data of all layers in the area to be identified is obtained according to the first electromagnetic wave data.

4. The fluid identification method according to claim 3, characterized in that: The method further comprises: obtaining first wide-area apparent resistivity data of all layers in the to-be-identified area according to the first electromagnetic wave data; and then: 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, the stratification 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 inversion apparent resistivity distribution sections includes: Establishing a geoelectrical model based on the multiple well-connected stratigraphic grid sections and the electrical comprehensive data body; 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 logging data includes logging resistivity; The wide-area fluid identification standard is obtained based on the well logging data, the oil and gas testing data and the target inversion apparent resistivity distribution profile, including: According to the well logging data and the oil and gas testing data, a first fluid identification standard of the to-be-identified area is obtained; wherein the first fluid identification standard identifies and divides the fluid in the to-be-identified area according to 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 the fluid plane identification result of the target layer in the to-be-identified area according to the multiple inversion apparent resistivity distribution profile fluid identification results comprises: According to the fluid identification results of the multiple inversion 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; Among them, the fluid types include gas layer, gas-water layer, gas-containing layer, and dry layer.

8. A fluid identification device, characterized in that: include: The first acquisition module is used to acquire geological information data of the area to be identified, wherein the geological information data 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 the horizons according to the lithological data and the logging data; A second acquisition module is used 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 used 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, used for performing joint constrained inversion according to the multiple well-connected formation grid sections and the electrical comprehensive data volume to obtain multiple inversion apparent resistivity distribution sections; A determination module, configured to determine a target inversion apparent resistivity distribution profile according to 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, 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 fluid in the to-be-identified area based on the wide-area apparent resistivity; A first identification module is used to perform fluid identification and division on the multiple inversion apparent resistivity distribution profiles according to the wide-area fluid identification standard to obtain multiple inversion apparent resistivity distribution profile fluid identification results; The second identification module is used to obtain the fluid plane identification result of the target layer in the area to be identified according to the multiple inversion 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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