An effective lower limit of hydrocarbon source rock identification method and device

Abstract

The present specification relates to the technical field of oil and gas exploration, and provides an effective lower limit of hydrocarbon source rock identification method and device. The method comprises: obtaining geochemical data of a plurality of source rock samples in a target reservoir; generating hydrocarbon correction on the geochemical data to determine the current hydrocarbon generation potential of the source rock samples; determining the current hydrocarbon generation potential and the original hydrocarbon generation potential of the source rock samples based on the corrected geochemical data; calculating the micro-migration hydrocarbon amount of the source rock samples according to the current hydrocarbon generation potential and the original hydrocarbon generation potential of the source rock samples; screening the source rock samples to obtain source rock samples meeting the preset micro-migration hydrocarbon amount requirement to determine the hydrocarbon expulsion ratio of the screened source rock samples; and performing regression analysis on the hydrocarbon expulsion ratio and the geochemical data to obtain a correlation relationship model of the hydrocarbon expulsion ratio and the geochemical data, so as to obtain the lower limit of the organic matter abundance and the lower limit of the organic matter maturity of the target reservoir according to the lower limit of the hydrocarbon expulsion. Through the embodiment of the present specification, the accurate identification of the effective hydrocarbon source rock with strong heterogeneity can be realized.

Description

Technical Field

[0001] This specification relates to the field of oil and gas exploration technology, and in particular to an effective method and apparatus for identifying the lower limit of hydrocarbon source rocks. Background Technology

[0002] Source rocks are rocks rich in organic matter that have been generated and expelled or are currently generating and expelling oil and gas during geological history. Modern hydrocarbon accumulation theory requires a quantitative evaluation of the hydrocarbon expulsion effect of source rocks. Effective source rocks refer to rock formations that both generate and expel oil and gas. Source rock research is a crucial foundation for understanding hydrocarbon enrichment mechanisms and predicting hydrocarbon reservoir distribution. Identifying effective source rocks is of great significance for elucidating hydrocarbon enrichment patterns. However, current criteria for identifying effective source rocks are based on extensive statistical data. While this provides important guidance for quickly identifying effective source rocks, it also has two potential shortcomings: First, there is no quantitative indicator of whether source rocks have expelled hydrocarbons; it is often indirectly expressed by the abundance and maturity of organic matter. Second, due to differences in sedimentary environment, parent material, and mineral composition, the lower limit of organic matter abundance varies significantly across different regions.

[0003] Furthermore, since source rocks, in addition to their role in hydrocarbon generation and expulsion, also serve as hydrocarbon reservoirs, this presents new challenges for identifying effective source rocks: First, shale and mudstone exhibit significant heterogeneity, meaning that not only do the geological characteristics of source rocks vary considerably across different regions, but the hydrocarbon generation and expulsion characteristics within source rocks from the same region may also differ. Second, micro-migration often occurs within source rocks, leading to source-reservoir delineation issues within shale formations. Some micro-reservoir units may not contain hydrocarbons generated spontaneously, but rather hydrocarbons expelled from micro-source units may have accumulated there. Therefore, a lower limit identification method for effective source rocks is urgently needed to accurately identify effective source rocks with strong heterogeneity. Summary of the Invention

[0004] Given the current difficulty in accurately identifying effective source rocks with strong heterogeneity, this scheme is proposed to overcome or at least partially solve the above problems.

[0005] On the one hand, the purpose of some embodiments of this specification is to provide an effective method for identifying the lower limit of hydrocarbon source rocks, the method including:

[0006] Obtain geochemical data from several source rock samples in the target reservoir;

[0007] Hydrocarbon generation correction is performed on the geochemical data to determine the current hydrocarbon generation potential of the source rock sample;

[0008] Based on the corrected geochemical data, the hydrocarbon generation and expulsion trends of the source rock samples were analyzed using hydrocarbon generation kinetics.

[0009] The original hydrocarbon generation potential of the source rock sample is determined by using the aforementioned hydrocarbon generation and expulsion trends and current hydrocarbon generation potential.

[0010] Calculate the amount of micro-transported hydrocarbons in the source rock sample based on its current hydrocarbon generation potential and original hydrocarbon generation potential.

[0011] Source rock samples that meet the preset requirements for micro-transported hydrocarbon content are screened from the source rock samples;

[0012] The hydrocarbon expulsion ratio of the screened source rock samples is determined based on the ratio of the amount of micro-transported hydrocarbons to the original hydrocarbon generation potential.

[0013] Regression analysis was performed on the hydrocarbon excretion ratio and the geochemical data to obtain a correlation model between the hydrocarbon excretion ratio and the geochemical data.

[0014] By inputting the preset lower limit value of hydrocarbon expulsion into the correlation model, the lower limit of organic matter abundance and the lower limit of organic matter maturity of the target reservoir are obtained.

[0015] Furthermore, the geochemical data includes at least one or more of rock pyrolysis data, total organic carbon, and vitrinite reflectance; the rock pyrolysis data includes at least the first peak data and the second peak data generated by the pyrolysis of the source rock sample.

[0016] Further, hydrocarbon generation correction is performed on the geochemical data to determine the current hydrocarbon generation potential of the source rock sample, including:

[0017] The lost hydrocarbons in the first peak data are corrected by using freeze-pyrolysis, and the adsorbed hydrocarbons in the second peak data are corrected by using multi-temperature-level pyrolysis, so as to achieve the correction of generated hydrocarbons in the rock pyrolysis data in the geochemical data;

[0018] Light hydrocarbon correction was performed based on the corrected rock pyrolysis data and total organic carbon to determine the current hydrocarbon generation potential of the source rock sample.

[0019] Furthermore, based on the corrected geochemical data, the hydrocarbon generation and expulsion trends of the source rock samples were analyzed using hydrocarbon generation kinetics, including:

[0020] The vitrinite reflectance is used as the degree of thermal evolution of the source rock sample, and the hydrocarbon generation and expulsion trend is determined based on hydrocarbon generation kinetics using the following formula:

[0021]

[0022] and / or

[0023]

[0024] Where Ro is the vitrinite reflectance, HI(Ro) is the trend of change in the original hydrocarbon generation conversion potential, used to represent the trend of hydrocarbon generation and expulsion, HI0 is the original hydrocarbon generation conversion potential, θ1 is the range of the hydrocarbon generation window, β1 is the period of large hydrocarbon generation, GPI(Ro) is the trend of change in the original hydrocarbon generation potential, used to represent the trend of hydrocarbon generation and expulsion, GPI0 is the original hydrocarbon generation potential, θ2 is the range of the hydrocarbon expulsion window, and β2 is the period of large hydrocarbon expulsion.

[0025] Furthermore, the original hydrocarbon generation potential of the source rock sample is determined using the aforementioned hydrocarbon generation and expulsion trends and current hydrocarbon generation potential, including:

[0026] The original hydrocarbon generation potential corresponding to the current hydrocarbon generation potential is determined based on the hydrocarbon generation and emission trend.

[0027] Further, based on the current and original hydrocarbon generation potential of the source rock sample, the amount of micro-transported hydrocarbons in the source rock sample is calculated, including:

[0028] The amount of micro-transported hydrocarbons is obtained by subtracting the current hydrocarbon generation potential from the original hydrocarbon generation potential.

[0029] Further, source rock samples that meet the preset micro-transport hydrocarbon content requirements are screened from the source rock samples, including:

[0030] Source rock samples are selected from the source rock samples whose micro-transported hydrocarbon content is greater than a first threshold, and the first threshold is a non-negative number.

[0031] Furthermore, regression analysis is performed on the hydrocarbon expulsion ratio and the geochemical data to obtain a correlation model between the hydrocarbon expulsion ratio and the geochemical data, including:

[0032] Regression analyses were performed on the hydrocarbon excretion ratio and total organic carbon, and on the hydrocarbon excretion ratio and vitrinite reflectance, respectively, to determine the first correlation between the hydrocarbon excretion ratio and total organic carbon, and the second correlation between the hydrocarbon excretion ratio and vitrinite reflectance.

[0033] Alignment is performed based on the hydrocarbon expulsion ratio to generate a three-dimensional correlation model based on the first and second two-dimensional correlations.

[0034] Furthermore, the preset lower limit value for hydrocarbon expulsion is input into the correlation model to obtain the lower limit of organic matter abundance and the lower limit of organic matter maturity of the target reservoir, including:

[0035] The total organic carbon is used as an indicator of organic matter abundance, and the vitrinite reflectance is used as an indicator of organic matter maturity.

[0036] The preset lower limit value of hydrocarbon emission is input into the correlation model to determine the value range of the organic matter abundance measurement index and the organic matter maturity measurement index under the constraint that the hydrocarbon emission ratio is greater than the lower limit value of hydrocarbon emission.

[0037] The lower limit of organic matter abundance and the lower limit of organic matter maturity of the target reservoir are determined based on the range of values.

[0038] On the other hand, some embodiments of this specification also provide an effective source rock lower limit identification device, the device comprising:

[0039] The receiving module is used to acquire geochemical data of several source rock samples in the target reservoir;

[0040] A correction module is used to perform hydrocarbon generation correction on the geochemical data to determine the current hydrocarbon generation potential of the source rock sample;

[0041] The analysis module is used to analyze the hydrocarbon generation and expulsion trends of the source rock sample based on hydrocarbon generation kinetics, using corrected geochemical data.

[0042] The determination module is used to determine the original hydrocarbon generation potential of the source rock sample by utilizing the hydrocarbon generation and expulsion trends and the current hydrocarbon generation potential.

[0043] The micro-transport hydrocarbon calculation module is used to calculate the micro-transport hydrocarbon amount of the source rock sample based on the current hydrocarbon generation potential and the original hydrocarbon generation potential of the source rock sample.

[0044] The screening module is used to screen source rock samples from the source rock samples to obtain source rock samples that meet the preset requirements for micro-transported hydrocarbon content;

[0045] The hydrocarbon expulsion ratio calculation module is used to determine the hydrocarbon expulsion ratio of the screened source rock sample based on the ratio of the amount of micro-transported hydrocarbons to the original hydrocarbon generation potential.

[0046] The regression module is used to perform regression analysis on the hydrocarbon excretion ratio and the geochemical data to obtain the correlation model between the hydrocarbon excretion ratio and the geochemical data.

[0047] The identification module is used to input the preset hydrocarbon emission lower limit value into the correlation model to obtain the lower limit of organic matter abundance and the lower limit of organic matter maturity of the target reservoir.

[0048] Some embodiments of this specification provide one or more technical solutions, which have at least the following technical effects:

[0049] The embodiments in this specification automatically acquire geochemical data of several source rock samples in the target reservoir. To reduce errors caused by the acquisition and transportation of source rock samples, the geochemical data is first corrected using generated hydrocarbons. Based on the corrected geochemical data, the current hydrocarbon generation potential of the source rock samples is accurately determined. Then, the hydrocarbon generation and expulsion trends of the source rock samples are analyzed based on the corrected geochemical data to accurately determine the original hydrocarbon generation potential of the source rock samples, thereby ensuring the accuracy of micro-transport hydrocarbon amounts. Source rock samples that meet the preset micro-transport hydrocarbon amount requirements are then screened to ensure the effectiveness of the screened source rock samples. Subsequently, regression analysis is performed on the correlation between the hydrocarbon expulsion ratio and geochemical data based on the screened source rock samples. The lower limit of organic matter abundance and the lower limit of organic matter maturity in the target reservoir are determined by using existing geochemical data and the correlation model obtained from the regression analysis, without introducing new data, and ensuring the accuracy of the lower limits of organic matter abundance and organic matter maturity.

[0050] The above description is merely an overview of some embodiments of the technical solutions in this specification. In order to better understand the technical means of some embodiments of this specification and to implement them in accordance with the content of the specification, and to make the above and other objects, features and advantages of some embodiments of this specification more apparent and understandable, specific implementation methods of some embodiments of this specification are given below. Attached Figure Description

[0051] To more clearly illustrate some embodiments or technical solutions in the prior art of this specification, the accompanying drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort. In the drawings:

[0052] Figure 1 A schematic diagram of an implementation system for an effective source rock lower limit identification method is shown in some embodiments of this specification;

[0053] Figure 2 A flowchart of an effective method for identifying the lower limit of hydrocarbon source rocks is shown in some embodiments of this specification;

[0054] Figure 3 This is a schematic diagram illustrating the steps for determining current hydrocarbon generation potential in some embodiments of this specification;

[0055] Figure 4 This is a schematic diagram illustrating the steps of establishing a related relationship model in some embodiments of this specification;

[0056] Figure 5 This is a schematic diagram illustrating the steps for obtaining the lower limit of organic matter abundance and the lower limit of organic matter maturity of the target reservoir in some embodiments of this specification;

[0057] Figure 6a This is a schematic diagram illustrating the hydrocarbon generation and emission trends in some embodiments of this specification;

[0058] Figure 6b This is a schematic diagram illustrating the hydrocarbon conversion rate in some embodiments of this specification;

[0059] Figure 7 This is a schematic diagram illustrating the lower limit of total organic carbon in effective source rocks in some embodiments of this specification;

[0060] Figure 8 This is a schematic diagram illustrating the lower limit of effective vitrinite reflectance of source rocks in some embodiments of this specification;

[0061] Figure 9 This is a three-dimensional schematic diagram used in some embodiments of this specification to identify the comprehensive lower limit of effective source rocks;

[0062] Figure 10 This is a schematic diagram of the structure of an effective source rock lower limit identification device in some embodiments of this specification;

[0063] Figure 11 This is a schematic diagram of the computer device structure provided in some embodiments of this specification.

[0064] [Explanation of Labels in the Attached Image]

[0065] 101. Terminal;

[0066] 102. Server;

[0067] 1001. Receiver module;

[0068] 1002. Calibration module;

[0069] 1003. Analysis Module;

[0070] 1004. Determine the module;

[0071] 1005. Micro-transport hydrocarbon amount calculation module;

[0072] 1006. Filtering module;

[0073] 1007. Hydrocarbon Exhaustion Ratio Calculation Module;

[0074] 1008. Regression Module;

[0075] 1009. Identification module;

[0076] 1102. Computer equipment;

[0077] 1104. Processor;

[0078] 1106. Memory;

[0079] 1108. Drive mechanism;

[0080] 1110. Input / output interface;

[0081] 1112. Input devices;

[0082] 1114. Output devices;

[0083] 1116. Presentation device;

[0084] 1118. Graphical User Interface;

[0085] 1120. Network interface;

[0086] 1122. Communication link;

[0087] 1124. Communication bus. Detailed Implementation

[0088] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in some embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on some embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0089] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings herein are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, apparatus, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0090] It should be noted that the acquisition, storage, use, and processing of data in the technical solution of this application all comply with the relevant provisions of relevant laws and regulations.

[0091] like Figure 1The diagram illustrates an implementation system for an effective hydrocarbon source rock lower limit identification method according to an embodiment of the present invention. The system may include a terminal 101 and a server 102. The terminal 101 and server 102 communicate via a network, which may include a Local Area Network (LAN), a Wide Area Network (WAN), the Internet, or a combination thereof, and is connected to a website, user equipment (e.g., a computing device), and a backend system. Staff can send an effective hydrocarbon source rock lower limit identification request to the server 102 via the terminal 101. Upon receiving the request, the server 102 retrieves geochemical data from its database for calculation and processing, obtains the identification result, and sends the result back to the terminal 101 so that staff can process tasks based on the identification result.

[0092] In the embodiments of this specification, server 102 may be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0093] In an optional embodiment, terminal 101 may be an electronic device, including but not limited to self-service terminal equipment, desktop computer, tablet computer, laptop computer, smart wearable device, etc. Optionally, the operating system running on the electronic device may include but not limited to Android, iOS, Linux, Windows, etc. Of course, terminal 101 is not limited to the above-mentioned physical electronic devices; it may also be software running on the above-mentioned electronic devices.

[0094] In addition, it should be noted that, Figure 1 The example shown is merely one application environment provided by this disclosure. In practical applications, it may include multiple terminals 101, and this specification does not impose any restrictions.

[0095] Figure 2 This is a flowchart illustrating an effective method for identifying the lower limit of hydrocarbon source rocks according to an embodiment of the present invention. This specification provides the method operation steps as shown in the embodiments or flowcharts, but based on conventional or non-inventive labor, more or fewer operation steps may be included. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only execution order. In actual system or device products, the methods can be executed in the order shown in the embodiments or drawings, or in parallel. Specifically, as shown... Figure 2As shown, when applied to the server side described above, the method may include:

[0096] S201: Obtain geochemical data of several source rock samples in the target reservoir;

[0097] S202: Perform hydrocarbon generation correction on the geochemical data to determine the current hydrocarbon generation potential of the source rock sample;

[0098] S203: Based on the corrected geochemical data, the hydrocarbon generation and expulsion trends of the source rock samples are analyzed based on hydrocarbon generation kinetics.

[0099] S204: Determine the original hydrocarbon generation potential of the source rock sample using the aforementioned hydrocarbon generation and expulsion trends and current hydrocarbon generation potential;

[0100] S205: Calculate the amount of micro-transported hydrocarbons in the source rock sample based on its current hydrocarbon generation potential and original hydrocarbon generation potential.

[0101] S206: Select source rock samples that meet the preset requirements for micro-transported hydrocarbon content from the source rock samples;

[0102] S207: Determine the hydrocarbon expulsion ratio of the source rock sample obtained from screening based on the ratio of the amount of micro-transported hydrocarbons to the original hydrocarbon generation potential.

[0103] S208: Perform regression analysis on the hydrocarbon excretion ratio and the geochemical data to obtain a correlation model between the hydrocarbon excretion ratio and the geochemical data;

[0104] S209: Input the preset lower limit value of hydrocarbon expulsion into the correlation model to obtain the lower limit of organic matter abundance and the lower limit of organic matter maturity of the target reservoir.

[0105] The embodiments in this specification automatically acquire geochemical data of several source rock samples in the target reservoir. To reduce errors caused by the acquisition and transportation of source rock samples, the geochemical data is first corrected using generated hydrocarbons. Based on the corrected geochemical data, the current hydrocarbon generation potential of the source rock samples is accurately determined. Then, the hydrocarbon generation and expulsion trends of the source rock samples are analyzed based on the corrected geochemical data to accurately determine the original hydrocarbon generation potential of the source rock samples, thereby ensuring the accuracy of micro-transport hydrocarbon amounts. Source rock samples that meet the preset micro-transport hydrocarbon amount requirements are then screened to ensure the effectiveness of the screened source rock samples. Subsequently, regression analysis is performed on the correlation between the hydrocarbon expulsion ratio and geochemical data based on the screened source rock samples. The lower limit of organic matter abundance and the lower limit of organic matter maturity in the target reservoir are determined by using existing geochemical data and the correlation model obtained from the regression analysis, without introducing new data, and ensuring the accuracy of the lower limits of organic matter abundance and organic matter maturity.

[0106] In some embodiments, the strata composed of source rocks are referred to as source layers or source rock layers. During the development of a sedimentary basin, source rock layers and non-source rock layers often inter-deposit within a certain geological period, forming interbedded layers of source rock layers and non-source rock layers within a single stratum. The combination of several source rock layers with the same lithological and lithofacies characteristics and the non-source rock layers between them is called a source rock stratum system. The target reservoir belongs to the source rock stratum system. Furthermore, the hydrocarbon migration between laminae or thin interlayers with different hydrocarbon generation and storage capacities within the source rock stratum system constitutes the source-reservoir structure background within the source rock stratum system. The hydrocarbon differential enrichment response under the condition is used to identify micro-migrated hydrocarbons, which refer to the hydrocarbons transported from the source rock to the reservoir unit after hydrocarbon generation. The reservoir unit is not a tight reservoir or a structural-lithological trap in the traditional sense, but refers to the part of the source rock that can store non-autogenous hydrocarbons. However, micro-migrated hydrocarbons are only used to identify existing data and are difficult to generalize to the prediction of effective source rocks in the whole region. Moreover, the current model of micro-migrated hydrocarbons relies on Tmax, which has great uncertainty and is often difficult to characterize maturity. Therefore, the use of Tmax to determine micro-migrated hydrocarbons has certain limitations.

[0107] Furthermore, in some embodiments, the geochemical data includes at least one or more of rock pyrolysis data, total organic carbon, and vitrinite reflectance; the rock pyrolysis data includes at least first peak data and second peak data generated by the pyrolysis of the source rock sample.

[0108] In some embodiments, geochemical data refers to the geochemical data of the target reservoir, which can be geochemical data of shale and / or carbonate source rocks. Rock pyrolysis data is data obtained through rock pyrolysis experiments and can be used to determine the type and maturity of organic matter and analyze the hydrocarbon generation potential of sediments. For example, in some embodiments, the rock pyrolysis process involves placing the source rock sample in a pyrolysis device, heating it to a pre-set temperature, and separating the hydrocarbon gases volatilized and decomposed at high temperature from the sample residue by purging with inert gas. Then, the free hydrocarbons in the sample are quantitatively analyzed. The content of free hydrocarbons and hydrogen-containing and oxygen-containing compounds emitted during the pyrolysis of insoluble organic matter (kerogen) is used to obtain S1 data (first peak data) and S2 data (second peak data). In some embodiments, rock pyrolysis data may also include S3 data (third peak data). Specifically, in some embodiments, S1 refers to the amount of free hydrocarbons in the rock (generated hydrocarbons), S2 refers to the amount of pyrolyzed hydrocarbons in the rock (pyrolyzed hydrocarbons), and S3 refers to the amount of CO2 produced by the pyrolysis of organic matter in the rock. The hydrocarbon generation potential of the source rock sample can be analyzed based on the rock pyrolysis data in the geochemical data.

[0109] See attached document Figure 3 In some embodiments, performing hydrocarbon generation correction on the geochemical data to determine the current hydrocarbon generation potential of the source rock sample may include:

[0110] S301: The lost hydrocarbons in the first peak data are corrected by cryogenic pyrolysis, and the adsorbed hydrocarbons in the second peak data are corrected by multi-temperature-level pyrolysis, so as to achieve the correction of generated hydrocarbons in the rock pyrolysis data in the geochemical data.

[0111] S302: Perform light hydrocarbon correction based on the corrected rock pyrolysis data and total organic carbon to determine the current hydrocarbon generation potential of the source rock sample.

[0112] It can be understood that, in some embodiments, during rock pyrolysis, the S1 data contains loss errors, and some hydrocarbons generated in conventional pyrolysis are incorrectly identified as S2 data due to adsorption. Therefore, cryogenic pyrolysis is used to correct the lost hydrocarbons in the first peak data, and multi-temperature-level pyrolysis is used to correct the adsorbed hydrocarbons in the second peak data, thereby correcting the S1 and S2 data. Since cryogenic pyrolysis and multi-temperature-level pyrolysis are not the main content of this invention, they will not be elaborated here. Subsequently, light hydrocarbon correction is performed based on the corrected rock pyrolysis data and total organic carbon. Light hydrocarbon correction aims to eliminate hydrocarbon loss caused by sample acquisition and storage processes, as well as errors in hydrocarbon generation due to experimental instruments and methods, including but not limited to empirical coefficient methods, kerogen hydrocarbon generation simulation experiments, light hydrocarbon loss physical simulation methods, and experimental instrument and process improvement methods. Furthermore, after correcting the S1 and S2 data, the current hydrocarbon generation potential of the source rock sample can be determined based on the total organic carbon using the following formula:

[0113] GPI1=((S 1C +S2) / TOC)×w

[0114] Wherein, GPI1 represents the current hydrocarbon generation potential, S 1C S1 represents the corrected S1, S2 represents the generated hydrocarbons, TOC represents the total organic carbon, and w represents the preset coefficient.

[0115] Furthermore, in some embodiments, based on corrected geochemical data, the hydrocarbon generation and expulsion trends of the source rock sample are analyzed according to hydrocarbon generation kinetics, including:

[0116] The vitrinite reflectance is used as the degree of thermal evolution of the source rock sample, and the hydrocarbon generation and expulsion trend is determined based on hydrocarbon generation kinetics using the following formula:

[0117]

[0118] and / or

[0119]

[0120] Where Ro is the vitrinite reflectance, HI(Ro) is the trend of change in the original hydrocarbon generation conversion potential, used to represent the trend of hydrocarbon generation and expulsion, HI0 is the original hydrocarbon generation conversion potential, θ1 is the range of the hydrocarbon generation window, β1 is the period of large hydrocarbon generation, GPI(Ro) is the trend of change in the original hydrocarbon generation potential, used to represent the trend of hydrocarbon generation and expulsion, GPI0 is the original hydrocarbon generation potential, θ2 is the range of the hydrocarbon expulsion window, and β2 is the period of large hydrocarbon expulsion.

[0121] In some embodiments, the hydrocarbon generation and expulsion trend can be represented by HI(Ro) and / or GPI(Ro). This trend can be used to calculate the original hydrocarbon generation potential based on the determined current hydrocarbon generation potential. Since both the original hydrocarbon generation potential and the original hydrocarbon generation conversion potential represent the hydrocarbon generation potential in the original time period, their numerical values ​​are the same. Specifically, as the source rock gradually develops from its original hydrocarbon generation potential to its current hydrocarbon generation potential, the S1 data generally increases, while the S2 data generally decreases. The sum of the S1 and S2 data also decreases due to thermal evolution and other factors. Corresponding to the decreasing state of the S2 data, HI... (Ro) shows a decreasing trend, corresponding to the decreasing state of the sum of S1 data and S2 data. GPI(Ro) also shows a decreasing trend. Therefore, HI(Ro) and GPI(Ro) can be used to characterize the hydrocarbon generation and expulsion trend. It should be noted that in the process of determining the hydrocarbon generation and expulsion trend, the original hydrocarbon generation potential can be regarded as a predicted value, which is obtained based on geochemical data. The specific calculation method is explained below. Furthermore, the source rock undergoes hydrocarbon generation and expulsion processes as the thermal evolution progresses. The degree of thermal evolution includes, but is not limited to, using Ro and Tmax for characterization. However, due to the application defects and limitations of Tmax, Ro is usually used to characterize the degree of thermal evolution in the embodiments of this specification.

[0122] Furthermore, in some embodiments, the original hydrocarbon generation potential of the source rock sample is determined using the hydrocarbon generation and expulsion trends and the current hydrocarbon generation potential, including:

[0123] The original hydrocarbon generation potential corresponding to the current hydrocarbon generation potential is determined based on the hydrocarbon generation and emission trend.

[0124] It can be understood that, in some embodiments, determining the original hydrocarbon generation potential corresponding to the current hydrocarbon generation potential is based on the assumption that each source rock sample has roughly the same hydrocarbon generation and expulsion trend. Specifically, the original hydrocarbon generation potential can be calculated using the following formula:

[0125] HI0 = (S2 / TOC) × w

[0126] Wherein, HI0 is the original hydrocarbon generation conversion potential, which is numerically the same as the original hydrocarbon generation potential GPI0, S2 is pyrolytic hydrocarbons, TOC is total organic carbon, and w is a preset coefficient.

[0127] Furthermore, in some embodiments, the amount of micro-transported hydrocarbons in the source rock sample is calculated based on its current and initial hydrocarbon generation potential, including:

[0128] The amount of micro-transported hydrocarbons is obtained by subtracting the current hydrocarbon generation potential from the original hydrocarbon generation potential.

[0129] Furthermore, in some embodiments, selecting source rock samples from the source rock samples that meet the preset requirements for micro-transported hydrocarbon amounts includes:

[0130] Source rock samples are selected from the source rock samples whose micro-transported hydrocarbon content is greater than a first threshold, and the first threshold is a non-negative number.

[0131] In some embodiments, the micro-transported hydrocarbon quantity can be understood as the difference between the original hydrocarbon generation potential and the current hydrocarbon generation potential, i.e., GPI0 minus GPI1. In some typical embodiments, the first threshold is often zero. This can be understood as the source rock sample having hydrocarbon effluent properties when the micro-transported hydrocarbon quantity is greater than zero, and conversely, having hydrocarbon effluent properties when it is less than zero. For source rock samples with hydrocarbon effluent properties, using them for subsequent calculations of the hydrocarbon effluent ratio to determine the lower limit of organic matter abundance and organic matter maturity of effective source rocks will lead to inaccurate results in the final lower limit of organic matter abundance and organic matter maturity of effective source rocks, because they themselves do not have hydrocarbon effluent properties. Therefore, the micro-transported hydrocarbon quantity requirement is used to screen source rock samples to ensure the validity of source rock samples and avoid invalid source rock samples interfering with the subsequent calculation process.

[0132] Furthermore, in some embodiments, the hydrocarbon expulsion ratio can be calculated using the following formula:

[0133] Pi = △Q i / ∑HI 0i

[0134] Where Pi represents the hydrocarbon emission ratio of the i-th sample; i = 1, 2, 3, ..., N, representing the number of samples; HI 0i ΔQ represents the initial hydrocarbon generation potential of the i-th sample; i Let represent the amount of hydrocarbons emitted from the i-th sample.

[0135] See attached document Figure 4 In some embodiments, regression analysis is performed on the hydrocarbon expulsion ratio and the geochemical data to obtain a correlation model between the hydrocarbon expulsion ratio and the geochemical data, which may include:

[0136] S401: Perform regression analysis on the hydrocarbon excretion ratio and total organic carbon, and the hydrocarbon excretion ratio and vitrinite reflectance, respectively, to determine the first correlation between the hydrocarbon excretion ratio and total organic carbon, and the second correlation between the hydrocarbon excretion ratio and vitrinite reflectance;

[0137] S402: Alignment is performed based on the hydrocarbon expulsion ratio to generate a three-dimensional correlation model based on the first and second two-dimensional correlation relationships.

[0138] In some embodiments, regression analysis is performed on the hydrocarbon expulsion ratio, total organic carbon, and vitrinite reflectance of several screened source rock samples. This allows for the establishment of a first correlation between the hydrocarbon expulsion ratio and total organic carbon, and a second correlation between the hydrocarbon expulsion ratio and vitrinite reflectance. Both the first and second correlations can be represented in two-dimensional space. Since both the first and second correlations have a hydrocarbon expulsion ratio dimension, a three-dimensional correlation model of hydrocarbon expulsion ratio-total organic carbon-vitrinite reflectance can be established by aligning the hydrocarbon expulsion ratio dimension. This enables the rapid and accurate determination of the distribution of total organic carbon and vitrinite reflectance of source rock samples based solely on the lower limit of the hydrocarbon expulsion ratio.

[0139] See attached document Figure 5 In some embodiments, a preset lower limit for hydrocarbon expulsion is input into the correlation model to obtain the lower limit for organic matter abundance and the lower limit for organic matter maturity of the target reservoir, which may include:

[0140] S501: The total organic carbon is used as an indicator of organic matter abundance, and the vitrinite reflectance is used as an indicator of organic matter maturity.

[0141] S502: Input the preset lower limit value of hydrocarbon emission into the correlation model to determine the value range of the organic matter abundance measurement index and the organic matter maturity measurement index under the constraint that the hydrocarbon emission ratio is greater than the lower limit value of hydrocarbon emission.

[0142] S503: Determine the lower limit of organic matter abundance and the lower limit of organic matter maturity of the target reservoir based on the value range.

[0143] It can be understood that, in some embodiments, organic matter abundance and organic matter maturity are important indicators for measuring the hydrocarbon generation capacity of source rocks. Both organic matter abundance and organic matter maturity can be evaluated using various evaluation standards. In the typical embodiments of this specification, total organic carbon can be used as an indicator of organic matter abundance and vitrinite reflectance can be used as an indicator of organic matter maturity. Without introducing new evaluation indicators, the lower limit of organic matter abundance and the lower limit of organic matter maturity of the target reservoir can be quickly and accurately determined on the premise that the hydrocarbon expulsion ratio is greater than the lower limit of hydrocarbon expulsion.

[0144] Furthermore, to facilitate understanding by those skilled in the art, the method described in this specification is further explained using a specific work area as an example. This work area has a series of relatively independent oil and gas-bearing fault depressions. In some embodiments, rock pyrolysis experiments, total organic carbon and vitrinite reflectance tests are performed on several source rock samples from this work area to obtain geochemical data corresponding to several source rock samples. The geochemical data includes at least S1, S2, total organic carbon and vitrinite reflectance. Analyzing the geochemical data can yield hydrocarbon generation and expulsion trends. The hydrocarbon generation and expulsion trends and hydrocarbon generation conversion rates can be referred to the appendix respectively. Figure 6a and appendix Figure 6b ,exist Figure 6a In the diagram, HI represents the hydrocarbon index, indicating the remaining hydrocarbon generation potential in the source rock; the Optimal HI trajectory represents the best hydrocarbon generation conversion path selected in the Monte Carlo simulation; and the Simulated trajectory represents different hydrocarbon generation evolution paths tested during the simulation. Figure 6b In the middle, the vertical axis HI TR The hydrocarbon generation conversion rate of the source rock is dimensionless, with 0.1 representing 10%. Ro is the vitrinite reflectance. To ensure the accuracy of the subsequent correlation model, a reference is attached. Figure 6a and Figure 6b The curves and distribution points in the data should be as abundant as possible. However, due to operational cost constraints, if it's difficult to achieve a sufficiently rich variety of curves and distribution points, priority should be given to maximizing the range of Ro. In a typical embodiment, the distribution range of Ro is at least 0.5%-1.2%. Subsequently, in some embodiments, source rock samples are screened based on geochemical data, and the corresponding hydrocarbon expulsion ratio is calculated based on the screened source rock samples to plot the data. Figure 7 The diagram showing the lower limit of total organic carbon in effective source rocks and Figure 8 The diagram shows the lower limit of vitrinite reflectance of effective source rocks. The lower limit of total organic carbon in effective source rocks is 0.3%, and the lower limit of vitrinite reflectance is 0.62%. Figure 7 and Figure 8 Alignment based on hydrocarbon expulsion ratio can yield the following: Figure 9 The diagram shown is a three-dimensional schematic for identifying the comprehensive lower limit of effective source rocks. In some embodiments, the lower limit of hydrocarbon expulsion can be obtained based on historical experience. For example, immature source rock samples with Ro < 0.5% are selected in the traditional sense, and the average hydrocarbon expulsion ratio of the immature source rock samples is calculated to obtain 6%, which is used as the lower limit of hydrocarbon expulsion.

[0145] Furthermore, in some embodiments, since the source rock samples obtained from the target reservoir may differ due to the complex internal structure and composition, the process of obtaining geochemical data from the source rock samples may further include:

[0146] Source rock samples were classified and evaluated based on different classification results to obtain the lower limits of organic matter abundance and organic matter maturity of multiple groups of effective source rocks. Then, the lower limits of organic matter abundance and organic matter maturity of the final target reservoir were selected from the lower limits of organic matter abundance and organic matter maturity of multiple groups of effective source rocks.

[0147] Furthermore, in some embodiments, the classification criteria include at least one or more of lithology, kerogen type, sedimentary facies, lithological type, and sedimentary structure. Specifically, from a lithological perspective, source rocks typically include mudstone and shale, and limestone, with intermediate types such as argillaceous limestone and calcareous mudstone, depending on mineral content. The lower limit for hydrocarbon generation and expulsion is mudstone > carbonate rock. Mudstone (clay minerals) usually has a strong adsorption capacity, requiring more organic matter to generate more hydrocarbons for expulsion. From a kerogen type perspective, source rocks are typically classified into four types: I, II1, II2, and III. The lower limit for hydrocarbon generation and expulsion is I < II1 < II2 < III, meaning that type I is of the highest quality and requires less organic matter for generation and expulsion. Hydrocarbons; from a sedimentary facies perspective, source rocks vary greatly depending on the sedimentary environment; taking terrestrial mudstone and shale as an example, deep lacustrine facies > semi-deep lacustrine > shallow lacustrine; from a lithological type perspective, based on the content of clay minerals, siliceous minerals, and calcareous minerals, they can be divided into clayey mudstone and shale, siliceous mudstone and shale, calcareous mudstone and shale, and mixed mudstone and shale, generally clayey mudstone and shale > calcareous mudstone and shale > siliceous mudstone and shale, while mixed mudstone and shale depends on the specific content; from a sedimentary structure perspective, sedimentary structures can be divided into laminated, layered, and massive source rocks, generally laminated mudstone and shale > layered mudstone and shale > massive mudstone and shale. The development of layers makes it easier for hydrocarbons to be expelled. Therefore, based on the matching degree between the target reservoir and the classification criteria, the lower limit of organic matter abundance and the lower limit of organic matter maturity with the highest matching degree are selected. Of course, in some embodiments, other methods can be used to select the lower limit of organic matter abundance and the lower limit of organic matter maturity of the target reservoir, which are not limited in this paper.

[0148] It should be noted that although the operation of the method of the present invention has been described in a specific order in the above embodiments and figures, this does not require or imply that the operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0149] Corresponding to the above-described method for identifying the lower limit of effective source rocks, some embodiments of this specification also provide a device for identifying the lower limit of effective source rocks, see reference. Figure 10 As shown, in some embodiments, the apparatus may include:

[0150] The receiving module 1001 is used to acquire geochemical data of several source rock samples in the target reservoir;

[0151] The correction module 1002 is used to perform hydrocarbon generation correction on the geochemical data to determine the current hydrocarbon generation potential of the source rock sample;

[0152] Analysis module 1003 is used to analyze the hydrocarbon generation and expulsion trends of the source rock sample based on hydrocarbon generation kinetics according to the corrected geochemical data.

[0153] The determination module 1004 is used to determine the original hydrocarbon generation potential of the source rock sample by utilizing the hydrocarbon generation and expulsion trends and the current hydrocarbon generation potential.

[0154] The micro-transport hydrocarbon calculation module 1005 is used to calculate the micro-transport hydrocarbon amount of the source rock sample based on the current hydrocarbon generation potential and the original hydrocarbon generation potential of the source rock sample.

[0155] The screening module 1006 is used to screen source rock samples from the source rock samples to obtain source rock samples that meet the preset requirements for micro-transported hydrocarbon content;

[0156] The hydrocarbon expulsion ratio calculation module 1007 is used to determine the hydrocarbon expulsion ratio of the screened source rock sample based on the ratio of the amount of micro-transported hydrocarbons to the original hydrocarbon generation potential.

[0157] The regression module 1008 is used to perform regression analysis on the hydrocarbon excretion ratio and the geochemical data to obtain the correlation model between the hydrocarbon excretion ratio and the geochemical data.

[0158] The identification module 1009 is used to input the preset hydrocarbon emission lower limit value into the correlation model to obtain the lower limit of organic matter abundance and the lower limit of organic matter maturity of the target reservoir.

[0159] For ease of description, the above devices are described in terms of function, divided into various units. Of course, in implementing this specification, the functions of each unit can be implemented in one or more software and / or hardware components.

[0160] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in the embodiments of this specification are all information and data authorized and agreed upon by the user and fully authorized by all parties.

[0161] It should be noted that the computer program product of this specification (this application) is a software product that mainly implements the methods of this specification (this application) through a computer program.

[0162] Embodiments of this specification also provide a computer device. For example... Figure 11As shown, in some embodiments of this specification, computer device 1102 may include one or more processors 1104, such as one or more central processing units (CPUs) or graphics processing units (GPUs), each processing unit implementing one or more hardware threads. Computer device 1102 may also include any memory 1106 for storing information of any kind, such as code, settings, data, etc. In one specific embodiment, a computer program is stored on memory 1106 and can run on processor 1104. When the computer program is run by processor 1104, it can execute instructions of the methods of any of the above embodiments. Non-limitingly, for example, memory 1106 may include any type of RAM, any type of ROM, flash memory device, hard disk, optical disk, etc. More generally, any memory can use any technology to store information. Further, any memory can provide volatile or non-volatile retention of information. Further, any memory can represent a fixed or removable component of computer device 1102. In one case, when processor 1104 executes associated instructions stored in any memory or combination of memories, computer device 1102 can perform any operation of the associated instructions. The computer device 1102 also includes one or more drive mechanisms 1108 for interacting with any memory, such as a hard disk drive mechanism, an optical disk drive mechanism, etc.

[0163] Computer device 1102 may also include an input / output interface 1110 (I / O) for receiving various inputs (via input device 1112) and providing various outputs (via output device 1114). A specific output mechanism may include a presentation device 1116 and an associated graphical user interface 1118 (GUI). In other embodiments, the input / output interface 1110 (I / O), input device 1112, and output device 1114 may be omitted, and the device may function solely as a computer device within a network. Computer device 1102 may also include one or more network interfaces 1120 for exchanging data with other devices via one or more communication links 1122. One or more communication buses 1124 couple the components described above together.

[0164] Communication link 1122 can be implemented in any way, such as via a local area network, a wide area network (e.g., the Internet), a point-to-point connection, or any combination thereof. Communication link 1122 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.

[0165] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), computer-readable storage media, and computer program products according to some embodiments of this specification. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processor to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processor, create a mechanism for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0166] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processor to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0167] These computer program instructions may also be loaded onto a computer or other programmable data processor, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable device for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0168] In a typical configuration, a computer device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0169] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0170] Computer-readable media, including both permanent and non-permanent, removable and non-removable media, can store information using any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by computer equipment. As defined in this specification, computer-readable media does not include transient media, such as modulated data signals and carrier waves.

[0171] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, the embodiments of this specification can take the form of computer program products implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0172] The embodiments described in this specification can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. The embodiments of this specification can also be practiced in distributed computing environments where tasks are performed by remote processors connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0173] It should also be understood that, in the embodiments of this specification, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0174] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0175] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the embodiments of this specification. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0176] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. An effective method for identifying the lower limit of hydrocarbon source rocks, characterized in that, The method includes: Obtain geochemical data from several source rock samples in the target reservoir; Hydrocarbon generation correction is performed on the geochemical data to determine the current hydrocarbon generation potential of the source rock sample; Based on the corrected geochemical data, the hydrocarbon generation and expulsion trends of the source rock samples were analyzed using hydrocarbon generation kinetics. The original hydrocarbon generation potential of the source rock sample is determined by using the aforementioned hydrocarbon generation and expulsion trends and current hydrocarbon generation potential. Calculate the amount of micro-transported hydrocarbons in the source rock sample based on its current hydrocarbon generation potential and original hydrocarbon generation potential. Source rock samples that meet the preset requirements for micro-transported hydrocarbon content are screened from the source rock samples; The hydrocarbon expulsion ratio of the screened source rock samples is determined based on the ratio of the amount of micro-transported hydrocarbons to the original hydrocarbon generation potential. Regression analysis was performed on the hydrocarbon excretion ratio and the geochemical data to obtain a correlation model between the hydrocarbon excretion ratio and the geochemical data. By inputting the preset lower limit value of hydrocarbon expulsion into the correlation model, the lower limit of organic matter abundance and the lower limit of organic matter maturity of the target reservoir are obtained. The process includes performing regression analysis on the hydrocarbon expulsion ratio and the geochemical data to obtain a correlation model between the hydrocarbon expulsion ratio and the geochemical data, including: Regression analyses were performed on the hydrocarbon excretion ratio and total organic carbon, and on the hydrocarbon excretion ratio and vitrinite reflectance, respectively, to determine the first correlation between the hydrocarbon excretion ratio and total organic carbon, and the second correlation between the hydrocarbon excretion ratio and vitrinite reflectance. Alignment is performed based on the hydrocarbon expulsion ratio to generate a three-dimensional correlation model based on the first and second two-dimensional correlation relationships; By inputting the preset hydrocarbon expulsion lower limit into the correlation model, the lower limits of organic matter abundance and organic matter maturity of the target reservoir are obtained, including: The total organic carbon is used as an indicator of organic matter abundance, and the vitrinite reflectance is used as an indicator of organic matter maturity. The preset lower limit value of hydrocarbon emission is input into the correlation model to determine the value range of the organic matter abundance measurement index and the organic matter maturity measurement index under the constraint that the hydrocarbon emission ratio is greater than the lower limit value of hydrocarbon emission. The lower limit of organic matter abundance and the lower limit of organic matter maturity of the target reservoir are determined based on the range of values.

2. The method according to claim 1, characterized in that, The geochemical data includes at least one or more of rock pyrolysis data, total organic carbon, and vitrinite reflectance; the rock pyrolysis data includes at least the first peak data and the second peak data generated by the pyrolysis of the source rock sample.

3. The method according to claim 2, characterized in that, Hydrocarbon generation correction is performed on the geochemical data to determine the current hydrocarbon generation potential of the source rock sample, including: The lost hydrocarbons in the first peak data are corrected by using freeze-pyrolysis, and the adsorbed hydrocarbons in the second peak data are corrected by using multi-temperature-level pyrolysis, so as to achieve the correction of generated hydrocarbons in the rock pyrolysis data in the geochemical data; Light hydrocarbon correction was performed based on the corrected rock pyrolysis data and total organic carbon to determine the current hydrocarbon generation potential of the source rock sample.

4. The method according to claim 2, characterized in that, Based on the corrected geochemical data, the hydrocarbon generation and expulsion trends of the source rock samples were analyzed using hydrocarbon generation kinetics, including: The vitrinite reflectance is used as the degree of thermal evolution of the source rock sample, and the hydrocarbon generation and expulsion trend is determined based on hydrocarbon generation kinetics using the following formula: and / or in, The reflectance of vitrinite. This represents the changing trend of the original hydrocarbon generation conversion potential, used to indicate the trend of hydrocarbon generation and expulsion. This represents the potential for converting original hydrocarbons. The range of the hydrocarbon generation window, This was a period of high hydrocarbon generation. This represents the changing trend of the original hydrocarbon generation potential, used to indicate the trend of hydrocarbon generation and expulsion. This represents the original hydrocarbon generation potential. The range of the hydrocarbon expulsion window, This was a period of significant hydrocarbon emissions.

5. The method according to claim 4, characterized in that, Determining the original hydrocarbon generation potential of the source rock sample using the aforementioned hydrocarbon generation and expulsion trends and current hydrocarbon generation potential includes: The original hydrocarbon generation potential corresponding to the current hydrocarbon generation potential is determined based on the hydrocarbon generation and emission trend.

6. The method according to claim 1, characterized in that, Based on the current and original hydrocarbon generation potential of the source rock sample, the amount of micro-transported hydrocarbons in the source rock sample is calculated, including: The amount of micro-transported hydrocarbons is obtained by subtracting the current hydrocarbon generation potential from the original hydrocarbon generation potential.

7. The method according to claim 1, characterized in that, Source rock samples that meet the preset requirements for micro-transported hydrocarbon content are screened from the source rock samples, including: Source rock samples are selected from the source rock samples whose micro-transported hydrocarbon content is greater than a first threshold, and the first threshold is a non-negative number.

8. An effective hydrocarbon source rock lower limit identification device, characterized in that, The device includes: The receiving module is used to acquire geochemical data of several source rock samples in the target reservoir; A correction module is used to perform hydrocarbon generation correction on the geochemical data to determine the current hydrocarbon generation potential of the source rock sample; The analysis module is used to analyze the hydrocarbon generation and expulsion trends of the source rock sample based on hydrocarbon generation kinetics, using corrected geochemical data. The determination module is used to determine the original hydrocarbon generation potential of the source rock sample by utilizing the hydrocarbon generation and expulsion trends and the current hydrocarbon generation potential. The micro-transport hydrocarbon calculation module is used to calculate the micro-transport hydrocarbon amount of the source rock sample based on the current hydrocarbon generation potential and the original hydrocarbon generation potential of the source rock sample. The screening module is used to screen source rock samples from the source rock samples to obtain source rock samples that meet the preset requirements for micro-transported hydrocarbon content; The hydrocarbon expulsion ratio calculation module is used to determine the hydrocarbon expulsion ratio of the screened source rock sample based on the ratio of the amount of micro-transported hydrocarbons to the original hydrocarbon generation potential. A regression module is used to perform regression analysis on the hydrocarbon excretion ratio and the geochemical data to obtain a correlation model between the hydrocarbon excretion ratio and the geochemical data. Specifically, regression analysis is performed on the hydrocarbon excretion ratio and total organic carbon, and on the hydrocarbon excretion ratio and vitrinite reflectance, respectively, to determine a first correlation between the hydrocarbon excretion ratio and total organic carbon, and a second correlation between the hydrocarbon excretion ratio and vitrinite reflectance. Alignment is then performed based on the hydrocarbon excretion ratio to generate a three-dimensional correlation model based on the two-dimensional first and second correlation relationships. The identification module is used to input a preset lower limit value for hydrocarbon expulsion into the correlation model to obtain the lower limit of organic matter abundance and the lower limit of organic matter maturity of the target reservoir; wherein, the total organic carbon is used as an indicator of organic matter abundance and the vitrinite reflectance is used as an indicator of organic matter maturity; the preset lower limit value for hydrocarbon expulsion is input into the correlation model to determine the value range of the indicator of organic matter abundance and the indicator of organic matter maturity under the constraint that the hydrocarbon expulsion ratio is greater than the lower limit value for hydrocarbon expulsion; the lower limit of organic matter abundance and the lower limit of organic matter maturity of the target reservoir are determined according to the value range.

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