Method for determining microcosmic characteristic influence factors of shale reservoir

Abstract

The invention provides a method for determining microcosmic characteristic influence factors of a shale reservoir. The method comprises the steps of rock core observation, sampling and experiment, and lithofacies type division according to rock core observation and experiment results; performing characteristic evaluation on different types of lithofacies, and determining favorable lithofacies types; analyzing reservoir microscopic characteristics of different types of lithofacies; and according to an analysis result, determining factors influencing the microscopic characteristics of the reservoir. According to the method, favorable lithofacies and reservoir microscopic feature analysis can be comprehensively and effectively carried out, the evaluation accuracy is improved, and the accuracy is improved by 40% and reaches 90%; the working efficiency is improved, invalid work is avoided, the workload of two persons in 10 days is reduced to be completed by one person in 10 days, and lithofacies evaluation and reservoir microscopic feature influence factor analysis can be efficiently completed.

Description

Technical Field

[0001] This invention belongs to the field of unconventional oil and gas exploration and development, and specifically relates to a method for determining the influencing factors of the microscopic characteristics of shale reservoirs. Background Technology

[0002] Shale reservoir characteristics, shale oil occurrence patterns, and fluidity are the core and key issues in shale oil geological research. Reservoir characteristics are the foundation of this research, encompassing the matching relationship between material composition and reservoir space, as well as the size, distribution, morphology, and connectivity of reservoir space. Current technologies consider micro- and nano-scale pore and fracture systems to be the primary spaces for hydrocarbon enrichment in shale. Characterizing and delineating these reservoir spaces is a prerequisite for effective shale oil evaluation and a core element in analyzing hydrocarbon occurrence states and enrichment mechanisms.

[0003] A method for determining shale bedding fracture porosity and evaluating oil and gas reservoirs (CN118777150A) discloses the following steps: Helium porosity testing is performed on shale samples to obtain the total porosity value; a low-temperature carbon dioxide adsorption experiment is conducted on the shale samples that have completed the helium porosity test to obtain the matrix micropore porosity value; the bedding surfaces of the shale samples that have completed the low-temperature carbon dioxide adsorption experiment are encapsulated with epoxy resin, and directional mercury intrusion porosimetry is performed perpendicular to the bedding direction to obtain the matrix macropore porosity value and matrix fracture porosity value, wherein the matrix macropores are matrix porosities greater than or equal to a preset threshold; the shale bedding fracture porosity value is obtained by subtracting the matrix micropore porosity value, matrix macropore porosity value, and matrix fracture porosity value from the obtained total porosity value.

[0004] A reservoir analysis method and system for shale oil reservoirs (CN118933718A) discloses the following steps: acquiring logging and well logging data of the section to be tested to determine the shale section to be tested; acquiring logging and well logging data of the shale section to be tested to determine the reservoir characteristic data of the shale section to be tested; inputting the reservoir characteristic data into a preset reservoir analysis coordinate system to obtain the reservoir analysis results of the shale section to be tested, wherein the reservoir analysis coordinate system is constructed based on the reservoir characteristics.

[0005] A method and system for quantitative characterization of pore space in shale oil reservoirs (CN119322081A) discloses the following: statistical analysis of micron-level equivalent pore structure parameters of shale oil reservoirs; statistical analysis of nano-level organic pore structure parameters of shale oil reservoirs; standardization of the micron-level equivalent pore structure parameters and the nano-level organic pore structure parameters to obtain the theoretical volume of the standardized pore structure in different intervals at different resolutions of the reservoir sample; calculation of the volume fraction of the theoretical volume in the standardized total pores and the volume fraction in the reservoir sample; and establishment of a full-scale pore distribution curve based on each volume fraction to characterize the proportion of pore volume of different pore sizes in the shale oil reservoir.

[0006] A method, apparatus, device, and storage medium for processing shale FIB-SEM images (CN119515708A) discloses: acquiring a shale sample FIB-SEM image to be processed; performing horizontal edge-preserving filtering on the FIB-SEM image to be processed to obtain a horizontal filtering result; and decomposing and removing vertical stripe noise based on the horizontal filtering result to obtain a target FIB-SEM image of the shale sample. By sequentially performing horizontal edge-preserving filtering and vertical stripe noise decomposition on the shale FIB-SEM image, vertical stripe noise is decomposed and eliminated while ensuring horizontal edge stability, thus obtaining an improved shale FIB-SEM image.

[0007] A method, apparatus, and equipment for determining pore-throat characteristics of shale (CN119470197A) discloses: obtaining a first water content, a second water content, and a third water content of a core sample from a target shale reservoir, wherein the first water content is used to characterize the water content of a dried core sample, the second water content is used to characterize the water content of a core sample saturated with fluid, and the third water content is used to characterize the water content of a centrifuged core sample; determining the movable water volume of the core sample based on the second and third water contents; determining the throat-bound water volume of the core sample based on the first and third water contents; and determining the pore-throat volume ratio of the target shale reservoir based on the movable water volume and the throat-bound water volume.

[0008] A method, apparatus, electronic device, and storage medium for identifying shale pore types (CN119667807A) discloses the following: The organic carbon content of the target stratum in the study area is calculated based on the acoustic logging curves, resistivity, and gamma ray. The porosity of the target stratum in the study area is calculated based on the acoustic logging curves. The organic porosity is determined using the organic carbon content, porosity, percentage of organic carbon converted to hydrocarbons in the shale, carbon index, apparent density of the shale, and skeletal density of organic matter. Based on the organic carbon content and porosity, an organic porosity estimation chart is constructed, and based on the organic porosity estimation chart and organic porosity, a semi-quantitative identification of pore types in highly mature shale is performed.

[0009] The article "Characteristics and Main Controlling Factors of High-Yield Shale Oil Reservoirs in the Fengcheng Formation of the Permian System in the Mahu Depression," published by Qian Yongxin et al. in January 2025 in Volume 37, Issue 1 of *Lithologic Oil and Gas Reservoirs*, records a detailed study on the reservoir characteristics and main controlling factors of high-yield shale oil in the Fengcheng Formation of the Permian System in the Mahu Depression through experimental analysis and testing data including thin sections, scanning electron microscopy, low-temperature nitrogen adsorption, high-pressure mercury intrusion porosimetry, core fluorescence, laser confocal microscopy, and production profiles. The results show that: ① The shale oil reservoirs in the Fengcheng Formation of the Permian System in the Mahu Depression can be classified into sandstone, dolomite, and mudstone types. Siltstone reservoirs are mainly composed of terrigenous clastic sediments, mudstone reservoirs are mainly composed of terrigenous-endogenous mixed sediments, and dolomite (gray) reservoirs are mainly composed of endogenous chemical sediments. The pore throat size and pore connectivity of the siltstone, dolomite, and mudstone reservoirs in the Fengcheng Formation of the Mahu Depression decrease sequentially. ② The Fengcheng Formation siltstone reservoirs in the Mahu Depression have the best oil-bearing potential, followed by mudstone reservoirs, while dolomite reservoirs have the worst oil-bearing potential. Larger pores and microfractures contain higher levels of free oil, while smaller pores contain higher levels of adsorbed oil. ③ High-quality source rocks and reservoirs in the Fengcheng Formation of the Mahu Depression control the high-yield areas and high-yield intervals of shale oil, respectively. Reservoirs with higher felsic mineral content, effective porosity, free oil porosity, fracture density, and brittleness index are favorable intervals for high shale oil production.

[0010] The article "Pore Structure Characteristics and Main Controlling Factors of Chang 7 Member Interlayer Shale Oil Reservoir in Heshui South Area" published by Fu Linpu et al. in Volume 49, Issue 1 of the Journal of Northeast Petroleum University records that: taking the Chang 7 Member interlayer shale oil reservoir in the Heshui South area of ​​the Ordos Basin as an example, the pore structure characteristics of the Chang 7 Member interlayer shale oil reservoir in the Heshui South area were analyzed by casting thin section, scanning electron microscopy, XRD analysis, high pressure mercury intrusion, constant rate mercury intrusion and nitrogen adsorption experiments, and the control effect of sedimentation and diagenesis on pore structure was explored. The results show that the average porosity of the Chang 7 shale oil reservoir in the Heshui South area is 8.47%, and the average permeability is 0.74 × 10⁻³ μm², classifying it as a typical ultra-low porosity and ultra-low permeability reservoir. The pore types are mainly residual intergranular pores and feldspar dissolution pores, with pore throat radii concentrated between 0.02 and 200.00 μm. The pore morphology is mainly plate-like parallel slit pores and semi-closed wedge pores. The pore structure is jointly controlled by sedimentary and diagenetic processes. Sedimentation laid the material basis for the shale oil reservoir, resulting in fine-grained sediments, high matrix volume fraction, and low initial porosity and permeability. During the strong compaction stage, the reservoir lost a large amount of intergranular porosity, and cementation further reduced reservoir properties. Later dissolution altered the reservoir, leading to the formation of dominant reservoirs. Sandy clastic flow sand bodies experienced significant porosity reduction due to cementation, while turbidite flow sand bodies experienced significant porosity reduction due to compaction. The sandy clastic flow sand bodies, having undergone moderate compaction, strong cementation, and moderate dissolution, are the main cause of the dominant reservoirs in the study area.

[0011] The article "Pore Structure Characteristics and Main Controlling Factors of Qiongzhusi Formation Shale in Southern Sichuan (Lower Cambrian)" published by Luo Sicong et al. in December 2024 in Volume 46, Issue 6 of the Journal of Southwest Petroleum University (Natural Science Edition) records that: In order to evaluate the characteristics and differences of two types of shale reservoirs in Qiongzhusi Formation in southern Sichuan, based on core data from drilling systems, and by comprehensively using experimental methods such as X-ray diffraction, argon ion polishing scanning electron microscopy, high-pressure mercury intrusion, and low-temperature N2 and CO2 adsorption, the TOC content, mineral composition, micropore type, pore structure characteristics and influencing factors of the two types of shale reservoirs were studied. Studies show that both types of shale reservoirs develop various types of micropores, with inorganic pores dominating overall. The proportion of organic pores is higher in organic-rich shale than in shale containing organic matter. The porosity of organic-containing shale (TOC content <1%) is 4.78%–6.02% (average 5.22%), with reservoir pore sizes mainly ranging from 20 to 100 nm, and macropores being the primary reservoir space (average 70.10%). The porosity of organic-rich shale (TOC content >1%) is 3.88%–7.06% (average 5.53%), with reservoir pore sizes mainly ranging from 1 to 50 nm, and mesopores being the primary reservoir space (average 81.81%). The specific surface area and volume of micropores in organic-containing shale are positively correlated with TOC content, while the specific surface area and volume of both micropores and mesopores in organic-rich shale are positively correlated with TOC content. The relationship between the two types of shale reservoirs and mineral composition is complex. The supporting structure constructed by quartz and feldspar lays the foundation for the original inorganic pores. TOC, clay minerals, and later diagenetic minerals fill the intergranular pores, changing the pore structure. The increase in TOC content has increased the proportion of organic pores to a certain extent.

[0012] The article "Pore Structure and Development Controlling Factors of Wujiaping Formation Shale Reservoirs in Eastern Sichuan," published by Gu Tianfu et al. in January 2025 in Volume 32, Issue 1 of *Fault-Block Oil and Gas Fields*, clarifies the pore structure and development influencing factors of the Wujiaping Formation shale reservoirs based on thin section and scanning electron microscopy observations, combined with TOC (total organic carbon) testing, X-ray diffraction analysis, and low-pressure gas adsorption experiments. The results show that: 1) Wujiaping Formation 1 and 2 are clayey shale and mixed shale, while Wujiaping Formation 3 is siliceous shale, calcareous shale, and mixed shale. 2) The reservoir space mainly consists of fractures, intergranular pores, and intragranular pores. Organic matter pores are relatively small, exhibiting ink bottle-like, plate-like, or slit-like pore shapes. Pore diameters are distributed in the range of 0.84–14.10 nm with a "multi-peak, multi-scale" characteristic. Pores smaller than 60 nm and 10 nm are the main contributors to the total pore volume and specific surface area, respectively. The shale exhibits high heterogeneity, with the heterogeneity within the pores being greater than that on the pore surface. 3) Increased quartz content promotes mesopore development, inhibits micropore formation, and enhances heterogeneity. Increased carbonate mineral content is detrimental to the development of micropores and mesopores but enhances reservoir heterogeneity. Increased clay mineral content and TOC promote micropore development and enhance reservoir homogeneity. 4) Based on pore type and mineral content, the Wujiaping Formation shale is divided into fracture-inorganic porous reservoirs with high clay mineral content and those with high brittle mineral content.

[0013] The article "Pore Structure Characteristics and Main Controlling Factors of Longmaxi Formation Shale in Northeast Chongqing," published by Fu Wending et al. in December 2024 in Volume 44, Issue 4 of *Sedimentary and Tethys Geology*, describes how, to investigate the pore structure characteristics and main controlling factors of deformed shale from the Longmaxi Formation in Northeast Chongqing, 12 shale samples were collected. The pore structure characteristics were systematically characterized using field emission scanning electron microscopy, liquid nitrogen adsorption, and carbon dioxide adsorption methods, and compared with pore structure parameters of Longmaxi Formation shale from different tectonic zones in the Sichuan Basin. The results show that the pores in the Longmaxi Formation shale in Northeast Chongqing mainly consist of organic pores, inorganic pores, and microfractures. Compared with marine shale of similar maturity in southern Sichuan Basin, the organic pores in the samples are less developed and smaller in size. Furthermore, inorganic pores and microfractures are relatively well-developed in the Longmaxi Formation shale of Northeast Chongqing. Based on the characteristics of pore and fracture development, inorganic pores can be classified into three categories: intergranular pores, clay mineral interlayer pores, and intragranular pores. Microfractures can be classified into organic matter-related microfractures and inorganic mineral-related microfractures. The effect of TOC content on micropores in the Longmaxi Formation shale of northeastern Chongqing exhibits a staged variation. When TOC < 5.93%, TOC content shows a strong positive correlation with micropore volume and specific surface area; when TOC > 5.93%, a negative correlation is shown. TOC content is not correlated with mesopore parameters, and the content of clay minerals and brittle minerals is not significantly correlated with shale porosity development. Scanning electron microscopy images show that increased tectonic compression intensity leads to a decrease in the number of pores in the Longmaxi Formation shale of northeastern Chongqing, and pore connectivity is disrupted to some extent. This causes the conversion of free shale gas in the shale reservoir into adsorbed shale gas, resulting in strong gas adsorption and storage primarily in the adsorbed form, thus improving the shale's gas storage capacity.

[0014] The article "Differences in Pore Structure and Evolution Patterns During Gas Reservoir Uplift: A Case Study of the Wufeng-Longmaxi Formation Shale Reservoirs in the Sichuan Basin and its Surrounding Areas," published by Wang Dandan et al. in the *Acta Geologica Sinica* in January 2025, records that: In the same pressure zone, organic-rich siliceous shale has a larger specific surface area, pore volume, and fractal dimension than organic-poor clayey shale; TOC has a greater impact on specific surface area and pore volume than clay minerals; In different pressure zones, organic-rich siliceous shale facies uplifted later, and shale with smaller uplift amplitude has a larger specific surface area, pore volume, roundness coefficient, and fractal dimension; Overpressure has a pore-preserving effect, preventing pores from being compacted and resulting in less deformation; The influence of rock facies on shale pore specific surface area is mainly reflected in micropores, while the influence of overpressure on shale pore volume is mainly reflected in mesopores and macropores.

[0015] The article "Dominant Reservoir Space and Its Main Controlling Factors in Continental Shale—A Case Study of the Paleogene System in the Subei Basin," published by Xing Lele et al. in February 2025 in *Fault-Block Oil and Gas Fields*, records that clay mineral transformation, organic matter hydrocarbon generation evolution, and dissolution shape the formation and development of reservoir space. The dominant reservoir space in continental shale is mainly composed of intergranular (crystal) pores of clay minerals, followed by dissolution pores; the development of microfractures effectively connects numerous pores, expanding the reservoir space. Carbonate rocks, fine-grained felsic rocks, and felsic-dolomite mixed sedimentary rocks exhibit better physical properties.

[0016] The article "Differences in Pore Structure and Main Controlling Factors of Different Sedimentary Microfacies in Deep Shale—Taking the Wufeng Formation-Longmaxi Formation of Well Z301 in Zigong Area, Southern Sichuan Basin as an Example" published by Li Zhe et al. in Natural Gas Geoscience in September 2024 states: In order to explore the differences in pore structure and main controlling factors of different sedimentary microfacies in deep shale, the Wufeng Formation-Longmaxi Formation of Well Z301 in Zigong Area, southern Sichuan Basin, was systematically cored. The article systematically carried out core-thin section-scanning electron microscopy observation, mineral content analysis, organic geochemical analysis, and N2 / CO2 adsorption and high-pressure mercury intrusion experiments. The vertical differences in pore structure of the Wufeng Formation-Longmaxi Formation shale reservoir were discussed and analyzed.

[0017] The article "Differences in Laminar Structure of Carbonate-Rich Shale in Jiyang Depression and Its Influence on Reservoir Quality—Taking Shahejie Formation Shale in Dongying Depression as an Example," published by Ni Liangtian et al. in the November 2024 issue of the *Acta Petrolei Sinica*, states that differences in shale laminar structure are an important factor causing differences in shale pore structure, thus affecting reservoir quality. Through detailed core description, whole-rock X-ray diffraction analysis, thin-section identification, field emission scanning electron microscopy, and nuclear magnetic resonance experiments, the development types and characteristics of laminar structures in carbonate-rich shale in the Jiyang Depression were clarified.

[0018] The article "Characteristics and Main Controlling Factors of Permian Dalong Formation Shale Reservoirs in Northeast Sichuan" published by Wang Wei et al. in Petroleum and Natural Gas Geology in October 2024 describes the following: Taking the deep-water shelf facies shale of Dalong Formation as the research object, using argon ion polishing scanning electron microscopy, low-temperature nitrogen adsorption-desorption method and high-pressure mercury intrusion testing data, through geochemical and mineral composition characteristics studies, a comparative analysis was conducted with marine shale reservoirs such as Silurian Longmaxi Formation, Permian Maokou Formation No. 3 and Wujiaping Formation No. 2, and the main controlling factors of Dalong Formation reservoir development were proposed.

[0019] The article "Characteristics and Controlling Factors of Permian Fengcheng Formation Shale Oil Reservoirs in Mahu Depression, Junggar Basin" published by Xu Lin et al. in September 2019 in *China Petroleum Exploration* records that the controlling factors influencing the development of Fengcheng Formation shale oil reservoirs mainly include sedimentary environment and sedimentary facies, rock type, organic carbon content and occurrence mode, alkaline mineral content, diagenesis, and fractures. Among these, sedimentary environment and sedimentary facies restrict the scale of reservoir development and the development of early porosity; silty sandstone, argillaceous siltstone, and dolomite have relatively good reservoir performance; organic carbon content is positively correlated with reservoir physical properties; the higher the alkaline mineral content, the higher the reservoir porosity; dolomitization and dissolution determine the formation of secondary porosity; and the development of numerous fractures under tectonic activity serves as reservoir space and permeation channels, leading to the development of dissolution pores around the fractures, which plays a positive and constructive role in improving reservoir porosity and permeability conditions and reservoir performance.

[0020] The article "Main Controlling Factors of Shale Oil Reservoir Properties in the Xigouzui Formation of the Jianghan Basin," published by Li Wenhao et al. in *Petroleum and Natural Gas Geology* in February 2016, records that: the reservoir space type of shale oil reservoirs is mainly inorganic porosity (including intercrystalline pores, intergranular pores, and dissolution pores), with a small amount of organic porosity and microfractures also present; the argillaceous dolomite and dolomite in the area have the best porosity and permeability conditions; the shale oil reservoirs in the Yajiao-Xiangou low uplift and Chentuokou depression both have secondary porosity development zones, which greatly improve reservoir properties; the influence of mineral composition on the shale oil reservoir properties of the Yajiao-Xiangou low uplift and Chentuokou depression differs, with porosity in the former showing no correlation with mineral composition, while porosity in the latter shows a negative correlation with clay mineral and detrital mineral content, but a positive correlation with dolomite content; the permeability in the area shows a negative correlation with detrital mineral and clay content, but a positive correlation with dolomite content.

[0021] The article "The Controlling Role of Fine-Grained Sedimentary Microfacies in the Microstructure of Shale Oil Reservoirs in the Dongying Depression of the Bohai Bay Basin," published by Zhang Shun et al. in *Petroleum and Natural Gas Geology* in December 2016, records that the mudstone and shale in the Dongying Depression have diverse mineral types. The fine-grained sedimentary rocks, previously considered high-quality source rocks, are actually mostly carbonate rocks. The reservoirs exhibit diverse pore and fracture types, with multi-scale pores and complex structures. The microstructural characteristics of mudstone and shale reservoirs differ across microfacies. The controlling role of sedimentary microfacies in reservoir microstructure is mainly manifested in controlling the mineral composition and texture, and the deposition and preservation conditions of organic matter, thus affecting pore type and structure. Mudstone and shale reservoirs with well-developed flat, broad, and semi-deep lacustrine microfacies have high organic matter content, with calcite as the dominant brittle mineral. They exhibit diverse pore and fracture types, moderate pore connectivity, and good pore openness, and can be considered favorable facies zones for shale oil exploration and development.

[0022] The article "Microscopic Porosity Characteristics of Taiyuan Formation Mudstone and Shale Reservoirs in Qinnan, Shanxi" published by Liu Jiaonan et al. in Special Oil and Gas Reservoirs in April 2016 records that: organic carbon content is positively correlated with micropore volume content; organic matter maturity is related to micropore and mesopore content; clay mineral content is positively correlated with mesopore volume content; and brittle mineral content contributes significantly to macropore volume.

[0023] The article "Characteristics and Classification Scheme of Microscopic Pore System in Marine Shale Reservoirs" published by Wu Yue et al. in *Geological Science and Technology Information* in July 2014 describes how, based on the relationship between pore development location and rock matrix, and the relationship between pore development genesis and rock matrix, shale reservoir pores are classified into intergranular pores, intragranular pores, organic matter pores, and microfractures, as well as skeletal mineral pores, clay mineral pores, organic matter pores, and microfractures. The diagenesis of inorganic minerals and the thermal maturation of organic matter are important factors controlling the evolution of shale reservoir pores.

[0024] The article "Microscopic Pore Structure Characteristics and Development Controlling Factors of Shale Gas Reservoirs—Taking the Longmaxi Formation in the XX Area of ​​Southern Sichuan and Northern Guizhou as an Example" published by Wei Xiangfeng et al. in Natural Gas Geoscience in October 2013 states that the specific surface area and pore volume of the mudstone and shale in the study area are relatively large and have a good positive correlation. It is believed that the more developed the micropores, the larger the specific surface area and pore volume of the mudstone and shale, which is more conducive to the adsorption and storage of shale gas by the mudstone and shale.

[0025] Although the above classification scheme solves some problems, its application to the determination of influencing factors of microscopic characteristics of shale reservoirs still has certain limitations as described in the background technology. Summary of the Invention

[0026] This application provides a method for determining the influencing factors of the microstructure of shale reservoirs, which can comprehensively and effectively evaluate the influencing factors of reservoir microstructure and improve the accuracy of the evaluation of favorable shale intervals.

[0027] In a first aspect, embodiments of this application provide a method for determining the influencing factors of the microscopic characteristics of shale reservoirs, including:

[0028] Core observation, sampling, and experiments; lithofacies classification based on core observation and experimental results;

[0029] Characteristic evaluation of different types of lithofacies to identify favorable lithofacies types;

[0030] Analyze the microscopic characteristics of reservoirs of different lithofacies types;

[0031] Based on the analysis results, the factors affecting the microstructure of the reservoir were identified.

[0032] In some embodiments, core observation, sampling, and experiments, and the classification of lithofacies types based on core observation and experimental results, include: systematically observing cores, selecting typical samples for sampling according to differences in lithology and sedimentary structure characteristics, conducting parallel experiments on samples at the same depth, and experimental items including rock pyrolysis, X-ray diffraction whole-rock analysis, helium porosity, pulsed permeability, ordinary thin section identification, nitrogen adsorption, argon ion profile scanning electron microscopy, and nuclear magnetic resonance experimental testing and analysis.

[0033] In some embodiments, core observation, sampling, and experiments, and the classification of lithofacies types based on core observation and experimental results, include: taking cylindrical samples perpendicular to the bedding planes, cutting cylindrical sections of the same size from both ends for rock pyrolysis, X-ray diffraction whole-rock analysis, ordinary thin section identification, nitrogen adsorption, and scanning electron microscopy experiments; dividing the remaining samples equally, one portion for helium porosity and pulsed permeability experiments, and the other portion for nuclear magnetic resonance experiments; obtaining free hydrocarbon (S1) and organic carbon (TOC) parameters using pyrolysis experiments, and calculating... The oil saturation index (OSI) was determined; the percentage content of minerals was obtained through whole-rock X-ray diffraction experiments, and the content of brittle minerals was calculated. These minerals included quartz, feldspar, calcite, dolomite, and ferrodolomite; sedimentary structures and bedding types were analyzed using ordinary thin sections; pore structure, pore size, and pore connectivity types were analyzed using nitrogen adsorption; pore types were analyzed using scanning electron microscopy; porosity φ and permeability K were analyzed using helium porosity and pulsed permeability; and pore structure, pore size, and oil saturation (S0) were analyzed using nuclear magnetic resonance (NMR).

[0034] In some embodiments, core observation, sampling, and experiments, and the classification of lithofacies types based on the results of core observation and experiments, include: classifying lithofacies types based on organic carbon, sedimentary structures, and mineral composition.

[0035] In some embodiments, the characteristics of different types of lithofacies are evaluated to identify favorable lithofacies types, including: comparison of oil-bearing, mobility, reservoir and compressibility parameters of different lithofacies to identify favorable lithofacies types; oil-bearing analysis parameters include organic carbon (TOC), oil saturation (S0), and free oil (S1); mobility analysis parameters include oil saturation index (OSI); reservoir parameters include helium porosity (φ) and pulse permeability (K); and compressibility parameters include brittle mineral content.

[0036] In some embodiments, the reservoir microstructure characteristics of different types of lithofacies are analyzed, including: analyzing the bedding type, bedding thickness, bedding ratio, pore type, pore connectivity, and pore ratio of different pore sizes of different lithofacies; bedding type is classified according to different bedding mineral compositions and colors; bedding thickness is identified by ordinary thin sections; bedding ratio is obtained with the same scale and the same field of view; pore type is determined by argon ion scanning electron microscopy; pore connectivity is classified into H2 type, H2-H3 type, and H3 type based on the nitrogen adsorption-desorption curve type.

[0037] In some embodiments, based on the analysis results, the factors affecting the microscopic reservoir characteristics are determined as follows: analyzing the relationship between porosity, the proportion of pores of different sizes, pore connectivity and mineral composition; analyzing the relationship between the content of felsic minerals, carbonate minerals and clay minerals and porosity; analyzing the relationship between the content of felsic minerals, carbonate minerals and clay minerals and pore size; analyzing the relationship between the content of felsic minerals and different pore types (H2, H2-H3, H3); analyzing the relationship between the content of carbonate minerals and different pore types (H2, H2-H3, H3); analyzing the relationship between the content of clay minerals and different pore types (H2, H2-H3, H3); and further analyzing the relationship between pore connectivity and minerals.

[0038] In some embodiments, the factors affecting micro-reservoir characteristics are determined based on the analysis results, including: analyzing the relationship between porosity and permeability and sedimentary structures, analyzing the relationship between oil content and sedimentary structures, and analyzing the relationship between mobility and sedimentary structures.

[0039] Secondly, this application provides an analytical method for the characteristics of shale reservoirs, including a method for determining the influencing factors of the microscopic characteristics of shale reservoirs as described in any of the above-mentioned claims.

[0040] Thirdly, this application provides a method for evaluating favorable strata in shale, including a method for determining the influencing factors of the microscopic characteristics of shale reservoirs as described in any of the above-mentioned methods.

[0041] The technical solution of this application, based on the analysis of the four properties (properties, morphology, and microstructure) of shale and the microscopic characteristics of the reservoir, clarifies the favorable lithofacies types and then evaluates the influencing factors of the microscopic characteristics of shale reservoirs. This solves the current problem of unclear evaluation of favorable lithofacies and the influencing factors of reservoir micropore characteristics, including the parameters and standards for evaluating favorable lithofacies, the influence of minerals on porosity, pore connectivity, pore structure, and pore size, and the influence of sedimentary structures on porosity, permeability, pore size, oil content, and mobility.

[0042] The method for determining the influencing factors of the microscopic characteristics of shale reservoirs in this application has the following beneficial effects:

[0043] (1) This application can identify favorable lithofacies types by determining the "four properties" parameters and standards for lithofacies evaluation, and the favorable lithofacies development intervals are the "sweet spot" intervals for shale oil exploration. It can also identify the influencing factors of micro-reservoir characteristics by analyzing micro-reservoir characteristics and their correlation with multiple factors.

[0044] (2) This application can comprehensively and effectively carry out the analysis of favorable lithofacies and reservoir micro-characteristics, improve the accuracy of the evaluation by 40 percentage points to 90%; improve work efficiency, avoid ineffective work, reduce the workload of 2 people in 10 days to 1 person in 10 days, and can efficiently complete lithofacies evaluation and reservoir micro-characteristic influencing factor analysis.

[0045] (3) It provides an important basis for the selection of favorable strata and efficient development in shale oil exploration, helps the successful drilling of horizontal wells in shale oil, achieves major exploration breakthroughs, and meets the needs of exploration and development. The method of this application has been applied to 15 wells in the Gaoyou and Jinhu depressions of the Subei Basin, with a cumulative oil and gas production of over 200,000 tons. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the method for determining the influencing factors of the microscopic characteristics of mudstone and shale reservoirs in an embodiment of this application;

[0047] Figure 2 This is a schematic diagram of the sampling method and experimental design in this application;

[0048] Figure 3 This is a diagram showing the relationship between lithology, mineral composition, and porosity.

[0049] Figure 4 This is a graph showing the relationship between the content of felsic minerals and the proportion of micropores.

[0050] Figure 5 This is a graph showing the relationship between carbonate mineral content and the proportion of micropores.

[0051] Figure 6 A graph showing the relationship between clay mineral content and the proportion of micropores;

[0052] Figure 7 This is a graph showing the relationship between the content of felsic minerals and the proportion of mesopores and macropores.

[0053] Figure 8 This is a graph showing the relationship between carbonate mineral content and the proportion of mesopores and macropores.

[0054] Figure 9 This is a graph showing the relationship between clay mineral content and the proportion of mesopores and macropores.

[0055] Figure 10 A graph showing the relationship between sedimentary structures and porosity, permeability, and the proportion of pores with different pore sizes;

[0056] Figure 11 This figure shows the proportion of micropores and mesopores in different rock facies. Detailed Implementation

[0057] The present application will be further described below with reference to the accompanying drawings and embodiments.

[0058] In the following description, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. The following description provides multiple embodiments of the invention, which can be substituted or combined with each other. Therefore, this application can also be considered to include all possible combinations of the same and / or different embodiments described. Thus, if one embodiment includes features A, B, and C, and another embodiment includes features B and D, then this application should also be considered to include embodiments containing one or more other possible combinations of features A, B, C, and D, even if such embodiments are not explicitly described in the following text. In this application, "mudstone" and "shale" have the same meaning.

[0059] Example 1

[0060] like Figure 1 As shown, the method for determining the influencing factors of the microscopic characteristics of shale reservoirs in this application includes: S101, core observation, sampling and experimentation, and classification of lithofacies types based on the core observation and experimental results; S103, characteristic evaluation of different types of lithofacies, and identification of favorable lithofacies types; S105, analysis of reservoir microscopic characteristics of different types of lithofacies; S107, determination of factors affecting microscopic reservoir characteristics based on the analysis results.

[0061] This application can comprehensively and effectively evaluate the influencing factors of favorable lithofacies types and reservoir microstructures, and improve the accuracy of evaluation of favorable shale intervals.

[0062] Example 2

[0063] The method for determining the influencing factors of the microscopic characteristics of shale reservoirs in this application includes:

[0064] The first step involves core observation, sampling, and experimental design. The core is systematically observed, and typical samples are selected based on differences in lithology and sedimentary structure characteristics. At least one sample is taken every 3-4 meters, and parallel experiments are conducted on samples at the same depth. Experiments include rock pyrolysis, X-ray diffraction whole-rock analysis, helium porosity, pulsed permeability, thin section identification, nitrogen adsorption, argon ion profile scanning electron microscopy, and nuclear magnetic resonance (NMR) analysis. A 2.5 x 10.0 cm cylindrical sample is taken vertically from the core bedding. This sample is divided into four parts, with 2.5 x 1.5 cm cylinders cut from each end for rock pyrolysis, X-ray diffraction whole-rock analysis, thin section identification, nitrogen adsorption, and scanning electron microscopy analysis. The remaining sample is divided into two parts, each a 2.5 x 3.5 cm cylinder. One part is used for helium porosity and pulsed permeability analysis, and the other for NMR analysis. Pyrolysis experiments were used to analyze and obtain parameters for free hydrocarbons (S1, mg / g) and organic carbon (TOC, %), and the oil saturation index (OSI, S1 / TOC*100 mg / g) was calculated. X-ray diffraction whole-rock experiments were used to analyze and obtain the percentage content (%) of minerals such as quartz, feldspar, calcite, dolomite, and ferrodolithite, and the content (%) of brittle minerals was calculated. Ordinary thin sections were used for identification to analyze sedimentary structures and bedding types. Nitrogen adsorption was used to analyze pore structure, pore size, and pore connectivity. Scanning electron microscopy was used to analyze pore types. Helium porosity and pulsed permeability were used to analyze porosity φ (%) and permeability K (mD). Nuclear magnetic resonance (NMR) was used to analyze pore structure, pore size, and oil saturation S0 (%).

[0065] The second step is to classify lithological types according to "organic carbon + sedimentary structure + mineral composition". Using Chinese Patent 202211179373.0, "A Method for Determining the Lithofacies Classification Scheme of Terrestrial Mixed Sedimentary Shale", the lithological types of mudstone and shale are determined. Based on a TOC content of less than 1% (low carbon), ≥2% and ≤4% (medium carbon), and >4% (high carbon), mudstone and shale are classified into high-carbon mudstone and shale, medium-carbon mudstone and shale, and low-carbon mudstone and shale. Sedimentary structures are also classified as laminated, layered, and massive. Laminated structures have a single-layer thickness of 1 cm, layered structures have a single-layer thickness of 1-2 cm, and massive structures have a single-layer thickness greater than 2 cm.

[0066] The third step involves comparing the oil-bearing, mobility, reservoir, and compressibility parameters of different lithofacies to identify favorable lithofacies types. Oil-bearing analysis parameters include total organic carbon (TOC), oil saturation (S0), and free oil (S1). Mobility analysis parameters include the oil saturation index (OSI) (S1 / TOC). Reservoir parameters include helium porosity (φ) and pulse permeability (K). Compressibility parameters are the content of brittle minerals (the proportion of quartz, feldspar, calcite, dolomite, and ferrodolithite minerals in the total mineral count; quartz and feldspar are referred to as felsic minerals, and calcite, dolomite, and ferrodolithite are referred to as carbonate minerals). Favorable lithofacies types should simultaneously meet the following requirements: total organic carbon (TOC) content ≥ 1.0%, oil saturation (S0) ≥ 35%, free oil (S1) ≥ 1.3 mg / g, oil saturation index (OSI) ≥ 110 mg / g, helium porosity (φ) ≥ 1.5%, pulse permeability (K) ≥ 1.0 mD, and brittle mineral content ≥ 60.0%.

[0067] The fourth step involves analyzing the bedding types, bedding thicknesses, bedding percentages, pore types, pore connectivity, and the percentage of pores with different diameters for different lithofacies. Bedding types are classified according to different mineral compositions and colors. Bedding thickness is determined using ordinary thin sections. Bedding percentages are obtained using the same scale and field of view. Pore types are determined using argon-ion scanning electron microscopy. Pore connectivity is classified based on nitrogen adsorption-desorption curves into H2 type (ink bottle-shaped pores, poor connectivity), H2-H3 type (ink bottle-shaped to wide parallel plate-shaped pores, moderate connectivity), and H3 type (wide parallel plate-shaped pores, good connectivity). Pore diameter is determined using Chinese Patent 202311153713.7, "A Method for Characterizing Pore Diameter in Shale Reservoirs," which clarifies the full-scale pore diameter distribution characteristics. Pore diameters between 0-100 nm are classified as small pores, and pore diameters greater than 100 nm are classified as medium to large pores. The percentage of pores with different diameters is then calculated.

[0068] The fifth step involves analyzing the relationship between porosity, the proportion of pores of different sizes, pore connectivity, and mineral composition. This includes analyzing the relationship between the content of felsic minerals, carbonate minerals, and clay minerals and porosity; analyzing the relationship between the content of felsic minerals, carbonate minerals, and clay minerals and small, medium, and large pores; and analyzing the relationship between the content of felsic minerals, carbonate minerals, and clay minerals and different pore types (H2, H2-H3, and H3), further analyzing the relationship between pore connectivity and mineral composition.

[0069] The sixth step is to analyze the relationship between porosity and permeability, oil content, mobility, and sedimentary structures.

[0070] Based on core observations, this application conducts targeted sampling and experimental design, combining various experimental testing and analysis methods to classify lithofacies types. It then evaluates the "four properties" (bedding, pore structure, pore size, and pore characteristics) of different lithofacies types, identifying favorable lithofacies types. Combining quantitative and qualitative methods, it meticulously analyzes reservoir micro-characteristics such as bedding type, bedding thickness, bedding ratio, pore type, pore connectivity, and the proportion of pores with different sizes. Furthermore, it analyzes factors influencing micro-reservoir characteristics, including porosity, permeability, the proportion of pores of different sizes, pore connectivity, oil-bearing capacity, mobility, and their relationship with mineral composition and sedimentary structures. This application not only identifies favorable lithofacies types but also further refines the factors influencing reservoir micro-characteristics, improving the accuracy and effectiveness of favorable lithofacies and reservoir micro-characteristic evaluation.

[0071] Example 3

[0072] Taking well XX in the Funing Formation shale oil well in the Gaoyou Depression of the Subei Basin as an example, the method for determining the influencing factors of the microscopic characteristics of the mudstone and shale reservoir in this application includes:

[0073] First step, such as Figure 2 As shown, the core observation, sampling, and experimental design were conducted. A 220m core sample with a diameter of 10cm was systematically observed. Typical samples were selected based on different lithologies and sedimentary structural characteristics. The lithologies included four types: felsic-claytic mixed shale, felsic-dolomic mixed shale, felsic shale, and dolomitic shale. Sedimentary structures included laminated, layered, and massive structures. Laminated structures had a single-layer thickness of less than 1cm, layered structures had a single-layer thickness of 1-2cm, and massive structures had a single-layer thickness greater than 2cm. Eight typical samples were selected: laminated felsic-claytic mixed shale, laminated felsic-dolomic mixed shale, laminated-layered felsic-claytic mixed shale, laminated-layered felsic-dolomic mixed shale, laminated-layered felsic shale, laminated dolomitic shale, massive felsic-claytic mixed shale, and massive felsic-dolomic mixed shale. Ensure at least one sample is taken every 3-4 meters. Take 70 samples from well XX, and conduct parallel experiments on samples at the same depth. Experiments include rock pyrolysis, X-ray diffraction whole-rock analysis, helium porosity, pulsed permeability, thin section analysis, nitrogen adsorption, argon ion radiography scanning electron microscopy, and nuclear magnetic resonance (NMR) analysis. Take a 2.5*10.0cm cylindrical sample perpendicular to the bedding plane from a 10cm diameter core. Divide this sample into four parts, cutting 2.5*1.5cm cylinders from each end for rock pyrolysis, X-ray diffraction whole-rock analysis, thin section analysis, nitrogen adsorption, and scanning electron microscopy analysis. Divide the remaining sample into two parts, each a 2.5*3.5cm cylinder. One part is used for helium porosity and pulsed permeability analysis, and the other for NMR analysis.

[0074] Pyrolysis experiments were used to analyze and obtain parameters for free hydrocarbons (S1, mg / g) and organic carbon (TOC, %), and the oil saturation index (OSI, S1 / TOC*100 mg / g) was calculated. X-ray diffraction whole-rock experiments were used to analyze and obtain the percentage content (%) of minerals such as quartz, feldspar, calcite, dolomite, and ferrodolithite, and the content (%) of brittle minerals was calculated. Ordinary thin sections were used for identification to analyze sedimentary structures and bedding types. Nitrogen adsorption was used to analyze pore structure, pore size, and pore connectivity. Scanning electron microscopy was used to analyze pore types. Helium porosity and pulsed permeability were used to analyze porosity φ (%) and permeability K (mD). Nuclear magnetic resonance (NMR) was used to analyze pore structure, pore size, and oil saturation S0 (%).

[0075] The second step involves determining the lithological type of mudstone and shale using Chinese Patent 202211179373.0, "A Method for Determining the Lithofacies Classification Scheme of Terrestrial Mixed Sedimentary Mudstone and Shale." Organic carbon content is determined based on the following criteria: less than 1% is low carbon; 2% to 4% is medium carbon; and greater than 4% is high carbon. This classifies mudstone and shale into high-carbon, medium-carbon, and low-carbon types. Sedimentary structures are also classified according to their thickness: lamellar, layered, and massive. Lamellar structures have a single-layer thickness of 1 cm, layered structures 1-2 cm, and massive structures greater than 2 cm. Finally, the lithological type is determined based on the combination of organic carbon, sedimentary structure, and mineral composition. The shale is classified into four types: medium-carbon lamellar felsic-claytic mixed shale (Type I), medium-carbon lamellar felsic-dolomite mixed shale (Type II), low-carbon lamellar / layered felsic-claytic mixed shale (Type III), low-carbon lamellar / layered felsic-dolomite mixed shale (Type IV), medium / low-carbon lamellar / layered felsic shale (Type V), medium-carbon lamellar dolomite shale (Type VI), medium-carbon massive felsic-claytic mixed shale (Type VII), and high-carbon massive felsic-dolomite mixed shale (Type VIII).

[0076] The third step involves comparing the oil-bearing, mobility, reservoir, and compressibility parameters of different lithofacies to identify favorable lithofacies types. Oil-bearing analysis parameters include total organic carbon (TOC), oil saturation (S0), and free oil (S1). Mobility analysis parameters include the oil saturation index (OSI) (S1 / TOC). Reservoir parameters include helium porosity (φ) and pulse permeability (K). Compressibility parameters are the content of brittle minerals (the proportion of quartz, feldspar, calcite, dolomite, and ferrodolithite minerals in the total mineral count; quartz and feldspar are referred to as felsic minerals, and calcite, dolomite, and ferrodolithite are referred to as carbonate minerals). Favorable lithofacies types should simultaneously meet the following requirements: total organic carbon (TOC) content ≥ 1.0%, oil saturation (S0) ≥ 35%, free oil (S1) ≥ 1.3 mg / g, oil saturation index (OSI) ≥ 110 mg / g, helium porosity (φ) ≥ 1.5%, pulse permeability (K) ≥ 1.0 mD, and brittle mineral content ≥ 60.0%. Based on comprehensive evaluation, Type I, Type II, and Type VI are considered favorable lithofacies types.

[0077] Table 1. Comparison of "Four Properties" Parameters of Different Lithofacies in Well XX

[0078]

[0079] The fourth step involves analyzing the bedding types, bedding thicknesses, bedding percentages, pore types, pore connectivity, and the percentage of pores with different diameters for different lithofacies. Bedding types are classified according to different mineral compositions and colors. Bedding thickness is determined using ordinary thin sections. Bedding percentages are obtained using the same scale and field of view. Pore types are determined using argon-ion scanning electron microscopy. Pore connectivity is classified based on nitrogen adsorption-desorption curves into H2 type (ink bottle-shaped pores, poor connectivity), H2-H3 type (ink bottle-shaped to wide parallel plate-shaped pores, moderate connectivity), and H3 type (wide parallel plate-shaped pores, good connectivity). Pore size is determined using Chinese Patent 202311153713.7, "A Method for Characterizing Pore Size in Shale Reservoirs," which clarifies the full-scale pore size distribution characteristics, including pore structure and pore size. Pore diameters between 0-100 nm are considered small pores, and pore diameters greater than 100 nm are considered medium to large pores. The percentage of pores with different diameters is then calculated. The characteristics of Type I to Type VIII shale are shown in Table 2.

[0080] Table 2. Comparison of Different Lithofacies Characteristics in Well XX

[0081]

[0082]

[0083] The fifth step involves analyzing the relationship between porosity, the proportion of pores of different sizes, pore connectivity, and mineral composition. This includes analyzing the relationship between the content of felsic minerals, carbonate minerals, and clay minerals and porosity.

[0084] like Figure 3 As shown, the carbonate mineral contents in felsic-claytic mixed shale and felsic shale are 20.6% and 16.4%, respectively, with helium porosities of 2.0% and 2.3%, respectively; the carbonate mineral content in felsic-dolitic mixed shale is 37.3%, with a porosity of 1.84%; and the carbonate mineral content in dolomitic shale is 58.7%, with a porosity of 1.70%. The higher the carbonate mineral content, the lower the porosity.

[0085] like Figures 4-9 As shown, the relationship between the contents of felsic minerals, carbonate minerals, and clay minerals and micropores, as well as mesopores and macropores, was analyzed. The carbonate mineral content showed a positive correlation with the proportion of micropores and a negative correlation with the proportion of mesopores and macropores. The felsic mineral content and clay mineral content showed a negative correlation with the proportion of micropores and a positive correlation with the proportion of mesopores and macropores.

[0086] This study analyzes the relationship between the contents of felsic minerals, carbonate minerals, and clay minerals and different pore types (H2, H2-H3, and H3), and further analyzes the relationship between pore connectivity and minerals. Grey dolomite shale is dominated by H3-type pores, exhibiting the best connectivity, followed by felsic shale, where both H2-H3 and H3-type pores are well-developed. Higher levels of either felsic or carbonate minerals as a single component correlate with better pore connectivity.

[0087] The sixth step is to analyze the relationship between porosity and permeability, oil content, mobility, and sedimentary structures.

[0088] like Figure 10 and Figure 11 As shown, the porosity of both laminated and layered shale is 1.9%, while that of massive shale is 1.04%. Laminated shale has the highest permeability at 2.25 mD, while the average permeability of massive shale is only 0.02 mD. Sedimentary structures influence porosity and permeability, but have little effect on pore size. In shales with the same lithology but different structures, the proportion of large pores ranges from 58% to 60%.

[0089] Types I, II, and VI shales have moderate TOC content and relatively high S1 content, with Type VI shale having the highest S1 at 1.64 mg / g. All three types of shale exhibit well-developed laminae with diverse laminae types, and different types of laminae are stacked and well-developed, indicating significant oil content within the pores. Both oil content and mobility are good. Types III and IV shales have relatively underdeveloped laminae, are mostly layered shales, and have lower average S1 and OSI, resulting in poorer oil content and mobility. Type V shale has well-developed felsic laminae, a TOC content of 0.74%, and low S1, indicating poor oil content. Combined with Table 1, Types VII and VIII massive shales have high average TOC and S1 content, the lowest OSI at 62.5 mg / g, and the worst mobility (see Table 1).

[0090] This application not only clarifies favorable lithofacies types but also further refines the factors influencing reservoir microstructure, improving the accuracy of favorable lithofacies and reservoir microstructure evaluation by 40 percentage points to 90%. It also increases work efficiency, avoiding ineffective work and reducing the workload from two people working for ten days to one person working for ten days. This allows for accurate and efficient evaluation of reservoir microstructures, providing crucial data for the selection and profitable development of "sweet spot" strata in shale oil exploration. It also facilitates successful drilling of horizontal wells in shale oil, achieving significant exploration breakthroughs and meeting the needs of exploration and development. The method described in this application has been applied to 15 wells in the Gaoyou and Jinhu depressions of the Subei Basin, resulting in a cumulative oil and gas production of over 200,000 tons.

[0091] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for determining the influencing factors of microscopic characteristics of shale reservoirs, characterized in that, include: Core observation, sampling, and experiments; lithofacies classification based on core observation and experimental results; Characteristic evaluation of different types of lithofacies to identify favorable lithofacies types; Analyze the microscopic characteristics of reservoirs of different lithofacies types; Based on the analysis results, the factors affecting the microstructure of the reservoir were identified.

2. The method for determining the influencing factors of the microscopic characteristics of shale reservoirs according to claim 1, characterized in that, Core observation, sampling, and experiments; based on the results of core observation and experiments, lithofacies types are classified as follows: The core samples were systematically observed, and typical samples were selected based on differences in lithology and sedimentary structure characteristics. Parallel experiments were conducted on samples at the same depth. The experimental items included rock pyrolysis, X-ray diffraction whole-rock analysis, helium porosity, pulse permeability, ordinary thin section identification, nitrogen adsorption, argon ion profile scanning electron microscopy, and nuclear magnetic resonance experimental testing and analysis.

3. The method for determining the influencing factors of the microscopic characteristics of shale reservoirs according to claim 2, characterized in that, Core observation, sampling, and experiments; based on the results of core observation and experiments, lithofacies types are classified as follows: Cylindrical samples were taken perpendicular to the bedding planes, with identical cylindrical sections cut from both ends for rock pyrolysis, X-ray diffraction whole-rock analysis, ordinary thin section identification, nitrogen adsorption, and scanning electron microscopy (SEM) analysis. The remaining samples were divided equally: one portion was used for helium porosity and pulsed permeability analysis, and the other for nuclear magnetic resonance (NMR) analysis. Pyrolysis analysis was used to obtain free hydrocarbon (S1) and organic carbon (TOC) parameters, and to determine the oil saturation index (OSI). X-ray diffraction whole-rock analysis was used to obtain the percentage of minerals and determine the content of brittle minerals, including quartz, feldspar, calcite, dolomite, and ferrodolithite. Ordinary thin section identification was used to analyze sedimentary structures and bedding types. Nitrogen adsorption analysis was used to analyze pore structure, pore size, and pore connectivity. SEM analysis was used to analyze pore types. Helium porosity and pulsed permeability analysis were used to analyze porosity (φ) and permeability (K). NMR analysis was used to analyze pore structure, pore size, and oil saturation (S0).

4. The method for determining the influencing factors of the microscopic characteristics of shale reservoirs according to any one of claims 1-3, characterized in that, Core observation, sampling, and experiments; classification of lithofacies based on core observation and experimental results includes: classification of lithofacies based on organic carbon, sedimentary structures, and mineral composition.

5. The method for determining the influencing factors of the microscopic characteristics of shale reservoirs according to any one of claims 1-3, characterized in that, Characteristic evaluation of different types of lithofacies was conducted to identify favorable lithofacies types, including: Comparison of oil-bearing, mobility, reservoir, and compressibility parameters of different lithofacies clarifies favorable lithofacies types. Oil-bearing analysis parameters include organic carbon (TOC), oil saturation (S0), and free oil (S1). Mobility analysis parameters include oil saturation index (OSI). Reservoir parameters include helium porosity (φ) and pulse permeability (K). Compressibility parameters include brittle mineral content.

6. The method for determining the influencing factors of the microscopic characteristics of shale reservoirs according to any one of claims 1-3, characterized in that, Analyze the microscopic characteristics of reservoirs of different lithofacies types, including: The analysis included bedding types, bedding thicknesses, bedding percentages, pore types, pore connectivity, and the percentage of pores with different diameters in different lithofacies. Bedding types were classified according to different mineral compositions and colors. Bedding thickness was determined using ordinary thin sections. Bedding percentages were obtained using the same scale and field of view. Pore types were determined using argon ion radiometric scanning electron microscopy. Pore connectivity was classified into H2 type, H2-H3 type, and H3 type based on nitrogen adsorption-desorption curves.

7. The method for determining the influencing factors of the microscopic characteristics of shale reservoirs according to any one of claims 1-3, characterized in that, Based on the analysis results, the factors affecting the microscopic reservoir characteristics were identified as follows: This study analyzes the relationship between porosity, the proportion of pores of different sizes, pore connectivity, and mineral composition; the relationship between the content of felsic minerals, carbonate minerals, and clay minerals and porosity; the relationship between the content of felsic minerals, carbonate minerals, and clay minerals and pore size; the relationship between the content of felsic minerals and different pore types (H2, H2-H3, and H3); the relationship between the content of carbonate minerals and different pore types (H2, H2-H3, and H3); the relationship between the content of clay minerals and different pore types (H2, H2-H3, and H3); and finally, the relationship between pore connectivity and mineral composition.

8. The method for determining the influencing factors of the microscopic characteristics of shale reservoirs according to any one of claims 1-3, characterized in that, Based on the analysis results, the factors affecting the microscopic reservoir characteristics were identified as follows: The relationship between porosity and permeability and sedimentary structures was analyzed, as were the relationship between oil content and sedimentary structures, and the relationship between mobility and sedimentary structures.

9. A method for analyzing the characteristics of mudstone and shale reservoirs, characterized in that, The method for determining the influencing factors of the microscopic characteristics of shale reservoirs as described in any one of claims 1-8.

10. A method for evaluating favorable strata in mudstone and shale, characterized in that, The method for determining the influencing factors of the microscopic characteristics of shale reservoirs as described in any one of claims 1-8.

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