Method for processing contribution rate of source rock of strong heterogeneous shale layer, electronic equipment, storage medium and program product

Abstract

According to the source rock contribution rate processing method for the strong heterogeneous shale bed, the electronic equipment, the storage medium and the program product provided by the embodiment of the invention, the micro-migration hydrocarbon amount of the rock core sample is obtained by quantitatively calculating the original hydrogen index and the current hydrocarbon generation potential value of the rock core sample; therefore, accurate quantitative evaluation on the hydrocarbon discharge amount of the rock core sample is realized. Furthermore, on the basis of the high-precision core sample micro-migration hydrocarbon amount, a discharged hydrocarbon sample is selected, and a shale layer is averagely divided, so that the heterogeneity of the shale is eliminated, the average discharged hydrocarbon amount and the total contribution value of each layer of the shale are accurately calculated, and the relative contribution rate of each layer of the shale is accurately obtained.

Description

Technical Field

[0001] The present application relates to the field of geological exploration, and in particular to a method for processing the hydrocarbon source rock contribution rate of a highly heterogeneous shale layer, an electronic device, a storage medium, and a program product. Background Art

[0002] Highly heterogeneous mud shales, as important source rocks for unconventional oil and gas, form the material basis for the occurrence of hydrocarbon resources such as shale gas and shale oil. Mud shales have unique microstructures and geochemical characteristics, with small pores, poor connectivity, and complex and diverse organic matter types and occurrence states, resulting in strong heterogeneity.

[0003] At present, biomarkers are usually used in existing technologies to determine the relative contribution rate of source rocks to hydrocarbon supply. First, it is necessary to systematically collect source rocks and crude oil samples from different layers and lithologies, and then process them through crushing, organic solvent extraction and group component separation; then, common biomarkers are analyzed with the help of gas chromatography and gas chromatography-mass spectrometry to obtain their distribution characteristics and structural information; finally, the similarity between crude oil and source rocks is intuitively found through fingerprint comparison, and a mixing model is constructed based on the mass balance principle. After parameter optimization, the relative contribution ratio of each source rock to crude oil is calculated.

[0004] However, the biomarkers in existing technologies are very numerous, complex, and complicated to operate. When it comes to highly heterogeneous shale layers with complex and diverse organic matter types and occurrence states, quantitative analysis errors are large and the accuracy and precision are low. Summary of the Invention

[0005] The embodiments of the present application provide a method for processing the hydrocarbon source rock contribution rate of a highly heterogeneous mud shale layer, an electronic device, a storage medium, and a program product, so as to accurately obtain the relative contribution rate of each mud shale layer.

[0006] In a first aspect, an embodiment of the present application provides a method for obtaining the relative contribution rate of each layer of shale, comprising:

[0007] Obtaining a first preset number of core samples, wherein the core samples are derived from any target shale block;

[0008] Calculate the original hydrogen index and present hydrocarbon generation potential of core samples;

[0009] The difference between the original hydrogen index and the present hydrocarbon generation potential is calculated to obtain the micro-migrated hydrocarbon volume of the core sample;

[0010] Selecting core samples having a micro-migrated hydrocarbon amount greater than a preset threshold value from the first preset number of core samples to obtain a second preset number of expelled hydrocarbon samples;

[0011] Divide the target shale block into N shale layers on average, where N is an integer greater than 1;

[0012] Based on the micro-migrated hydrocarbon amount of the discharged hydrocarbon samples, the average discharged hydrocarbon amount of the discharged hydrocarbon samples corresponding to each shale layer is determined;

[0013] The sum of the average hydrocarbon discharge of all shale layers was calculated to obtain the total contribution value;

[0014] The ratio of the average expelled hydrocarbon amount of the expelled hydrocarbon sample of each shale layer to the total contribution value is calculated to obtain the relative contribution rate of each shale layer.

[0015] In one possible embodiment, the total organic carbon content, pyrolysis hydrocarbon content, and maximum pyrolysis peak temperature of the core sample are obtained;

[0016] Determine the hydrogen index of the core sample based on the total organic carbon content and the amount of pyrolytic hydrocarbons;

[0017] The hydrocarbon conversion rate of the core sample was determined based on the hydrogen index and the highest pyrolysis peak temperature;

[0018] The original hydrogen index of the core sample was determined based on the hydrogen index and hydrocarbon conversion rate.

[0019] In one possible embodiment, the kerogen type of the core sample is determined based on the hydrogen index and the highest pyrolysis peak temperature;

[0020] Based on the kerogen type of the core sample, an evolution model of the corresponding kerogen type is established;

[0021] The hydrocarbon conversion rate of the core samples was determined based on the evolution model of the corresponding kerogen type.

[0022] In one possible embodiment, the light hydrocarbon loss rate and the amount of pyrolysis-soluble hydrocarbons of the core sample are obtained;

[0023] The present hydrocarbon generation potential of the core samples was determined based on the light hydrocarbon loss rate and the amount of pyrolysis-soluble hydrocarbons.

[0024] In one possible implementation, core samples having a micro-migration hydrocarbon amount less than a preset threshold are selected from the first preset number of core samples to obtain a third preset number of input hydrocarbon samples;

[0025] Based on the discharged hydrocarbon sample and the input hydrocarbon sample corresponding to the shale layer, it is determined that the shale layer is at least one of a hydrocarbon reservoir layer or a hydrocarbon supply layer.

[0026] In one possible implementation, the total migration amount of the shale layer is calculated based on the micro-migration amount of the discharged hydrocarbon sample and the micro-migration amount of the input hydrocarbon sample to which the shale layer belongs;

[0027] If the total amount of migrated hydrocarbons in the shale layer is greater than a preset threshold, the shale layer is determined to be a hydrocarbon-supplying layer;

[0028] If the total amount of migrated hydrocarbons in the shale layer is less than a preset threshold, the shale layer is determined to be a hydrocarbon reservoir.

[0029] In a second aspect, an embodiment of the present application provides a device for processing the hydrocarbon source rock contribution rate of a highly heterogeneous shale layer, comprising:

[0030] an acquisition module, configured to acquire a first preset number of core samples, wherein the core samples are derived from any target shale block;

[0031] A processing module for calculating the original hydrogen index and present-day hydrocarbon generation potential of core samples;

[0032] The processing module is also used to calculate the difference between the original hydrogen index and the present hydrocarbon generation potential value to obtain the micro-migrated hydrocarbon volume of the core sample;

[0033] a selection module for selecting core samples having a micro-migrated hydrocarbon amount greater than a preset threshold value from a first preset number of core samples to obtain a second preset number of discharged hydrocarbon samples;

[0034] The selection module is further used to divide the target shale block into N shale layers on average, where N is an integer greater than 1;

[0035] a determination module for determining an average discharged hydrocarbon amount of the discharged hydrocarbon samples corresponding to each shale layer based on the micro-migrated hydrocarbon amount of the discharged hydrocarbon samples;

[0036] The processing module is also used to calculate the sum of the average expelled hydrocarbons of all shale layers to obtain the total contribution value;

[0037] The processing module is further used to calculate the ratio of the average expelled hydrocarbon amount of the expelled hydrocarbon samples of each shale layer to the total contribution value, so as to obtain the relative contribution rate of each shale layer.

[0038] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a memory, a processor;

[0039] Memory stores computer-executable instructions;

[0040] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0041] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementation methods of the first aspect.

[0042] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0043] The methods, electronic devices, storage media, and program products provided in the embodiments of the present application for processing the source rock contribution rate of highly heterogeneous shale layers quantitatively calculate the original hydrogen index and current hydrocarbon generation potential of core samples to obtain the micro-migrated hydrocarbon volume of the core samples, thereby accurately quantitatively evaluating the expelled hydrocarbon volume of the core samples. Furthermore, based on the highly accurate micro-migrated hydrocarbon volume of the core samples, the expelled hydrocarbon samples are selected and the shale layers are evenly divided to eliminate the heterogeneity of the shale. The average expelled hydrocarbon volume and total contribution value of each shale layer are then accurately calculated, thereby accurately obtaining the relative contribution rate of each shale layer. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0045] Figure 1a Schematic diagram 1 of a process for processing the source rock contribution rate of a highly heterogeneous shale layer provided in an embodiment of the present application;

[0046] Figure 1b A distribution diagram of the discharged hydrocarbon sample provided in the embodiment of the present application;

[0047] Figure 2 Schematic diagram of the process of processing the source rock contribution rate of the highly heterogeneous shale layer provided in the embodiment of the present application Figure 2 ;

[0048] Figure 3 A light hydrocarbon correction chart and a light hydrocarbon loss rate diagram provided in the embodiments of this application;

[0049] Figure 4 A schematic diagram of the structure of a device for processing the source rock contribution rate of a strongly heterogeneous shale layer provided in an embodiment of the present application;

[0050] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0051] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0052] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0053] As global demand for energy sources such as oil and natural gas continues to grow, oil and gas exploration and development efforts are deepening. Accurately determining the relative contribution of source rocks to hydrocarbon supply helps clarify the source of hydrocarbons in oil and gas reservoirs, guiding exploration personnel to more targeted oil and gas resource searches, improving exploration success rates, and reducing exploration costs.

[0054] Highly heterogeneous mud shales, as important source rocks for unconventional oil and gas, form the material basis for the occurrence of hydrocarbon resources such as shale gas and shale oil. Mud shales have unique microstructures and geochemical characteristics, characterized by small pores, poor connectivity, and complex and diverse organic matter types and occurrence states.

[0055] At present, biomarkers are usually used in existing technologies to determine the relative contribution rate of source rocks to hydrocarbon supply. First, it is necessary to systematically collect source rocks and crude oil samples from different layers and lithologies, and then process them through crushing, organic solvent extraction and group component separation; then, common biomarkers are analyzed with the help of gas chromatography and gas chromatography-mass spectrometry to obtain their distribution characteristics and structural information; finally, the similarity between crude oil and source rocks is intuitively found through fingerprint comparison, and a mixing model is constructed based on the mass balance principle. After parameter optimization, the relative contribution ratio of each source rock to crude oil is calculated.

[0056] However, the biomarkers in existing technologies are very numerous, complex, and complicated to operate. When it comes to highly heterogeneous shale layers with complex and diverse organic matter types and occurrence states, quantitative analysis errors are large and the accuracy and precision are low.

[0057] To address these technical issues, the inventors proposed the following technical concept: Because highly heterogeneous shale layers contain complex and diverse organic matter types, they proposed using precise quantitative analysis techniques to conduct in-depth analysis of core samples obtained from these layers. This process focused on accurately extracting data related to hydrocarbons in the core samples. Using this precise data, they constructed a scientifically sound computational model, ultimately achieving precise calculation of the relative contribution of the shale layer.

[0058] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0059] Figure 1a A flow chart of a method for processing the source rock contribution rate of a highly heterogeneous shale layer provided in an embodiment of the present application is shown in FIG1 . The method includes:

[0060] S101. Obtain a first preset number of core samples, where the core samples are from any target shale block.

[0061] For example, based on the research objectives and resource requirements, the Paleogene Shahejie Formation in the Dongpu Depression of the Bohai Bay Basin was selected as the target shale block. Within this target shale block, referring to previous geological exploration data, areas with different geological characteristics, such as changes in formation thickness and areas with significant lithologic differences, were marked as potential locations for core sample collection. Core drilling operations were carried out at the planned sampling points to obtain core samples, which were then numbered, resulting in 118 core samples.

[0062] S102. Calculate the original hydrogen index and current hydrocarbon generation potential of the core sample.

[0063] Specifically, the core samples are crushed and ground, and the original hydrogen index and current hydrocarbon generation potential of the core samples are calculated using a pyrolysis instrument.

[0064] S103. Calculate the difference between the original hydrogen index and the current hydrocarbon generation potential value to obtain the micro-migrated hydrocarbon volume of the core sample.

[0065] Specifically, the micro-migration hydrocarbon volume of the core sample is expressed as follows:

[0066] ΔQ = HI O - I HGP (1)

[0067] Where ΔQ is the amount of micro-migrated hydrocarbons in the core sample; HI O is the original hydrogen index, in mg / g; I HGP It is the current hydrocarbon generation potential value, and the unit is mg / g.

[0068] In a possible embodiment, the unit of the micro-migrated hydrocarbon amount is mg / g per unit TOC. In order to more accurately evaluate the relative contribution rate, the micro-migrated hydrocarbon amount needs to be multiplied by TOC.

[0069] S104: Select core samples with micro-migrated hydrocarbon amounts greater than a preset threshold from the first preset number of core samples to obtain a second preset number of expelled hydrocarbon samples.

[0070] For example, the preset threshold is 0, and the core samples with micro-migration hydrocarbon content greater than 0 are selected as expelled hydrocarbon samples. The micro-migration hydrocarbon content of 118 core samples of the Paleogene Shahejie Formation in the Dongpu Depression of the Bohai Bay Basin ranges from -480.19 to 170.95 mg / g, mainly distributed in the range of -107.82 to 170.95 mg / g, with an average value of 3.56 mg / g. Among them, 66 expelled hydrocarbon samples were selected, and the micro-migration hydrocarbon content ranged from 0.01 to 170.95 mg / g, with an average value of 69.42 mg / g. Figure 1b As shown, Figure 1b This is a distribution diagram of the discharged hydrocarbon samples provided in an embodiment of the present application. The discharged hydrocarbon samples are distributed in the depth range of 3870m to 3970m in the target shale block.

[0071] S105. Divide the target shale block into N shale layers on average, where N is an integer greater than 1.

[0072] For example, Figure 1b As shown in the figure, the interval where the core samples in the target shale block are mainly distributed, that is, the depth interval from 3870m to 3970m, is evenly divided into 10 shale layers at intervals of 10m.

[0073] S106 : Based on the micro-migrated hydrocarbon amount of the discharged hydrocarbon sample, determine the average discharged hydrocarbon amount of the discharged hydrocarbon sample corresponding to each shale layer.

[0074] Specifically, the sum of the micro-migrated hydrocarbon amounts of the discharged hydrocarbon samples corresponding to each shale layer is calculated and divided by the number of the corresponding discharged hydrocarbon samples to determine the average discharged hydrocarbon amount of the discharged hydrocarbon samples corresponding to each shale layer.

[0075] S107. Calculate the sum of the average hydrocarbon discharge amounts of all shale layers to obtain a total contribution value.

[0076] S108 , calculating the ratio of the average expelled hydrocarbon amount of the expelled hydrocarbon samples of each shale layer to the total contribution value, so as to obtain the relative contribution rate of each shale layer.

[0077] For example, taking 118 core samples from the Paleogene Shahejie Formation in the Dongpu Sag of the Bohai Bay Basin as an example, the total contribution value is 554 mg / g. Seven hydrocarbon-producing samples were found at depths of 3870-3880 m, with an average hydrocarbon yield of 103.7514286 mg / g, for a relative contribution of 18.73%. Ten hydrocarbon-producing samples were found at depths of 3880-3890 m, with an average hydrocarbon yield of 70.672 mg / g, for a relative contribution of 12.76%. Five hydrocarbon-producing samples were found at depths of 3890-3900 m, with an average hydrocarbon yield of 15.648 mg / g, for a relative contribution of 2.82%. Five hydrocarbon-producing samples were found at depths of 3900-3910 m, with an average hydrocarbon yield of 70.672 mg / g, for a relative contribution of 12.76%. There were five hydrocarbon samples at depths of 3890-3900 m, with an average hydrocarbon yield of 35.546 mg / g, a relative contribution of 6.42%. There was one hydrocarbon sample at depths of 3910-3920 m, with an average hydrocarbon yield of 13.63 mg / g, a relative contribution of 2.46%. There were three hydrocarbon samples at depths of 3920-3930 m, with an average hydrocarbon yield of 50.8166667 mg / g, a relative contribution of 9.17%. There were eight hydrocarbon samples at depths of 3930-3940 m, with an average hydrocarbon yield of 67.0675 mg / g, a relative contribution of 12.10%. There were seven hydrocarbon samples at depths of 3940-3950 m, with an average hydrocarbon yield of 89.47714286 mg / g, a relative contribution of 16.15%. There were 9 hydrocarbon samples discharged from the depth of 3950-3960m, with an average hydrocarbon discharge of 20.62mg / g, a relative contribution rate of 3.72%. There were 8 hydrocarbon samples discharged from the depth of 3960-3970m, with an average hydrocarbon discharge of 86.83375mg / g, a relative contribution rate of 15.67%.

[0078] The method for processing the source rock contribution rate of highly heterogeneous shale layers provided in the present embodiment of the application quantitatively calculates the original hydrogen index and current hydrocarbon generation potential of core samples, thereby obtaining the micro-migrated hydrocarbon volume of the core samples, thereby accurately quantitatively evaluating the expelled hydrocarbon volume of the core samples. Furthermore, based on the highly accurate micro-migrated hydrocarbon volume of the core samples, the expelled hydrocarbon samples are selected and the shale layers are evenly divided to eliminate the heterogeneity of the shale. The average expelled hydrocarbon volume and total contribution value of each shale layer are then accurately calculated, thereby accurately obtaining the relative contribution rate of each shale layer.

[0079] Figure 2 Schematic diagram of the process of processing the source rock contribution rate of the highly heterogeneous shale layer provided in the embodiment of the present application Figure 2 ,like Figure 2 As shown, the method includes:

[0080] S201. Obtain a first preset number of core samples, where the core samples are from any target shale block.

[0081] It should be noted that the specific implementation of S201 can refer to the specific implementation of S101, and will not be described in detail here.

[0082] S202. Calculate the original hydrogen index and current hydrocarbon generation potential value of the core sample.

[0083] In one possible embodiment, calculating the original hydrogen index of a core sample includes obtaining the total organic carbon content, pyrolysis hydrocarbon yield, and maximum pyrolysis peak temperature of the core sample. Determining the hydrogen index of the core sample based on the total organic carbon content and pyrolysis hydrocarbon yield. Determining the hydrocarbon generation conversion rate of the core sample based on the hydrogen index and the maximum pyrolysis peak temperature. Determining the original hydrogen index of the core sample based on the hydrogen index and the hydrocarbon generation conversion rate.

[0084] Specifically, the core sample is pyrolyzed to obtain the pyrolysis data of the core sample, and the pyrolysis data are statistically sorted and averaged to obtain the total organic carbon content, pyrolysis hydrocarbon content and maximum pyrolysis peak temperature of the core sample. Based on the total organic carbon content and pyrolysis hydrocarbon content, the hydrogen index of the core sample is determined as shown in the following formula (2), including:

[0085] HI=S2*100 / TOC (2)

[0086] Wherein, HI is the hydrogen index of the core sample; S2 is the amount of pyrolysis hydrocarbons in the core sample; TOC is the total organic carbon content of the core sample.

[0087] Furthermore, based on the hydrogen index and hydrocarbon conversion rate, the original hydrogen index of the core sample is determined as shown in the following formula (3), including:

[0088] HI O =HI / (1-TR) (3)

[0089] Among them, HI O is the original hydrogen index of the core sample; HI is the hydrogen index of the core sample; TR is the hydrocarbon generation conversion rate of the core sample.

[0090] It is possible to determine the hydrocarbon generation conversion rate of the core sample based on the hydrogen index and the maximum pyrolysis peak temperature, including: determining the kerogen type of the core sample based on the hydrogen index and the maximum pyrolysis peak temperature; establishing an evolution model corresponding to the kerogen type based on the kerogen type of the core sample; and determining the hydrocarbon generation conversion rate of the core sample based on the evolution model corresponding to the kerogen type.

[0091] Specifically, based on the hydrogen index and the highest pyrolysis peak temperature, a hydrogen index-highest pyrolysis peak temperature scatter plot is established, and based on the hydrogen index-highest pyrolysis peak temperature scatter plot, the kerogen type of the core sample is determined to be any one of type I kerogen, type II1 kerogen, type II2 kerogen and type III kerogen.

[0092] Based on the kerogen types of the core samples and the data-driven model of kerogen hydrocarbon generation dynamics, numerical simulations were performed using IBM-SPSS simulation software to establish a scatter point evolution model of the hydrogen index of different types of kerogen with the highest pyrolysis peak temperature, as shown in the following formulas (4) to (7), including:

[0093]

[0094]

[0095] Among them, HI1 is the simulated hydrogen index corresponding to different maximum pyrolysis peak temperatures Tmax in the evolution model of type I kerogen; HI2 is the simulated hydrogen index corresponding to different maximum pyrolysis peak temperatures Tmax in the evolution model of type II1 kerogen; HI3 is the simulated hydrogen index corresponding to different maximum pyrolysis peak temperatures Tmax in the evolution model of type II2 kerogen; HI4 is the simulated hydrogen index corresponding to different maximum pyrolysis peak temperatures Tmax in the evolution model of type III kerogen; Tmax is the highest pyrolysis peak temperature of the core sample.

[0096] Furthermore, based on the evolution model of the corresponding kerogen type, the hydrocarbon conversion rate of the core sample is determined as shown in the following formula (8), including:

[0097] TR=[HI O -HI X ] / HI O (8)

[0098] Among them, HI O is the original hydrogen index of shale, HI X is the simulated hydrogen index corresponding to core samples of different kerogen types, and x is any one of 1, 2, 3, and 4.

[0099] In one possible embodiment, calculating the present hydrocarbon generation potential of the core sample includes obtaining a light hydrocarbon loss rate and a pyrolysis-soluble hydrocarbon content of the core sample, and determining the present hydrocarbon generation potential of the core sample based on the light hydrocarbon loss rate and the pyrolysis-soluble hydrocarbon content.

[0100] Specifically, the core samples were pyrolyzed to obtain pyrolysis data. Based on the pyrolysis data, a light hydrocarbon correction chart and a light hydrocarbon loss rate diagram were established. Figure 3 The light hydrocarbon correction chart and light hydrocarbon loss rate diagram provided in the embodiment of this application are as follows: Figure 3As shown in the figure on the left (the black solid circle represents the marine source rock - Valverde Basin, the black hollow circle represents various source rock types and basins, the thick line is linear (marine source rock - Valverde Basin), and the thin line is linear (various source rock types and basins)) is used to indicate that there is a relationship between the API index (i.e., the vertical axis API Gravity in the left figure) and the light hydrocarbon loss (i.e., the horizontal axis C15minus-wt.%) in the left figure. An empirical statistical chart is made. The API index refers to an indicator used to measure oil density. Type II kerogen includes type II1 kerogen and type II2 kerogen. Based on this, the API is calculated using crude oil density in the figure on the right. The range of light hydrocarbon loss is obtained through the left chart, and the average value is calculated to obtain a light hydrocarbon loss rate (or gaseous hydrocarbon + light hydrocarbon loss) of approximately 33%.

[0101] Furthermore, based on the light hydrocarbon loss rate and the pyrolysis-soluble hydrocarbon amount, the pyrolysis-soluble hydrocarbon amount is corrected to obtain the corrected pyrolysis-soluble hydrocarbon amount, as shown in the following formula (9), including:

[0102] S 1C =S1 / (1-loss) (9)

[0103] Among them, S 1C is the amount of soluble hydrocarbons in pyrolysis corrected; S1 is the amount of soluble hydrocarbons in pyrolysis; loss is the loss rate of light hydrocarbons.

[0104] Furthermore, based on the amount of pyrolysis-soluble hydrocarbons, the present hydrocarbon generation potential of the core sample is determined as shown in the following formula (10), including:

[0105] I HGP =(S 1C +S2) / TOC*100 (10)

[0106] Among them, I HGP is the present hydrocarbon generation potential value of the core sample; S 1C is the amount of pyrolysis-soluble hydrocarbons corrected; S2 is the amount of pyrolysis hydrocarbons in the core sample; TOC is the total organic carbon content of the core sample.

[0107] S203. Calculate the difference between the original hydrogen index and the current hydrocarbon generation potential value to obtain the micro-migrated hydrocarbon volume of the core sample.

[0108] S204: Select core samples whose micro-migrated hydrocarbon amount is greater than a preset threshold value from the first preset number of core samples to obtain a second preset number of discharged hydrocarbon samples.

[0109] S205. Divide the target shale block into N shale layers on average, where N is an integer greater than 2.

[0110] S206 : Based on the micro-migrated hydrocarbon amount of the discharged hydrocarbon sample, determine the average discharged hydrocarbon amount of the discharged hydrocarbon sample corresponding to each shale layer.

[0111] S207. Calculate the sum of the average hydrocarbon discharge amounts of all shale layers to obtain a total contribution value.

[0112] S208 : Calculate the ratio of the average expelled hydrocarbon amount of the expelled hydrocarbon samples of each shale layer to the total contribution value to obtain the relative contribution rate of each shale layer.

[0113] It should be noted that the specific implementation of S203 to S208 can refer to the specific implementation of S103 to S108, and will not be described in detail here.

[0114] S209 , selecting core samples whose micro-migrated hydrocarbon amount is less than a preset threshold value from the first preset number of core samples to obtain a third preset number of input hydrocarbon samples.

[0115] For example, with a preset threshold of 0, core samples with micromigration hydrocarbon concentrations less than 0 were selected as input hydrocarbon samples. The micromigration hydrocarbon concentrations of 118 core samples from the Paleogene Shahejie Formation in the Dongpu Sag of the Bohai Bay Basin ranged from -480.19 to 170.95 mg / g, primarily from -107.82 to 170.95 mg / g, with an average of 3.56 mg / g. Fifty-two of these samples, representing 44.07% of the total, were selected, with charge concentrations ranging from -0.36 to 480.19 mg / g, and an average of -82.56 mg / g.

[0116] S210: Determine whether the shale layer is at least one of a hydrocarbon reservoir layer and a hydrocarbon supply layer based on the discharged hydrocarbon sample and the input hydrocarbon sample corresponding to the shale layer.

[0117] Specifically, if the number of discharged hydrocarbon samples corresponding to the shale layer is greater than the number of input hydrocarbon samples, the shale layer is determined to be a hydrocarbon supply layer. If the number of discharged hydrocarbon samples corresponding to the shale layer is less than the number of input hydrocarbon samples, the shale layer is determined to be a hydrocarbon reservoir layer.

[0118] In one possible implementation, the total migrated hydrocarbon volume of the shale layer is calculated based on the micro-migrated hydrocarbon volume of the discharged hydrocarbon sample and the micro-migrated hydrocarbon volume of the input hydrocarbon sample. If the total migrated hydrocarbon volume of the shale layer is greater than a preset threshold, the shale layer is determined to be a hydrocarbon supply layer. If the total migrated hydrocarbon volume of the shale layer is less than the preset threshold, the shale layer is determined to be a hydrocarbon reservoir layer.

[0119] For example, the preset threshold is 0. Taking 118 core samples of the Paleogene Shahejie Formation in the Dongpu Sag of the Bohai Bay Basin as an example, there are 7 expelled hydrocarbon samples and 8 input hydrocarbon samples at 3870-3880m, which are mainly due to external hydrocarbon injection. The total migrated hydrocarbon amount is -26.23mg / g, which is less than 0 and is determined to be a hydrocarbon reservoir; there are 10 expelled hydrocarbon samples and 3 input hydrocarbon samples at a depth of 3880-3890m, which are mainly due to hydrocarbon expulsion, with a total migrated hydrocarbon amount of 641.01mg / g, which is greater than 0 is determined as a hydrocarbon supply layer; there are 5 hydrocarbon discharge samples at the depth of 3890-3900m, which are mainly due to hydrocarbon expulsion, with a total hydrocarbon migration amount of 78.24mg / g, which is greater than 0 and is determined as a hydrocarbon supply layer; there are 10 hydrocarbon discharge samples at the depth of 3900-3910m, which are mainly due to hydrocarbon expulsion, with a total hydrocarbon migration amount of 177.73mg / g, which is greater than 0 and is determined as a hydrocarbon supply layer; there is 1 hydrocarbon discharge sample at the depth of 3910-3920m, which is mainly due to hydrocarbon expulsion, with a total hydrocarbon migration amount of 13.63mg / g g, which is greater than 0 and is determined to be a hydrocarbon supply layer; there are 3 hydrocarbon discharge samples at the depth of 3920-3930m, which are mainly due to hydrocarbon expulsion, with a total migration hydrocarbon amount of 152.45 mg / g, which is greater than 0 and is determined to be a hydrocarbon supply layer; there are 8 hydrocarbon discharge samples and 20 hydrocarbon input samples at the depth of 3930-3940m, which are mainly due to external hydrocarbon injection, with a total migration hydrocarbon amount of -1913.50 mg / g, which is less than 0 and is determined to be a hydrocarbon reservoir; there are 7 hydrocarbon discharge samples and 13 hydrocarbon input samples at the depth of 3940-3950m, which are mainly due to external hydrocarbon injection, with a total migration hydrocarbon amount of -1913.50 mg / g, which is less than 0 and is determined to be a hydrocarbon reservoir. The injected hydrocarbon samples were mainly injected from outside, with a total migrated hydrocarbon amount of -1447.89 mg / g, which was less than 0 and was determined to be a hydrocarbon reservoir. There were 9 discharged hydrocarbon samples at a depth of 3950-3960m, which were mainly caused by hydrocarbon expulsion, with a total migrated hydrocarbon amount of 185.58 mg / g, which was greater than 0 and was determined to be a hydrocarbon supply layer. There were 8 discharged hydrocarbon samples and 8 input hydrocarbon samples at a depth of 3960-3970m, which were mainly caused by hydrocarbon expulsion, with a total migrated hydrocarbon amount of 368.30 mg / g, which was greater than 0 and was determined to be a hydrocarbon supply layer.

[0120] The method for processing the source rock contribution rate of highly heterogeneous shale layers provided in the present embodiment of the application quantitatively calculates the original hydrogen index and current hydrocarbon generation potential of core samples, thereby obtaining the micro-migrated hydrocarbon volume of the core samples, thereby accurately quantitatively evaluating the expelled hydrocarbon volume of the core samples. Furthermore, based on the highly accurate micro-migrated hydrocarbon volume of the core samples, the expelled hydrocarbon samples are selected and the shale layers are evenly divided to eliminate the heterogeneity of the shale. The average expelled hydrocarbon volume and total contribution value of each shale layer are then accurately calculated, thereby accurately obtaining the relative contribution rate of each shale layer.

[0121] Furthermore, by acquiring only three key data points from core samples—total organic carbon content, pyrolysis hydrocarbon yield, and peak pyrolysis temperature—important parameters such as the hydrogen index, hydrocarbon generation conversion rate, and original hydrogen index can be gradually determined. This avoids the collection and processing of large amounts of complex data, saving time and costs, and improving research efficiency. In practice, acquiring fewer data points also makes it easier to ensure data accuracy and reliability, reducing the errors and interference that can arise from excessive data. Determining the hydrocarbon generation conversion rate using the hydrogen index and peak pyrolysis temperature fully considers the thermal evolution characteristics of organic matter and the influence of hydrogen content on the hydrocarbon generation process. These two parameters directly reflect key information about the core sample's pyrolysis process. By establishing a reasonable model or algorithm, the hydrocarbon generation conversion rate can be accurately calculated. Determining the original hydrogen index based on the hydrogen index and hydrocarbon generation conversion rate fully utilizes existing experimental data and calculation results, accurately reconstructing the original hydrogen index through analysis of the hydrocarbon generation process in the core sample.

[0122] Furthermore, the use of the evolution model of the corresponding kerogen type to determine the hydrocarbon generation conversion rate of the core sample can fully consider the impact of different types of kerogen on the hydrocarbon generation process of the core sample, thereby improving the accuracy of the hydrocarbon generation conversion rate calculation.

[0123] Furthermore, determining the current hydrocarbon generation potential by determining the core sample's light hydrocarbon loss rate and pyrolysis-soluble hydrocarbon content, two key parameters, provides a comprehensive assessment of the hydrocarbon content of the core sample under different conditions. The light hydrocarbon loss rate reflects the loss of light hydrocarbons during geological processes, while the pyrolysis-soluble hydrocarbon content reflects the amount of hydrocarbons currently extractable from the core sample. Combining these two parameters more accurately reflects the core sample's actual hydrocarbon generation capacity, avoiding the limitations of a single indicator.

[0124] Furthermore, accurately determining whether a shale layer is a hydrocarbon reservoir or a hydrocarbon-supplying layer is of crucial guiding significance for oil and gas exploration. If a shale layer is determined to be a hydrocarbon reservoir, it can be targeted during exploration, with increased exploration efforts aimed at identifying areas of possible oil and gas accumulation. If it is a hydrocarbon-supplying layer, the location of surrounding reservoirs can be predicted by studying its hydrocarbon supply characteristics and migration pathways, thereby expanding the exploration scope. This helps improve the efficiency and success rate of oil and gas exploration, reduces exploration costs and reduces blindness, and provides strong support for the effective development of oil and gas resources.

[0125] The total migrated hydrocarbon volume was then calculated based on the micro-migrated hydrocarbon volume of the discharged and input hydrocarbon samples belonging to the shale layer, quantifying the migration of hydrocarbons within the shale layer. This quantitative approach makes the study of shale layers more precise and scientific, avoiding subjective judgments and vague descriptions, and accurately reflects the actual scale and extent of hydrocarbon migration within the shale layer. Comparing the total migrated hydrocarbon volume with a preset threshold provides a simple and effective method for determining whether a shale layer is a hydrocarbon source or reservoir. This quantitative data-based judgment method can more accurately clarify the function and role of shale layers in the oil and gas accumulation process, providing a reliable basis for oil and gas geological research.

[0126] Figure 4 The schematic diagram of the structure of the device for processing the source rock contribution rate of the highly heterogeneous shale layer provided in the embodiment of the present application is as follows: Figure 4 As shown, the device 40 for processing the source rock contribution rate of a highly heterogeneous shale layer provided in this embodiment includes an acquisition module 401 , a processing module 402 , a selection module 403 and a determination module 404 .

[0127] An acquisition module 401 is configured to acquire a first preset number of core samples, wherein the core samples are derived from any target shale block;

[0128] Processing module 402, for calculating the original hydrogen index and the present hydrocarbon generation potential value of the core sample;

[0129] The processing module 402 is also used to calculate the difference between the original hydrogen index and the current hydrocarbon generation potential value to obtain the micro-migrated hydrocarbon volume of the core sample;

[0130] A selection module 403 is configured to select core samples having a micro-migrated hydrocarbon amount greater than a preset threshold value from the first preset number of core samples to obtain a second preset number of expelled hydrocarbon samples;

[0131] The selection module 403 is further configured to divide the target shale block into N shale layers on an even basis, where N is an integer greater than 1;

[0132] A determination module 404 is configured to determine an average expelled hydrocarbon amount of the expelled hydrocarbon samples corresponding to each shale layer based on the micro-migrated hydrocarbon amount of the expelled hydrocarbon samples;

[0133] The processing module 402 is further configured to calculate the sum of the average hydrocarbon discharge amounts of all shale layers to obtain a total contribution value;

[0134] The processing module 402 is further configured to calculate the ratio of the average expelled hydrocarbon amount of the expelled hydrocarbon samples of each shale layer to the total contribution value, so as to obtain the relative contribution rate of each shale layer.

[0135] In a possible embodiment, the processing module 402 is further used to obtain the total organic carbon content, pyrolysis hydrocarbon content, and maximum pyrolysis peak temperature of the core sample;

[0136] Determine the hydrogen index of the core sample based on the total organic carbon content and the amount of pyrolytic hydrocarbons;

[0137] The hydrocarbon conversion rate of the core sample was determined based on the hydrogen index and the highest pyrolysis peak temperature;

[0138] The original hydrogen index of the core sample was determined based on the hydrogen index and hydrocarbon conversion rate.

[0139] In one possible embodiment, the processing module 402 is further configured to determine the kerogen type of the core sample based on the hydrogen index and the highest pyrolysis peak temperature;

[0140] Based on the kerogen type of the core sample, an evolution model of the corresponding kerogen type is established;

[0141] The hydrocarbon conversion rate of the core samples was determined based on the evolution model of the corresponding kerogen type.

[0142] In a possible embodiment, the processing module 402 is further used to obtain the light hydrocarbon loss rate and the amount of pyrolysis-soluble hydrocarbons of the core sample;

[0143] The present hydrocarbon generation potential of the core samples was determined based on the light hydrocarbon loss rate and the amount of pyrolysis-soluble hydrocarbons.

[0144] In a possible embodiment, the processing module 402 is further configured to select core samples having a micro-migration hydrocarbon amount less than a preset threshold value from the first preset number of core samples to obtain a third preset number of input hydrocarbon samples;

[0145] Based on the discharged hydrocarbon sample and the input hydrocarbon sample corresponding to the shale layer, it is determined that the shale layer is at least one of a hydrocarbon reservoir layer or a hydrocarbon supply layer.

[0146] In one possible embodiment, the processing module 402 is further configured to calculate the total migrated hydrocarbon volume of the shale layer based on the micro-migrated hydrocarbon volume of the discharged hydrocarbon sample and the micro-migrated hydrocarbon volume of the input hydrocarbon sample to which the shale layer belongs;

[0147] If the total amount of migrated hydrocarbons in the shale layer is greater than a preset threshold, the shale layer is determined to be a hydrocarbon-supplying layer;

[0148] If the total amount of migrated hydrocarbons in the shale layer is less than a preset threshold, the shale layer is determined to be a hydrocarbon reservoir.

[0149] The device for processing the source rock contribution rate of a highly heterogeneous shale layer provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effects are similar and will not be described in detail in this embodiment.

[0150] Figure 5 This is a schematic diagram of the structure of the electronic device provided in the embodiment of the present application. Figure 5 As shown, the electronic device 50 provided in this embodiment includes: at least one processor 501 and a memory 502. Optionally, the device 50 further includes a communication component 503. The processor 501, the memory 502 and the communication component 503 are connected via a bus.

[0151] In a specific implementation process, at least one processor 501 executes the computer-executable instructions stored in the memory 502, so that the at least one processor 501 performs the above method.

[0152] The specific implementation process of the processor 501 can be found in the above method embodiment. Its implementation principle and technical effects are similar and will not be repeated here in this embodiment.

[0153] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly executed by a hardware processor or by a combination of hardware and software modules in the processor.

[0154] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (NVM), such as at least one disk memory.

[0155] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be classified into address buses, data buses, and control buses. For ease of illustration, the buses in the drawings of this application are not limited to just one bus or just one type of bus.

[0156] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0157] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0158] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile memory 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, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0159] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist in a device as discrete components.

[0160] The division of units is merely a logical functional division; actual implementations may employ alternative divisions, such as combining or integrating multiple units or components into another system, or omitting or disabling certain features. Furthermore, any direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units, either through an interface, electrical, mechanical, or other means.

[0161] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0162] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0163] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the 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 for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program code.

[0164] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0165] Finally, it should be noted that those skilled in the art will readily identify other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art not disclosed herein. The present invention is not limited to the precise structure described above and illustrated in the accompanying drawings, and various modifications and variations may be made without departing from the scope thereof. The scope of the present invention is limited solely by the appended claims.

Claims

1. A method for processing the source rock contribution rate of a highly heterogeneous shale layer, characterized in that: include: Obtaining a first preset number of core samples, wherein the core samples are derived from any target shale block; Calculating the original hydrogen index and the present hydrocarbon generation potential value of the core sample; Calculating the difference between the original hydrogen index and the current hydrocarbon generation potential value to obtain the micro-migrated hydrocarbon amount of the core sample; Selecting core samples having a micro-migrated hydrocarbon amount greater than a preset threshold value from the first preset number of core samples to obtain a second preset number of expelled hydrocarbon samples; Dividing the target shale block into N shale layers on average, where N is an integer greater than 1; Determining an average expelled hydrocarbon amount of the expelled hydrocarbon samples corresponding to each shale layer based on the micro-migrated hydrocarbon amount of the expelled hydrocarbon samples; The sum of the average hydrocarbon discharge of all shale layers was calculated to obtain the total contribution value; The ratio of the average expelled hydrocarbon amount of the expelled hydrocarbon sample of each shale layer to the total contribution value is calculated to obtain the relative contribution rate of each shale layer.

2. The method according to claim 1, characterized in that The calculating the original hydrogen index of the core sample comprises: Obtaining the total organic carbon content, pyrolysis hydrocarbon content, and maximum pyrolysis peak temperature of the core sample; determining a hydrogen index of the core sample based on the total organic carbon content and the amount of pyrolytic hydrocarbons; determining a hydrocarbon generation conversion rate of the core sample based on the hydrogen index and the highest pyrolysis peak temperature; The original hydrogen index of the core sample is determined based on the hydrogen index and the hydrocarbon generation conversion rate.

3. The method according to claim 2, characterized in that The determining of the hydrocarbon generation conversion rate of the core sample based on the hydrogen index and the maximum pyrolysis peak temperature includes: determining the kerogen type of the core sample based on the hydrogen index and the highest pyrolysis peak temperature; Based on the kerogen type of the core sample, establishing an evolution model of the corresponding kerogen type; Based on the evolution model of the corresponding kerogen type, the hydrocarbon conversion rate of the core sample is determined.

4. The method according to any one of claims 1 to 3, characterized in that Calculate the present hydrocarbon generation potential of the core sample, including: Obtaining the light hydrocarbon loss rate and the amount of pyrolysis-soluble hydrocarbons of the core sample; The present hydrocarbon generation potential value of the core sample is determined based on the light hydrocarbon loss rate and the amount of pyrolysis-soluble hydrocarbons.

5. The method according to any one of claims 1 to 3, characterized in that Also includes: Selecting core samples having a micro-migration hydrocarbon amount less than a preset threshold value from the first preset number of core samples to obtain a third preset number of input hydrocarbon samples; Based on the discharged hydrocarbon sample and the input hydrocarbon sample corresponding to the shale layer, it is determined that the shale layer is at least one of a hydrocarbon reservoir layer and a hydrocarbon supply layer.

6. The method according to claim 5, characterized in that Determining, based on the discharged hydrocarbon sample and the input hydrocarbon sample corresponding to the shale layer, that the shale layer is at least one of a hydrocarbon reservoir layer or a hydrocarbon supply layer comprises: Calculating the total migration amount of the shale layer based on the micro-migration amount of hydrocarbons of the discharged hydrocarbon sample and the micro-migration amount of hydrocarbons of the input hydrocarbon sample to which the shale layer belongs; If the total amount of migrated hydrocarbons in the shale layer is greater than a preset threshold, the shale layer is determined to be a hydrocarbon-supplying layer; If the total amount of migrated hydrocarbons in the shale layer is less than a preset threshold, the shale layer is determined to be a hydrocarbon reservoir.

7. A device for processing the hydrocarbon source rock contribution rate of a strongly heterogeneous shale layer, characterized in that: include: an acquisition module, configured to acquire a first preset number of core samples, wherein the core samples are derived from any target shale block; a processing module, configured to calculate an original hydrogen index and a present hydrocarbon generation potential value of the core sample; The processing module is further configured to calculate the difference between the original hydrogen index and the current hydrocarbon generation potential value to obtain the amount of micro-migrated hydrocarbons in the core sample; a selection module, configured to select core samples having a micro-migrated hydrocarbon amount greater than a preset threshold value from the first preset number of core samples, to obtain a second preset number of discharged hydrocarbon samples; The selection module is further configured to divide the target shale block into N shale layers on average, where N is an integer greater than 1; a determination module, configured to determine an average discharged hydrocarbon amount of the discharged hydrocarbon samples corresponding to each shale layer based on the micro-migrated hydrocarbon amount of the discharged hydrocarbon samples; The processing module is also used to calculate the sum of the average expelled hydrocarbons of all shale layers to obtain the total contribution value; The processing module is further configured to calculate the ratio of the average expelled hydrocarbon amount of the expelled hydrocarbon samples of each shale layer to the total contribution value, so as to obtain the relative contribution rate of each shale layer.

8. An electronic device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 6 when executed by a processor.

10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

Images