A coal seam CO2 geological storage caprock breakthrough pressure prediction method and system based on mercury intrusion fractal theory

Abstract

The present application belongs to the technical field of coal seam CO2 geological storage, and proposes a coal seam CO2 geological storage caprock breakthrough pressure prediction method and system based on mercury injection fractal theory, which comprises obtaining the mercury injection experiment data of the target caprock of CO2 geological storage; based on the mercury injection experiment data, the fractal dimension is calculated, and the mercury injection process is divided into multiple continuous stages according to the change characteristics of the fractal dimension; the critical stage corresponding to the pore structure being penetrated by the non-wetting phase fluid is identified, and the mercury injection pressure corresponding to the end of the critical stage is determined as the breakthrough pressure of the caprock; based on the breakthrough pressure, the evaluation of the sealing capacity of the coal seam CO2 geological storage caprock is realized. The method can not only maintain the high efficiency advantage of the mercury injection method, but also truly reflect the fluid breakthrough process, and realize high-precision breakthrough pressure prediction.

Description

Technical Field

[0001] This invention belongs to the field of coal seam CO2 geological storage technology, and relates to a method and system for predicting the caprock breakthrough pressure of coal seam CO2 geological storage based on mercury intrusion fractal theory. Background Technology

[0002] During geological storage, due to the buoyancy effect, injected CO2 tends to migrate upwards. Therefore, the sealing of the caprock is a core geological element to prevent gas leakage and ensure the safety of storage.

[0003] When the integrity of the geological caprock is compromised, CO2 leakage primarily occurs through molecular diffusion and infiltration. While the diffusion rate of CO2 molecules within the caprock is extremely slow, when the CO2 pressure overcomes the dual constraints of hydrostatic pressure and capillary pressure, a continuous seepage channel is formed, causing the capillary sealing mechanism to fail and triggering leakage. Breakthrough pressure is one of the most direct and important indicators for evaluating the caprock's sealing performance; it is defined as the fluid pressure threshold that the non-wetting phase (CO2) must overcome to penetrate the interconnected pores of the rock when it displaces the wetting phase (coalbed water).

[0004] Currently, laboratory methods for testing CO2 breakthrough pressure include direct and indirect methods. Direct methods determine the breakthrough pressure directly through physical displacement experiments, mainly including continuous displacement, distributed pressurization, and pulse decay methods. Direct methods obtain experimental data close to the true value by extending the testing time, but they have drawbacks such as stringent sample requirements, long experimental cycles, and the need for repeated verification. Therefore, indirect methods, represented by mercury intrusion porosimetry, are more widely used in practice. Traditional mercury intrusion porosimetry typically defines the breakthrough pressure empirically as the mercury intrusion pressure corresponding to a mercury saturation of 10%. While this method significantly improves efficiency, its inherent defects are also very prominent: First, the 10% threshold lacks solid physical mechanism support and is purely empirically set, leading to a large and unstable deviation between the predicted results and the actual breakthrough pressure; second, this method does not consider the confining pressure effect in the actual formation environment.

[0005] To overcome the limitations of the aforementioned empirical methods, existing research has proposed some improved indirect prediction models. For example, Chinese patent CN119375092A obtains pore size distribution curves by analyzing mercury intrusion porosimetry data and uses the pressure corresponding to the peak pore size distribution (i.e., the pore size with the largest contribution to pore volume) as the breakthrough pressure after conversion using the Laplace equation. Chinese patent CN119354803A establishes a statistical empirical relationship between porosity and mercury intrusion pressure by collecting a large number of core samples with different porosities, and then calculates the breakthrough pressure. These improved methods, to some extent, break free from the dependence on a fixed saturation threshold, reflecting a more refined characterization of the pore structure. However, these improved models still have significant shortcomings. They are essentially still statistical analyses of the final static structure of the rock pore system, failing to reveal the physical process of non-wetting phase fluids dynamically intruding under pressure and ultimately breaking through the pore network. Whether based on the peak pore size distribution or the empirical relationship of porosity, it is difficult to accurately capture the key connecting throats controlling the breakthrough behavior, thus limiting the prediction accuracy and universality.

[0006] Therefore, there is an urgent need in this field for a breakthrough pressure prediction method that can maintain the high efficiency of mercury intrusion porosimetry while accurately reflecting the fluid breakthrough process, thereby achieving high-precision prediction. Summary of the Invention

[0007] This invention proposes a method and system for predicting the breakthrough pressure of CO2 geological sealing caprock in coal seams based on mercury intrusion fractal theory. This method dynamically applies fractal theory to the analysis of mercury intrusion process. By identifying the fractal stages of pore structure evolution, the physical threshold of breakthrough pressure is determined, which can effectively improve the prediction accuracy.

[0008] The technical solution of this invention is implemented as follows:

[0009] Technical Topic 1

[0010] A method for predicting the burst pressure of CO2 geological sealing caprock in coal seams based on mercury intrusion fractal theory includes the following steps:

[0011] Obtain mercury intrusion porosimetry data of the caprock of the CO2 geological sequestration target;

[0012] Based on the mercury intrusion test data, the fractal dimension was calculated, and the mercury injection process was divided into multiple continuous stages according to the characteristics of the fractal dimension change.

[0013] Identify the critical stage corresponding to the penetration of the pore structure by non-wetting phase fluid, and determine the mercury ingress pressure at the end of the critical stage as the breakthrough pressure of the caprock.

[0014] Based on the aforementioned breakthrough pressure, the ability to break through the geological sealing caprock of coal seams for CO2 can be predicted.

[0015] Preferably, the calculation of the fractal dimension includes the following steps:

[0016] Based on the mercury porosimetry experimental data, plot the relationship curve between ln(dV / dP) and ln(P);

[0017] The relationship curve is piecewise linearly fitted, and the slope of each fitted line segment is denoted as K;

[0018] The fractal dimension D corresponding to each stage is calculated using the formula D = 4 + K.

[0019] Where V is the cumulative mercury inlet volume and P is the mercury inlet pressure.

[0020] Preferably, the mercury injection process is divided into multiple continuous stages based on the characteristics of fractal dimension variation, including:

[0021] The mercury injection process is divided into four stages: initial seepage stage D1, pressure transition stage D2, pore filling stage D3, and compression stage D4; wherein, the critical stage is the pore filling stage D3.

[0022] Preferably, the mercury injection pressure corresponding to the end of the critical stage is determined according to the following steps:

[0023] The relationship curves of ln(dV / dP) and ln(P) were linearly fitted segment by segment from the low-pressure side to the high-pressure side. When the goodness of fit decreased significantly, indicating that the mercury ingress mechanism changed from pore filling to rock skeleton compression, the compression stage D4 was determined. The mercury ingress pressure corresponding to the end of the fitted line segment of the compression stage D4 was taken as the mercury ingress pressure corresponding to the end of the critical stage. This end pressure was determined as the breakthrough pressure of the caprock. In the fourth stage (D4), it is no longer pore filling, but rock skeleton compression. The linear relationship between mercury ingress and pressure deteriorates, and R² suddenly decreases.

[0024] Preferably, based on the breakthrough pressure, the prediction of the breakthrough capability of the coal seam CO2 geological sealing caprock includes: converting the breakthrough pressure into the equivalent capillary pressure under the target fluid system;

[0025] The target fluid system is a mercury-water system or a CO2-water system.

[0026] The preferred conversion for the CO2-water system is as follows:

[0027] ;

[0028] in: , These are the capillary pressures for mercury-driven air and CO2-driven water, respectively. , These refer to the surface tension and contact angle under mercury-driven air conditions, respectively. , These refer to surface tension and contact angle under CO2-driven water conditions, respectively.

[0029] Preferably, after obtaining mercury intrusion porosimetry data of the caprock of the CO2 geological sequestration target, the method further includes the step of correcting the original mercury intrusion porosimetry data to eliminate the pitting effect caused by the surface roughness of the rock.

[0030] Preferably, the rock is mudstone, shale, siltstone, or dense sandstone.

[0031] Preferably, the mudstone can be silty mudstone.

[0032] Technical Theme Two

[0033] The present invention also provides a system for performing the method as described in Technical Subject 1, comprising:

[0034] Input device, used to receive mercury porosimetry experimental data;

[0035] The processor is configured to invoke and execute computer program instructions stored in memory to implement the steps of the method as described in any one of claims 1-6;

[0036] Output devices are used to output predicted values ​​of breakthrough pressure, fractal stage division results, or cap layer sealing capacity evaluation reports.

[0037] A memory, connected to the processor, is used to store computer program instructions and various types of data.

[0038] The beneficial effects of the present invention using the above technical solution are as follows:

[0039] This invention conducts mercury intrusion experiments on the sample in the examples, and obtains the mercury injection increment curve and mercury injection cumulative curve based on the experimental results. Fractal theory is used to analyze the evolution trend of the pore structure, and the evolution stages of the pore structure are identified by combining the fractal dimension calculation results with the mercury intrusion characteristics of the sample. The mercury intrusion pressure at the end of the third stage (micropore filling stage) is determined as the breakthrough pressure, and this pressure value is converted into the equivalent capillary pressure under the Hg-H2O system and the CO2-H2O system according to the difference in interfacial tension, thereby establishing a method for predicting the breakthrough pressure of rock caprock. Compared with the traditional method that defines the pressure corresponding to 10% mercury saturation as the breakthrough pressure, this method has higher accuracy. Especially in the simulation of the CO2-H2O system, due to the consideration of multiphase coupling effects, the calculated structure is closer to the actual engineering conditions. Attached Figure Description

[0040] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0041] Figure 1 This is a flowchart of the method for predicting the pressure breakthrough of the caprock in the geological sealing of CO2 in coal seams based on the mercury intrusion fractal theory of the present invention.

[0042] Figure 2 This is a schematic diagram of the fractal characteristic curve of the rock sample of the present invention.

[0043] Figure 3 The images show the mercury volume increment, cumulative mercury volume curve, and pore fractal dimension fitting diagrams for rock samples 1 and 2 of this invention.

[0044] a is the mercury volume increment and cumulative mercury volume curve of rock sample 1, b is the mercury volume increment and cumulative mercury volume curve of rock sample 2, c is the pore fractal dimension fitting diagram of sample 1 based on mercury intrusion porosimetry results, and d is the pore fractal dimension fitting diagram of sample 2 based on mercury intrusion porosimetry results. Detailed Implementation

[0045] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0046] Example 1

[0047] like Figure 1 The diagram shows a flowchart of a method for predicting the burst pressure of CO2 geological sequestration caprock in coal seams based on mercury intrusion fractal theory. The overall steps are: data acquisition → fractal analysis → stage identification → pressure determination → system conversion, specifically including the following steps:

[0048] Step 1: Obtain mercury intrusion porosimetry (MIP) profiles from caprock samples.

[0049] First, the original mercury intrusion porosimetry (MIP) curves were obtained based on the MIP experiments: these included the incremental mercury injection curve and the cumulative mercury injection curve. The incremental mercury injection curve reflects the increase in mercury injection volume per unit pressure change as pressure increases; the cumulative mercury injection curve shows the cumulative change in mercury injection volume as pressure increases, explaining the process by which the pores of the rock sample are gradually filled as pressure increases.

[0050] 1. Sample preparation:

[0051] 1.1 Obtain representative caprock samples from the study area. Example 1: Sample 1 was taken from Hudi Mine in Qinshui Basin, Shanxi Province, and identified as mudstone after rock sample analysis; Sample 2: silty mudstone.

[0052] 1.2 Cut the sample material into a regular shape and break the sample to about 2 cm to minimize the influence of mineral impurities, man-made cracks and structural cracks on the measurement results.

[0053] 1.3 Place the sample in a drying oven and dry it at a constant temperature of 70~80 ℃ for 12 h.

[0054] 2. Mercury porosimetry experiment:

[0055] A Micromeritics 9310 mercury porosimetry instrument (USA) was used. The dried sample was placed in a dilatometer and a vacuum was created. Pressure was gradually applied to allow mercury to penetrate the rock pores, and the pressure points (P0) were precisely recorded. i The corresponding mercury volume increment (ΔV) i ).

[0056] 3. Curve plotting and correction:

[0057] 3.1 Plotting the original curve: Plot the original mercury injection curve with pressure as the horizontal axis and the cumulative mercury injection volume as the vertical axis, which is the relationship between the volume of mercury entering the pores of the rock sample and the mercury injection pressure.

[0058] 3.2 Correction for the Skin Effect: Based on the skin effect mechanism, the original curve is corrected for surface roughness. The skin effect refers to a non-pore-filling signal generated in the early stage of mercury intrusion porosimetry (MIP) experiments, caused by factors such as surface roughness of the rock sample, resulting in mercury adhering to irregular areas on the sample surface before actually penetrating the pores. This effect artificially inflates the cumulative mercury intrusion in the low-pressure range (usually below about 0.1 MPa), thus distorting the characterization of the true pore structure, especially macropores and fractures. According to the guidance on skin effect correction in the national standard GB / T 29171-2023 "Determination of Rock Capillary Pressure Curves, Clause 4.4.5", in the traditional empirical method that uses the pressure corresponding to 10% mercury saturation as the breakthrough pressure, the usual practice is to treat data points within the skin effect range (usually from the initial pressure to about 0.1 MPa) as invalid data, discard them when calculating mercury saturation, and accumulate the effective mercury intrusion volume from the next pressure stage. In the correction process, this invention first identifies the initial pressure range dominated by the skin effect. Subsequently, using linear fitting, curve translation, or a standard recommended algorithm, the artificially inflated mercury volume within this interval is subtracted from the cumulative mercury injection, thereby generating corrected mercury injection increment and cumulative curves. This corrected data will serve as the sole input for all subsequent fractal calculations and stage divisions, ensuring that the fractal dimension D accurately reflects the geometric characteristics of the rock's internal pore structure, rather than being affected by surface morphology.

[0059] 3.3 Generate mercury injection increment curves and mercury injection cumulative curves:

[0060] The mercury volume increment data points corresponding to the pressure are obtained from the original mercury injection curve. Based on these data points, the mercury injection increment curve and mercury injection cumulative curve are then obtained. Specifically, the steps include:

[0061] 3.3.1 Obtain the mercury injection accumulation curve through the pressure point.

[0062] Set the starting pressure P0, which is usually 0 or the minimum test pressure, and set the corresponding cumulative volume V0 to 0.

[0063] For each pressure point P i (i>1), the corresponding mercury volume increment is ΔV i ΔV exists. i =ΔV1+ΔV2+…+ΔV i ;

[0064] ΔV i Adding it to V, the cumulative mercury volume is: V i =V0+ΔV i ;

[0065] (P i V i () is a point on the cumulative mercury porosimetry curve.

[0066] 3.3.2 Obtain the mercury injection increment curve based on the original mercury injection curve.

[0067] The pressure points P were obtained from the original mercury intrusion porosimetry curve. i and the corresponding mercury volume increment ΔV i .

[0068] Use (P) i , ΔV i Plot the mercury injection increment curve. The horizontal axis represents pressure, and the vertical axis represents the mercury volume increment. Peak values ​​correspond to specific pore diameters, while valley values ​​represent areas with poor pore connectivity or large pore diameter variations.

[0069] Step 2: Calculate fractal dimension and divide stages based on mercury intrusion porosimetry curves.

[0070] 1. The mercury volume increment ΔV obtained from the mercury intrusion porosimetry curve. i The cumulative mercury volume was determined, and the fractal dimension of the sample was quantitatively calculated using the Menger model.

[0071] Based on the mercury intrusion porosimetry (MIP) test results, a fractal model (Menger sponge model) was used to determine the fractal dimension by examining the proportional relationship between the pore size distribution and the fractal dimension of the rock sample surface. Under low pressure, mercury can penetrate the microfractures in the rock sample, while under high pressure, it can penetrate the pores. The mercury injection pressure P and the pore radius r satisfy the Washburn equation, i.e.:

[0072] (1)

[0073] Where: P c σ is the mercury injection pressure, MPa; σ is the surface tension of mercury, with a value of 485 × 10⁻⁶. -3 N / m, θ is the contact angle of mercury, with a value of 130°. r is the pore radius, nm.

[0074] There is a proportional relationship between the sample pore size distribution (dV / dr) and the fractal dimension D. Combining this with the Washburn equation, the fractal dimension can be calculated.

[0075] (2)

[0076] Where V is the pore volume, approximately equal to the cumulative mercury intrusion volume, in cm. 3 / g; D represents the fractal dimension.

[0077] Based on the mercury intrusion porosimetry results, and according to the proportional relationship between ln(dV / dP) and ln(P), the fractal dimension fitting line segment is obtained, the slope K of the line is acquired, and the fractal dimension D is calculated, i.e.:

[0078] (3)

[0079] Where D is the fractal dimension of the sample pores, and K is the slope of the fractal dimension fitting line segment.

[0080] 2. Identifying the stages of pore structure evolution:

[0081] Based on the fractal characteristic curves of the rock samples, the mercury injection process into the rock samples can be divided into four stages, with corresponding fractal dimensions denoted as D1, D2, D3, and D4, respectively. Figure 2 This is a schematic diagram of the fractal characteristic curves of a rock sample.

[0082] In stage I (initial seepage stage D1), mercury first adheres to the rough sample surface (peeling effect), and then penetrates large-scale cracks, i.e., open intergranular pores.

[0083] In stage II (pressure transition stage D2), the significant increase in mercury pressure leads to the accumulation of capillary pressure, which breaks through the edges of rock particles in a short period of time. The fractal dimension increases significantly in this stage, indicating that the increased complexity of the pore structure has a significant hindering effect on fluid transport.

[0084] Stage III (pore-filling stage D3) involves mercury intrusion into the pores within the grains, characterizing the actual structural features of the intergranular pores in the rock sample. Towards the end of this stage, the micropores tend to become saturated, and the mercury pressure reaches a threshold (i.e., breakthrough pressure), triggering rock structural damage.

[0085] Stage IV (compression stage D4): After the internal pores are completely saturated, sustained pressure causes compressive deformation in the rock sample. The appearance of this stage indicates that mercury has penetrated the internal pore system of the rock. During mercury intrusion, pore compression gradually becomes apparent with increasing pressure.

[0086] When performing piecewise linear fitting on the ln(dV / dP) – ln(P) relationship curve, the coefficient of determination R² for each fitted segment can be used to assist in evaluating the significance of fractal characteristics and stage division. Typically, the main stages characterizing pore structure evolution—initial seepage, pressure transition, and pore filling—show high goodness of fit, ensuring the reliability of the fractal dimension D calculation. As the mercury ingress pressure rises to its highest range, the goodness of fit decreases significantly, indicating that the dominant mechanism of mercury ingress has shifted from pore filling to the compression deformation of the rock skeleton; this range corresponds to the compression stage D4. This significant inflection point in the goodness of fit clearly marks the physical endpoint of the pore filling stage D3. This endpoint signifies that the non-wetting phase fluid has completely penetrated the effective interconnected pore network in the rock. Therefore, determining the pressure corresponding to the end of stage D3 as the breakthrough pressure has clear physical mechanism support; this point is precisely the critical pressure threshold for fluid to gradually fill and form a penetrating seepage channel. In practice, the change in the coefficient of determination R² of the piecewise fitting can be used to assist in the judgment. For example, when the R² value of a newly fitted segment decreases significantly compared to the R² value of its immediate preceding stage, such as by more than 20 percentage points, it can be considered an indicative signal of a significant decrease in goodness of fit. Combined with the trend of fractal dimension changes, this is used to comprehensively determine whether the segment has entered the compression stage D4. This significant inflection point in goodness of fit clearly marks the physical endpoint of the pore-filling stage D3. For example, as... Figure 3 In this embodiment, the goodness of fit R² in the pore filling stage is ≥0.95, while the R² in the compression stage shows a significant decrease. The R² in the compression stage of sample 1 and sample 2 are 0.6349 and 0.3768, respectively.

[0087] like Figure 3 The figures show the mercury volume increment, cumulative mercury volume curve, and pore fractal dimension fitting diagrams for rock samples 1 and 2 of this invention; a is the mercury volume increment and cumulative mercury volume curve of sample 1, b is the mercury volume increment and cumulative mercury volume curve of sample 2, c is the pore fractal dimension fitting diagram of sample 1 based on the mercury intrusion porosimetry experiment results, and d is the pore fractal dimension fitting diagram of sample 2 based on the mercury intrusion porosimetry experiment results.

[0088] Step 3: Determine the breakthrough pressure and perform system conversion.

[0089] 1. Determine the breakthrough pressure: The mercury injection pressure corresponding to the end of the third stage (pore filling stage). This was determined to be the breakthrough pressure of the caprock.

[0090] 2. Convert to the target fluid system:

[0091] To apply this to practical engineering, the breakthrough pressure of the mercury-air system measured in the laboratory needs to be converted to the CO2-water system in the underground reservoir.

[0092] The capillary pressure in the gas-water two-phase system is:

[0093] (4)

[0094] in, Capillary pressure under mercury-driven water displacement conditions. The mercury injection pressure under mercury-driven air conditions. , The surface tensions of water and mercury are respectively, with a value of 72.75 × 10⁻⁶. -3 N / m and 485×10 -3 N / m; , These are the contact angles between water and mercury, with values ​​of 0° and 130° respectively.

[0095] Formula for converting capillary pressure in rocks under mercury-air and CO2-water conditions:

[0096] (5)

[0097] in: , These are the capillary pressures for mercury-driven air and CO2-driven water, respectively. , These refer to the surface tension and contact angle under mercury-driven air conditions, respectively, with values ​​of 485 × 10⁻⁶. -3 N / m, 130°; , These refer to the surface tension and contact angle under CO2 water displacement conditions, respectively. In this invention, the surface tension of CO2 under standard conditions (20 °C, 1 atm) is set to 25 × 10⁻⁶. -3 N / m. Since the CO2 sequestration caprock is generally a hydrophilic surface with a contact angle between 0 and 90°, and the contact angle varies among different rocks, this study set the contact angle at 60°.

[0098] Step 4: Output the prediction results

[0099] Finally, the equivalent capillary pressure in the CO2-water system was obtained. This is the predicted caprock breach pressure. Based on this prediction, the sealing capacity and leakage risk of the CO2 geological sequestration caprock in coal seams can be quantitatively assessed.

[0100] Actual calculation verification:

[0101] The method of this invention determines the threshold pressure corresponding to the termination point of stage III as the breakthrough pressure, while the traditional indirect method records the pressure corresponding to 10% of the mercury saturation curve as the breakthrough pressure. The mercury pressure values ​​obtained by the two methods are respectively denoted as... , Converted to capillary pressure, they are denoted as follows: , and , The breakthrough pressure obtained by directly testing using the step-by-step pressurization method is recorded. Error analysis was performed on the capillary pressure obtained by the present invention and the capillary pressure obtained by the traditional direct method, respectively, and the breakthrough pressure obtained by the distributed pressure method. The relative error results were denoted as δ. Fra δ 10 %. The comparison results of the method of the present invention, the traditional indirect method and the stepwise pressurization method are shown in Table 1.

[0102] Table 1

[0103]

[0104] The stepwise pressurization method (direct method) for determining rock breakthrough pressure is as follows: A saturated water-filled rock sample is placed in a triaxial core clamping device, maintaining a constant confining pressure environment downstream. Supercritical CO2 is injected upstream according to a preset pressure gradient to conduct an immiscible displacement experiment. Each pressure gradient must be maintained until the system reaches a two-phase flow equilibrium state, while simultaneously monitoring the downstream outflow rate and gas-phase breakthrough signal. When the applied CO2 displacement pressure gradient exceeds the capillary force threshold of the rock sample, the interfacial tension between the gas and liquid phases is broken, and CO2 forms a continuous phase flow channel. At this point, a gas breakthrough event is detected by a downstream high-precision pressure sensor. Combined with the real-time acquired displacement pressure difference-time curve, the critical pressure gradient at the first appearance of stable gas-phase flow is taken as the rock sample breakthrough pressure value.

[0105] Table 1 uses relative error to represent the error analysis between the calculation results of the traditional indirect method and the fractal analysis method of this invention and the directly tested distributed pressure values ​​in the laboratory, as shown below:

[0106]

[0107] It is evident that the method of this invention significantly improves the calculation accuracy by identifying the evolution stage of pore structure through fractal features: when the mercury ingress pressure is converted to the Hg-H2O system ( The calculation results are compared with traditional methods. The method received better corrections; when the simulation system was a CO2-H2O system ( Although the calculation results are lower than those considering multiphase coupling effects, the calculation results are lower. However, the error has decreased to some extent and is closer to the test value. .

[0108] The present invention also provides a system for performing a method for predicting the breakthrough pressure of coal seam CO2 geological sealing caprock based on mercury intrusion porosimetry fractal theory. The system achieves automatic processing, fractal analysis and high-precision prediction of breakthrough pressure of mercury intrusion porosimetry experimental data through the combination of hardware and software.

[0109] The system includes input devices, a processor, output devices, and memory. These components are interconnected and work together via a system bus.

[0110] 1. Input device, used to receive user input instructions and external data.

[0111] The input device can be a touch screen, keyboard, mouse, or a communication interface for directly importing data from the mercury porosimeter, such as a USB interface, Ethernet port, or Bluetooth module.

[0112] Data reception: The data input or imported through this device mainly includes: raw data from mercury porosimetry experiments: pressure points P at each pressure point. i and the corresponding mercury volume increment ΔV i .

[0113] 2. Memory, used to store computer programs and various types of data.

[0114] The memory may be a high-speed solid-state drive, or may include random access memory and read-only memory.

[0115] Storage content:

[0116] Computer program: Stores program instructions for implementing a method to predict the pressure breakthrough of the caprock in the geological sealing of CO2 in coal seams based on mercury intrusion fractal theory.

[0117] Database: Used to store raw data sent by input devices, intermediate data generated by the processor, and final result data, such as the calculated fractal dimension, the slope K of the fitted curve, and the predicted value of the breakthrough pressure.

[0118] Model parameter library: Pre-stored recommended values ​​for surface tension and contact angle for different rock types.

[0119] 3. The processor, as the core of the system's computing and control, is configured to call and execute program instructions in memory to complete the entire prediction process.

[0120] The processor can be a central processing unit, a graphics processing unit, or a dedicated digital signal processor. Its built-in algorithm module, when executing program instructions, specifically implements the following functions:

[0121] Data preprocessing module: Reads raw data, corrects for the fretting effect, and automatically generates mercury injection increment curves and mercury injection cumulative curves.

[0122] Fractal dimension calculation module: Perform piecewise linear fitting on the data according to formula (2) and calculate the fractal dimension D of each stage.

[0123] Stage identification module: Based on the change of fractal dimension, it automatically identifies and divides the four stages of mercury injection (initial seepage, pressure jump, pore filling, and compression).

[0124] Breakthrough pressure determination module: Automatically marks the pressure corresponding to the end of the pore filling stage, i.e., the third stage, as the breakthrough pressure.

[0125] Pressure conversion module: Based on the user's selection, the Laplace equation is invoked to convert the breakthrough pressure into the equivalent capillary pressure in the Hg-H2O system or CO2-H2O system.

[0126] Report generation module: Integrates all analysis results to generate a structured caprock closure capacity evaluation report.

[0127] 4. Output devices, used to display or transmit the results processed by the processor to the user.

[0128] The output device can be a display screen, a printer, or a network interface for communicating with a remote server.

[0129] Output: Predicted breakthrough pressure values ​​in the CO2-H2O system.

[0130] Users import raw mercury intrusion porosimetry data via the input device and initiate analysis. The processor calls the program in memory, sequentially executing steps such as data preprocessing, fractal calculation, stage identification, pressure determination and conversion, and presents the final results and analysis process visually on the output device. The entire process is highly automated, greatly improving the efficiency and accuracy of prediction.

[0131] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for predicting the pressure of the caprock in coal seam CO2 geological sealing based on mercury intrusion fractal theory, characterized in that, Includes the following steps: Obtain mercury intrusion porosimetry data of the caprock of the CO2 geological sequestration target; Based on the mercury intrusion test data, the fractal dimension was calculated, and the mercury injection process was divided into multiple continuous stages according to the characteristics of the fractal dimension change. Identify the critical stage corresponding to the penetration of the pore structure by non-wetting phase fluid, and determine the mercury ingress pressure at the end of the critical stage as the breakthrough pressure of the caprock. Based on the aforementioned breakthrough pressure, the ability to break through the geological sealing caprock of coal seams for CO2 can be predicted.

2. The method for predicting the breakthrough pressure of coal seam CO2 geological sealing caprock based on mercury intrusion fractal theory according to claim 1, characterized in that, The calculation of the fractal dimension includes the following steps: Based on the mercury porosimetry experimental data, plot the relationship curve between ln(dV / dP) and ln(P); The relationship curve is piecewise linearly fitted, and the slope of each fitted line segment is denoted as K; The fractal dimension D corresponding to each stage is calculated using the formula D = 4 + K. Where V is the cumulative mercury inlet volume and P is the mercury inlet pressure.

3. The method for predicting the pressure breakthrough of the caprock in coal seam CO2 geological sealing based on mercury intrusion fractal theory according to claim 1, characterized in that, Based on the characteristics of fractal dimension variation, the mercury injection process is divided into multiple continuous stages, including: The mercury injection process is divided into four stages: initial seepage stage D1, pressure transition stage D2, pore filling stage D3, and compression stage D4; wherein, the critical stage is the pore filling stage D3.

4. The method for predicting the breakthrough pressure of coal seam CO2 geological sealing caprock based on mercury intrusion fractal theory according to claim 3, characterized in that, The mercury injection pressure corresponding to the end of the critical stage is determined according to the following steps: The relationship curves of ln(dV / dP) and ln(P) were linearly fitted segment by segment from the low-pressure side to the high-pressure side. When the goodness of fit decreased significantly, indicating that the mercury ingress mechanism changed from pore filling to rock skeleton compression, it was determined that the compression stage D4 had been entered. The mercury ingress pressure corresponding to the end point of the fitted line segment before the compression stage D4 was taken as the mercury ingress pressure corresponding to the end of the critical stage.

5. The method for predicting the breakthrough pressure of coal seam CO2 geological sealing caprock based on mercury intrusion fractal theory according to claim 1, characterized in that, Based on the breakthrough pressure, the prediction of the breakthrough capability of the coal seam CO2 geological sealing caprock is achieved, including: converting the breakthrough pressure into the equivalent capillary pressure under the target fluid system; The target fluid system is a mercury-water system or a CO2-water system.

6. The method for predicting the breakthrough pressure of coal seam CO2 geological sealing caprock based on mercury intrusion fractal theory according to claim 4, characterized in that, The conversion of CO2-water system is as follows: ； in: , These are the capillary pressures for mercury-driven air and CO2-driven water, respectively. , These refer to the surface tension and contact angle under mercury-driven air conditions, respectively. , These refer to surface tension and contact angle under CO2-driven water conditions, respectively.

7. The method for predicting the caprock breakthrough pressure of coal seam CO2 geological sealing based on mercury intrusion fractal theory according to claim 1, characterized in that, After obtaining mercury intrusion porosimetry data of the caprock of the CO2 geological sequestration target, the following steps are also included: correcting the original mercury intrusion porosimetry data to eliminate the pitting effect caused by the surface roughness of the rock.

8. The method for predicting the caprock breakthrough pressure of coal seam CO2 geological sealing based on mercury intrusion fractal theory according to claim 1, characterized in that, The rock is mudstone, shale, siltstone or dense sandstone.

9. A system for performing the method as described in any one of claims 1-8, characterized in that, include: Input device, used to receive mercury porosimetry experimental data; The processor is configured to invoke and execute computer program instructions stored in memory to implement the steps of the method as described in any one of claims 1-6; Output devices are used to output predicted values ​​of breakthrough pressure, fractal stage division results, or cap layer sealing capacity evaluation reports. A memory, connected to the processor, is used to store computer program instructions and various types of data.

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