A method and apparatus for predicting total organic carbon content of shale

Abstract

The application provides a method and device for predicting total organic carbon content of shale, comprising: selecting shale samples from multiple wells for testing, obtaining total organic carbon content and wave impedance value of the shale, performing correlation analysis on the total organic carbon content and the wave impedance value, and selecting a target well with a correlation greater than a preset threshold; in the target well, obtaining total organic carbon content and wave impedance data of shale from different blocks and different layers of wells; drawing a crossplot of total organic carbon content and wave impedance of different blocks and different layers; constructing a quantitative relationship between total organic carbon content and wave impedance of different blocks and different layers based on the crossplot; obtaining wave impedance data of a well to be predicted, predicting shale distribution according to the wave impedance data; and substituting wave impedance data of a shale distribution area into a quantitative relationship corresponding to a block and a layer where the shale distribution area is located, to predict total organic carbon content of the shale. The method can more accurately predict total organic carbon content of shale.

Description

Technical Field

[0001] This invention belongs to the field of petroleum exploration technology, specifically relating to a method and apparatus for predicting the total organic carbon content of mudstone and shale. Background Technology

[0002] Quantitative characterization of shale and prediction of the distribution of total organic carbon (TOC) in shale are of great significance for shale oil and gas exploration and development, and oil and gas resource assessment.

[0003] Currently, seismic inversion is a crucial method for predicting TOC content in shale and mudstone. It establishes the relationship between acoustic impedance and TOC, and then converts the acoustic impedance data into TOC content. However, acoustic impedance is influenced by various factors, including sedimentary facies and diagenesis in the inversion area, leading to complex variations in impedance values. This reduces the correlation between acoustic impedance and TOC, further resulting in poor accuracy in TOC content prediction. Summary of the Invention

[0004] To address the problem of poor accuracy in predicting TOC in shale and mudstone in existing technologies, this invention provides a method and apparatus for predicting the total organic carbon content of shale and mudstone.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for predicting the total organic carbon content of mudstone and shale, characterized by comprising:

[0007] Shale samples were selected from multiple wells for testing to obtain the total organic carbon content and wave impedance value of the shale. Correlation analysis was performed on the total organic carbon content and wave impedance value, and target wells with a correlation greater than a preset threshold were selected.

[0008] In the target well, total organic carbon content and acoustic impedance data of mudstone and shale from different blocks and different strata were obtained; cross-plots of total organic carbon content and acoustic impedance were plotted for different blocks and different strata; and quantitative relationships between total organic carbon content and acoustic impedance were constructed based on the cross-plots.

[0009] Obtain the acoustic impedance data of the well to be predicted, and predict the distribution of mudstone and shale based on the acoustic impedance data; substitute the acoustic impedance data of the mudstone and shale distribution area into the quantitative relationship corresponding to the block and stratigraphic position of the mudstone and shale distribution area to predict the total organic carbon content of mudstone and shale.

[0010] Optionally, predicting the distribution of mudstone and shale based on acoustic impedance data includes:

[0011] Obtain logging data from typical wells in different blocks and strata, and plot the wave impedance frequency distribution maps of mudstone and shale with different total organic carbon contents, as well as the wave impedance frequency distribution maps of sandstone, based on the logging data.

[0012] The threshold values ​​for distinguishing mudstone and sandstone in different blocks and at different strata are determined based on the wave impedance frequency distribution diagram.

[0013] The wave impedance data is compared with the threshold values ​​for the corresponding block and stratum; if it is less than or equal to the threshold value, it is considered mudstone or shale.

[0014] Optionally, the acoustic impedance data of the well to be predicted is obtained, including:

[0015] Obtain the density logging and sonic logging curves of the well to be predicted; calculate the acoustic impedance data based on the density logging and sonic logging curves; or,

[0016] Seismic data of the well to be predicted is acquired, and wave impedance data is obtained through inversion algorithm based on the seismic data and wave impedance model.

[0017] Optionally, after predicting the distribution of mudstone and shale and the total organic carbon content of mudstone and shale, the method further includes:

[0018] Based on the predicted distribution of mudstone and shale and the predicted total organic carbon content, a thickness map of high-quality source rocks and a planar distribution map of total organic carbon content were drawn.

[0019] Optionally, several wells may be typical wells reflecting the characteristics of source rocks.

[0020] The present invention also provides a device for predicting the total organic carbon content of shale, comprising:

[0021] The analysis module is used to select mudstone and shale samples from multiple wells for testing, obtain the total organic carbon content and wave impedance value of mudstone and shale, perform correlation analysis on the total organic carbon content and wave impedance value, and select target wells with a correlation greater than a preset threshold.

[0022] The module is used to acquire total organic carbon content and wave impedance data of mudstone and shale from different blocks and different layers in the target well; draw cross-plots of total organic carbon content and wave impedance in different blocks and different layers; and construct quantitative relationships between total organic carbon content and wave impedance in different blocks and different layers based on the cross-plots.

[0023] The prediction module is used to acquire the wave impedance data of the well to be predicted, and predict the distribution of mudstone and shale based on the wave impedance data; by substituting the wave impedance data of the mudstone and shale distribution area into the quantitative relationship corresponding to the block and stratigraphic position of the mudstone and shale distribution area, the total organic carbon content of mudstone and shale is predicted.

[0024] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described method for predicting the total organic carbon content of mudstone and shale.

[0025] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for predicting the total organic carbon content of shale.

[0026] The method for predicting the total organic carbon content of shale provided by this invention has the following beneficial effects:

[0027] This invention performs correlation analysis on the total organic carbon (TOC) content and acoustic impedance (ADI) values ​​of shale and mudstone from multiple wells. Target wells with a correlation greater than a preset threshold are selected for analysis. Quantitative relationships between TOC and ADI are constructed for different blocks and strata to predict the TOC content of shale and mudstone. First, the analysis focuses on target wells with a correlation greater than the preset threshold, as their data better reflect the true relationship between TOC and ADI. Second, since different strata represent formations with different lithological characteristics and sedimentary environments, and different blocks also have different sedimentary environments, their impact on ADI varies. Therefore, the quantitative relationship between TOC and ADI is constructed according to blocks and strata, resulting in a stronger correlation between ADI and TOC and enabling more accurate prediction of TOC content. Attached Figure Description

[0028] To more clearly illustrate the embodiments and design schemes of the present invention, the accompanying drawings required for this embodiment will be briefly described below. The drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 A schematic flowchart illustrating a method for predicting the total organic carbon content of mudstone and shale, provided in an embodiment of the present invention;

[0030] Figure 2 A graph showing the relationship between TOC content and wave impedance in wells of different blocks is provided as an embodiment of the present invention. Figure 2 Figure (a) shows the relationship between TOC content and wave impedance in the W1 block; Figure 2 Figure (b) shows the relationship between TOC content and wave impedance in the W2 block. Figure 2 Figure (c) shows the relationship between TOC content and wave impedance for the W3 block. Figure 2 Figure (d) shows the relationship between TOC content and wave impedance for the W4 block.

[0031] Figure 3 An impedance frequency distribution diagram corresponding to different blocks at different layers is provided for an embodiment of the present invention; Figure 3 Figure (a) shows the wave impedance frequency distribution corresponding to block W9 in layer E1; Figure 3 Figure (b) shows the wave impedance frequency distribution corresponding to block W10 in layer E1; Figure 3 Figure (c) shows the wave impedance frequency distribution of block W19 in layer E1; Figure 3 Figure (d) shows the wave impedance frequency distribution of block W5 in layer E1. Detailed Implementation

[0032] To enable those skilled in the art to better understand and implement the technical solutions of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and should not be construed as limiting the scope of protection of the present invention.

[0033] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the technical solution of this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0034] Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. In the description of this invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "connected" or "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances. In the description of this invention, unless otherwise stated, "a plurality of" means two or more, which will not be elaborated further here.

[0035] Before introducing the present invention, the terminology involved in the present invention will be introduced.

[0036] Sedimentary facies refers to the formation environment and characteristics of sediments. Different sedimentary facies have different rock compositions, structures, and sedimentary environments, which directly affect the physical properties of rocks, including wave impedance. For example, some reservoir sandstones in the Ordos Basin exhibit strong variability, complexity, and heterogeneity in their petrological characteristics, pore structure, and physical properties due to different sedimentary environments. These characteristics affect the correlation between wave impedance and TOC (Total Wave Impedance).

[0037] Diagenesis refers to the various geological processes that transform sediments into rocks. These processes, such as compaction, cementation, and dissolution, alter the pore structure and physical properties of rocks, thereby affecting their acoustic impedance. For example, compaction and cementation are major causes of deterioration in reservoir properties; these processes change the acoustic impedance of rocks, affecting their correlation with total thermal equilibrium (TOC).

[0038] In summary, the combined effects of sedimentary facies, diagenesis, and other factors lead to complex variations in wave impedance values, which reduces their correlation with TOC and affects the accuracy of TOC prediction.

[0039] To address the issue of poor accuracy in predicting TOC in shale using existing technologies, this invention provides a method for predicting the total organic carbon content of shale, such as... Figure 1 As shown, the method includes the following steps:

[0040] S1. Select mudstone and shale samples from multiple wells for testing, obtain the total organic carbon content and wave impedance value of the mudstone and shale, perform correlation analysis on the total organic carbon content and wave impedance value, and select target wells with a correlation greater than a preset threshold.

[0041] Among them, several wells are typical wells with high-quality and representative logging data. Optionally, wells reflecting the characteristics of source rocks among multiple candidate wells can be selected as typical wells. The selection of these wells is based on several key characteristics of source rocks in order to more accurately assess the potential of source rocks and the oil and gas resources formed therefrom.

[0042] For example, shale core samples are collected from typical wells, and the depth, lithology, and geological background information of the samples are recorded. Laboratory tests are performed on the samples to obtain TOC content and acoustic impedance values. Using statistical software such as Excel or Python, a cross-plot of TOC content and acoustic impedance for each well sample point is plotted, and correlation coefficients, such as the Pearson correlation coefficient, are calculated to assess the correlation between the two. Finally, target wells with a correlation greater than a preset threshold (e.g., 70%) are selected.

[0043] Optionally, the total organic carbon (TOC) content can be determined by methods such as thermal oxidation or wet oxidation. The embodiments of the present invention do not specifically limit the method for determining the total organic carbon content.

[0044] S2. In the target well, acquire total organic carbon content and wave impedance data of mudstone and shale from wells at different strata in different blocks; plot the cross-plot of total organic carbon content and wave impedance at different strata in different blocks; and construct a quantitative relationship between total organic carbon content and wave impedance at different strata in different blocks based on the cross-plot.

[0045] In this embodiment of the invention, the strata of the study area are divided into the E layer (Enping Formation) and the W layer (Wenchang Formation). The E layer can be further divided into two secondary stratigraphic units, E1 and E2, according to changes in lithology, fossil assemblage, and sedimentary environment. The area is divided into Block A (depression) and Block B (depression). Block A represents the northern half of the basin, and Block B represents the southern half of the basin. Block A and Block B have different sedimentary facies and diagenetic processes.

[0046] The Enping and Wenchang groups will be introduced below:

[0047] Enping Formation: Mainly formed in lacustrine and deltaic environments, consisting mainly of fine-grained sediments, with rock characteristics typically dominated by mudstone and shale, and is an important source rock for hydrocarbons.

[0048] The Wenchang Formation is dominated by a lacustrine environment. Its sediments are coarser than those of the Wenchang Formation and contain sandstone and coal seams in addition to mudstone, showing a more complex sedimentary sequence.

[0049] It is evident that the Enping Formation and the Wenchang Formation possess different lithological characteristics and sedimentary environments, and also exhibit significant differences in diagenesis and sedimentary facies.

[0050] Furthermore, data on total organic carbon content and acoustic impedance of shale from wells in different strata and blocks were obtained, and cross-plots of total organic carbon content and acoustic impedance at different strata in different blocks were plotted, such as... Figure 2 As shown, Figure 2 This is a schematic diagram of the intersection of total organic carbon content and wave impedance in different blocks, provided as an embodiment of the present invention.

[0051] For example, such as Figure 2 As shown, W1-W4 are sub-blocks that divide block A and block B according to preset rules. Figure 2 In the histograms, the horizontal axis represents wave impedance, and the vertical axis represents TOC content. By observing the change in TOC content with wave impedance, a quantitative relationship between the total organic carbon content and wave impedance of the well in that sub-block can be constructed. In this quantitative relationship, x represents wave impedance, and y represents TOC content. Furthermore, the correlation coefficient R between wave impedance and TOC content can be obtained by analyzing the histograms. 2For example, in well W1, the correlation coefficient between wave impedance and TOC content is 0.9187, meaning the correlation is greater than 90%. Observation shows that the correlation coefficient between wave impedance and TOC content in wells of each sub-block is above 70%, indicating that dividing the study area into blocks can improve the correlation between wave impedance and TOC content.

[0052] Similarly, for different layers, a quantitative relationship between the total organic carbon content and the wave impedance can also be established.

[0053] In this invention, stratigraphic levels and blocks can be studied separately, or they can be studied together. Specifically, the total organic carbon content and acoustic impedance data of different blocks in each stratigraphic level are obtained, and the intersection diagram of total organic carbon content and acoustic impedance of different blocks in each stratigraphic level is plotted. Then, quantitative relationships corresponding to different blocks in each stratigraphic level are established. For example, the quantitative relationship corresponding to block A in stratigraphic level E, the quantitative relationship corresponding to block B in stratigraphic level E, the quantitative relationship corresponding to block A in stratigraphic level W, the quantitative relationship corresponding to block B in stratigraphic level W, etc.

[0054] S3. Obtain the wave impedance data of the well to be predicted, and predict the distribution of mudstone and shale based on the wave impedance data; substitute the wave impedance data of the mudstone and shale distribution area into the quantitative relationship corresponding to the block and stratigraphic position of the mudstone and shale distribution area to predict the total organic carbon content of mudstone and shale.

[0055] In this invention, the wave impedance data of the well to be predicted can be obtained in the following two ways.

[0056] Method 1: Obtain the density logging curve and sonic logging curve of the well to be predicted; calculate the wave impedance data based on the density logging curve and sonic logging curve.

[0057] Specifically, the sonic transit time value at each depth point is obtained from the sonic logging data. Then, the P-wave velocity at each depth point is calculated using the following formula ( ):

[0058] .

[0059] Then, the density value at each depth point is obtained from the density logging data, and the P-wave velocity at each depth point is multiplied by the density value to obtain the wave impedance (AI) at that point.

[0060] Method 2: Obtain seismic data of the well to be predicted, and obtain wave impedance data based on the seismic data through an inversion algorithm.

[0061] Specifically, the seismic data of the well to be predicted is acquired, and the seismic data is preprocessed, including denoising, filtering, and improving the signal-to-noise ratio, to obtain high-quality seismic records. Seismic wavelets are extracted from the seismic records, and the reflection coefficient sequence is extracted using the deconvolution method based on the convolution relationship between the seismic records and the seismic wavelets. An inversion algorithm is determined, such as generalized linear inversion, iterative inversion, or trace integral inversion. The extracted reflection coefficient sequence and the given initial wave impedance value are input into the inversion algorithm, and the corresponding wave impedance sequence is obtained through the calculation of the inversion algorithm.

[0062] Furthermore, the distribution of mudstone and shale is predicted based on wave impedance data.

[0063] This invention distinguishes between sandstone and mudstone / shale by analyzing the impedance histograms of different lithologies and setting lithology discrimination thresholds for different blocks and strata.

[0064] Specifically, the process is as follows:

[0065] Step 1: Obtain logging data from wells at different strata in different blocks, and plot the wave impedance frequency distribution maps for mudstone and shale with different total organic carbon contents, as well as the wave impedance frequency distribution maps for sandstone, based on the logging data.

[0066] The logging data includes sonic logging data, density logging data, resistivity logging data, and natural gamma spectroscopy (NGS) logging data.

[0067] For example, acoustic impedance is calculated using sonic logging data and density logging data; TOC content is assessed using natural gamma ray spectroscopy, acoustic, density, and resistivity logging data; for shale, acoustic impedance data are categorized according to TOC content; and statistical methods (such as histograms) are used to display the frequency distribution of acoustic impedance for different categories. Figure 3 As shown, Figure 3 The waveform impedance frequency distribution diagrams for different blocks at different layers are shown.

[0068] Step 2: Determine the threshold values ​​for distinguishing mudstone and sandstone in different layers and blocks based on the wave impedance frequency distribution diagram.

[0069] For example, such as Figure 3 As shown, based on the frequency variation trends of the acoustic impedance of shale and sandstone, two envelopes are drawn, and the acoustic impedance corresponding to the intersection of the two envelopes is determined as the threshold value. For example, the threshold value corresponding to block W9 of layer E1 is 8800 m / s*g / cm3, the threshold value corresponding to block W10 of layer E1 is 10200 m / s*g / cm3, and the threshold value corresponding to block W19 of layer E1 is 10200 m / s*g / cm3.

[0070] Step 3: Compare the wave impedance data with the threshold values ​​of the corresponding blocks and layers. If the data is less than or equal to the threshold value, it is considered mudstone or shale.

[0071] Specifically, the wave impedance data of the well to be logged is compared with the threshold values ​​of the block and formation where the well is located. If it is less than or equal to the threshold, it is mudstone or shale; if it is greater than the threshold, it is sandstone.

[0072] In the above embodiments, threshold values ​​are divided according to different layers and blocks, which can more accurately identify mudstone and sandstone.

[0073] Furthermore, since a quantitative relationship between total organic carbon content and wave impedance was established in S2 for different strata and blocks, once the distribution of mudstone and shale is determined, it is only necessary to substitute the wave impedance data of the mudstone and shale distribution area into the quantitative relationship corresponding to the block and stratum for calculation to obtain the TOC data volume.

[0074] In this invention, after predicting the total organic carbon content of mudstone and shale and identifying the distribution of mudstone and shale in the area to be predicted, a thickness map of high-quality source rocks and a planar distribution map of total organic carbon content can be drawn based on the predicted total organic content and mudstone and shale distribution.

[0075] It should be understood that shale and mudstone are common source rocks. Source rock thickness maps show the thickness distribution of source rocks; TOC planar distribution maps show the organic matter content distribution in source rocks, and high TOC values ​​usually indicate higher hydrocarbon generation potential. Drawing thickness maps and total organic carbon content planar distribution maps of high-quality source rocks can help identify exploration targets, understand sedimentary environments, conduct risk assessments, and guide drilling and development, which is of great significance for oil and gas exploration and development.

[0076] Based on the same inventive concept, embodiments of the present invention also provide a device for predicting the total organic carbon content of mudstone and shale, the device comprising:

[0077] The analysis module is used to select shale samples from multiple wells for testing, obtain the total organic carbon content and wave impedance value of the shale, perform correlation analysis on the total organic carbon content and wave impedance value, and select target wells with a correlation greater than a preset threshold.

[0078] The module is used to acquire total organic carbon content and wave impedance data of mudstone and shale from different blocks and different strata in the target well; draw cross-plots of total organic carbon content and wave impedance in different blocks and different strata; and construct quantitative relationships between total organic carbon content and wave impedance in different blocks and different strata based on the cross-plots.

[0079] The prediction module is used to acquire the wave impedance data of the well to be predicted, and predict the distribution of mudstone and shale based on the wave impedance data; by substituting the wave impedance data of the mudstone and shale distribution area into the quantitative relationship corresponding to the block and stratigraphic position of the mudstone and shale distribution area, the total organic carbon content of mudstone and shale is predicted.

[0080] The modules in the aforementioned device for predicting the total organic carbon content of shale can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0081] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the steps in the method embodiment for predicting the total organic carbon content of shale. Specific implementation methods can be found in the method embodiment, and will not be repeated here.

[0082] Furthermore, the present invention also provides a non-transitory computer-readable storage medium containing instructions on which a computer program is stored. For example, a memory containing instructions that can be executed by a processor of a computer device to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc. When the computer program is executed by the processor, it can implement the steps in the method embodiment for predicting the total organic carbon content of shale. Specific implementation methods can be found in the method embodiment, and will not be repeated here.

[0083] Those skilled in the art will understand that embodiments of the present invention can provide methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0084] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0085] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0086] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0087] It should be noted that the specific embodiments described above enable those skilled in the art to more fully understand the present invention, but do not limit the present invention in any way. Therefore, although the present invention has been described in detail in this specification and embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the present invention; and all technical solutions and improvements that do not depart from the spirit and scope of the present invention are covered within the protection scope of the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims. Any simple variations or equivalent substitutions of technical solutions that can be readily obtained by those skilled in the art within the scope of the technology disclosed in the present invention are within the protection scope of the present invention.

Claims

1. A method of predicting total organic carbon content of shale, characterized by, The method comprises the following steps: Selecting shale samples from a plurality of typical wells reflecting characteristics of source rocks for testing to obtain total organic carbon content and wave impedance values of the shale, and performing correlation analysis on the total organic carbon content and the wave impedance values to select target wells with a correlation greater than a preset threshold; In the target wells, obtaining total organic carbon content, logging data and wave impedance data of shale from wells in different blocks and different layers; drawing wave impedance frequency distribution graphs of shale corresponding to different total organic carbon contents and wave impedance frequency distribution graphs of sandstone corresponding to the logging data; determining threshold values for distinguishing shale and sandstone in different blocks and different layers according to the wave impedance frequency distribution graphs; and drawing a crossplot of total organic carbon content and wave impedance in different blocks and different layers, and constructing a quantitative relationship between total organic carbon content and wave impedance in different blocks and different layers based on the crossplot; Obtaining wave impedance data of a well to be predicted, comparing the wave impedance data with the threshold values corresponding to the block and the layer, and determining a shale distribution area when the wave impedance data is less than or equal to the threshold value; and substituting the wave impedance data of the shale distribution area into a quantitative relationship corresponding to the block and the layer where the shale distribution area is located to predict total organic carbon content of the shale.

2. The method for predicting total organic carbon content of shale according to claim 1, wherein, The method for obtaining wave impedance data of a well to be predicted comprises the following steps: Obtaining a density logging curve and an acoustic logging curve of the well to be predicted; calculating wave impedance data according to the density logging curve and the acoustic logging curve; or Obtaining seismic data of the well to be predicted, and obtaining wave impedance data through an inversion algorithm based on the seismic data.

3. The method for predicting total organic carbon content of shale of claim 1, wherein, After predicting shale distribution and total organic carbon content of the shale, the method further comprises the following steps: Drawing a high-quality source rock thickness map and a total organic carbon content planar distribution map based on the predicted shale distribution and the predicted total organic carbon content.

4. A device for predicting total organic carbon content of shale, characterized by, The method comprises the following steps: An analysis module is configured to select shale samples from a plurality of typical wells reflecting characteristics of source rocks for testing to obtain total organic carbon content and wave impedance values of the shale, and perform correlation analysis on the total organic carbon content and the wave impedance values to select target wells with a correlation greater than a preset threshold; A construction module is configured to, in the target wells, obtain total organic carbon content, logging data and wave impedance data of shale from wells in different blocks and different layers; draw wave impedance frequency distribution graphs of shale corresponding to different total organic carbon contents and wave impedance frequency distribution graphs of sandstone corresponding to the logging data; determine threshold values for distinguishing shale and sandstone in different blocks and different layers according to the wave impedance frequency distribution graphs; and draw a crossplot of total organic carbon content and wave impedance in different blocks and different layers, and construct a quantitative relationship between total organic carbon content and wave impedance in different blocks and different layers based on the crossplot; A prediction module is configured to obtain wave impedance data of a well to be predicted, compare the wave impedance data with the threshold values corresponding to the block and the layer, and determine a shale distribution area when the wave impedance data is less than or equal to the threshold value; and substitute the wave impedance data of the shale distribution area into a quantitative relationship corresponding to the block and the layer where the shale distribution area is located to predict total organic carbon content of the shale.

5. A computer device, comprising: The mud shale total organic carbon content prediction method of any one of claims 1-3 is implemented by a processor executing a computer program stored on a memory.

6. A computer-readable storage medium, characterized in that, The mud shale total organic carbon content prediction method of any one of claims 1-3 is implemented by a processor executing a computer program stored on a memory.

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