A comprehensive evaluation method for tight sandstone reservoirs and non-reservoirs

Abstract

The present application belongs to the technical field of oil and gas field development measurement, and specifically relates to a comprehensive evaluation method for tight sandstone reservoirs and non-reservoirs, which comprehensively evaluates different types of reservoirs and non-reservoirs by constructing reservoir classification evaluation standards. The construction of the reservoir classification evaluation standard comprises the following steps: taking rock samples to perform pump pressure experiments to obtain a pore structure parameter group, analyzing pore throat distribution characteristics and grading, and determining the correlation with reservoir physical properties; using SPASS software to statistically analyze the correlation between pore throat characteristic parameters and reservoir physical properties, and optimizing the classification parameters; using a high-power microscope to take images of rock sample slices, performing full-view splicing, and then performing pore shape classification statistics; based on the pore throat grading, combining the correlation, the optimized parameters and the shape statistical results, the evaluation standard is constituted. The present application is innovative in technical fusion, parameter optimization and process standardization, makes up for the deficiencies of traditional methods in pore structure characterization, provides a precise and scientific means for the classification of tight sandstone reservoirs, and has theoretical and engineering application value for the development of unconventional oil and gas resources.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas field development measurement technology, and in particular relates to a comprehensive evaluation method for tight sandstone reservoirs and non-reservoirs. Background Technology

[0002] Tight sandstone reservoirs, as an important component of unconventional oil and gas, are characterized by complex pore structures and strong heterogeneity. In some parts of China, tight sandstone reservoirs are shallowly buried (0–1500 m), with some areas exposed at the surface showing good oil and gas displays, but exploration levels are low. Therefore, there is an urgent need to establish scientific reservoir classification methods to guide development.

[0003] The formation of tight sandstone reservoirs is influenced by both sedimentation and diagenesis. Sedimentation controls the rock composition, grain size, and sorting of sandstone reservoirs, which in turn affect subsequent diagenetic processes, including diagenetic type, sequence, and intensity. This determines the degree to which diagenesis improves or damages the reservoir space, ultimately leading to tight reservoirs with different pore-throat structures and macroscopic reservoir properties. Therefore, different pore-throat characteristics are a comprehensive manifestation of multiple factors influencing reservoir type. When classifying reservoirs, the reservoir source—the pore-throat—must be considered. Reservoir capacity and permeability are significantly affected by microscopic pore-throat structural characteristics, and accurate evaluation of pore-throat structure plays a crucial role in reservoir classification.

[0004] Currently, two main techniques are used to study the microstructure of tight sandstone reservoirs: (1) qualitative characterization techniques (indirect testing or visual imaging), which involve statistical analysis of thin sections and conventional reservoir properties using methods such as optical microscopy, field emission scanning electron microscopy, and CT scanning; and (2) quantitative evaluation techniques (fluid injection and nuclear magnetic resonance), including mercury intrusion porosimetry, gas adsorption experiments, and nuclear magnetic resonance experiments. The pore throat structure is evaluated based on parameters such as displacement pressure, exit efficiency, and mean radius obtained from mercury intrusion porosimetry; parameters such as pore size distribution, specific surface area, and pore volume are obtained from gas adsorption experiments; and pore size distribution is evaluated based on nuclear magnetic resonance measurements.

[0005] However, the aforementioned traditional evaluation methods have limitations. Firstly, there are shortcomings in single experimental testing techniques: existing pore structure characterization techniques (such as mercury intrusion porosimetry, gas adsorption experiments, and nuclear magnetic resonance) each have their own limitations. For example, ordinary mercury intrusion porosimetry is inaccurate in characterizing small pore throats, and high-pressure mercury intrusion may cause pore deformation; gas adsorption and desorption have errors under high-temperature environments; and nuclear magnetic resonance is not suitable for reservoirs with excessively large differences in pore throat scale. Secondly, the evaluation index system is singular: traditional methods rely heavily on macroscopic reservoir properties such as permeability and porosity, lacking comprehensive analysis of pore throat structure (such as displacement pressure and average pore throat radius) and pore geometric parameters (such as pore shape and connectivity), making it difficult to truly reflect the microscopic characteristics of the reservoir. Finally, there is insufficient geological adaptability: in some areas, sandstone exhibits characteristics of multi-stage superposition, thin sand bodies, and large variations in reservoir properties, making it difficult for traditional methods to accurately characterize the spatial distribution and heterogeneity of the reservoir. Therefore, it is necessary to consider adopting a fusion of techniques to characterize the pore structure of tight sandstone reservoirs at multiple scales. Summary of the Invention

[0006] The purpose of this invention is to address the shortcomings of traditional evaluation methods by proposing a comprehensive evaluation method for tight sandstone reservoirs and non-reservoirs. This method utilizes SPASS software to analyze the correlation between various pore structure parameters, optimize parameter selection, and employs ImageJ software to perform statistical analysis of pore geometric parameters on large, thin sections with full-view mosaicking. This establishes a classification standard for tight sandstone reservoirs and facilitates a comprehensive evaluation study of tight sandstone reservoir classification. This approach solves the aforementioned problems, clarifies the reservoir type characteristics of the study area, and provides a new research method for regions with similar geological conditions.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: A comprehensive evaluation method for tight sandstone reservoirs and non-reservoirs involves constructing reservoir classification and evaluation criteria, and then comprehensively evaluating different types of reservoirs and non-reservoirs based on these criteria. The construction of the reservoir classification and evaluation criteria includes the following steps: Several rock samples were taken to form an experimental sample group. A pump test was performed on each rock sample in the experimental sample group to obtain the pore structure parameter group of the experimental sample group with rock samples as the unit. Based on the analysis of pore structure parameter set, the distribution characteristics of pore throat are identified, the scale classification of pore throat is clarified, and the correlation between pore throat distribution characteristics and reservoir properties is determined. SPASS software was used to perform correlation statistical analysis between pore throat characteristic parameters and reservoir properties, and reservoir classification parameters were optimized based on the correlation. Prepare thin sections of rock samples, take images of the thin sections using a high-powered microscope, stitch the images of the thin sections together in the entire field of view, and then classify and statistically analyze the pore morphology of the thin sections in the entire field of view. Based on the pore throat size classification, combined with the correlation between pore throat distribution characteristics and reservoir properties, optimized reservoir classification parameters, and pore morphology classification statistics, the whole is used as the reservoir classification evaluation standard.

[0008] Preferably, the pump test includes the following steps: S1, observe whether the rock sample contains grease and / or impurities; if so, clean the rock sample and proceed to step S2; if not, proceed directly to step S2. S2, remove moisture from the rock sample, and then place the rock sample in a dry and constant temperature environment to wait for the pump test; S3, standardize the calibration of the pump and control the ambient temperature and humidity to a suitable level; S4. Place the rock sample into the pressure pump instrument and obtain the pore structure parameters of the rock sample through the pressure pump instrument.

[0009] Preferably, in step S1, the rock sample is cleaned using alcohol or acetone as a cleaning agent, combined with ultrasonic cleaning.

[0010] Preferably, in step S2, the method for removing moisture from the rock sample is oven drying or vacuum drying; wherein the oven drying method involves placing the rock sample in an oven at 105℃±5℃ for at least 12 hours.

[0011] Preferably, in step S3, suitable ambient temperature and humidity means: temperature range 20-25°C; humidity range 30%-60%.

[0012] Preferably, the pore throat characteristic parameters include 11 parameters, namely: maximum pore throat radius, average pore throat radius, median pore throat radius, discharge pressure, median pressure, maximum mercury ingress saturation, mercury removal saturation, mercury removal efficiency, sorting coefficient, mean coefficient, and deviation.

[0013] Preferably, the optimization of reservoir classification parameters involves selecting pore-throat characteristic parameters with a correlation greater than 0.25 to participate in the construction of reservoir classification evaluation criteria.

[0014] Preferably, in the process of classifying and statistically analyzing pore morphology, the geometric morphology of pores is divided into polygonal, circular, triangular, slit-shaped, and parallel plate-shaped pores.

[0015] Preferably, in the process of classifying and statistically analyzing pore morphology, the better the sorting and the higher the proportion of irregular polygonal and triangular pores, the higher the porosity and permeability.

[0016] Preferably, the full-view stitching is performed using Leica Application Suite software to stitch thin-slice images at high resolution.

[0017] Preferably, ImageJ software is used to classify and statistically analyze the pore morphology of the thin section across the entire field of view.

[0018] The beneficial effects of this invention are: 1) Overcoming the limitations of single technologies to achieve multi-scale pore structure characterization. This invention innovatively integrates mercury intrusion porosimetry (quantitative) and thin-section image analysis (qualitative) techniques. Through the synergistic analysis of 11 pore throat parameters (such as maximum pore throat radius and mercury removal efficiency) and pore morphology classification (polygonal / slit-shaped, etc.), it overcomes the inherent defects of traditional single technologies. For example, mercury intrusion porosimetry can obtain pore throat radius distribution data, while thin-section image analysis can statistically analyze pore connectivity characteristics. The two complement each other to reveal reservoir permeability, effectively making up for the technical shortcomings of mercury intrusion porosimetry in characterizing small pore throats and nuclear magnetic resonance inability to adapt to reservoirs with large pore throat differences.

[0019] 2) Constructing a multi-parameter coupled reservoir classification standard. Through SPSS correlation analysis, key indicators with a correlation >0.25 (such as displacement pressure and sorting coefficient) were selected from 11 pore-throat characteristic parameters, breaking through the traditional single evaluation model that relies solely on permeability / porosity. Simultaneously, an innovative pore morphology classification (higher polygon ratio indicates better permeability) was introduced, incorporating geometric features into the evaluation system. This makes the reservoir classification standard more accurately reflect microscopic characteristics and significantly improves the ability to identify complex pore structures.

[0020] 3) Establish standardized experimental procedures to improve data reliability. Establish a comprehensive quality control system: employ ultrasonic-solvent combined cleaning (alcohol / acetone + ultrasonic waves) to remove impurities from rock samples, combined with vacuum drying (50℃±2℃) technology to avoid high-temperature damage and ensure the originality of the pore structure; strictly control temperature and humidity (20-25℃, 30%-60%RH) to reduce thermal expansion and moisture absorption interference of rock samples, and calibrate the pressure pump (error <0.02%FS / ℃) to ensure the accuracy and repeatability of experimental data from the source.

[0021] 4) Enhanced adaptability to complex geological conditions. Addressing geological challenges such as thin sand bodies and strong heterogeneity, Leica software is used for full-view thin section stitching (millimeter-level coverage), overcoming the limitations of traditional methods in terms of observation range. Combined with coupled analysis of pore morphology classification and pore throat parameters, the spatial distribution characteristics of multi-stage superimposed reservoirs can be precisely characterized, making it particularly suitable for evaluating complex tight sandstone reservoirs exposed at the surface and shallow (0-1500m) depths.

[0022] 6) Improve reservoir classification accuracy and development guidance value. A pore-throat parameter-reservoir property correlation model is established based on SPSS correlation analysis, and quantitative classification standards are proposed (e.g., high-quality reservoirs have Rmax > 0.5 μm and mercury removal efficiency > 40%), providing a scientific basis for production capacity prediction. By combining pore morphology classification (high proportion of slotted pores indicates low permeability) with mercury injection parameters, sweet spots and non-reservoirs can be accurately distinguished, significantly improving reservoir classification accuracy and providing efficient decision support for unconventional oil and gas reservoir development. Attached Figure Description

[0023] Figure 1 This is a schematic diagram illustrating the typical characteristics of the pore radius distribution in type A mesopore-throat type pores; Figure 2 A schematic diagram illustrating the typical characteristics of the pore radius distribution in the small-pore-narrow-throat type of Class B pores; Figure 3 A schematic diagram illustrating the typical characteristics of the radius distribution of Class C small-hole-narrow-throat pores; Figure 4 A diagram showing the relationship between the porosity of primary intergranular pores and physical properties in the reservoir evaluation study area; Figure 5 This is a cross-plot of the maximum pore throat radius and reservoir physical parameters in the reservoir evaluation study area; Figure 6 This is a cross-plot of the average pore throat radius and reservoir physical parameters in the reservoir evaluation study area. Figure 7 This is a cross-plot of median pore throat radius and reservoir physical parameters in the reservoir evaluation study area. Figure 8 A cross-plot of displacement pressure and reservoir physical parameters in the reservoir evaluation study area; Figure 9 This is a cross-plot of median pressure and reservoir physical parameters in the reservoir evaluation study area. Figure 10 This is a cross-plot of the maximum mercury saturation and reservoir physical parameters in the reservoir evaluation study area; Figure 11 A cross-plot of mercury removal saturation and reservoir physical parameters in the reservoir evaluation study area; Figure 12 A cross-plot of mercury removal efficiency and reservoir physical parameters in the reservoir evaluation study area; Figure 13 A cross-plot of selection coefficients and reservoir physical parameters is used to distinguish reservoir evaluation studies; Figure 14 A cross-plot of mean coefficients and reservoir physical property parameters for the reservoir evaluation study area; Figure 15 This is a cross-plot of the skewness and reservoir physical parameters in the reservoir evaluation study area. Figure 16 This is a schematic diagram of a full-view thin section of a rock sample in the reservoir evaluation study area. Detailed Implementation

[0024] To make the purpose, technical solution and advantages of the invention clearer, the technical solution of the invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the invention, but not all embodiments.

[0025] Therefore, the following detailed description of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0026] Example 1 This embodiment discloses a comprehensive evaluation method for tight sandstone reservoirs and non-reservoirs. As a preferred embodiment of the invention, it involves constructing a reservoir classification evaluation standard and then comprehensively evaluating different types of reservoirs and non-reservoirs based on this standard. The construction of the reservoir classification evaluation standard includes the following steps: Several rock samples were used to form an experimental sample group. A pump-pressure experiment was conducted on each rock sample in the group to obtain a set of pore structure parameters for the entire sample group. The pump-pressure experiment is based on the principle that mercury can enter pores of different sizes in rock samples under different pressures. By gradually increasing the pressure, mercury is forced into the pores of the rock samples. Based on the relationship between pressure and the amount of mercury injected, pore structure parameters such as pore size, pore volume, and throat radius are calculated. These pore structure parameters obtained through the pump-pressure experiment are fundamental data for subsequent reservoir characteristic analysis. They directly reflect the microscopic pore characteristics of the rock samples and provide data support for a deeper understanding of the reservoir.

[0027] This study analyzes the pore throat distribution characteristics based on pore structure parameter sets, clarifies the pore throat size classification, and determines the correlation between pore throat distribution characteristics and reservoir properties. Statistical analysis of pore structure parameters, such as plotting frequency distribution curves of pore size and throat radius, identifies the distribution patterns of pore throats of different sizes. Simultaneously, the pore throat distribution characteristics are compared with reservoir properties such as permeability and porosity to investigate their intrinsic relationships. Determining the pore throat size classification facilitates reservoir classification and evaluation. Identifying the correlation between pore throat distribution characteristics and reservoir properties reveals the controlling factors of reservoir properties, providing a theoretical basis for subsequent optimization of reservoir classification parameters.

[0028] SPASS software was used to perform correlation statistical analysis between pore-throat characteristic parameters and reservoir properties, and reservoir classification parameters were optimized based on the correlation. SPASS software quantitatively analyzed the linear or nonlinear correlation between pore-throat characteristic parameters and reservoir property parameters by calculating statistical indicators such as correlation coefficients. Based on the strength of the correlation, it was determined which pore-throat characteristic parameters had a significant impact on reservoir properties. Parameters closely related to reservoir properties were selected from numerous pore-throat characteristic parameters as key indicators for reservoir classification. This simplifies the reservoir classification process and improves the accuracy and effectiveness of classification.

[0029] Thin sections of rock samples are prepared by capturing images using a high-powered microscope. These images are then stitched together across the entire field of view, and the pore morphology of the thin sections is classified and statistically analyzed. Thin sections of rock samples can visually demonstrate the microstructure of rocks, and the high-powered microscope allows for clear observation of pore morphology. Through full-field stitching technology, multiple local images are combined into a complete thin section image, enabling comprehensive observation of the rock sample pores. Pores are classified and statistically analyzed based on their shape, size, connectivity, and other characteristics. Pore morphology information is obtained, as pore morphology has a significant impact on the fluid flow characteristics of reservoirs. Through classification and statistical analysis, the distribution of different pore morphologies in the rock samples is understood, providing more comprehensive information for reservoir evaluation.

[0030] Based on pore throat size classification, and combining the correlation between pore throat distribution characteristics and reservoir properties, optimized reservoir classification parameters, and statistical results of pore morphology classification, a comprehensive reservoir classification and evaluation standard is established. This involves integrating the information obtained in the preceding steps, comprehensively considering factors such as pore throat size, the relationship between pore throat distribution and reservoir properties, optimized parameters, and pore morphology, to construct a comprehensive evaluation standard system reflecting reservoir characteristics. This technical solution provides a scientific and systematic standard for the comprehensive evaluation of tight sandstone reservoirs and non-reservoirs, enabling accurate and objective reservoir classification and evaluation in practical applications, and providing strong technical support for oil and gas exploration and development.

[0031] Example 2 This embodiment discloses a comprehensive evaluation method for tight sandstone reservoirs and non-reservoirs. As a preferred embodiment of the present invention, based on Embodiment 1, its pump test includes the following steps: S1: Observe the surface and interior of the rock sample using an optical microscope or scanning electron microscope to check for grease and / or impurities. If not, proceed directly to step S2. If yes, clean the rock sample before proceeding to step S2. Specifically: remove impurities using an organic solvent (such as petroleum ether) or ultrasonic cleaning, then rinse with deionized water and dry. Grease and impurities can clog the pore throats of the rock sample, causing mercury to fail to accurately reflect the pore structure in the pump test. Ultrasonic cleaning uses high-frequency vibration to remove contaminants from the rock sample surface, while organic solvents can dissolve grease-like substances. Cleaning eliminates interfering substances on the surface and within the pores of the rock sample, ensuring the accuracy of subsequent pump test data.

[0032] S2. The rock sample was placed in a vacuum drying oven and dried at 105°C for 24 hours, then transferred to a desiccator to cool to room temperature. Moisture occupies pore space, affecting the amount of mercury injected and the calculation of pore structure parameters. Vacuum drying accelerates moisture evaporation and avoids high-temperature damage to the mineral structure of the rock sample. Drying ensures the rock sample is completely dry, eliminating the influence of moisture on pore volume measurements.

[0033] S3. The pressure calibrator was performed using standard glass microspheres, covering a range of 0-200 MPa. Simultaneously, the laboratory temperature and humidity were controlled at 23℃±2℃ and relative humidity ≤50%. The standard glass microspheres have a known pore structure, which verifies the accuracy of the pressure-volume relationship of the pressure calibrator. Temperature and humidity control prevents the rock samples from expanding or contracting due to environmental changes. These procedures ensure the measurement accuracy of the pressure calibrator, maintain consistent experimental conditions, and reduce systematic errors.

[0034] S4. The rock sample is loaded into the sample chamber of the pressure pump instrument, and a gradient pressure (0-200 MPa) is applied. The relationship between mercury injection volume and pressure is recorded. Pore structure parameters such as pore radius, throat radius, and pore volume are calculated using the Washburn equation. Mercury overcomes surface tension to enter the pores under high pressure. Based on the relationship between pressure and mercury intrusion, combined with the Washburn equation (… The pore throat radius can be inverted. This allows for the acquisition of key parameters characterizing the microstructure of rock samples, providing fundamental data support for reservoir classification and evaluation.

[0035] Based on Example 1, this embodiment further clarifies the standardized operating procedure for the pump pressure experiment. Through measures such as impurity pretreatment, precise temperature-controlled drying, and instrument calibration, the accuracy of obtaining pore structure parameters is significantly improved.

[0036] Example 3 This embodiment discloses a comprehensive evaluation method for tight sandstone reservoirs and non-reservoir areas. As a preferred embodiment of the present invention, based on Embodiment 2, in step S1, the rock sample is cleaned using alcohol or acetone as a cleaning agent, combined with ultrasonic cleaning. Specifically, the following steps can be implemented: using analytical grade alcohol or acetone as a cleaning agent; immersing the rock sample in the cleaning agent and treating it in an ultrasonic cleaner for 15-30 minutes; removing the rock sample and rinsing it with deionized water, then drying it in a vacuum drying oven.

[0037] In this technical solution, alcohol / acetone has strong dissolving power and can effectively remove organic contaminants such as oil and asphalt from the surface and pores of rock samples. Ultrasonic waves generate cavitation in the liquid, creating localized high pressure and high temperature through the collapse of microbubbles, thus stripping away solid particles adhering to the pores of the rock sample. Finally, vacuum drying accelerates the evaporation of residual solvents and avoids secondary contamination.

[0038] This technical solution thoroughly removes organic / inorganic impurities from the surface and internal pores of rock samples while preserving the original pore structure of the rock sample, providing a clean pore system for subsequent pump-pump experiments and ensuring the authenticity of mercury intrusion data. Compared to Example 2, this example significantly improves the cleanliness of rock sample pretreatment by introducing ultrasonic-solvent combined cleaning technology, effectively solving the technical problem that dense sandstone pores are easily blocked by tiny impurities.

[0039] Example 4 This embodiment discloses a comprehensive evaluation method for tight sandstone reservoirs and non-reservoirs. As a preferred embodiment of the present invention, based on embodiment 2 or 3, in step S2, the method for removing moisture from the rock sample is oven drying or vacuum drying; wherein the oven drying method involves placing the rock sample in an oven at 105℃±5℃ for at least 12 hours.

[0040] The oven drying method can be implemented as follows: Place the rock sample in a forced-air drying oven, set the temperature to 105℃±5℃, and dry continuously for at least 12 hours. Weigh the rock sample every 6 hours until the difference between two consecutive weighings is less than 0.01g. Constant temperature heating evaporates the free and adsorbed water in the pores of the rock sample, while forced air circulation accelerates the drying efficiency. The constant weight method ensures complete removal of moisture. It is suitable for rock samples that do not contain heat-sensitive minerals (such as montmorillonite), achieving deep drying in a low-cost manner.

[0041] The vacuum drying method can be implemented as follows: Place the rock sample in a vacuum drying oven, set the temperature to 50℃±2℃ and the vacuum degree to 0.1MPa, and dry for 6-8 hours. The vacuum environment lowers the boiling point of water, allowing moisture to evaporate rapidly at low temperatures, thus avoiding damage to the rock sample structure caused by high temperatures. This method is suitable for rock samples containing clay minerals or organic matter, preventing mineral dehydration or organic matter decomposition due to high temperatures.

[0042] Table 1: A Summary of the Differences Between Oven Drying and Vacuum Drying Methods

[0043] Compared to Examples 2 and 3, this embodiment provides two drying modes, which ensures both the drying effect and adaptability to different rock sample types.

[0044] Example 5 This embodiment discloses a comprehensive evaluation method for tight sandstone reservoirs and non-reservoir areas. As a preferred embodiment of the present invention, based on Embodiments 2, 3, or 4, in step S3, suitable environmental temperature and humidity means: temperature range 20-25°C; humidity range 30%-60%. Specifically, the following operations can be implemented: using a constant temperature and humidity laboratory (equipped with an air conditioning system and dehumidification / humidification device), stabilizing the temperature within the range of 20-25°C and controlling the humidity within the range of 30%-60%; recording the laboratory temperature and humidity data every hour to ensure that the parameter fluctuations throughout the pressure pump experiment do not exceed ±1°C and ±5%RH; turning on the temperature and humidity control equipment 30 minutes before the experiment to reach the target environmental parameters in advance.

[0045] Temperature control: The mineral composition of rock samples (such as clay minerals) is sensitive to temperature; 20-25℃ can avoid pore deformation caused by thermal expansion. At the same time, the accuracy of the pressure sensor of the pressure pump instrument is significantly affected by temperature (temperature coefficient approximately 0.02%FS / ℃).

[0046] Humidity control: When the ambient humidity exceeds 60%, the surface of the rock sample may absorb moisture from the air; when the humidity is below 30%, it may cause the expansion of microcracks inside the rock sample.

[0047] This technical solution maintains the stability of the physical properties of rock samples by controlling the ambient temperature and humidity, preventing changes in ambient temperature and humidity from interfering with the pore structure; it also ensures that the pump pressure measuring system is in optimal working condition, thereby improving the accuracy of pore parameter acquisition.

[0048] Table 2: Overview of Temperature and Humidity Control

[0049] Compared to Examples 2, 3, and 4, this example effectively solves the problem of environmental factors interfering with the experimental data of dense sandstone by establishing temperature and humidity control standards.

[0050] Example 6 This embodiment discloses a comprehensive evaluation method for tight sandstone reservoirs and non-reservoirs. As a preferred embodiment of the invention, it applies any one of the embodiments 1-5 to a practical application. Taking a certain study area (hereinafter referred to as the reservoir evaluation study area) as an example, the pore throat distribution characteristics are analyzed based on the pore structure parameter set to clarify the pore throat scale classification and determine the correlation between pore throat distribution characteristics and reservoir properties. Specifically, through statistical analysis of mercury intrusion porosimetry (MIP) data, it was found that the reservoir pore throat distribution in this reservoir evaluation study area is mainly multi-peaked and coarse-grained, with moderate pore throat sorting (sorting coefficient 1.62–3.12, skewness coefficient 0.02–1.62, mean coefficient 6.18–12.53), and displacement pressure between 0.71 and 1.81 MPa, with a median pressure of 6–38.49 MPa. Based on different MIP curve morphologies and pore throat distribution characteristics, the reservoir pore structure of the reservoir evaluation study area is divided into three types: Figure 1 The type A with a central pore and a central throat shown is shown. Figure 2 The type B shown is a small-hole, narrow-throat type. Figure 3 The diagram shows type C, a small-pore to fine-throat type. Type A pore structures are predominantly composed of primary intergranular pores and dissolution pores, mainly mesopores to medium throats, with good connectivity and reservoir properties, representing the best pore structure type. Type B pore structures are predominantly composed of primary intergranular pores, intergranular dissolution pores, and micropores, with pore throats mainly consisting of small to medium pores to fine throats, moderate connectivity, and good reservoir properties. Type C pore structures have a small number of primary intergranular pores, with pore throats mainly consisting of small to fine throats, and moderate to poor connectivity. Overall, the reservoir evaluation study area is relatively dense, with a moderate concentration of pore throats, poor uniformity, and relatively coarse pore throat sizes, but good connectivity. Finally, a schematic diagram showing the relationship between primary intergranular pore porosity and reservoir properties is provided (e.g., ...). Figure 4 As shown in the figure, a strong positive correlation was found between the porosity of primary intergranular spaces and reservoir properties.

[0051] Example 7 This embodiment discloses a comprehensive evaluation method for tight sandstone reservoirs and non-reservoirs. As a preferred embodiment of the present invention, based on any one of the embodiments 1-6, its pore throat characteristic parameters include 11.

[0052] Radius-related parameters include: maximum pore throat radius, average pore throat radius, and median pore throat radius. The maximum pore throat radius is the throat radius corresponding to the first entry of mercury into the rock sample during mercury intrusion porosimetry (MIP). It reflects the size of the largest connecting throat in the rock and controls the initial fluid permeability. The average pore throat radius is the arithmetic mean of all pore throat radii, characterizing the overall pore throat development level and positively correlated with permeability. The median pore throat radius is the throat radius corresponding to a mercury saturation level of 50%, reflecting the concentrated trend of pore throat distribution and influencing the lower limit of reservoir productivity.

[0053] Pressure parameters: Displacement pressure and median pressure. Displacement pressure is the minimum pressure required for mercury to begin entering a rock sample; it characterizes the minimum opening pressure of the rock throat and is inversely proportional to the maximum throat radius. Median pressure is the pressure corresponding to a mercury saturation of 50%, reflecting the pressure conditions when half of the throats are occupied by mercury, and is directly related to the median throat radius.

[0054] Saturation parameters include: maximum mercury ingress saturation, mercury removal saturation, and mercury removal efficiency. Maximum mercury ingress saturation is the percentage of the maximum volume of mercury injected during a mercury intrusion porosimetry (MIP) experiment relative to the total pore volume, reflecting the proportion of effectively connected pores in the rock and showing a positive correlation with permeability. Mercury removal saturation is the percentage of the volume of mercury remaining in the rock sample after the removal process relative to the total pore volume, reflecting the complexity of the pore structure; more residual mercury indicates higher throat tortuosity. Mercury removal efficiency is calculated as (maximum mercury ingress saturation - mercury removal saturation) / maximum mercury ingress saturation × 100%, characterizing the fluid mobility under capillary forces; higher mercury removal efficiency indicates greater reservoir development potential.

[0055] The following parameters characterize the pore throat distribution: sorting coefficient, mean coefficient, and skewness. The sorting coefficient is the ratio of the standard deviation to the mean of the pore throat radius, measuring the uniformity of the pore throat size; a smaller sorting coefficient indicates a more concentrated pore throat distribution. The mean coefficient is the ratio of the mean to the median of the pore throat radius, reflecting the symmetry of the pore throat distribution; a mean coefficient closer to 1 indicates a more symmetrical distribution. Skewness is the degree of skewness in the pore throat distribution; a positive skewness indicates that small pore throats are dominant, while a negative skewness indicates that large pore throats are dominant.

[0056] Taking the reservoir evaluation study area in Example 6 as an example, cross-plots of pore throat characteristic parameters and reservoir physical property parameters in the reservoir evaluation study area were generated using SPASS software. Figures 5-15 Correlation analysis was performed on the pore-throat characteristic parameters and reservoir properties, and a statistical table of the correlation between pore-throat characteristic parameters and reservoir properties was created (as shown in Table 3), where y represents the pore-throat characteristic parameters, x represents the reservoir properties, and so on. The correlation is indicated by the parameters with a correlation greater than 0.25. These parameters were selected for use in constructing reservoir classification and evaluation criteria. It can be seen that, for the reservoir evaluation study area, the correlations between the maximum pore-throat radius, average pore-throat radius, displacement pressure, mercury removal saturation, mercury removal efficiency, sorting coefficient, and mean coefficient and reservoir properties are all greater than 0.25. Therefore, these parameters can be used in constructing reservoir classification and evaluation criteria.

[0057] Table 3: Statistical Table of Correlation Between Pore-throat Characteristic Parameters and Reservoir Properties

[0058] Example 8 This embodiment discloses a comprehensive evaluation method for tight sandstone reservoirs and non-reservoir areas. As a preferred embodiment of the present invention, based on any of Embodiments 1-7, taking the reservoir evaluation study area in Embodiment 6 or 7 as an example, thin sections of rock samples are prepared. Thin section images are captured using a high-power microscope, and high-resolution stitching of the thin section images is performed using Leica Application Suite software. The resulting full-view thin section is shown below. Figure 16 As shown, ImageJ software was used to classify and statistically analyze the pore morphology of the entire field of view thin sections, classifying pore geometry into polygonal, near-circular, triangular, slit-shaped, and parallel plate-shaped forms. By statistically analyzing the relationship between the proportion of pore morphology and reservoir properties, it was found that better sorting, and a higher proportion of irregular polygonal and triangular pores, resulted in higher porosity and permeability.

[0059] Example 9 This embodiment discloses a comprehensive evaluation method for tight sandstone reservoirs and non-reservoirs. As a preferred implementation of the present invention, based on Embodiment 8, a comprehensive evaluation of the reservoir evaluation study area is conducted based on the reservoir classification evaluation criteria constructed therein. Among them: Class I high-quality reservoirs are mainly characterized by medium-pore to medium-throat pore combinations, with pore morphologies mainly consisting of irregular polygons and triangles. Specific pore throat characteristic parameters are shown in Table 2; Class II good reservoirs are mainly characterized by small to medium pore to fine-throat pore combinations, with pore morphologies mainly consisting of irregular polygons. Specific pore throat characteristic parameters are shown in Table 2; Class III general reservoirs are mainly characterized by small pore to fine-throat pore combinations, with pore morphologies mainly consisting of irregular polygons and near-circular shapes. Specific pore throat characteristic parameters are shown in Table 2; Class IV non-reservoir pore throat combinations are mainly characterized by micropore to micro-throat pore combinations, with pore morphologies mainly consisting of extremely small slits and near-circular shapes. Specific pore throat characteristic parameters are shown in Table 4.

[0060] Table 4: Comprehensive Evaluation Table of Reservoir Evaluation Study Areas

Claims

1. A comprehensive evaluation method for tight sandstone reservoirs and non-reservoir areas, characterized in that, This involves constructing a reservoir classification and evaluation standard, and then comprehensively evaluating different types of reservoirs and non-reservoirs based on this standard. The construction of the reservoir classification and evaluation standard includes the following steps: Several rock samples were taken to form an experimental sample group. A pump test was performed on each rock sample in the experimental sample group to obtain the pore structure parameter group of the experimental sample group with rock samples as the unit. Based on the analysis of pore structure parameter set, the distribution characteristics of pore throat are identified, the scale classification of pore throat is clarified, and the correlation between pore throat distribution characteristics and reservoir properties is determined. SPASS software was used to perform correlation statistical analysis between pore throat characteristic parameters and reservoir properties, and reservoir classification parameters were optimized based on the correlation. Prepare thin sections of rock samples, take images of the thin sections using a high-powered microscope, stitch the images of the thin sections together in the entire field of view, and then classify and statistically analyze the pore morphology of the thin sections in the entire field of view. Based on the pore throat size classification, combined with the correlation between pore throat distribution characteristics and reservoir properties, optimized reservoir classification parameters, and pore morphology classification statistics, the whole is used as the reservoir classification evaluation standard.

2. The comprehensive evaluation method for tight sandstone reservoirs and non-reservoir areas as described in claim 1, characterized in that, The pump test includes the following steps: S1, observe whether the rock sample contains grease and / or impurities; if so, clean the rock sample and proceed to step S2; if not, proceed directly to step S2. S2, remove moisture from the rock sample, and then place the rock sample in a dry and constant temperature environment to wait for the pump test; S3, standardize the calibration of the pump and control the ambient temperature and humidity to a suitable level; S4. Place the rock sample into the pressure pump instrument and obtain the pore structure parameters of the rock sample through the pressure pump instrument.

3. The comprehensive evaluation method for tight sandstone reservoirs and non-reservoir areas as described in claim 2, characterized in that, In step S1, the rock sample is cleaned using alcohol or acetone as a cleaning agent, combined with ultrasonic cleaning.

4. The comprehensive evaluation method for tight sandstone reservoirs and non-reservoir areas as described in claim 2, characterized in that, In step S2, the method for removing moisture from the rock sample is either oven drying or vacuum drying; wherein the oven drying method involves placing the rock sample in an oven at 105℃±5℃ for at least 12 hours.

5. The comprehensive evaluation method for tight sandstone reservoirs and non-reservoir areas as described in claim 2, characterized in that, In step S3, suitable ambient temperature and humidity means: temperature range 20-25°C; humidity range 30%-60%.

6. The comprehensive evaluation method for tight sandstone reservoirs and non-reservoir areas as described in claim 1, characterized in that, The pore throat characteristic parameters include 11 parameters: maximum pore throat radius, average pore throat radius, median pore throat radius, discharge pressure, median pressure, maximum mercury ingress saturation, mercury removal saturation, mercury removal efficiency, sorting coefficient, mean coefficient, and deviation.

7. The comprehensive evaluation method for tight sandstone reservoirs and non-reservoir areas as described in claim 1, characterized in that, The optimization of reservoir classification parameters involves selecting pore-throat characteristic parameters with a correlation greater than 0.25 to participate in the construction of reservoir classification evaluation criteria.

8. The comprehensive evaluation method for tight sandstone reservoirs and non-reservoir areas as described in claim 1, characterized in that, In the process of classifying and statistically analyzing pore morphology, the geometric morphology of pores is divided into polygonal, circular, triangular, slit-shaped, and parallel plate-shaped pores.

9. The comprehensive evaluation method for tight sandstone reservoirs and non-reservoir areas as described in claim 8, characterized in that, In the process of classifying and statistically analyzing pore morphology, it is clear that the better the sorting ability and the greater the proportion of irregular polygonal and triangular pores, the higher the porosity and permeability.

10. The comprehensive evaluation method for tight sandstone reservoirs and non-reservoir areas as described in claim 1, characterized in that, The full-view stitching is performed using Leica Application Suite software to stitch together high-resolution thin-slice images.

11. The comprehensive evaluation method for tight sandstone reservoirs and non-reservoir areas as described in claim 1, characterized in that, ImageJ software was used to classify and statistically analyze the pore morphology of thin sections across the entire field of view.

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