A method and device for source-reservoir evaluation of shale

Abstract

The embodiment of the present application provides a shale source-reservoir evaluation method and device, solves the problem that the existing evaluation method cannot effectively and intuitively reflect the source-reservoir configuration of over-mature shale samples. The shale source-reservoir evaluation method provided by the embodiment of the present application comprises the following steps: obtaining parameter information of first shale samples; obtaining original source-reservoir coupling coefficients of all the first shale samples based on the parameter information of the first shale samples; obtaining second shale samples based on the source-reservoir coefficients of the first shale samples; obtaining the average value of vitrinite reflectivity of all the second shale samples; obtaining the source-reservoir coefficients of all the first shale samples based on the average value of vitrinite reflectivity of the second shale samples and the source-reservoir coefficients of the first shale samples; and performing source-reservoir evaluation on shale based on the source-reservoir coefficients of all the first shale samples.

Description

Technical Field

[0001] This invention relates to the field of shale gas geological exploration technology, specifically to a method and apparatus for evaluating the source and reservoir of shale. Background Technology

[0002] Shale gas is widely distributed and abundant in China. As an unconventional natural gas resource, shale gas is characterized by its self-generation and self-storage, and its integrated source and storage system. Therefore, it is necessary to evaluate and study the organic matter of the shale gas source and the pores that store the shale gas as a "source-storage" system.

[0003] When the thermal evolution of shale formations within a study area varies significantly, the use of source-reservoir coupling evaluation methods and calculation formulas to assess the source-reservoir coupling relationship of shale in that region is somewhat limited. Due to the influence of regional tectonic movements and diagenesis, shale samples in some areas of the same study area may have entered the organic matter carbonization stage, exhibiting excessively high thermal maturity (typically Ro greater than 3.5%). Even if the organic carbon content of such samples is not low and a certain level of porosity is developed, a large number of organic pores close due to diagenetic compaction or organic matter decomposition, leading to changes in the source-reservoir configuration and coupling relationship of the shale, and to some extent, reducing the natural gas adsorption capacity. Therefore, the source-reservoir coupling coefficient composed solely of TOC and porosity cannot effectively and intuitively reflect the source-reservoir configuration of excessively mature shale samples. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a source-reservoir evaluation method and apparatus for shale, which solves the problem that existing evaluation methods cannot effectively and intuitively reflect the source-reservoir configuration of overly mature shale samples.

[0005] An embodiment of the present invention provides a source-reservoir evaluation method for shale, comprising:

[0006] Obtain parameter information for the first shale sample;

[0007] Based on the parameter information of the first shale sample, the original source-reservoir coupling coefficients of all the first shale samples are obtained, and the second shale sample is obtained based on the source-reservoir coefficients of the first shale sample.

[0008] Obtain the average vitrinite reflectance of all second shale samples;

[0009] The source-reservoir coefficients of all first shale samples are obtained based on the average vitrinite reflectance of the second shale sample and the source-reservoir coefficient of the first shale sample, and the source-reservoir evaluation of the shale is carried out based on the source-reservoir coefficients of all first shale samples.

[0010] In one embodiment, the parameter information includes at least one of shale thermal maturity parameters, organic matter abundance parameters, and reservoir characteristic parameters.

[0011] In one embodiment, the formula for obtaining the original source-reservoir coupling coefficient of all the first shale samples based on the parameter information of the first shale sample is as follows:

[0012] Where o is the original source-storage coupling coefficient; TOC is the total organic carbon content; Porosity is a characteristic of storage.

[0013] In one embodiment, the step of obtaining the second shale sample based on the source-reservoir coefficient of the first shale sample includes:

[0014] The original source-reservoir coupling coefficients of all the shale samples were sorted.

[0015] The first cumulative probability curve of the original source-reservoir coupling coefficient of the shale samples is obtained based on the ranking results of the original source-reservoir coupling coefficients of all the shale samples.

[0016] The second shale sample was obtained based on the first cumulative probability curve.

[0017] In one implementation, the step of obtaining the second shale sample based on the first cumulative probability curve includes:

[0018] Dividing the curve into ten equal parts, intervals with cumulative coefficients accounting for 40%, 35%, and 25% of the total are selected on the first cumulative probability curve. The interval [0, 40%) represents shale samples with moderate source-reservoir conditions, [40%, 75%) represents shale samples with moderate source-reservoir conditions, and [75%, 100%) represents shale samples with superior source-reservoir conditions. The second shale sample is the shale sample with superior source-reservoir conditions. In one embodiment, the formula for obtaining the source-reservoir coefficient of all first shale samples based on the average vitrinite reflectance of the second shale sample and the source-reservoir coefficient of the first shale sample is:

[0019]

[0020] Where i represents the source-reservoir coefficient of all shale samples in the target stratigraphic position of all cored wells in the target area; o represents the original source-reservoir coupling coefficient; and Ro represents the vitrinite reflectivity. This represents the average reflectance of vitrinite.

[0021] In one embodiment, the step of evaluating the source-reservoir of shale based on the source-reservoir coefficients of all first shale samples includes:

[0022] Sort all the source-reservoir coefficients of the first shale samples in ascending order;

[0023] Based on the ranking of the source-reservoir coefficients of all the first shale samples, a second cumulative probability curve of the source-reservoir coefficients of all the first shale samples is generated.

[0024] Shale source and reservoir evaluation is performed based on the second cumulative probability curve.

[0025] In one implementation, the step of evaluating the source and reservoir of shale based on the second cumulative probability curve includes:

[0026] Divide the curve into ten equal parts and select intervals on the second cumulative probability curve where the cumulative coefficient accounts for 40%, 35%, and 25% of the total, respectively. The interval [0, 40%) represents shale samples with medium source-reservoir conditions, [40%, 75%) represents shale samples with medium source-reservoir conditions, and [75%, 100%] represents shale samples with good source-reservoir conditions.

[0027] An embodiment of the present invention provides a source-reservoir evaluation device for shale, comprising:

[0028] The acquisition module is used to acquire parameter information of the first shale sample and to acquire the average vitrinite reflectance of all second shale samples.

[0029] The processing module is used to obtain the original source-reservoir coupling coefficient of all first shale samples based on the parameter information of the first shale sample, obtain the second shale sample based on the source-reservoir coefficient of the first shale sample, and obtain the source-reservoir coefficient of all first shale samples based on the average vitrinite reflectance of the second shale sample and the source-reservoir coefficient of the first shale sample.

[0030] The evaluation module is used to evaluate the source and reservoir of shale based on the source-reservoir coefficients of all first shale samples.

[0031] An embodiment of the present invention provides an electronic device including a memory and a processor. The memory is used to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the aforementioned shale source-reservoir evaluation method.

[0032] An embodiment of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, is used to implement the aforementioned shale source-reservoir evaluation method.

[0033] This invention provides a source-reservoir evaluation method and apparatus for shale. The shale source-reservoir evaluation method includes: acquiring parameter information of a first shale sample; obtaining the original source-reservoir coupling coefficient of all first shale samples based on the parameter information of the first shale sample; obtaining a second shale sample based on the source-reservoir coefficient of the first shale sample; acquiring the average vitrinite reflectance of all second shale samples; obtaining the source-reservoir coefficient of all first shale samples based on the average vitrinite reflectance of the second shale samples and the source-reservoir coefficient of the first shale samples; and performing source-reservoir evaluation of the shale based on the source-reservoir coefficient of all first shale samples.

[0034] This invention introduces the parameter (Ro) characterizing thermal maturity to optimize existing source-reservoir coefficient formulas, providing a source-reservoir coupling evaluation method suitable for highly-to-over-mature shale. This allows highly-to-over-mature shale samples to be analyzed together with shale samples of moderate maturity for source-reservoir coupling evaluation. Compared with existing technologies, this invention has the following advantages:

[0035] (1) In order to overcome the shortcomings of the source-reservoir coupling evaluation results caused by the large difference in the thermal evolution degree of the target area, this invention provides a source-reservoir coupling evaluation method applicable to high-to-overmature shale, so that high-to-overmature shale samples and shale samples with moderate maturity can be carried out together for source-reservoir coupling evaluation analysis, making it more universal.

[0036] (2) Research has found that the source-reservoir coefficient i obtained by the method described in this invention is not only applicable to marine shale samples for technical testing, but also applicable to the source-reservoir evaluation of terrestrial and marine-continental transitional shale for which existing technology is applicable, which is conducive to the promotion of the results. Attached Figure Description

[0037] Figure 1 The diagram shows a flowchart of a source-reservoir evaluation method for shale provided in an embodiment of the present invention.

[0038] Figure 2 The diagram shown is a schematic representation of a specific process for calculating the source-reservoir coefficient of a sample and conducting source-reservoir coupling evaluation according to an embodiment of the present invention.

[0039] Figure 3 The diagram shown is a schematic representation of a specific process for calculating the source-reservoir coefficient of a sample and conducting source-reservoir coupling evaluation according to an embodiment of the present invention.

[0040] Figure 4 The figure shown is a cumulative probability curve of a source-storage coefficient o according to an embodiment of the present invention.

[0041] Figure 5 The figure shown is a cumulative probability curve of a source-storage coefficient i provided in an embodiment of the present invention.

[0042] Figure 6 The diagram shown is a schematic representation of a shale source-reservoir evaluation device according to an embodiment of the present invention. Detailed Implementation

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] Shale gas is widely distributed and abundant in my country. Currently, commonly used comprehensive evaluation parameters for shale gas typically include organic matter abundance, brittle mineral content, physical properties, shale thickness, mechanical parameters, burial depth, preservation conditions, maximum gas content, and sedimentary facies. As an unconventional natural gas resource, shale gas is characterized by its self-generation and self-storage, integrating source and reservoir. Therefore, it is necessary to evaluate and study the organic matter of the shale gas source and the porosity of the shale gas reservoir as a single "source-reservoir" system.

[0045] When the thermal evolution of shale formations within the target strata varies significantly in a study area, the use of previously proposed source-reservoir coupling evaluation methods and calculation formulas to assess the source-reservoir coupling relationship of shale in that region can be limited to some extent. Due to the influence of regional tectonic movements and diagenesis, shale samples in some areas of the same study area may have entered the organic matter carbonization stage, exhibiting excessively high thermal maturity (typically Ro greater than 3.5%). Even if the organic carbon content of such samples is not low and a certain level of porosity is developed, a large number of organic pores close due to diagenetic compaction or organic matter decomposition, leading to changes in the source-reservoir configuration and coupling relationship of the shale, and to some extent, reducing the natural gas adsorption capacity. Therefore, the source-reservoir coupling coefficient composed solely of organic carbon content and porosity cannot effectively and intuitively reflect the source-reservoir configuration of excessively mature shale samples. It is necessary to optimize the original formula by introducing a parameter (Ro) characterizing thermal maturity, based on the source-reservoir coupling coefficient calculation methods proposed by previous researchers.

[0046] However, it's difficult to establish a clear correlation between the Ro value and the gas content and reservoir performance of shale; a higher Ro value does not necessarily mean better source-reservoir conditions. When the Ro value is too high or too low, kerogen does not possess good gas generation potential. The Barnett Shale in the United States produces 366 × 10⁻⁶ gas annually. 8 m 3 All the shale gas is of thermogenic origin, with a lower limit of 1.1% Ro (Hiu RJ et al., 2007).

[0047] In China, marine shale often undergoes complex and multi-stage thermal history changes, resulting in a slightly higher lower limit for thermal maturity. In some excessively mature shale formations, abundant natural gas may be present. For example, in some marine shale formations, the thermal maturity (Ro) is as high as 5.5%, and the total organic carbon (TOC) content is as high as 8.02%. Gas anomalies were still observed in the 1723.4–1726.7m interval of this well, with rain-like bubbles observed in the drilling mud, indicating a gas content of 38%, which ignited with a blue flame. This demonstrates that although thermal maturity may be high in some areas, it is inappropriate to generalize and assume that when Ro exceeds a certain fixed value, organic hydrocarbon generation no longer contributes to shale gas production.

[0048] To overcome the shortcomings of existing technologies in source-reservoir evaluation of highly mature shale, this invention introduces a parameter (Ro) characterizing thermal maturity to optimize the existing source-reservoir coefficient formula, providing a source-reservoir coupling evaluation method suitable for highly-over-mature shale. This allows highly-over-mature shale samples to be analyzed together with shale samples of moderate maturity. Specific implementation methods are described in the following examples.

[0049] Example 1:

[0050] This embodiment provides a method for evaluating the source and reservoir of shale, such as... Figure 1 As shown, the source-reservoir evaluation method for shale includes:

[0051] Step 01: Obtain parameter information of the first shale sample. Optionally, the parameter information includes at least one of the following: shale thermal maturity parameters, organic matter abundance parameters, and reservoir characteristic parameters.

[0052] Based on the known geological data of the exploration area, shale from the target stratigraphic level of the core wells in the target exploration area was collected as the research object. Multiple shale samples were selected from the exploration wells used as the research object to obtain parameters for characterizing the thermal maturity of the shale, parameters for characterizing the abundance of organic matter, and parameters for characterizing the reservoir characteristics.

[0053] Step 02: Based on the parameter information of the first shale sample, obtain the original source-reservoir coupling coefficient of all the first shale samples, and obtain the second shale sample based on the source-reservoir coefficient of the first shale sample.

[0054] The formula for obtaining the original source-reservoir coupling coefficient of all the first shale samples based on the parameter information of the first shale sample is as follows:

[0055] The source-reservoir coefficient 'o' refers to the original source-reservoir coupling coefficient. Vitrin reflectance (Ro) is selected as a parameter characterizing shale thermal maturity, total organic carbon content (TOC) is selected as a parameter characterizing organic matter abundance, and porosity is selected as a parameter... Parameters used to characterize reservoir characteristics include: vitrinite reflectance (Ro), used to characterize thermal maturity, obtained through whole-rock reflectance measurements; total organic carbon (TOC), used to characterize organic matter abundance, obtained through organic geochemical experiments; and porosity, used to characterize reservoir characteristics. The results were obtained through reservoir porosity measurement experiments.

[0056] Step 03: Obtain the average vitrinite reflectance of all second shale samples.

[0057] Calculate the source-reservoir coefficient 'o' of all shale samples from all cored wells in the target area, select shale samples with superior source-reservoir coupling conditions as second shale samples, and obtain the average vitrinite reflectance of all second shale samples.

[0058] The step of obtaining the second shale sample based on the source-reservoir coefficient of the first shale sample includes:

[0059] Step 031: Sort the original source-reservoir coupling coefficients of all the shale samples; calculate the source-reservoir coefficient o of all shale samples in the target strata of the study area, and sort all the source-reservoir coefficient o parameters in ascending order.

[0060] Step 032: Based on the ranking results of the original source-reservoir coupling coefficients of all the shale samples, obtain the first cumulative probability curve of the original source-reservoir coupling coefficients of the shale samples.

[0061] Step 033: Obtain the second shale sample based on the first cumulative probability curve.

[0062] Optionally, a cumulative probability curve of the source-reservoir coefficient o is plotted for all shale samples, with the source-reservoir coefficient o divided into ten equal intervals, and the cumulative probability of the source-reservoir coefficient o is determined: on the cumulative probability curve of the source-reservoir coefficient o, the intervals with the cumulative coefficient accounting for 40%, 35%, and 25% of the total are selected, that is, the cumulative probabilities of the intervals [0, 40%), [40%, 75%), and [75%, 100%) represent shale samples with poor, medium, and good source-reservoir conditions, respectively.

[0063] Optionally, shale samples with a cumulative probability of source-reservoir coefficient o in the range of [75%, 100%] are selected as high-quality shale, i.e., second shale.

[0064] Step 04: Based on the average vitrinite reflectance of the second shale sample and the source-reservoir coefficient of the first shale sample, obtain the source-reservoir coefficient of all first shale samples, and evaluate the source-reservoir of the shale based on the source-reservoir coefficient of all first shale samples.

[0065] In collecting and statistically analyzing the average vitrinite reflectance (Ro) In this process, only high-quality shale samples with a cumulative probability of 75%–100% for the source-reservoir coefficient o are selected for arithmetic mean, instead of using the arithmetic mean of the vitrinite reflectance (Ro) of all samples from the target strata in the study area. Only by following the statistical method for vitrinite reflectance data in this invention can this average Ro be obtained. Only then can it represent the thermal maturity level of high-quality shale in the target strata of the target area.

[0066] Calculate and obtain the source-reservoir coefficient i for all shale samples in the target stratigraphic position of all core wells in the target area. Based on the classification of this coefficient, conduct source-reservoir coupling evaluation and analysis of mature shale.

[0067] The formula for obtaining the source-reservoir coefficient of all first shale samples based on the average vitrinite reflectance of the second shale sample and the source-reservoir coefficient of the first shale sample is as follows:

[0068]

[0069] Where i represents the source-reservoir coefficient of all shale samples in the target stratigraphic position of all cored wells in the target area; o represents the original source-reservoir coupling coefficient; and Ro represents the vitrinite reflectivity. This represents the average vitrinite reflectance of the second shale sample.

[0070] The step of evaluating the source and reservoir of shale based on the source-reservoir coefficients of all first shale samples includes:

[0071] Step 041: Sort the source-reservoir coefficients of all the first shale samples in ascending order, calculate the source-reservoir coefficient i of all shale samples in the target stratum of the study area, and sort all the source-reservoir coefficient i parameters in ascending order.

[0072] Step 042: Based on the ranking results of the source-reservoir coefficients of all the first shale samples, make a second cumulative probability curve of the source-reservoir coefficients of all the first shale samples; make a cumulative probability curve of the source-reservoir coefficient i of all shale samples, with the source-reservoir coefficient i divided into ten equal parts as intervals, and determine the cumulative probability of the source-reservoir coefficient i.

[0073] Step 043: Evaluate the source and reservoir of shale based on the second cumulative probability curve. Using ten equal divisions as intervals, select intervals on the cumulative probability curve of source-reservoir coefficient i where the cumulative coefficient accounts for 40%, 35%, and 25% of the total, respectively. That is, the cumulative probabilities of intervals [0, 40%), [40%, 75%), and [75%, 100%) represent shale samples with poor, moderate, and good source-reservoir coupling conditions, respectively.

[0074] Optionally, the interval [0, 40%) represents shale samples with medium source-reservoir conditions, [40%, 75%) represents shale samples with medium source-reservoir conditions, and [75%, 100%] represents shale samples with excellent source-reservoir conditions.

[0075] Example 2:

[0076] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, these descriptions do not constitute a limitation of the present invention and are merely illustrative. The advantages of the present invention will become clearer and easier to understand through this description.

[0077] Core observation and related testing analysis were conducted on the Lower Carboniferous Luzhai Formation in the northern part of the Guizhong Depression. Source-reservoir coupling evaluation was carried out according to the source-reservoir coupling evaluation method based on highly-overmature shale as described in this invention. A total of 256 samples were collected from the marine shale of the Luzhai Formation in the six wells. The thermal maturity of the shale varied greatly, with Ro ranging from 1.75% to 4.08%. Furthermore, TOC ranged from 0.36% to 5.00%, and porosity ranged from 0.50% to 7.8%.

[0078] like Figure 2 As shown, the source-reservoir evaluation method for shale includes:

[0079] Step 1: Based on the known geological data of the northern part of the Guizhong Depression, marine shale from six core wells of the Lower Carboniferous Luzhai Formation was collected as the research object.

[0080] Step 2: Obtain parameters from the shale samples to characterize the thermal maturity of the shale, the abundance of organic matter, and the reservoir characteristics.

[0081] Step 3: Calculate the source-reservoir coefficient o for all shale samples in the target stratigraphic position of all core wells in the target area, select high-quality shale samples with good source-reservoir coupling conditions, and obtain the vitrinite reflectance of all high-quality shale samples. average value.

[0082] Step 4: Calculate and obtain the source-reservoir coefficient i of all shale samples in the target stratigraphic position of all core wells in the target area, classify them according to the coefficient, and carry out source-reservoir coupling evaluation and analysis of mature shale.

[0083] Specifically, in step 2, vitrinite reflectance (Ro) was selected as a parameter characterizing the thermal maturity of shale, with a total of 27 data points; total organic carbon content (TOC) was selected as a parameter characterizing organic matter abundance, with a total of 256 data points; porosity was selected... A total of 256 data points were used as parameters to characterize the storage features.

[0084] refer to Figure 3 As shown, specifically, in step 2, the vitrinite reflectance (Ro), used to characterize thermal maturity, is obtained through whole-rock reflectance measurement experiments; the organic carbon content (TOC), used to characterize organic matter abundance, is obtained through organic geochemical experiments; and the porosity, used to characterize reservoir characteristics... The porosity was obtained through reservoir porosity measurement experiments, including porosity measurement experiments on irregular shale samples.

[0085] Specifically, in step 3, the steps for selecting high-quality shale with good source-reservoir coupling conditions are as follows:

[0086] Step K1: Calculate the source-reservoir coefficient o for all shale samples in the target stratigraphic region of the study area. The calculation formula is: Source-reservoir coefficient Sort all source and storage coefficients in ascending order.

[0087] Step K2: Calculate the cumulative probability curves of the source-reservoir coefficients for all shale samples (see attached). Figure 4 The source-reservoir coefficient o is divided into ten equal intervals, and the cumulative probability of the source-reservoir coefficient o is determined: on the cumulative probability curve of the source-reservoir coefficient o, intervals with a cumulative coefficient accounting for 40%, 35%, and 25% of the total are selected, that is, the cumulative probabilities of the intervals [0, 40%), [40%, 75%), and [75%, 100%) represent shale samples with poor, moderate, and good source-reservoir conditions, respectively. In the embodiment, the source-reservoir coefficient o is distributed in the intervals [0, 2.6), [2.6, 5.3), and [5.3, 21.6], representing shale samples with poor, moderate, and good source-reservoir conditions, respectively.

[0088] Step K3: Select shale samples with a cumulative probability of source-reservoir coefficient o in the range [75%, 100%) as high-quality shale. In this embodiment, 130 samples with a source-reservoir coefficient o distributed in the range [5.3, 21.6] were selected as high-quality shale samples.

[0089] Step K4: Further, calculate the average vitrinite reflectance of all high-quality shale samples, denoted as . In this embodiment, 130 high-quality shale samples contained 12 Ro data points. The arithmetic mean of Ro was calculated to obtain... It is 3.06%.

[0090] Specifically, in step K4, the average reflectance (Ro) of the vitrinite is collected and statistically analyzed. In this process, only high-quality shale samples with a cumulative probability of 75%–100% for the source-reservoir coefficient o are selected for arithmetic mean, instead of using the arithmetic mean of the vitrinite reflectance (Ro) of all samples from the target strata in the study area. Only by following the statistical method for vitrinite reflectance data in this invention can this average Ro be obtained. Only then can it represent the thermal maturity level of high-quality shale in the target strata of the target area.

[0091] In the above technical solution, the method for determining the classification evaluation criteria of the source-storage coefficient i in step 4 is as follows:

[0092] Step N1: Calculate the source-reservoir coefficient i of all shale samples in the target stratigraphic position of the study area. The calculation formula is as follows: All source-reservoir coefficients (i) are sorted in ascending order. In this example, 27 samples of the Luzhai Formation shale for which Ro data were collected were analyzed, and their source-reservoir coefficients (i) were calculated and sorted in ascending order.

[0093] Step N2: Calculate the cumulative probability curves of the source-reservoir coefficient i for all shale samples (see appendix). Figure 5 The source-storage coefficient i is divided into ten equal intervals, and the cumulative probability of the source-storage coefficient i is determined.

[0094] Step N3: On the cumulative probability curve of the source-reservoir coefficient i, select intervals where the cumulative coefficient accounts for 40%, 35%, and 25% of the total, respectively. That is, the cumulative probabilities of the intervals [0, 40%), [40%, 75%), and [75%, 100%) represent shale samples with poor, moderate, and good source-reservoir coupling conditions, respectively. In the embodiment, the source-reservoir coefficient i is distributed in the intervals [0, 5.5), [5.5, 26.5), and [26.5, 56.4], representing shale samples with poor, moderate, and good source-reservoir coupling conditions, respectively.

[0095] Based on the combined verification of argon-ion polishing scanning electron microscopy observations, as well as data from TOC, porosity, and adsorption tests, samples with an Ro value greater than 4.0% have reached the organic matter carbonization stage. Even with high organic matter content (TOC range 3.1%–4.1%), the shale's hydrocarbon generation capacity is depleted, and organic pores and intercrystalline pores of clay minerals are significantly reduced (porosity range 0.68%–2.82%), resulting in a decreased adsorption capacity for natural gas (average total pore volume 0.0092 ml / g, average specific surface area 6.033 m²). 2 The combined effects of these factors ( / g) significantly damage the source and reservoir quality of shale.

[0096] Using the source-reservoir coupling evaluation method based on over-mature shale, none of the sample points with Ro values ​​greater than 4.0% in the Luzhai Formation shale samples in the study area fell into the region of "good source-reservoir coupling conditions".

[0097] Example 3:

[0098] This embodiment provides a source-reservoir evaluation device 100 for shale. For example... Figure 6 As shown, the shale source-reservoir evaluation device includes an acquisition module 10, a processing module 20, and an evaluation module 30. Among them,

[0099] The acquisition module 10 is used to acquire parameter information of the first shale sample and to acquire the average vitrinite reflectance of all second shale samples.

[0100] The processing module 20 is used to obtain the original source-reservoir coupling coefficient of all first shale samples based on the parameter information of the first shale sample, obtain the second shale sample based on the source-reservoir coefficient of the first shale sample, and obtain the source-reservoir coefficient of all first shale samples based on the average vitrinite reflectance of the second shale sample and the source-reservoir coefficient of the first shale sample.

[0101] Evaluation module 30 is used to evaluate the source and reservoir of shale based on the source-reservoir coefficients of all first shale samples.

[0102] The acquisition module 10 is used to acquire parameter information of the first shale sample and send the parameter information of the first shale sample to the processing module 20. The processing module 20 obtains the original source-reservoir coupling coefficient of all the first shale samples based on the parameter information of the first shale sample, and obtains the second shale sample based on the source-reservoir coefficient of the first shale sample. Then, the acquisition module 10 acquires the average vitrinite reflectance of all the second shale samples. The processing module 20 obtains the source-reservoir coefficient of all the first shale samples based on the average vitrinite reflectance of the second shale samples and the source-reservoir coefficient of the first shale samples. Finally, the evaluation module 30 is used to evaluate the source and reservoir of the shale based on the source-reservoir coefficient of all the first shale samples.

[0103] The formula for obtaining the original source-reservoir coupling coefficient of all the first shale samples based on the parameter information of the first shale sample is as follows: o represents the original source-storage coupling coefficient; Ro represents the vitrinite reflectivity. The average reflectance of vitrinite. Source-storage coefficient; TOC is the total organic carbon content; Porosity is a characteristic of storage.

[0104] In addition, the processing module 20 is also used to sort the original source-reservoir coupling coefficients of all the shale samples; to obtain the first cumulative probability curve of the original source-reservoir coupling coefficients of the shale samples based on the sorting results of the original source-reservoir coupling coefficients of all the shale samples; and to obtain the second shale sample based on the first cumulative probability curve.

[0105] The step of obtaining the second shale sample based on the first cumulative probability curve includes: dividing the curve into ten equal parts and selecting intervals on the first cumulative probability curve where the cumulative coefficient accounts for 40%, 35%, and 25% of the total, respectively. The interval [0, 40%) represents shale samples with medium source-reservoir conditions, [40%, 75%) represents shale samples with medium source-reservoir conditions, and [75%, 100%] represents shale samples with good source-reservoir conditions.

[0106] The formula for obtaining the source-reservoir coefficient of all first shale samples based on the average vitrinite reflectance of the second shale sample and the source-reservoir coefficient of the first shale sample is as follows: Where o is the source-storage coefficient; Ro is the vitrinite reflectivity; denoted as the average vitrinite reflectance. Where i represents the source-reservoir coefficient of all shale samples from all cored wells in the target area; o represents the original source-reservoir coupling coefficient; and Ro represents the vitrinite reflectance. This represents the average vitrinite reflectance of the second shale sample.

[0107] The evaluation module 30 is also used to sort the source-reservoir coefficients of all the first shale samples in ascending order; to generate a second cumulative probability curve of the source-reservoir coefficients of all the first shale samples based on the sorting results of the source-reservoir coefficients of all the first shale samples; and to evaluate the source and reservoir of the shale based on the second cumulative probability curve.

[0108] The step of evaluating the source and reservoir of shale based on the second cumulative probability curve includes: selecting intervals on the second cumulative probability curve with cumulative coefficients accounting for 40%, 35%, and 25% of the total, divided into ten equal parts, where the interval [0, 40%) represents shale samples with medium source and reservoir conditions, [40%, 75%) represents shale samples with medium source and reservoir conditions, and [75%, 100%] represents shale samples with excellent source and reservoir conditions.

[0109] Example 4:

[0110] This embodiment provides an electronic device, which may be a mobile phone, computer, or tablet computer, etc., including a memory and a processor. The memory stores a computer program, which, when executed by the processor, implements the shale source-reservoir evaluation method as described in Embodiment 1. It is understood that the electronic device may further include an input / output (I / O) interface and communication components.

[0111] The processor is used to execute all or part of the steps in the shale source-reservoir evaluation method as described in Embodiment 1. The memory is used to store various types of data, which may include, for example, instructions for any application or method in an electronic device, as well as application-related data.

[0112] The processor may be implemented as an Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), controller, microcontroller, microprocessor, or other electronic components, and is used to execute the shale source-reservoir evaluation method in Embodiment 1 above.

[0113] The memory 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 storage, flash memory, magnetic disk, or optical disk.

[0114] The source-reservoir evaluation methods for shale based on the above modules include:

[0115] Step 01: Obtain parameter information of the first shale sample. Optionally, the parameter information includes at least one of the following: shale thermal maturity parameters, organic matter abundance parameters, and reservoir characteristic parameters.

[0116] Based on the known geological data of the exploration area, shale from the target stratigraphic level of the core wells in the target exploration area was collected as the research object. Multiple shale samples were selected from the exploration wells used as the research object to obtain parameters for characterizing the thermal maturity of the shale, parameters for characterizing the abundance of organic matter, and parameters for characterizing the reservoir characteristics.

[0117] Step 02: Based on the parameter information of the first shale sample, obtain the original source-reservoir coupling coefficient of all the first shale samples, and obtain the second shale sample based on the source-reservoir coefficient of the first shale sample.

[0118] The formula for obtaining the original source-reservoir coupling coefficient of all the first shale samples based on the parameter information of the first shale sample is as follows:

[0119] The source-reservoir coefficient 'o' refers to the original source-reservoir coupling coefficient. Vitrin reflectance (Ro) is selected as a parameter characterizing shale thermal maturity, total organic carbon content (TOC) is selected as a parameter characterizing organic matter abundance, and porosity is selected as a parameter... Parameters used to characterize reservoir characteristics include: vitrinite reflectance (Ro), used to characterize thermal maturity, obtained through whole-rock reflectance measurements; total organic carbon (TOC), used to characterize organic matter abundance, obtained through organic geochemical experiments; and porosity, used to characterize reservoir characteristics. The results were obtained through reservoir porosity measurement experiments.

[0120] Step 03: Obtain the average vitrinite reflectance of all second shale samples.

[0121] Calculate the source-reservoir coefficient 'o' of all shale samples from all core wells in the target area, select high-quality shale samples with good source-reservoir coupling conditions, and obtain the average vitrinite reflectance of all high-quality shale samples.

[0122] The step of obtaining the second shale sample based on the source-reservoir coefficient of the first shale sample includes:

[0123] Step 031: Sort the original source-reservoir coupling coefficients of all the shale samples; calculate the source-reservoir coefficient o of all shale samples in the target strata of the study area, and sort all the source-reservoir coefficient o parameters in ascending order.

[0124] Step 032: Based on the ranking results of the original source-reservoir coupling coefficients of all the shale samples, obtain the first cumulative probability curve of the original source-reservoir coupling coefficients of the shale samples.

[0125] Step 033: Obtain the second shale sample based on the first cumulative probability curve.

[0126] Optionally, a cumulative probability curve of the source-reservoir coefficient o is plotted for all shale samples, with the source-reservoir coefficient o divided into ten equal intervals, and the cumulative probability of the source-reservoir coefficient o is determined: on the cumulative probability curve of the source-reservoir coefficient o, the intervals with the cumulative coefficient accounting for 40%, 35%, and 25% of the total are selected, that is, the cumulative probabilities of the intervals [0, 40%), [40%, 75%), and [75%, 100%) represent shale samples with poor, medium, and good source-reservoir conditions, respectively.

[0127] Optionally, shale samples with a cumulative probability of source-reservoir coefficient o in the range of [75%, 100%] are selected as high-quality shale.

[0128] Step 04: Based on the average vitrinite reflectance of the second shale sample and the source-reservoir coefficient of the first shale sample, obtain the source-reservoir coefficient of all first shale samples, and evaluate the source-reservoir of the shale based on the source-reservoir coefficient of all first shale samples.

[0129] In collecting and statistically analyzing the average vitrinite reflectance (Ro) In this process, only high-quality shale samples with a cumulative probability of 75%–100% for the source-reservoir coefficient o are selected for arithmetic mean, instead of using the arithmetic mean of the vitrinite reflectance (Ro) of all samples from the target strata in the study area. Only by following the statistical method for vitrinite reflectance data in this invention can this average Ro be obtained. Only then can it represent the thermal maturity level of high-quality shale in the target strata of the target area.

[0130] Calculate and obtain the source-reservoir coefficient i for all shale samples in the target stratigraphic position of all core wells in the target area. Based on the classification of this coefficient, conduct source-reservoir coupling evaluation and analysis of mature shale.

[0131] The formula for obtaining the source-reservoir coefficient of all first shale samples based on the average vitrinite reflectance of the second shale sample and the source-reservoir coefficient of the first shale sample is as follows:

[0132]

[0133] Where i represents the source-reservoir coefficient of all shale samples in the target stratigraphic position of all cored wells in the target area; o represents the original source-reservoir coupling coefficient; and Ro represents the vitrinite reflectivity. The average vitrinite reflectance of the second shale sample; TOC represents the total organic carbon content. Porosity is a characteristic of storage.

[0134] The step of evaluating the source and reservoir of shale based on the source-reservoir coefficients of all first shale samples includes:

[0135] Step 041: Sort the source-reservoir coefficients of all the first shale samples in ascending order, calculate the source-reservoir coefficient i of all shale samples in the target stratum of the study area, and sort all the source-reservoir coefficient i parameters in ascending order.

[0136] Step 042: Based on the ranking results of the source-reservoir coefficients of all the first shale samples, make a second cumulative probability curve of the source-reservoir coefficients of all the first shale samples; make a cumulative probability curve of the source-reservoir coefficient i of all shale samples, with the source-reservoir coefficient i divided into ten equal parts as intervals, and determine the cumulative probability of the source-reservoir coefficient i.

[0137] Step 043: Evaluate the source and reservoir of shale based on the second cumulative probability curve. Using ten equal divisions as intervals, select intervals on the cumulative probability curve of source-reservoir coefficient i where the cumulative coefficient accounts for 40%, 35%, and 25% of the total, respectively. That is, the cumulative probabilities of intervals [0, 40%), [40%, 75%), and [75%, 100%) represent shale samples with poor, moderate, and good source-reservoir coupling conditions, respectively.

[0138] Optionally, the interval [0, 40%) represents shale samples with medium source-reservoir conditions, [40%, 75%) represents shale samples with medium source-reservoir conditions, and [75%, 100%] represents shale samples with excellent source-reservoir conditions.

[0139] Example 5:

[0140] This embodiment also provides a computer-readable storage medium. The functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. If the functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium.

[0141] Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0142] The aforementioned storage media include: flash memory, hard disks, multimedia cards, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disks, optical discs, servers, APP application stores, and various other media capable of storing program verification codes, on which computer programs are stored. When the computer program is executed by a processor, it can implement the following method steps:

[0143] Step 01: Obtain parameter information of the first shale sample. Optionally, the parameter information includes at least one of the following: shale thermal maturity parameters, organic matter abundance parameters, and reservoir characteristic parameters.

[0144] Based on the known geological data of the exploration area, shale from the target stratigraphic level of the core wells in the target exploration area was collected as the research object. Multiple shale samples were selected from the exploration wells used as the research object to obtain parameters for characterizing the thermal maturity of the shale, parameters for characterizing the abundance of organic matter, and parameters for characterizing the reservoir characteristics.

[0145] Step 02: Based on the parameter information of the first shale sample, obtain the original source-reservoir coupling coefficient of all the first shale samples, and obtain the second shale sample based on the source-reservoir coefficient of the first shale sample.

[0146] The formula for obtaining the original source-reservoir coupling coefficient of all the first shale samples based on the parameter information of the first shale sample is as follows:

[0147] The source-reservoir coefficient 'o' refers to the original source-reservoir coupling coefficient. Vitrin reflectance (Ro) is selected as a parameter characterizing shale thermal maturity, total organic carbon content (TOC) is selected as a parameter characterizing organic matter abundance, and porosity is selected as a parameter... Parameters used to characterize reservoir characteristics include: vitrinite reflectance (Ro), used to characterize thermal maturity, obtained through whole-rock reflectance measurements; total organic carbon (TOC), used to characterize organic matter abundance, obtained through organic geochemical experiments; and porosity, used to characterize reservoir characteristics. The results were obtained through reservoir porosity measurement experiments.

[0148] Step 03: Obtain the average vitrinite reflectance of all second shale samples.

[0149] Calculate the source-reservoir coefficient 'o' of all shale samples from all core wells in the target area, select high-quality shale samples with good source-reservoir coupling conditions, and obtain the average vitrinite reflectance of all high-quality shale samples.

[0150]

[0151] The step of obtaining the second shale sample based on the source-reservoir coefficient of the first shale sample includes:

[0152] Step 031: Sort the original source-reservoir coupling coefficients of all the shale samples; calculate the source-reservoir coefficient o of all shale samples in the target strata of the study area, and sort all the source-reservoir coefficient o parameters in ascending order.

[0153] Step 032: Based on the ranking results of the original source-reservoir coupling coefficients of all the shale samples, obtain the first cumulative probability curve of the original source-reservoir coupling coefficients of the shale samples.

[0154] Step 033: Obtain the second shale sample based on the first cumulative probability curve.

[0155] Optionally, a cumulative probability curve of the source-reservoir coefficient o is plotted for all shale samples, with the source-reservoir coefficient o divided into ten equal intervals, and the cumulative probability of the source-reservoir coefficient o is determined: on the cumulative probability curve of the source-reservoir coefficient o, the intervals with the cumulative coefficient accounting for 40%, 35%, and 25% of the total are selected, that is, the cumulative probabilities of the intervals [0, 40%), [40%, 75%), and [75%, 100%) represent shale samples with poor, medium, and good source-reservoir conditions, respectively.

[0156] Optionally, shale samples with a cumulative probability of source-reservoir coefficient o in the range of [75%, 100%] are selected as high-quality shale.

[0157] Step 04: Based on the average vitrinite reflectance of the second shale sample and the source-reservoir coefficient of the first shale sample, obtain the source-reservoir coefficient of all first shale samples, and evaluate the source-reservoir of the shale based on the source-reservoir coefficient of all first shale samples.

[0158] In collecting and statistically analyzing the average vitrinite reflectance (Ro) In this process, only high-quality shale samples with a cumulative probability of 75%–100% for the source-reservoir coefficient o are selected for arithmetic mean, instead of using the arithmetic mean of the vitrinite reflectance (Ro) of all samples from the target strata in the study area. Only by following the statistical method for vitrinite reflectance data in this invention can this average Ro be obtained. Only then can it represent the thermal maturity level of high-quality shale in the target strata of the target area.

[0159] Calculate and obtain the source-reservoir coefficient i for all shale samples in the target stratigraphic position of all core wells in the target area. Based on the classification of this coefficient, conduct source-reservoir coupling evaluation and analysis of mature shale.

[0160] The formula for obtaining the source-reservoir coefficient of all first shale samples based on the average vitrinite reflectance of the second shale sample and the source-reservoir coefficient of the first shale sample is as follows:

[0161]

[0162] Where i represents the source-reservoir coefficient of all shale samples in the target stratigraphic position of all cored wells in the target area; o represents the original source-reservoir coupling coefficient; and Ro represents the vitrinite reflectivity. The average reflectance of vitrinite is given; TOC represents the total organic carbon content. Porosity is a characteristic of storage.

[0163] The step of evaluating the source and reservoir of shale based on the source-reservoir coefficients of all first shale samples includes:

[0164] Step 041: Sort the source-reservoir coefficients of all the first shale samples in ascending order, calculate the source-reservoir coefficient i of all shale samples in the target stratum of the study area, and sort all the source-reservoir coefficient i parameters in ascending order.

[0165] Step 042: Based on the ranking results of the source-reservoir coefficients of all the first shale samples, make a second cumulative probability curve of the source-reservoir coefficients of all the first shale samples; make a cumulative probability curve of the source-reservoir coefficient i of all shale samples, with the source-reservoir coefficient i divided into ten equal parts as intervals, and determine the cumulative probability of the source-reservoir coefficient i.

[0166] Step 043: Evaluate the source and reservoir of shale based on the second cumulative probability curve. Using ten equal divisions as intervals, select intervals on the cumulative probability curve of source-reservoir coefficient i where the cumulative coefficient accounts for 40%, 35%, and 25% of the total, respectively. That is, the cumulative probabilities of intervals [0, 40%), [40%, 75%), and [75%, 100%) represent shale samples with poor, moderate, and good source-reservoir coupling conditions, respectively.

[0167] Optionally, the interval [0, 40%) represents shale samples with medium source-reservoir conditions, [40%, 75%) represents shale samples with medium source-reservoir conditions, and [75%, 100%] represents shale samples with excellent source-reservoir conditions.

[0168] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention. It will be clearly understood by those skilled in the art that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0169] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0170] The basic principles of this application have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this application are merely examples and not limitations, and should not be considered as essential features of each embodiment of this application. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the application to the necessity of employing the aforementioned specific details for implementation.

[0171] The block diagrams of devices, apparatuses, devices, and systems involved in this application are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner.

[0172] It should also be noted that in the apparatus, equipment, and methods of this application, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered as equivalent solutions of this application.

[0173] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of this application. Therefore, this application is not intended to be limited to the aspects shown herein, but rather to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0174] In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. All directional indications (such as up, down, left, right, front, back, top, bottom, etc.) in the embodiments of this application are only used to explain the relative positional relationships and movement of the components in a specific posture (as shown in the figures). If the specific posture changes, the directional indication will also change accordingly. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices.

[0175] Furthermore, the reference to "embodiment" herein means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0176] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims. The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0177] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method of source-reservoir evaluation of shale, characterized by, The method comprises the following steps: obtaining parameter information of first shale samples; obtaining original source-reservoir coupling coefficients of all the first shale samples based on the parameter information of the first shale samples, and obtaining second shale samples based on the original source-reservoir coupling coefficients of the first shale samples; obtaining average vitrinite reflectance of all the second shale samples; obtaining source-reservoir coefficients of all the first shale samples based on the average vitrinite reflectance of the second shale samples and the original source-reservoir coupling coefficients of the first shale samples, and evaluating the shale based on the source-reservoir coefficients of all the first shale samples; the formula for obtaining the original source-reservoir coupling coefficients of all the first shale samples based on the parameter information of the first shale samples is o = TOC x φ x 10000; wherein, o is the original source-reservoir coupling coefficient; TOC is the total organic carbon content; and φ is the porosity of the reservoir characteristics; the formula for obtaining the source-reservoir coefficients of all the first shale samples based on the average vitrinite reflectance of the second shale samples and the original source-reservoir coupling coefficients of the first shale samples is s = o x R o; ； Wherein, i is the source-reservoir coefficient of all shale samples of target layer position of all coring wells in target area; o is the original source-reservoir coupling coefficient; Ro is the vitrinite reflectance; is the average value of vitrinite reflectance.

2. The method of source-reservoir evaluation of shales according to claim 1, wherein, the parameter information comprises at least one of shale thermal maturity parameters, organic matter abundance parameters and reservoir characteristics parameters.

3. The method of source-reservoir evaluation of shales of claim 1, wherein, the step of obtaining the second shale samples based on the source-reservoir coefficients of the first shale samples comprises: sorting the original source-reservoir coupling coefficients of all the shale samples; obtaining a first cumulative probability curve of the original source-reservoir coupling coefficients of the shale samples based on the sorting results of the original source-reservoir coupling coefficients of all the shale samples; obtaining the second shale samples based on the first cumulative probability curve.

4. The method of source-reservoir evaluation of shales of claim 3, wherein, the step of obtaining the second shale samples based on the first cumulative probability curve comprises: selecting intervals with cumulative coefficients accounting for 40%, 35% and 25% of the total on the first cumulative probability curve as intervals, wherein the interval [0, 40%) represents shale samples with poor source-reservoir conditions, the interval [40%, 75%) represents shale samples with medium source-reservoir conditions, and the interval [75%, 100%] represents shale samples with good source-reservoir conditions; and the second shale samples are the shale samples with good source-reservoir conditions.

5. The method of claim 1, wherein, the step of evaluating the shale based on the source-reservoir coefficients of all the first shale samples comprises: sorting the source-reservoir coefficients of all the first shale samples in ascending order; obtaining a second cumulative probability curve of the source-reservoir coefficients of all the first shale samples based on the sorting results of the source-reservoir coefficients of all the first shale samples; evaluating the shale based on the second cumulative probability curve.

6. The method of source-reservoir evaluation of shales of claim 5, wherein, the step of evaluating the shale based on the second cumulative probability curve comprises: selecting intervals with cumulative coefficients accounting for 40%, 35% and 25% of the total on the second cumulative probability curve as intervals, wherein the interval [0, 40%) represents shale samples with poor source-reservoir conditions, the interval [40%, 75%) represents shale samples with medium source-reservoir conditions, and the interval [75%, 100%] represents shale samples with good source-reservoir conditions.

7. A source-reservoir evaluation apparatus for shale, characterized by, The method comprises the following steps: an obtaining module, configured to obtain parameter information of first shale samples; an obtaining module, configured to obtain average vitrinite reflectance of all the second shale samples; The processing module is configured to obtain original source-reservoir coupling coefficients of all the first shale samples based on the parameter information of the first shale samples, obtain a second shale sample based on the original source-reservoir coupling coefficients of the first shale samples, and obtain source-reservoir coefficients of all the first shale samples based on the average vitrinite reflectance of the second shale sample and the original source-reservoir coupling coefficients of the first shale samples. The evaluation module is configured to evaluate the source-reservoir of the shale based on the source-reservoir coefficients of all the first shale samples. The formula for obtaining the original source-reservoir coupling coefficients of all the first shale samples based on the parameter information of the first shale samples is: o = TOC x φ x 10000, where o is the original source-reservoir coupling coefficient, TOC is the total organic carbon content, and φ is the porosity of the reservoir characteristics. The formula for obtaining the source-reservoir coefficients of all the first shale samples based on the average vitrinite reflectance of the second shale sample and the original source-reservoir coupling coefficients of the first shale samples is: ； Wherein, i is the source-reservoir coefficient of all shale samples of target layer position of all coring wells in target area; o is the original source-reservoir coupling coefficient; Ro is the vitrinite reflectance; is the average value of vitrinite reflectance.

8. An electronic device, comprising: The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the source-reservoir evaluation method of the shale.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the source-reservoir evaluation method of the shale.

Images