A method and system for predicting breakthrough pressure of mudstone caprock for CO2 geological storage

Abstract

The present invention relates to the field of geological storage technology, and specifically to a method and system for predicting the breakthrough pressure of a mudstone caprock for geological storage of CO2. The prediction method comprises the following steps: obtaining a mercury injection curve of a mudstone caprock for geological storage of CO2; obtaining a calibrated mercury injection curve using the mercury injection curve; obtaining a relationship curve between porosity and mercury injection pressure based on the calibrated mercury injection curve; obtaining a predicted value of the breakthrough pressure through the relationship curve; and realizing the prediction of the breakthrough pressure of a mudstone caprock for geological storage of CO2 according to the predicted value. The present invention establishes a scientific and reasonable prediction model based on in-depth research and extensive coverage of the characteristics of various types of mudstone samples, thereby realizing low-cost, high-efficiency and high-precision prediction of the breakthrough pressure of the mudstone caprock.

Description

Technical Field

[0001] The present invention relates to the technical field of geological storage, and in particular to a method and system for predicting the breakthrough pressure of a mudstone caprock for geological storage of CO2. Background Art

[0002] The breakthrough pressure of the mudstone caprock is a key indicator for evaluating its sealing performance. Specifically, when the accumulated pressure of CO2 below the mudstone caprock exceeds the capillary breakthrough pressure threshold of the mudstone caprock, CO2 will penetrate the tiny pore structure of the mudstone caprock, resulting in CO2 leakage. Therefore, measuring the breakthrough pressure of the mudstone caprock helps predict potential leakage risks and take corresponding preventive measures.

[0003] In the prior art, the core in-situ test method and the indirect test method are usually used to determine the breakthrough pressure of the mudstone caprock. On the one hand, the core in-situ test methods include the step-by-step pressurization method, the dynamic method, the suction method, the residual pressure difference method and the continuous injection method. The step-by-step pressurization method is affected by the pressure increment at the inlet end and the corresponding maintenance time, resulting in problems such as long time and low accuracy in determining the breakthrough pressure; the dynamic method is affected by the pressure gradient and capillary pressure, resulting in a large difference between the calculated value and the actual value of the breakthrough pressure; the suction method is affected by the permeability, resulting in less accurate results of the breakthrough pressure; the residual pressure difference method has a relatively complex process of core drainage and water absorption, resulting in a large difference between the measured value and the actual value of the breakthrough pressure; the continuous injection method ignores the viscosity gradient of water, resulting in an overestimation of the breakthrough pressure. On the other hand, the indirect core testing methods include mercury injection and empirical relationship methods. The mercury injection method mostly uses the pressure corresponding to 10% mercury saturation as the breakthrough pressure, which is quite different from the actual value; the empirical relationship method involves test values ​​such as rock permeability, porosity, clay content and water saturation, and is only applicable to specific regions, rock types and test conditions. Therefore, based on the consideration of different mudstone samples, different porosities and mercury injection curves, the critical pore size of the non-wetting phase breaking through different mudstone samples is defined, and the mudstone breakthrough pressure is predicted, which is conducive to solving the problem of low accuracy of existing theoretical prediction models or prediction methods.

[0004] At present, there is not much research on the breakthrough pressure of mudstone caprocks for CO2 geological storage, and there is no specific method to quickly predict the breakthrough pressure of mudstone caprocks for CO2 geological storage. Summary of the invention

[0005] In view of the defects in the prior art, the present invention provides a method and system for predicting the breakthrough pressure of mudstone caprock for CO2 geological storage.

[0006] On the one hand, the method for predicting the breakthrough pressure of the CO2 geological storage mudstone cap layer provided by the present invention includes the following steps: obtaining a mercury injection curve of the CO2 geological storage mudstone cap layer; using the mercury injection curve to obtain a calibrated mercury injection curve; based on the calibrated mercury injection curve, obtaining a relationship curve between porosity and mercury injection pressure; obtaining a predicted value of the breakthrough pressure through the relationship curve; and realizing the prediction of the breakthrough pressure of the CO2 geological storage mudstone cap layer according to the predicted value. The present invention obtains a relationship curve between porosity and mercury injection pressure by obtaining and calibrating the mercury injection curve of the CO2 geological storage mudstone cap layer, greatly improving the prediction speed and accuracy of the breakthrough pressure, realizing a scientific quantitative evaluation of the sealing performance of the mudstone cap layer, further laying a solid foundation for the safe design and long-term monitoring of the CO2 geological storage project, ensuring the dual achievement of environmental protection and storage effects, and demonstrating the powerful application efficiency of technical prediction in the field of geological engineering.

[0007] Optionally, the mercury injection curve of the mudstone caprock for CO2 geological storage is obtained, including: obtaining an original mercury injection curve of the mudstone caprock for CO2 geological storage; and obtaining a corresponding mercury injection curve according to the original mercury injection curve. The mercury injection curve obtained by the present invention intuitively shows the characteristics of the change of the pore structure of the mudstone with pressure, which is a key basis for evaluating the stability of CO2 storage; the obtained mercury injection curve not only accurately reflects the characteristics of the pore structure of the mudstone caprock, but also provides scientific support for evaluating the safety and effectiveness of CO2 geological storage, ensuring the long-term and safe storage of CO2 deep underground.

[0008] Optionally, the obtaining of the mercury injection curve according to the original mercury injection curve includes: obtaining a mercury injection cumulative curve and a mercury injection incremental curve through the original mercury injection curve. The present invention obtains a mercury injection cumulative curve and a mercury injection incremental curve through the original mercury injection curve of the mudstone caprock for CO2 geological storage. Among them, the mercury injection cumulative curve shows the cumulative change of the mercury injection volume with the increase of pressure, revealing the gradual filling process of the mudstone pores; the mercury injection incremental curve depicts the increase of the mercury injection amount under the unit pressure change, reflecting the slight difference in the pore structure; the mercury injection curve is not only an in-depth insight into the pore characteristics of the mudstone caprock, but also provides a strong scientific basis for the design and implementation of the CO2 geological storage project, ensuring the rationality and reliability of the technical solution.

[0009] Optionally, the use of the mercury injection curve to obtain a calibrated mercury injection curve includes: using the mercury injection curve to perform curve fitting; and obtaining a calibrated mercury injection curve according to the result of the curve fitting. The present invention reduces data noise, smoothes the curve trend, and more accurately reflects the pore structure characteristics of the mudstone caprock by performing curve fitting on the mercury injection curve; the obtained calibrated mercury injection curve provides more accurate and reliable basic data for risk assessment, reservoir evaluation and engineering design of CO2 geological storage projects, ensures the scientificity and safety of the storage plan, and is an indispensable and important tool in geological storage technology.

[0010] Optionally, obtaining the relationship curve between porosity and mercury injection pressure based on the calibrated mercury injection curve includes: performing linear fitting of porosity and mercury injection pressure based on the calibrated mercury injection curve; and obtaining the relationship curve between porosity and mercury injection pressure according to the result of the linear fitting. Based on the calibrated mercury injection curve, the present invention obtains the pressure of mudstone samples with different porosities at different mercury saturations through linear analysis, and further obtains the relationship curve between porosity and mercury injection pressure. The relationship curve between porosity and mercury injection pressure shows the quantitative relationship between the two, which provides an important reference basis for understanding the seepage characteristics of mudstone caprock and predicting fluid migration during CO2 storage, and further promotes the precise application of geological storage technology.

[0011] Optionally, obtaining the predicted value of the breakthrough pressure through the relationship curve includes: determining the critical pore size through the relationship curve; and obtaining the predicted value of the breakthrough pressure based on the critical pore size. The present invention obtains the critical pore size through the linear relationship curve between porosity and mercury injection pressure, and obtains the predicted value of the breakthrough pressure in combination with the Laplace equation. The critical pore size is a key dividing point in the pore system, which marks the pore size at which the fluid begins to penetrate significantly; the breakthrough pressure is an important parameter for evaluating the stability of the fluid storage system, reflecting the minimum pressure required for the fluid to break through the caprock pore system; the predicted value better evaluates the risks of CO2 storage projects and provides strong data support for engineering design and safety assessment.

[0012] Optionally, obtaining the predicted value of the breakthrough pressure according to the critical pore size includes: constructing a prediction model of the breakthrough pressure according to the critical pore size and the Laplace equation; obtaining the predicted value of the breakthrough pressure using the prediction model. The present invention constructs a prediction model of the breakthrough pressure through the critical pore size and the Laplace equation, and the prediction model effectively integrates the microscopic characteristics of the pore structure and the principles of macroscopic fluid dynamics, accurately reflecting the decisive influence of the pore size on the breakthrough pressure of the fluid; by inputting the specific value of the critical pore size, the predicted value of the breakthrough pressure is successfully obtained, and the predicted value not only provides an important basis for evaluating the stability of the fluid storage system, but also provides a scientific basis and strong support for related engineering design and safety assessment work, ensuring the smooth implementation of the project and long-term safe operation.

[0013] Optionally, the Laplace equation is as follows:

[0014] ,

[0015] in, is the mercury injection pressure, is the interfacial tension, is the contact angle, The Laplace equation used in the present invention has the following effects: first, by giving the interfacial tension and contact angle, it is helpful to predict the pressure of the fluid entering the porous medium; second, by changing the contact angle parameter in the equation, it is helpful to analyze the influence of different pore structures on the fluid penetration behavior; third, by the influence of interfacial tension on the fluid penetration pressure, it is helpful to understand the behavior of multiphase fluid in the underground environment.

[0016] Optionally, the prediction model satisfies the following expression:

[0017] ,

[0018] in, is the predicted value of the corresponding gas breakthrough pressure, is the interfacial tension, is the contact angle, The prediction model constructed by the present invention has the following effects: first, it directly relates the influence of the physical properties of the fluid and the structural characteristics of the porous medium on the breakthrough pressure, which is conducive to quickly obtaining the breakthrough pressure required for the fluid to enter the porous medium, and provides key parameters for the field of geological storage technology; second, it not only simplifies the complex physical process, but also improves the accuracy of the prediction, and is an important tool for studying the behavior of fluids in porous media.

[0019] In the second aspect, the prediction system for the breakthrough pressure of the mudstone caprock for geological storage of CO2 provided by the present invention comprises an input device, a processor, an output device and a memory, wherein the input device, the processor, the output device and the memory are interconnected, wherein the memory is used to store a computer program, the computer program comprises program instructions, the processor is configured to call the program instructions, and the system uses the method for predicting the breakthrough pressure of the mudstone caprock for geological storage of CO2. The prediction system for the breakthrough pressure of the mudstone caprock for geological storage of CO2 provided by the present invention has high integration, compact structure, and has the characteristics of rapid prediction, accuracy, practicality, flexibility and safety, and is of great significance for promoting the development and application of CO2 geological storage technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a flow chart of a method for predicting breakthrough pressure of mudstone caprock for CO2 geological storage according to an embodiment of the present invention;

[0021] Figure 2 A mercury pressure curve diagram of a mudstone cap layer for CO2 geological storage according to an embodiment of the present invention;

[0022] Figure 3 This is a graph of mercury injection calibration of mudstone caprock for CO2 geological storage according to an embodiment of the present invention;

[0023] Figure 4 A curve diagram showing the relationship between the porosity of the mudstone cap rock and the mercury injection pressure in the CO2 geological storage according to an embodiment of the present invention;

[0024] Figure 5 A comparison chart of predicted values ​​and measured values ​​of different prediction models in an embodiment of the present invention;

[0025] Figure 6 Schematic diagram of the structure of a system for predicting the breakthrough pressure of a mudstone caprock for CO2 geological storage according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] The specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described herein are only for illustration and are not intended to limit the present invention. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present invention. However, it is obvious to those of ordinary skill in the art that these specific details do not need to be adopted to implement the present invention. In other examples, in order to avoid confusing the present invention, known circuits, software or methods are not specifically described.

[0027] Throughout the specification, references to "one embodiment," "an embodiment," "an example," or "an example" mean that a particular feature, structure, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment of the present invention. Therefore, the phrases "in one embodiment," "in an embodiment," "an example," or "an example" appearing in various places throughout the specification do not necessarily all refer to the same embodiment or example. In addition, particular features, structures, or characteristics may be combined in one or more embodiments or examples in any suitable combination and / or subcombination. In addition, it should be understood by those of ordinary skill in the art that the figures provided herein are for illustrative purposes and that the figures are not necessarily drawn to scale.

[0028] See also Figure 1 The embodiment of the present invention provides a method for predicting the breakthrough pressure of a mudstone caprock for CO2 geological storage, the method comprising the following steps:

[0029] S1. Obtain the mercury injection curve of the mudstone caprock for CO2 geological storage.

[0030] Among them, S1 includes the following steps:

[0031] S11. Obtain the original mercury injection curve of the mudstone caprock for CO2 geological storage.

[0032] In one embodiment, the mercury injection original curve of the CO2 geological storage mudstone caprock is obtained according to the mercury injection method. The mercury injection method comprises the following steps:

[0033] S111. Obtain test materials for mudstone caprock for CO2 geological storage.

[0034] Specifically, representative samples of CO2 geological storage mudstone caprock are selected to ensure that the samples are crack-free, non-weathered and of appropriate size.

[0035] Furthermore, the mudstone caprock samples were cut into regular shapes, and the surface adsorbed particles were removed and freeze-vacuum dried to ensure that there were no impurities on the sample surface.

[0036] Furthermore, mercury with high purity and no chemical impurities is selected.

[0037] S112. Experimental device for obtaining mudstone caprock for CO2 geological storage.

[0038] Specifically, a suitable mercury injection device is selected according to the test requirements, and the test device includes a high-pressure mercury source, a pressure control system, a mercury volume measurement system and a data recording system.

[0039] Furthermore, the device was installed and calibrated according to its instructions to ensure proper operation.

[0040] S113. Conduct tests using the test materials and test equipment.

[0041] Specifically, the laboratory environment was adjusted to a stable state, and environmental conditions such as atmospheric pressure, temperature, and humidity were recorded at the beginning of the experiment.

[0042] Furthermore, the processed mudstone caprock samples were connected to the mercury injection device to ensure good sealing.

[0043] Furthermore, the pressure of mercury is gradually increased through a pressure control system, so that mercury gradually enters the pores of the mudstone cap layer, and the volume of mercury entering the mudstone pores under different pressures is recorded.

[0044] Furthermore, the height difference of the mercury column and the corresponding change in mercury volume are accurately recorded each time the pressure is increased.

[0045] S114. Based on the test results, the original mercury injection curve of the mudstone caprock for CO2 geological storage is obtained.

[0046] Specifically, the original mercury injection curve is drawn based on the test record data. The horizontal axis represents pressure, and the vertical axis represents the cumulative amount of mercury injection, that is, the relationship between the volume of mercury entering the pores of the mudstone sample and the mercury injection pressure. This curve can reflect the pore structure characteristics of the mudstone caprock from the side, including pore size, distribution and connectivity.

[0047] Furthermore, based on the mechanism of the hemp skin effect, the original mercury injection curve is corrected for surface roughness, and the specific correction methods include but are not limited to numerical correction, curve fitting, and reference to standard curves. The numerical correction method calculates the additional mercury injection amount caused by the hemp skin effect based on experimental data, and subtracts this part of the volume from the total mercury injection amount to obtain the corrected mercury injection amount; the curve fitting method uses a suitable mathematical model to fit the original curve, while considering the influence of the hemp skin effect, and corrects the curve by adjusting the model parameters; the reference to standard curve method first measures the mercury injection curve of a standard sample with a known small surface roughness as a reference, and then corrects the original curve of the experimental sample based on the curve.

[0048] It should be noted that in the mercury injection method, the volume of the cavities between the rough outer surface of the rock sample and the mercury contact surface will affect the measurement results. These cavities are filled with mercury during the process of increasing pressure, but they do not actually enter the pore throat system, resulting in a larger mercury saturation value.

[0049] S12. Obtaining a mercury injection cumulative curve and a mercury injection incremental curve through the original mercury injection curve.

[0050] In one embodiment, a series of data points of pressure and corresponding mercury volume increment are obtained through the original mercury injection curve; and then a mercury injection cumulative curve and a mercury injection incremental curve are obtained based on the data points. Specifically, the steps include:

[0051] S121. Obtain a mercury injection cumulative curve through the original mercury injection curve.

[0052] Specifically, set a starting point pressure The starting point pressure is usually 0 or the lowest measured pressure, and the corresponding cumulative volume is set is 0.

[0053] Furthermore, for each pressure point and its corresponding mercury volume increment , perform the following steps:

[0054] Calculate from arrive Cumulative mercury volume increase: = + + +

[0055] Will Add to The new cumulative mercury volume is obtained:

[0056] ,

[0057] Record As a point on the mercury injection accumulation curve.

[0058] Further, using the recorded points Draw the cumulative mercury injection curve. Figure 2 As shown in the figure, the dark solid line represents the cumulative mercury injection curve. The horizontal axis represents pressure and the vertical axis represents the cumulative mercury volume. The curve shows the cumulative filling of mercury as the pressure increases. The change in the slope of the curve can reflect the distribution of pore size. The area with a larger slope indicates the presence of a large number of pores with similar pore sizes.

[0059] S122. Obtain a mercury injection incremental curve through the original mercury injection curve.

[0060] Specifically, each pressure point is directly extracted from the original mercury injection curve data and its corresponding mercury volume increment .

[0061] Furthermore, using As data points, a mercury injection curve is drawn. Figure 2As shown in the figure, the light solid line represents the mercury injection increment curve. The horizontal axis represents pressure and the vertical axis represents the mercury volume increment. This curve directly shows the amount of mercury filled at each pressure step, which is very useful for analyzing pore connectivity and distribution details. The peak corresponds to pores of a specific pore size, while the valley value indicates an area with poor pore connectivity or large pore size variation.

[0062] S13. According to the mercury injection cumulative curve and the mercury injection incremental curve, a critical pore size and a corresponding mercury injection pressure and mercury injection saturation are obtained.

[0063] In one embodiment, the mercury injection cumulative curve, the mercury injection incremental curve and the mercury injection original curve are plotted on the same graph to obtain a mercury injection curve, such as Figure 2 As shown. The mercury injection curve can determine the pore size and mercury injection saturation. The process of determining the critical pore size and mercury injection saturation is as follows:

[0064] In the mercury injection curve, draw the tangents of the mercury injection increment curve at different stages and find the intersection of the two tangents, such as Figure 2 As shown by the dotted line in .

[0065] Furthermore, the mercury injection pressure and mercury injection saturation corresponding to the point are determined according to the abscissa of the intersection point.

[0066] Furthermore, the mercury injection pressure is substituted into the Laplace equation to determine the pore size. The Laplace equation is as follows:

[0067] ,

[0068] in, is the mercury injection pressure, is the interfacial tension, is the contact angle, is the critical aperture.

[0069] The mercury injection saturation is determined based on the mercury injection cumulative curve.

[0070] It is important to note that the mercury injection cumulative curve and the mercury injection incremental curve are placed in the same graph for comparison. By observing the relative position and change trend of the two curves, a more comprehensive understanding of the pore structure characteristics of the sample can be obtained. For example, it is possible to analyze which pressure intervals contribute the most to the total pore volume, and whether the pores in these intervals have specific pore size distribution and connectivity characteristics.

[0071] S2. Using the mercury injection curve, a calibration mercury injection curve is obtained.

[0072] Among them, S2 includes the following steps:

[0073] S21. Perform curve fitting using the mercury injection curve.

[0074] In one embodiment, considering the differences in mercury injection curves of mudstones with different porosities, two groups with the largest and smallest porosities are selected from 32 groups of mudstone samples with different porosities, and mercury injection curves are obtained and calibrated.

[0075] Specifically, the mercury injection curve is used to extract data points of pressure and cumulative mercury injection amount corresponding to the mercury injection curve.

[0076] Further, the data points are organized into a table format and imported into a data analysis software, including but not limited to Excel, MATLAB and Python.

[0077] Furthermore, the curve fitting function in the data analysis software is used to fit the above two groups of mercury injection curves using a fitting equation. The fitting equation includes a logarithmic equation and a polynomial equation, and the logarithmic equation is as follows:

[0078]

[0079] The polynomial equation is as follows:

[0080]

[0081] in, Indicates pressure, Indicates the cumulative amount of mercury input.

[0082] Furthermore, observe how well the fitted curve matches the original data points. Ideally, the fitted curve should pass through or be close to most of the data points.

[0083] It should be noted that curve fitting using mercury intrusion curves is an important method for analyzing the pore structure of porous materials. Curve fitting is conducive to extracting key parameters of pore distribution, such as pore size distribution, pore volume, etc.

[0084] S22. Obtain a calibrated mercury injection curve according to the curve fitting result.

[0085] In one embodiment, statistical indicators are used to evaluate the quality of the fitting effect, and the statistical indicators include but are not limited to correlation coefficients. They are 0.9935 and 0.9864 respectively, with a very high correlation, so the logarithmic equation and the polynomial equation can be approximated as the equation for calibrating the mercury injection curve.

[0086] Furthermore, the fitting equation is used to calibrate mercury injection curves corresponding to multiple groups of samples with different porosities to obtain multiple groups of calibrated mercury injection curves.

[0087] See also Figure 3 , Figure 3 The calibrated mercury injection curves corresponding to the two groups of samples with the largest and smallest porosities in the porosity mudstone samples are given. Among them, the abscissa represents the mercury injection pressure, the ordinate represents the mercury injection saturation, the light solid line is the unfitted mercury injection curve corresponding to the sample with the largest porosity, the light dotted line is the calibrated mercury injection curve corresponding to the sample with the largest porosity after being fitted by the logarithmic equation, the dark solid line is the unfitted mercury injection curve corresponding to the sample with the smallest porosity, and the dark dotted line is the calibrated mercury injection curve corresponding to the sample with the smallest porosity after being fitted by the polynomial equation.

[0088] It should be noted that obtaining a calibrated mercury injection curve based on the curve fitting results is actually to apply the fitted mathematical model to a series of continuous pressure values ​​to generate a smooth curve that can represent the trend of the original mercury injection data. This curve is called a calibrated mercury injection curve, which can be used for subsequent analysis, prediction or comparison with other experimental data.

[0089] S3. Based on the calibrated mercury injection curve, a relationship curve between porosity and mercury injection pressure is obtained.

[0090] Among them, S3 includes the following steps:

[0091] S31. Based on the calibrated mercury injection curve, perform linear fitting of porosity and mercury injection pressure.

[0092] In one embodiment, the relationship between porosity and mercury injection pressure is determined based on a plurality of sets of calibrated mercury injection curves with different mercury injection saturations.

[0093] Specifically, data points of mercury injection pressure and mercury injection saturation are obtained according to the plurality of groups of calibrated mercury injection curves with different mercury injection saturations.

[0094] Furthermore, based on the data points of the mercury injection pressure and the mercury injection saturation, data points of the porosity and the mercury injection saturation corresponding to the calibrated mercury injection curve are obtained.

[0095] Furthermore, a linear fit is performed on the data points of the porosity and mercury saturation. The linear fit equation is: ,in, represents the porosity, Indicates the mercury inlet pressure.

[0096] It should be noted that the pore structure characteristics of porous materials can be effectively analyzed by using the calibrated mercury injection curve to perform linear fitting of porosity and mercury injection pressure.

[0097] S32. According to the result of the linear fitting, a relationship curve between porosity and mercury injection pressure is obtained.

[0098] In one embodiment, the porosity and mercury injection pressure are fitted using a linear fitting equation to obtain a relationship curve between the porosity and the mercury injection pressure.

[0099] See also Figure 4 , Figure 4 The solid line in the figure shows the relationship between mercury injection pressure and porosity after fitting, and the triangle symbol represents the discrete data points that are not fitted. The horizontal axis represents porosity and the vertical axis represents mercury injection pressure. Figure 4 It can be seen that with the increase of porosity, the mercury injection pressure gradually decreases.

[0100] S4. Obtain a predicted value of the breakthrough pressure through the relationship curve.

[0101] Among them, S4 includes the following steps:

[0102] S41. Determine the critical aperture by the relationship curve;

[0103] In one embodiment, a linear analysis is performed on the relationship curve between porosity and mercury injection pressure to obtain the mercury injection pressure of mudstone samples with different porosities at different mercury injection saturations. The critical pore sizes of different mudstone samples are determined based on the above.

[0104] It is important to note that the determination of the critical pore size plays a key role in predicting the breakthrough pressure.

[0105] S42. Based on the critical pore size and Laplace equation, a prediction model for breakthrough pressure is constructed.

[0106] In one embodiment, the interfacial tension and contact angle of the corresponding test system are selected, and the critical pore size is substituted into the Laplace equation, that is, a prediction model of breakthrough pressure is constructed, and the prediction model satisfies the following expression:

[0107] ,

[0108] in, is the predicted value of the corresponding gas breakthrough pressure, is the interfacial tension, is the contact angle, is the critical aperture.

[0109] Furthermore, the prediction model is compared with other existing prediction models.

[0110] See also Figure 5 , Figure 5The horizontal axis represents the predicted value, the vertical axis represents the measured value, the solid square represents the data point of the prediction model of the present invention, the cross represents the data point of the prediction model of Stavropoulou and Laloui (2022), the triangular circle represents the data point of the prediction model of Zhou (2022), and the hollow square represents the prediction model with a mercury injection saturation of 10%. The Stavropoulou and Laloui (2022) prediction model calculates the breakthrough pressure by idealizing the rock pores into circular tube bundles through the Kozeny-Carman and Young-Laplace equations. Zhou (2022) calculates the breakthrough pressure by establishing the relationship between the breakthrough pressure and porosity of a few specific mudstone samples. The prediction model with a mercury injection saturation of 10% uses its corresponding breakthrough pressure value as the prediction value.

[0111] Depend on Figure 5 It can be seen that the calculation accuracy of the prediction model of Stavropoulou and Laloui (2022) is low; the application range of the prediction model of Zhou (2022) is small and the accuracy is low; the prediction data of the prediction model with a mercury saturation of 10% has a large degree of discreteness and low accuracy; the prediction data of the prediction model of the present invention has a small degree of discreteness and high accuracy.

[0112] S43. Using the prediction model, obtain a predicted value of breakthrough pressure.

[0113] Wherein, S43 further comprises the following steps:

[0114] S431. Perform model training on the prediction model.

[0115] In one embodiment, the prediction model is trained using historical data to obtain a trained prediction model, wherein the prediction value discreteness corresponding to the trained prediction model is relatively low.

[0116] S432. Perform model verification on the prediction model.

[0117] In one embodiment, the trained model is validated using the test set data, and the prediction performance of the model is evaluated by determining the difference between the predicted value and the actual value.

[0118] S433. Obtain a predicted value of breakthrough pressure using the prediction model with the best prediction performance.

[0119] In one embodiment, actual data such as interfacial tension, contact angle and pore size are substituted into the prediction model with the best prediction performance to obtain a predicted value of the breakthrough pressure.

[0120] S5. Based on the predicted value, the breakthrough pressure of the mudstone caprock for CO2 geological storage is predicted.

[0121] In one embodiment, the prediction results are analyzed based on the predicted values ​​and compared with the actual conditions for verification.

[0122] Specifically, Figure 5 As shown, the predicted value falls within the dotted line, has a low degree of dispersion, and has an approximate linear relationship with the measured value.

[0123] Furthermore, based on the analysis results of the predicted values, the breakthrough pressure of the mudstone caprock for CO2 geological storage is predicted.

[0124] See also Figure 6 , Figure 6 The present invention is a schematic diagram of a system structure for predicting the breakthrough pressure of a CO2 geological storage mudstone caprock in an embodiment of the present invention. The system includes an input device, a processor, an output device, and a memory, wherein the input device, the processor, the output device, and the memory are interconnected, the memory is used to store a computer program, the computer program includes program instructions, the processor is configured to call the program instructions, and the system uses the method for predicting the breakthrough pressure of a CO2 geological storage mudstone caprock.

[0125] In this embodiment, the input device uses a touch screen, and the touch screen is mainly used to input data information such as mercury injection pressure, mercury injection increment, mercury injection cumulative amount, interfacial tension, contact angle and pore size.

[0126] The processor has a built-in model algorithm, including a prediction model algorithm for breakthrough pressure, for solving and analyzing the predicted value of breakthrough pressure.

[0127] The output device uses a display screen, which is mainly used to display the results obtained through processing by the processor.

[0128] The memory adopts a high-speed solid-state hard disk to store the original data input by the input device and the result data processed by the processor. The memory has the characteristics of fast reading and writing speed, large capacity and high reliability, and can meet the needs of large data storage.

[0129] In summary, the method and system for predicting the breakthrough pressure of mudstone caprock for CO2 geological storage proposed in the present invention, based on in-depth research and extensive coverage of the characteristics of various types of mudstone samples, achieves low-cost, high-efficiency and high-precision prediction of the breakthrough pressure of mudstone caprock.

[0130] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A method for predicting breakthrough pressure of mudstone caprock for CO2 geological storage, characterized in that: The prediction method comprises the following steps: Obtain the original mercury injection curve of the mudstone caprock for CO2 geological storage; Obtaining a mercury injection cumulative curve and a mercury injection incremental curve through the original mercury injection curve; Draw two tangent lines at different stages of the mercury injection increment curve, and find the intersection of the two tangent lines; Based on the intersection of the two tangent lines and in combination with the mercury injection accumulation curve, the mercury injection pressure and mercury injection saturation are determined; Mercury injection curves of mudstone samples with different porosities were selected and curve fitting was performed to obtain multiple groups of calibrated mercury injection curves with different mercury saturations. According to the calibrated mercury injection curve, a relationship curve between porosity and mercury injection pressure is obtained; According to the relationship curve, the mercury injection pressure of mudstone samples with different porosities at different mercury injection saturations is obtained; The mercury injection pressure of the mudstone samples with different porosities at different mercury injection saturations is substituted into the Laplace equation to obtain the critical pore size; the Laplace equation is as follows: in, is the mercury injection pressure, is the interfacial tension, is the contact angle, is the critical aperture; A prediction model for breakthrough pressure is constructed, and the prediction model satisfies the following expression: in, is the predicted value of the corresponding gas breakthrough pressure, is the interfacial tension, is the contact angle, is the critical aperture; Obtaining a predicted value of breakthrough pressure through the critical pore size and the prediction model; According to the predicted value, the breakthrough pressure of the mudstone caprock for CO2 geological storage is predicted.

2. A system for predicting the breakthrough pressure of a mudstone caprock for geological storage of CO2, the system using the method for predicting the breakthrough pressure of a mudstone caprock for geological storage of CO2 as claimed in claim 1, characterized in that: The system includes an input device, a processor, an output device and a memory, wherein the input device, the processor, the output device and the memory are connected to each other, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions.

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