Logging evaluation method and device for organic carbon content of paste-containing argillaceous hydrocarbon source rock

Abstract

The invention relates to the professional technical field of new energy terrestrial heat, in particular to a logging evaluation method and device for the organic carbon content of paste-containing argillaceous hydrocarbon source rock.The method comprises the steps that a first interval transit time value is substituted into a first logging curve correction model to be corrected, and then a corrected second interval transit time value is obtained; calculating a first shale content based on the first measurement curve; based on the first shale content, the second interval transit time value and the first resistivity value, the organic carbon content corresponding to the measured hydrocarbon source rock stratum is calculated; according to the method, a well logging curve correction model under the influence of hydrocarbon source rock maturity difference is newly added, then a high-gamma curve response model containing the deposition influence of fine particles such as gypsum source rock is established, finally, the organic carbon content of a whole well section is calculated through the established calibration relation, high-precision evaluation of the organic matter abundance of the hydrocarbon source rock is achieved, and the method is suitable for the high-precision evaluation of the abundance of the hydrocarbon source rock. And a practical and effective method is provided for logging evaluation of the paste-containing argillaceous hydrocarbon source rock.

Description

Technical Field

[0001] The present invention relates to the field of new energy geothermal technology, and in particular to a method and device for evaluating the organic carbon content of gypsum-containing source rocks. Background Art

[0002] Organic carbon content (TOC) is the main indicator of the abundance of organic matter in source rocks. The traditional method of obtaining it is to conduct experimental analysis on core or cuttings samples. Due to the cost of coring and experimental efficiency, it is not suitable for continuous analysis of TOC of the entire source rock of all exploration wells. Due to the heterogeneity of source rocks, the average value of a small number of discrete TOC laboratory analyses has a large error.

[0003] At present, the common technical method in the oil industry is to obtain relatively continuous TOC through well logging curves. It was first proposed by Exxon and Esso in 1979 based on the statistical analysis of core data of actual well data. It is mainly based on the difference in the response of acoustic time difference and resistivity logging curves to shale layers. For complex lithology formations such as those rich in gypsum, since the acoustic time difference and resistivity response are affected by lithology, maturity of source rocks, oil and gas content and compaction, the actual application error of this technology is large, and it is basically not applicable to formations with large maturity differences, source rocks containing gypsum, and deep thin interbedded source rocks. Summary of the invention

[0004] The purpose of the present invention is to provide a method and device for evaluating the organic carbon content of gypsum-containing argillaceous source rocks, so as to improve the above-mentioned technical problems.

[0005] In order to achieve the above objectives, the present application provides the following technical solutions:

[0006] On the one hand, an embodiment of the present application provides a method for evaluating the organic carbon content of gypsum-containing mudstone source rocks by logging, the method comprising: constructing a logging curve correction model for source rock maturity differences, recorded as a first logging curve correction model; obtaining a first acoustic wave time difference value obtained by measurement, and bringing the first acoustic wave time difference value into the first logging curve correction model for correction processing, thereby obtaining the first acoustic wave time difference value after correction, recorded as a second acoustic wave time difference value; calculating a first mud content based on a first measurement curve, the first measurement curve being a measured natural potential curve or a gamma curve; and calculating the organic carbon content corresponding to the measured source rock layer based on the first mud content, the second acoustic wave time difference value and the first resistivity value.

[0007] Optionally, it is characterized in that the first logging curve correction model is:

[0008] AC 2=AC+(AC depth - mudstone ACmax depth) / stratum thickness*(mudstone ACmax - mudstone ACmin);

[0009] In the formula, AC 2 is the time difference value of the second sound wave, and AC is the time difference value of the first sound wave.

[0010] Optionally, calculating the organic carbon content corresponding to the measured source rock layer based on the first shale content, the second acoustic wave time difference value and the first resistivity value includes:

[0011] If the first shale content is greater than 0.5, and the second acoustic time difference value is less than the acoustic time difference baseline value, and the first resistivity value is less than the resistivity baseline value, then the organic carbon content corresponding to the source rock layer is calculated based on the first organic carbon content calculation formula, and the first organic carbon content calculation formula is:

[0012] TOC=a*(0.02*(AC 2 -AC baseline value)+log(RT / RT baseline value))+b;

[0013] Where Vsh is the first mud content, TOC is the organic carbon content, AC 2 is the second acoustic time difference value, AC baseline value is the acoustic time difference baseline value, RT is the first resistivity value, RT baseline value is the resistivity baseline value, a and b are the fitting curve coefficient and corresponding constant of TOC and amplitude difference obtained by laboratory analysis, respectively.

[0014] Optionally, calculating the organic carbon content corresponding to the measured source rock layer based on the first shale content, the second acoustic wave time difference value and the first resistivity value includes:

[0015] If the first mud content is greater than 0.5, and the second acoustic time difference value is greater than the acoustic time difference baseline value, and the first resistivity value is greater than the resistivity baseline value, then the organic carbon content corresponding to the source rock layer is calculated based on the second organic carbon content calculation formula, and the second organic carbon content calculation formula is:

[0016] TOC = Carbon recovery coefficient*a*(0.02*(AC 2 -AC baseline value)+log(RT / RT baseline value))+b;

[0017] In the formula, TOC is the organic carbon content, AC is 2 is the second acoustic time difference value, AC baseline value is the acoustic time difference baseline value, RT is the first resistivity value, RT baseline value is the resistivity baseline value, a and b are the fitting curve coefficient and corresponding constant of TOC and amplitude difference obtained by laboratory analysis, respectively, and the carbon recovery coefficient is measured by historical test data.

[0018] In a second aspect, an embodiment of the present application provides a well logging evaluation device for organic carbon content of gypsum-containing argillaceous source rock, the device comprising:

[0019] The first construction module is used to construct a well logging curve correction model for source rock maturity differences, which is recorded as the first well logging curve correction model;

[0020] A first acquisition module is used to acquire the first acoustic wave time difference value obtained through measurement, and bring the first acoustic wave time difference value into the first logging curve correction model for correction processing, thereby obtaining the first acoustic wave time difference value after correction processing, which is recorded as the second acoustic wave time difference value;

[0021] A first calculation module, configured to calculate a first mud content based on a first measurement curve, wherein the first measurement curve is a measured spontaneous potential curve or a gamma curve;

[0022] The second calculation module is used to calculate the organic carbon content corresponding to the measured source rock layer based on the first mud content, the second acoustic wave time difference value and the first resistivity value.

[0023] In a third aspect, an embodiment of the present application provides a well logging evaluation device for organic carbon content of gypsum-mudstone source rocks, the device comprising a memory and a processor.

[0024] The memory is used to store computer programs; the processor is used to implement the steps of the above-mentioned method for evaluating the organic carbon content of gypsum-containing argillaceous source rocks when executing the computer programs.

[0025] In a fourth aspect, an embodiment of the present application provides a medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the above-mentioned method for well logging evaluation of organic carbon content of gypsum-containing mudstone source rock are implemented.

[0026] The beneficial effects of the present invention are:

[0027] In order to solve the problem that the fitting calculation formula has poor correlation and large calculation error due to the influence of lithology such as gypsum when evaluating the organic matter in source rocks during well logging, the present invention firstly adds a well logging curve correction model under the influence of source rock maturity difference, and then establishes a model of high gamma curve response affected by the deposition of fine particles such as gypsum source rocks, and finally uses the established calibration relationship to calculate the organic carbon content of the entire well section, so as to achieve high-precision evaluation of the abundance of organic matter in source rocks, provide a practical and effective method for well logging evaluation of gypsum-mud source rocks, and provide a basis for finely describing the spatial distribution of organic matter in source rocks and predicting favorable oil and gas exploration prospect areas in oil and gas exploration.

[0028] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or be understood by practicing the embodiments of the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0030] Figure 1 It is a schematic flow chart of a method for evaluating the organic carbon content of gypsum-containing argillaceous source rock described in an embodiment of the present invention;

[0031] Figure 2 It is a schematic diagram of the structure of a well logging evaluation device for organic carbon content of gypsum-containing mudstone source rock described in an embodiment of the present invention;

[0032] Figure 3 It is a schematic diagram of the structure of a well logging evaluation device for organic carbon content of gypsum-containing mudstone source rock described in an embodiment of the present invention;

[0033] Figure 4 This is the AC curve characteristic of the Hetan 1 well described in the embodiment of the present invention.

[0034] Figure 5 The figure is a comparison of the TOC calculation results of the two methods in the Hetan 1 well in the Linhe Depression described in the embodiments of the present invention.

[0035] Figure 6 This is a correlation diagram between the calculated TOC and the measured TOC of the Hetan 1 well described in an embodiment of the present invention. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0037] It should be noted that similar reference numerals or letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0038] Example 1

[0039] like Figure 1 As shown, this embodiment provides a method for well logging evaluation of organic carbon content in gypsum-containing argillaceous source rocks, the method comprising step S100, step S200, step S300 and step S400.

[0040] Step S100, constructing a well logging curve correction model for source rock maturity differences, recorded as a first well logging curve correction model;

[0041] Step S200, obtaining the first acoustic wave time difference value obtained by measurement, and bringing the first acoustic wave time difference value into the first logging curve correction model for correction processing, thereby obtaining the first acoustic wave time difference value after correction processing, which is recorded as the second acoustic wave time difference value;

[0042] Step S300: Calculate a first mud content based on a first measurement curve, where the first measurement curve is a measured spontaneous potential curve or a gamma curve;

[0043] Step S400: Calculate the organic carbon content of the measured source rock layer based on the first mud content, the second acoustic wave time difference value and the first resistivity value.

[0044] Wherein, the first logging curve correction model is:

[0045] AC 2 =AC+(AC depth - mudstone ACmax depth) / stratum thickness*(mudstone ACmax - mudstone ACmin);

[0046] In the formula, AC 2 is the time difference value of the second sound wave, and AC is the time difference value of the first sound wave.

[0047] Secondly, in step S400, the organic carbon content corresponding to the measured source rock layer is calculated based on the first shale content, the second acoustic wave time difference value and the first resistivity value, including:

[0048] Step S410: If the first shale content is greater than 0.5, and the second acoustic time difference value is less than the acoustic time difference baseline value, and the first resistivity value is less than the resistivity baseline value, then the organic carbon content corresponding to the source rock layer is calculated based on the first organic carbon content calculation formula, and the first organic carbon content calculation formula is:

[0049] TOC=a*(0.02*(AC 2 -AC baseline value)+log(RT / RT baseline value))+b;

[0050] Where Vsh is the first mud content, TOC is the organic carbon content, AC 2 is the second acoustic time difference value, AC baseline value is the acoustic time difference baseline value, RT is the first resistivity value, RT baseline value is the resistivity baseline value, a and b are the fitting curve coefficient and corresponding constant of TOC and amplitude difference obtained by laboratory analysis, respectively.

[0051] In step S400, the organic carbon content corresponding to the measured source rock layer is calculated based on the first shale content, the second acoustic time difference value and the first resistivity value, including:

[0052] Step S420: If the first shale content is greater than 0.5, and the second acoustic time difference value is greater than the acoustic time difference baseline value, and the first resistivity value is greater than the resistivity baseline value, then the organic carbon content corresponding to the source rock layer is calculated based on the second organic carbon content calculation formula, and the second organic carbon content calculation formula is:

[0053] TOC = Carbon recovery coefficient*a*(0.02*(AC 2 -AC baseline value)+log(RT / RT baseline value))+b;

[0054] In the formula, TOC is the organic carbon content, AC is 2 is the second acoustic time difference value, AC baseline value is the acoustic time difference baseline value, RT is the first resistivity value, RT baseline value is the resistivity baseline value, a and b are the fitting curve coefficient and corresponding constant of TOC and amplitude difference obtained by laboratory analysis, respectively, and the carbon recovery coefficient is measured by historical test data.

[0055] In this implementation, in order to solve the problem of poor correlation of fitting calculation formulas and large calculation errors caused by the influence of lithology such as gypsum when evaluating organic matter in source rocks by logging, a logging curve correction model under the influence of source rock maturity differences was first added. Secondly, a model of high gamma curve response affected by fine-grained sedimentation such as gypsum source rocks was established. Finally, the established calibration relationship was used to calculate the organic carbon content of the entire well section, achieving high-precision evaluation of the abundance of organic matter in source rocks. This provides a practical and effective method for logging evaluation of gypsum-containing mudstone source rocks, and provides a basis for finely describing the spatial distribution of organic matter in source rocks and predicting favorable oil and gas exploration prospects in oil and gas exploration.

[0056] Example 2

[0057] This embodiment is used to fully explain the principle of the entire technical solution:

[0058] The solution is to solve the problems of large maturity span, large changes in acoustic time difference of source rocks distributed from immature to highly mature, large changes in formation resistivity of source rocks containing gypsum in saline environment, difficulty in calculating TOC values ​​of deep thin interbedded source rocks through logging curves, and large errors in the results of conventional evaluation methods.

[0059] First, as the maturity of source rocks changes, the acoustic time difference decreases from 300-600μs / m to 100-200μs / m, and the acoustic time difference value decreases significantly. According to conventional logging evaluation methods for source rocks, the top acoustic time difference baseline is quite different from the bottom.

[0060] Second, gypsum is often developed when source rocks are in a saline environment. Compared with conventional mudstone, the acoustic time difference value of gypsum-containing mudstone is basically the same, but the resistance response value is abnormally high, up to 5000ohm.m, which is several orders of magnitude higher than that of conventional mudstone.

[0061] Third, the acoustic time difference of deep and thin interlayers is basically small, the resistance changes rapidly, and often appears thorny.

[0062] The invention relates to a comprehensive application of geochemical technology and logging information to achieve quantitative evaluation of organic carbon content in gypsum-rich mudstone source rocks, belonging to a comprehensive method for quantitative evaluation of geophysical logging source rocks in petroleum geological exploration that is different from traditional evaluation technology.

[0063] Firstly, a well logging curve correction model under the influence of source rock maturity difference is established. Secondly, a model of the sedimentary influence of fine particles such as gypsum source rocks is established. Finally, the TOC of the source rock layer is calculated using the established calibration relationship.

[0064] (1) Well logging curve correction model for source rock maturity differences:

[0065] With the change of the maturity of the hydrocarbon source rock, the acoustic time difference decreases from 300 - 600 μs / m to 100 - 200 μs / m, and the decrease in the acoustic time difference value is significantly about 30 - 50%. According to the conventional logging evaluation method for hydrocarbon source rocks, there is a large difference between the acoustic time difference baseline at the top and the bottom, and the acoustic time difference baseline needs to be corrected.

[0066] The correction formula is:

[0067] AC correction = AC + (depth where AC is located - depth where shale ACmax is located) / formation thickness * (shale ACmax - shale ACmin)

[0068] (2) Calculation method for gypsum-bearing hydrocarbon source rocks / (3) High-precision identification calculation method for deep thin interbedded hydrocarbon source rocks.

[0069] The conventional logging evaluation calculation formula for hydrocarbon source rocks is:

[0070] TOC = -a * ((0.02 * (AC - AC baseline value) + log(RT / RT baseline value)) + b

[0071] TOC: Total organic carbon content; a: Fitting curve coefficient; b: Fitting curve constant; AC: Acoustic time difference value

[0072] AC baseline value: Acoustic time difference curve baseline value; RT: Resistivity value; RT baseline value: Resistivity curve baseline value

[0073] For the logging evaluation of gypsum-bearing shale hydrocarbon source rocks, first distinguish shale and sandstone formations through the spontaneous potential curve or gamma curve. The calculation formula is:

[0074] Vsh (shale content) = (SP - SPmin) / (SPmax - SPmin).

[0075] In addition, use the judgment statement IF statement. If RT is greater than the sandstone RTmax, then the lithology is non-hydrocarbon source rock. Remove the formation section containing gypsum rock.

[0076] The specific calculation formula is:

[0077] TOC = IF((Vsh > 0.5, AC - AC baseline value < 0, TOC background value));

[0078] IF: Vsh > 0.5, AC - AC baseline value > 0, RT < RT baseline value, then the hydrocarbon source rock is an immature - low maturity hydrocarbon source rock, the hydrocarbon source rock has not generated or expelled a large amount of hydrocarbons, and the TOC content is generally high. Determine the fitting curve coefficient a and the constant b through the TOC and amplitude difference analyzed in the laboratory. The TOC content calculation formula is:

[0079] TOC = IF(Vsh > 0.5 && AC > AC baseline value && RT < RT baseline value, a * (0.02 * (AC - AC baseline value) + log(RT / RT baseline value)) + b, TOC background value);

[0080] IF: When AC - AC baseline value > 0 and RT > RT baseline value, the source rock is a mature source rock, and the TOC analyzed in the laboratory is generally low. Therefore, the correlation coefficient does not need to be too high. The fitting curve coefficients a and the constant b are determined by the TOC analyzed in the laboratory and the amplitude difference. The TOC content calculation formula is:

[0081] TOC = IF(Vsh > 0.5 && AC > AC baseline value && RT > RT baseline value), carbon recovery coefficient * a * (0.02 * (AC - AC baseline value) + log(RT / RT baseline value)) + b;

[0082] (3) High-precision identification calculation method for deep thin interbedded source rocks

[0083] For deep sandstone-mudstone thin layer source rocks, the TOC content calculation formula is:

[0084] TOC = a * (0.02 * (AC + (depth where AC is located - depth where mudstone ACmax is located) / formation thickness * (mudstone ACmax - mudstone ACmin) - AC baseline value) + log(RT / RT baseline value)) + b.

[0085] Applied to the evaluation of deep - ultra - deep thin layer gypsum - bearing argillaceous source rocks in the Linhe Formation of the Linhe Depression. The Linhe Formation in the Linhe Depression has a large sedimentary thickness and a burial depth of about 3000 - 6500m. At present, Well Hetan 1 drilled more than six thousand meters deep near the sag area only revealed the sediment of the second member of the Linhe Formation. The upper part of the first member of the Linhe Formation in Well Hetan 1 is the Wuyuan Formation, which is brown and gray mudstone intercalated with light gray siltstone. The thickness of the gray mudstone in the Wuyuan Formation is about 60m, mainly medium - poor source rocks; the Linhe Formation is gray mudstone intercalated with light gray siltstone and fine sandstone, with oil and gas shows. The thickness of the gray mudstone is 200.5m, and the acoustic time difference value shows an obvious decreasing trend in the Linhe Formation. Figure 4 。

[0086] The TOC value calculated by the conventional source rock logging evaluation ( Figure 5 TOC1 curve in it) is small, and generally TOC < 0.7%. Using the calculation method for gypsum - bearing source rocks and the calculation method for deep - ultra - deep thin layer source rocks, the calculated TOC value is between 0.39% - 1.35% ( Figure 5 TOC2 curve in it). This is more in line with the geological understanding. The first member of the Linhe Formation is dark mudstone, and the laboratory - tested TOC value is between 0.53% - 1.3% ( Figure 5The TOC and S1+S2 contents are moderate, and the asphalt A content is high. The organic matter abundance of its source rock is higher than that of the brown mudstone of the Wuyuan Formation. The calculated TOC is more consistent with the laboratory test results. Figure 6 .

[0087] The invention is applicable to gypsum source rock formations in saline environments and formations with large maturity spans. It has broad application prospects in the fields of oil and gas exploration and resource evaluation, and provides support for predicting favorable oil and gas exploration areas.

[0088] The use of logging data to study and evaluate oil-generating rocks began in foreign countries in the 1970s, and domestic work in this area has also made certain progress, but it is basically not applicable to the evaluation of thin-layer source rocks containing gypsum.

[0089] The method of this patent invention provides a new method for calculating the organic carbon content of gypsum-containing mudstone source rocks. It is the same as the commonly used method for the case where there is no obvious abnormality in the acoustic time difference and resistance logging response. This method works better in the intervals containing gypsum mudstone and thin interbedded mudstone.

[0090] Through the study and evaluation of the source rocks in the Linhe Depression, the organic matter maturity of the source rocks of the Linhe Formation is in the low-mature-mature stage in the Nalin Lake, Linhua and Xinghua areas, and in the mature-high-mature stage in the Guangming anticline, and the maturity basically increases from the south to the north. The content of biomarkers S / (S+R)-C29 and ββ-C29 ranges from 5% to 45%. The source rocks of the Guyang Formation are in the mature-high-mature evolution stage as a whole, and the content of biomarkers S / (S+R)-C29 and ββ-C29 ranges from 20% to 55%. The maturity difference is large.

[0091] The method invented in this patent solves the problem of poor correlation of calculation models of gypsum-containing mudstone and thin interbedded mudstone under different maturity conditions, indicating that based on the geochemical analysis scale of source rock core samples, the relatively continuous organic carbon content of source rocks can be calculated more accurately.

[0092] Example 3

[0093] like Figure 2 As shown, this embodiment provides a well logging evaluation device for organic carbon content of gypsum-containing argillaceous source rock, the device comprising:

[0094] The first construction module 71 is used to construct a well logging curve correction model for source rock maturity differences, which is referred to as the first well logging curve correction model;

[0095] The first acquisition module 72 is used to acquire the first acoustic wave time difference value obtained through measurement, and bring the first acoustic wave time difference value into the first logging curve correction model for correction processing, thereby obtaining the first acoustic wave time difference value after correction processing, which is recorded as the second acoustic wave time difference value;

[0096] A first calculation module 73, configured to calculate a first mud content based on a first measurement curve, where the first measurement curve is a measured spontaneous potential curve or a gamma curve;

[0097] The second calculation module 74 is used to calculate the organic carbon content corresponding to the measured source rock layer based on the first mud content, the second acoustic wave time difference value and the first resistivity value.

[0098] It should be noted that, regarding the device in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment of the method, and will not be elaborated here.

[0099] Example 4

[0100] Corresponding to the above method embodiment, the embodiment of the present disclosure also provides an organic carbon content logging evaluation device for gypsum-mudstone source rock. The organic carbon content logging evaluation device for gypsum-mudstone source rock described below and the organic carbon content logging evaluation method for gypsum-mudstone source rock described above can be referenced to each other.

[0101] Figure 3 FIG. 8 is a block diagram of an organic carbon content logging evaluation device 800 for gypsum-containing argillaceous source rocks according to an exemplary embodiment. Figure 3 As shown, the electronic device 800 may include: a processor 801 and a memory 802. The electronic device 800 may also include one or more of a multimedia component 803, an I / O interface 804, and a communication component 805.

[0102] The processor 801 is used to control the overall operation of the electronic device 800 to complete all or part of the steps in the above-mentioned method for evaluating the organic carbon content of gypsum-containing argillaceous source rocks. The memory 802 is used to store various types of data to support the operation of the electronic device 800, and these data may include, for example, instructions for any application or method used to operate on the electronic device 800, and application-related data, such as contact data, sent and received messages, pictures, audio, video, etc. The memory 802 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, disk or optical disk. The multimedia component 803 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 802 or sent via the communication component 805. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 804 provides an interface between the processor 801 and other interface modules, and the above-mentioned other interface modules can be keyboards, mice, buttons, etc. These buttons can be virtual buttons or physical buttons. The communication component 805 is used for wired or wireless communication between the electronic device 800 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding communication component 805 may include: Wi-Fi module, Bluetooth module, NFC module.

[0103] In an exemplary embodiment, the electronic device 800 can be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned organic carbon content logging evaluation method for gypsum-containing mudstone source rocks.

[0104] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the above-mentioned method for evaluating the organic carbon content of gypsum-containing argillaceous source rocks by logging are implemented. For example, the computer-readable storage medium may be the above-mentioned memory 802 including program instructions, and the above-mentioned program instructions may be executed by the processor 801 of the electronic device 800 to complete the above-mentioned method for evaluating the organic carbon content of gypsum-containing argillaceous source rocks by logging.

[0105] Example 5

[0106] Corresponding to the above method embodiment, the embodiment of the present disclosure further provides a readable storage medium. The readable storage medium described below and the organic carbon content logging evaluation method of gypsum-containing mudstone source rock described above can be referenced to each other.

[0107] A readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for well logging evaluation of organic carbon content of gypsum-containing argillaceous source rock of the above method embodiment.

[0108] The readable storage medium may specifically be a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or other readable storage medium that can store program codes.

[0109] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for evaluating the organic carbon content of gypsum-containing argillaceous source rocks by logging, characterized in that: The method comprises: A well logging curve correction model for source rock maturity differences is constructed, which is referred to as the first well logging curve correction model; Acquiring the first acoustic wave time difference value obtained through measurement, and bringing the first acoustic wave time difference value into the first logging curve correction model for correction processing, thereby obtaining the first acoustic wave time difference value after correction processing, which is recorded as the second acoustic wave time difference value; Calculating a first mud content based on a first measurement curve, where the first measurement curve is a measured spontaneous potential curve or a gamma curve; Based on the first mud content, the second acoustic wave time difference value and the first resistivity value, the organic carbon content corresponding to the measured source rock layer is calculated.

2. The method for evaluating the organic carbon content of gypsum-containing argillaceous source rock according to claim 1, characterized in that: The first logging curve correction model is: AC2 = AC + (depth of AC - depth of mudstone ACmax) / formation thickness * (mudstone ACmax - mudstone ACmin); Wherein, AC2 is the second sound wave time difference value, and AC is the first sound wave time difference value.

3. The method for evaluating the organic carbon content of gypsum-containing argillaceous source rock according to claim 1, characterized in that: Based on the first shale content, the second acoustic wave time difference value and the first resistivity value, the organic carbon content corresponding to the measured source rock layer is calculated, including: If the first shale content is greater than 0.5, and the second acoustic time difference value is less than the acoustic time difference baseline value, and the first resistivity value is less than the resistivity baseline value, then the organic carbon content corresponding to the source rock layer is calculated based on the first organic carbon content calculation formula, and the first organic carbon content calculation formula is: TOC = a*(0.02*(AC2-AC baseline value)+log(RT / RT baseline value))+b; Wherein, Vsh is the first mud content, TOC is the organic carbon content, AC2 is the second acoustic time difference value, AC baseline value is the acoustic time difference baseline value, RT is the first resistivity value, RT baseline value is the resistivity baseline value, a and b are the fitting curve coefficient and corresponding constant of TOC and amplitude difference obtained by laboratory analysis, respectively.

4. The method for evaluating the organic carbon content of gypsum-containing argillaceous source rock according to claim 1, characterized in that: Based on the first shale content, the second acoustic wave time difference value and the first resistivity value, the organic carbon content corresponding to the measured source rock layer is calculated, including: If the first mud content is greater than 0.5, and the second acoustic time difference value is greater than the acoustic time difference baseline value, and the first resistivity value is greater than the resistivity baseline value, then the organic carbon content corresponding to the source rock layer is calculated based on the second organic carbon content calculation formula, and the second organic carbon content calculation formula is: TOC = carbon recovery coefficient * a * (0.02 * (AC2-AC baseline value) + log (RT / RT baseline value)) + b; Wherein, TOC is the organic carbon content, AC2 is the second acoustic time difference value, AC baseline value is the acoustic time difference baseline value, RT is the first resistivity value, RT baseline value is the resistivity baseline value, a and b are the fitting curve coefficient and corresponding constant of TOC and amplitude difference obtained by laboratory analysis, respectively, and the carbon recovery coefficient is measured by historical test data.

5. A well logging evaluation device for organic carbon content of gypsum-containing argillaceous source rock, characterized in that: The device comprises: The first construction module is used to construct a well logging curve correction model for source rock maturity differences, which is recorded as the first well logging curve correction model; A first acquisition module is used to acquire the first acoustic wave time difference value obtained through measurement, and bring the first acoustic wave time difference value into the first logging curve correction model for correction processing, thereby obtaining the first acoustic wave time difference value after correction processing, which is recorded as the second acoustic wave time difference value; A first calculation module, configured to calculate a first mud content based on a first measurement curve, wherein the first measurement curve is a measured spontaneous potential curve or a gamma curve; The second calculation module is used to calculate the organic carbon content corresponding to the measured source rock layer based on the first mud content, the second acoustic wave time difference value and the first resistivity value.

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