Experimental Analysis Method for Dynamic Blockage of Salt Crystallization in Real Porous Networks

Abstract

This invention discloses an experimental analysis method for dynamic blockage of salt crystallization under a real pore network. A heterogeneous microfluidic chip is constructed based on the pore structure of a real core sample. Microfluidic experimental equipment is installed. Pressure difference-normalized time curves are obtained during CO2 injection into the chip in saturated pure water and saturated saline water. The gas-liquid two-phase flow behavior, salt crystallization nucleation, crystal growth, and deposition processes within the microchannels of the microfluidic chip are recorded. The pore volume blockage rate is quantitatively calculated based on image analysis, and the pressure contribution term is normalized and quantitatively characterized. A final comprehensive blockage index is calculated by combining the pore volume blockage rate and the pressure contribution term. Experimental conditions are varied, and the experiment is repeated to obtain salt precipitation blockage data under different conditions. This invention combines image recognition and pressure data fusion analysis to propose a comprehensive dynamic blockage index, achieving continuous quantitative discrimination and dynamic evolution characterization of different blockage states.

Description

Technical Field

[0001] This invention relates to the field of saline aquifer CO2 geological sequestration technology, and in particular to experimental simulation technology for reservoir permeability damage caused by salt precipitation crystallization. Background Technology

[0002] CO2 geological sequestration is an important technical approach to mitigate the greenhouse effect, and saline aquifers are considered one of the most promising sequestration sites due to their wide distribution and large storage potential. However, during CO2 injection, formation water evaporation leads to increased ion concentration and the precipitation of salt crystals. This salt precipitation phenomenon significantly reduces reservoir permeability, affecting sequestration efficiency and long-term safety. Salt crystals clogging pore throats not only reduce the effective CO2 injection rate but may also cause abnormal increases in wellbore pressure, threatening engineering safety. Currently, some studies on salt precipitation in saline aquifer CO2 sequestration use microfluidic chips to visualize the salt crystallization process, simulate CO2 injection conditions, and analyze the impact of salt precipitation on porosity and permeability. Although some progress has been made, there is a lack of observation and quantitative analysis of the dynamic process of salt precipitation. Existing studies mostly focus on static observation or qualitative analysis of the salt precipitation process, lacking tracking of the entire process of crystal growth and clogging, and even more so, lacking quantitative characterization methods for the degree of clogging. Summary of the Invention

[0003] The main objective of this invention is to provide an experimental analysis method for the dynamic blockage of salt crystals in a real porous network. By integrating microscopic imaging technology, the growth and blockage process of salt crystals in the porous network can be observed and recorded in real time, and a quantitative characterization method can be developed to evaluate the degree of blockage in porous media.

[0004] To achieve the above objectives, the present invention employs the following technical solution to realize the observation of the dynamic blockage process of salt crystallization and the analysis of the degree of blockage:

[0005] An experimental analysis method for dynamic blockage of salt crystallization in a real porous network includes the following steps:

[0006] S1. Constructing a heterogeneous microfluidic chip based on the pore structure of real rock cores;

[0007] S2. Install and connect the microfluidic experimental equipment;

[0008] S3. Obtain the pressure difference-normalized time curve of the chip during CO2 injection in saturated pure water;

[0009] S4. Obtain the pressure difference-normalized time curve of the chip during CO2 injection in saturated saline water, and continuously record the gas-liquid two-phase flow behavior, salt crystallization nucleation, crystal growth and deposition process in the microchannel of the microfluidic chip using a high-speed micro-camera system.

[0010] S5. Quantitatively calculate the pore volume blockage rate based on image analysis, normalize and quantitatively characterize the pressure contribution term, and finally calculate the final comprehensive blockage index by combining the pore volume blockage rate and the pressure contribution term.

[0011] S6. Change the experimental conditions and repeat the experiment to obtain salting-out blockage data under different conditions.

[0012] In the above scheme, the microfluidic experimental equipment includes a CO2 injection pump, a thermostatic holder, a microfluidic chip, a constant pressure tracking pump, a high-speed microscopic imaging system, and a workstation. The microfluidic chip is integrated into the thermostatic holder. The CO2 injection pump is connected to the inlet of the microfluidic chip through an inlet pipe, and the outlet of the microfluidic chip is connected to the constant pressure tracking pump through an outlet pipe. An inlet pressure sensor is installed on the inlet pipe, and an outlet pressure sensor is installed on the outlet pipe. The high-speed microscopic imaging system is located on the side of the thermostatic holder and integrates a microscope lens and a high-speed camera. The inlet pressure sensor, the outlet pressure sensor, and the high-speed microscopic imaging system are respectively connected to the workstation through signal lines.

[0013] In the above scheme, a valve is also provided on the inlet pipe; a back pressure valve is also provided on the outlet pipe.

[0014] In the above scheme, the specific experimental methods for S3 include:

[0015] S31. Set experimental parameters before the experiment begins, including temperature, system pressure, and CO2 injection rate;

[0016] S32. After the experimental parameters are set, the degassed pure water is injected into the microfluidic chip at constant pressure to ensure that the pore space is completely saturated and there are no residual bubbles.

[0017] S33. Start the CO2 injection program to displace the pure water in the pores at a preset constant flow rate. During this process, the inlet pressure is synchronously collected by pressure sensors installed at the inlet and outlet. P in and export pressure P out Real-time calculation of pressure difference P 0= P in - P out And plot the dynamic pressure difference-normalized time curve. P 0- t / t 0max , t For time, t 0max For when P 0 reaches its maximum value P 0maxThe time of day.

[0018] In the above scheme, the specific experimental method for S4 includes:

[0019] S41. Set the same experimental parameters as in stage S3;

[0020] S42. After heating the pre-prepared saline solution to the same experimental temperature as in stage S3, inject it into the microfluidic chip at a constant pressure until the pore space is completely saturated.

[0021] S43. Start the CO2 injection program to displace the saline water in the pores at a preset constant flow rate. During this process, the inlet pressure is synchronously collected by pressure sensors installed at the inlet and outlet. P’ in and export pressure P’ out Real-time calculation of pressure difference P s = P’ in - P ’ out And plot the dynamic pressure difference-normalized time curve. P s - t / t smax , t smax For when P s Reaching the maximum value P smax The system simultaneously starts a high-speed microscopic imaging system to continuously record the gas-liquid two-phase flow behavior, salt crystallization nucleation, crystal growth and deposition process within the microchannel; all pressure data and image data are synchronized at the millisecond level.

[0022] In the above scheme, S5, the method for quantitatively calculating the pore volume blockage rate based on image analysis is as follows: preprocess each frame of image, segment the salt crystallization blockage area using an adaptive threshold algorithm, and calculate the blockage area at each time step. A b The pore volume blockage rate is systematically calculated at fixed time intervals. F c ,draw F c With normalization time t / t smax Changing curve F c - t / t smax Record the maximum value throughout the entire experiment. F cmax .

[0023] In the above scheme, the normalization and quantitative characterization of the pressure contribution term in S5 are specifically performed as follows: to eliminate the influence of experimental condition fluctuations and highlight the additional flow resistance caused by salt crystallization, a dimensionless pressure contribution term is defined. F p :

[0024] F p =1- P 0 / P s

[0025] In the formula, P 0 represents the pressure difference during the CO2 displacement process in saturated pure water, and is the baseline flow resistance under salt-free conditions. P s This represents the pressure difference during the CO2 displacement process in saturated saline water.

[0026] In the above scheme, in S5, the specific method for calculating the final comprehensive congestion index is as follows: constructing a comprehensive congestion index.

[0027]

[0028] In the formula, F c Pore ​​volume blockage rate, F p As a contribution to stress;

[0029] Divided by experimental results The value is used to evaluate the degree of congestion.

[0030] In the above schemes, different The following values ​​evaluate the degree of congestion:

[0031] No blockage;

[0032] 2. Weak blockage;

[0033] Severe congestion;

[0034] 0.4, completely blocked.

[0035] In the above scheme, S6 adopts a full factorial experimental design method, systematically changing the combination of four key variables: temperature, pressure, injection rate, and salt concentration. Each variable is set with 3-5 levels, and a total of 50-80 sets of experiments are completed. Each set of experiments is repeated 3 times to ensure data reproducibility, and the experimental data are automatically stored in a structured database.

[0036] The beneficial effects of this invention are:

[0037] This invention proposes a method for analyzing the dynamic blockage of salt crystals in a real pore network. By tracking the entire dynamic process of salt crystals from nucleation and growth to pore blockage in real time, and combining image recognition with pressure data fusion analysis, a comprehensive dynamic blockage index is proposed. F It enables continuous quantitative discrimination and dynamic evolution characterization of different blockage states, such as no blockage, weak blockage, strong blockage and complete blockage, and significantly improves the spatiotemporal analysis capability of the dynamic blockage mechanism of crystallization.

[0038] Microfluidic experimental equipment can precisely control experimental conditions within the range of 5–15 MPa pressure and 20–90 ℃ temperature to simulate real geological environments. It supports full-factor experiments under different temperatures, pressures, salinities, and injection rates, providing a reliable experimental evaluation method for the risk of salt precipitation blockage in CO2 geological sequestration. By quantitatively analyzing the blockage patterns, it provides experimental basis and theoretical support for accurately assessing the risk of salt crystallization blockage in CO2 sequestration in saline aquifers, optimizing injection schemes (such as temperature, pressure, injection rate, and brine composition control), and designing efficient unblocking measures.

[0039] This invention fills the gap in current microfluidic research regarding the quantitative analysis of dynamic salt crystallization blockage at the real pore scale, and promotes the development of CO2 geological storage technology towards a more precise and safer direction. This invention not only provides a reliable experimental platform for salt formation risk research in fields such as CO2 geological storage and oil and gas extraction, but can also be used for optimizing prevention and control strategies and evaluating their effectiveness. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a schematic flowchart of the experimental analysis method for dynamic blockage of salt crystallization under real porous network in this invention;

[0042] Figure 2 This is a diagram of the actual rock pore network in an embodiment of the present invention;

[0043] Figure 3 This is a diagram of a microfluidic chip constructed based on a real rock pore network in an embodiment of the present invention;

[0044] Figure 4 This is a schematic diagram of the microfluidic experimental device used in the embodiments of the present invention;

[0045] Figure 5 These are the injection pressure curves before and after blockage in this embodiment of the invention;

[0046] Figure 6 This is a photograph showing the result of salting out when CO2 is injected into a chip saturated with salt water in an embodiment of the present invention.

[0047] In the diagram: 1. CO2 injection pump; 2. Valve; 3. Inlet pressure sensor; 4. Thermostatic clamp; 5. Outlet pressure sensor; 6. Back pressure valve; 7. Constant pressure tracking pump; 8. Microfluidic chip; 9. High-speed microscope imaging system; 10. Workstation. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0049] It should be noted that the illustrations provided in the embodiments of the present invention are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the number, shape and size of the components in actual implementation. In actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0050] In this invention, it should also be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. Furthermore, the terms "first" and "second" are used only for descriptive and distinguishing purposes and should not be construed as indicating or implying relative importance.

[0051] like Figure 1 As shown, this invention proposes an experimental analysis method for dynamic blockage of salt crystallization in a real porous network, comprising the following steps:

[0052] S1. Constructing a heterogeneous microfluidic chip based on the pore structure of real rock cores.

[0053] Based on CT scan data of target reservoir cores, a microfluidic chip with a realistic heterogeneous pore structure is constructed using high-precision photolithography or 3D printing technology. The chip's pore network rigorously replicates the pore size distribution (typically 10-200 μm), tortuosity (1.2-2.5), and connectivity characteristics of actual reservoirs, ensuring the geological representativeness of the experiment. The microfluidic chip body is made of high-pressure resistant borosilicate glass or surface-modified PDMS material, capable of withstanding working pressures above 15 MPa, and features a transparent observation window with a thickness ≤1 mm. The channel surface undergoes a controllable hydrophilic / hydrophobic treatment, allowing for flexible simulation of reservoir conditions with varying wettability.

[0054] S2. Install and connect the microfluidic experimental equipment.

[0055] like Figure 2 As shown, the microfluidic experimental setup employs a modular design, comprising a high-precision CO2 injection pump 1, a thermostatic clamp 4, a microfluidic chip 8, a constant-pressure tracking pump 7, a high-speed microscopic imaging system 9, and a workstation 10. The microfluidic chip 8 is integrated into the thermostatic clamp 4. The CO2 injection pump 1 is connected to the inlet of the microfluidic chip 8 via an inlet pipe, and the outlet of the microfluidic chip 8 is connected to the constant-pressure tracking pump 7 via an outlet pipe. The inlet pipe is equipped with an inlet pressure sensor 3 and a valve 2, while the outlet pipe is equipped with an outlet pressure sensor 5 and a backpressure valve 6. The high-speed microscopic imaging system 9 is located on the side of the thermostatic clamp 4 and integrates a 20-100x long working distance microscope lens and a high-speed camera, with a maximum frame rate of 1000fps. The inlet pressure sensor 3, the outlet pressure sensor 5, and the high-speed microscopic imaging system 9 are connected to the workstation 10 via signal lines, storing the acquired pressure data and images in the workstation 10.

[0056] The constant pressure tracking pump 7 has a control accuracy of ±0.01 mL / min; the operating temperature inside the thermostatic clamp is 20-90℃; the range of the inlet pressure sensor 3 and the outlet pressure sensor 5 is 0-20 MPa, with an accuracy of ±0.1% FS. The inlet and outlet pipelines use 1 / 16-inch high-pressure pipelines, and sealed joints are used to ensure high-pressure airtightness.

[0057] S3. Obtain the pressure difference-normalized time curve of the chip during CO2 injection in saturated pure water. P 0- t / t 0max Specific experimental methods include:

[0058] S31. Before the experiment begins, accurately set the experimental parameters, including temperature, system pressure, and CO2 injection rate. Temperature is controlled by a high-precision thermostatic clamp 4, with a typical setting range of 40 to 60 degrees Celsius and a temperature control accuracy of ±0.5℃. System pressure is regulated in a closed loop by a fully automatic backpressure valve 6, with an operating pressure range of 5 to 15 MPa and stability better than 0.1 MPa. The CO2 injection rate is precisely controlled by a precision CO2 injection pump 1, with a flow rate range of 0.01 to 1 mL / min and a resolution of 0.001 mL / min.

[0059] S32. After the experimental parameters are set, the degassed pure water is injected into the microfluidic chip at constant pressure to ensure that the pore space is completely saturated and there are no residual air bubbles.

[0060] S33. Start the CO2 injection program to displace the pure water in the pores at a preset constant flow rate. During this process, the inlet pressure is synchronously collected by pressure sensors installed at the inlet and outlet at a set sampling frequency. P in and export pressure P out Real-time calculation of pressure difference P 0= P in - P out ,when P 0 reaches its maximum value P 0max Time recording t 0max Normalize the time term: t / t 0max (Values ​​range from 0 to 1), plot the dynamic pressure difference-normalized time curve. P 0- t / t 0max .

[0061] S4. Obtain the pressure difference-normalized time curve of the chip during CO2 injection in saturated saline water. P s - t / t smax The gas-liquid two-phase flow behavior, salt crystallization nucleation, crystal growth, and deposition processes within the microchannels of the microfluidic chip were continuously recorded using a high-speed microscopic imaging system. Specific experimental methods included:

[0062] S41. All experimental parameters, such as set temperature, system pressure, and CO2 injection rate, are completely consistent with those in S3 to ensure comparability of experimental conditions.

[0063] S42. Using a pre-prepared saline solution (NaCl concentration 0-20 wt%, which can be adjusted according to the actual formation water salinity), the saline solution is heated to the same experimental temperature as in stage S3 (temperature control accuracy ±0.5℃) through a constant temperature circulation system, and then injected into the microfluidic chip at a constant pressure until the pore space is completely saturated.

[0064] S43. Start the CO2 injection program to displace the saline water in the pores at a preset constant flow rate. During this process, the inlet pressure is synchronously collected by pressure sensors installed at the inlet and outlet at a set sampling frequency. P’ in and export pressure P’ out Real-time calculation of pressure difference P s = P’ in - P’ out ,when P s Reaching the maximum value P smax Time recording t smax Normalize the time term: t / t smax (Values ​​range from 0 to 1), and plot the dynamic pressure difference-normalized time curve. P s - t / t smax The high-speed microscopic imaging system is started simultaneously, continuously recording the gas-liquid two-phase flow behavior, salt crystallization nucleation, crystal growth and deposition process in the microchannel according to the set acquisition frequency; all pressure data and image data are synchronized at the millisecond level through precise hardware triggering and software timestamps.

[0065] S5. Based on image analysis, the pore volume blockage rate is quantitatively calculated, and then the pressure contribution term is normalized and quantitatively characterized to calculate the final comprehensive blockage index.

[0066] S5-1. Quantitative Calculation of Pore Volume Blockage Rate Based on Image Analysis

[0067] Image processing techniques were employed to quantitatively analyze the acquired microscopic dynamic processes. Each image frame underwent preprocessing (including background correction, contrast enhancement, and noise filtering). An adaptive thresholding algorithm was used to segment the salt crystallization blockage region, and the blockage area at each time step was calculated. A b During the analysis, the pore volume blockage rate is systematically calculated at fixed time intervals. F c pore volume blockage rate F cCalculate using the following formula:

[0068] F c = A b / A t

[0069] In the formula, A t The initial pore area was obtained by calibrating the blank chip image acquired before the experiment.

[0070] Because all pressure and image data are synchronized at the millisecond level during the brine injection process, it is possible to draw... F c With normalization time t / t smax Changing curve F c - t / t smax Record the maximum value throughout the entire experiment. F cmax It can also calculate curves. F c - t / t smax The first derivative is used to analyze the variation characteristics of the blockage rate.

[0071] S5-2. Normalization and Quantitative Characterization of Pressure Contribution Term

[0072] To eliminate the effects of fluctuations in experimental conditions and highlight the additional flow resistance caused by salt crystallization, a dimensionless pressure contribution term is defined. F p :

[0073] F p =1- P 0 / P s

[0074] In the formula, P 0 represents the pressure difference during the CO2 displacement process in saturated pure water, and is the baseline flow resistance under salt-free conditions. P s This represents the pressure difference during the CO2 displacement process in saturated saline water. This indicator... F p The contribution of the additional pressure differential due to salt crystallization was quantified: when there is no blockage, P s = P 0, F p = 0; when a complete blockage occurs, Ps >> P 0, F p Approaching 1. F p It is a dynamic value. After normalizing the time as described above, we can calculate the values ​​at the same time. P 0 / P s Finally, the dynamic was calculated. F p This normalization process enables the comparability of pressure data under different experimental conditions and directly reflects the degree of influence of salt crystallization on flow resistance.

[0075] S5-3. Calculate the final comprehensive congestion index.

[0076] To comprehensively reflect both microscopic visual information (direct observation) and macroscopic pressure response (flow performance), a comprehensive congestion index is constructed.

[0077]

[0078] In the formula, F c Pore ​​volume blockage rate, F p Contribution to stress.

[0079] Experiments showed that when there is no blockage, and It is 0 at this time. The value is 0; when completely blocked, due to P s Much larger P 0, at this time Approximately 1, while It is approximately 0.2 at this time. The value is 0.447. Different divisions are based on experimental results. The following table evaluates the degree of congestion:

[0080]

[0081] S6. Change the experimental conditions and repeat the experiment to obtain salting-out blockage data under different conditions.

[0082] A full factorial experimental design was employed, systematically varying combinations of four key variables (temperature, pressure, injection rate, and salt concentration), with 3-5 levels for each variable, resulting in 50-80 experimental groups. Each experiment was repeated three times to ensure data reproducibility, and the experimental data were automatically stored in a structured database. Additional experimental groups were added for special operating conditions (such as supercritical CO2 conditions). This design comprehensively covers the parameter range that may be encountered in actual storage projects and captures the interactions between parameters. The experimental duration was dynamically adjusted according to the blockage development, typically ranging from 2 to 8 hours, until the system pressure differential reached a steady state or rose to three times its initial value.

[0083] The following is a specific experimental case to illustrate the experimental analysis method for dynamic blockage of salt crystallization under real porous networks, including the following steps:

[0084] S1: Based on the CT scan data of the target reservoir core (e.g.) Figure 2 As shown), a microfluidic chip with a real heterogeneous porous structure is constructed using high-precision photolithography technology (such as...). Figure 3 (As shown). The chip's pore network strictly replicates the pore size distribution of actual reservoirs (mainly ranging from 10 to 200 μm), with a tortuosity of 1.8 and an etching depth of 15 μm. The chip body is made of high-pressure resistant borosilicate glass, capable of withstanding working pressures above 15 MPa, and features a 1 mm thick transparent observation window. The channel surface is hydrophilically treated to simulate hydrophilic reservoir conditions.

[0085] S2: As Figure 4 As shown, the microfluidic experimental equipment was installed and connected. All equipment was cleaned and dried before the experiment to ensure the system was clean.

[0086] S3: The temperature is set to 30℃ via a high-precision thermostatic clamp control system; the system pressure is set to 5 MPa via a fully automatic backpressure valve; and the CO2 injection rate is set to 0.1 mL / min. After parameter settings are complete, degassed pure water is injected into the microfluidic chip at constant pressure to ensure complete saturation of the pore space and absence of air bubbles. Subsequently, a preset constant flow rate of CO2 displaces the pure water in the pores. A high-precision pressure sensor synchronously acquires the inlet pressure at a sampling frequency of 10 Hz. P in and export pressure P out Real-time calculation of pressure difference P 0= P in - P out ,when P 0 reaches its maximum value P 0max Time recordingt 0max Normalize the time term: t / t 0max (Values ​​range from 0 to 1), plot the dynamic pressure difference-normalized time curve. P 0- t / t 0max .,like Figure 5 As shown. By analyzing the characteristics of this curve, the maximum pressure difference during the CO2 displacement process is extracted. P 0max (Approximately 30 kPa).

[0087] S4: Maintain all experimental parameters, including temperature, system pressure, and CO2 injection rate, exactly as set in stage S3. Using a pre-prepared saline solution (NaCl concentration 80,000 ppm, approximately 8 wt%), heat the saline solution to the same experimental temperature (30°C) as in stage S3 using a constant-temperature circulation system, and then inject it into the chip at a constant pressure until complete saturation. Start the CO2 injection program to displace the saline solution in the pores at a preset constant flow rate. During this process, the inlet pressure is synchronously collected using pressure sensors located at the inlet and outlet at a sampling frequency of 10 Hz. P’ in and export pressure P’ out Real-time calculation of pressure difference P s = P’ in - P’ out ,when P s Reaching the maximum value P smax Time recording t smax Normalize the time term: t / t smax (Values ​​range from 0 to 1), and plot the dynamic pressure difference-normalized time curve. P s - t / t smax ,like Figure 5 As shown, the maximum pressure difference value during the CO2 displacement process is extracted. P smax (Approximately 170 kPa). A high-speed microscopic imaging system was simultaneously activated to continuously record the gas-liquid two-phase flow behavior, salt crystallization nucleation, crystal growth, and deposition process within the microchannel at a sampling frequency of 1 frame / second.

[0088] S5-1: Perform quantitative analysis on the acquired microscopic dynamic process images and calculate the blockage area at each time step. A bThe analysis is performed systematically at fixed time intervals (one frame is extracted every 5 seconds). F c Values, drawn to form F c Curves of variation with normalized time F c - t / t smax To obtain the maximum value at the point of final blockage. F cmax (Approximately 0.13). Simultaneously, the first derivative of the curve was calculated to analyze the characteristics of changes in the blockage rate.

[0089] S5-2: Calculate the dimensionless pressure contribution term F p = 1 - P 0 / P s Substitute P 0max ≈ 30 kPa, P smax ≈ 170kPa, calculated to obtain the maximum value at the point of final blockage. F pmax ≈ 0.824. This indicator quantifies the percentage of additional pressure differential contribution caused by salt crystallization.

[0090] S5-3: Calculate the overall congestion index:

[0091]

[0092] Substitution F p ≈ 0.824, F c ≈ 0.13 (Calculated value of the final chip image after blockage, such as...) Figure 6 As shown), the calculation yields F ≈ 0.327. (Compare to different values) F According to the evaluation table of blockage severity, this condition is considered severe blockage.

[0093] S6: Experiments were repeated under different conditions to obtain salting-out blockage data. A full factorial experimental design was used, systematically changing combinations of four key variables (temperature: 30, 45, 60℃; pressure: 5, 10, 15 MPa; injection rate: 0.01, 0.05, 0.1 mL / min; salt concentration: 0, 40000, 80000, 120000, 160000 ppm), completing a total of 60 experiments. Experimental results showed that the comprehensive blockage index... F It is closely related to various operating parameters and saline concentration. Safe operating range (weak clogging, F<0.2) mainly occurs under the following conditions: salt concentration ≤ 40000 ppm, injection rate ≤ 0.05 mL / min, temperature ≥ 45°C, and pressure ≥ 10 MPa.

[0094] It should be noted that, depending on the implementation needs, the various steps / components described in this application can be broken down into more steps / components, or two or more steps / components or parts of the operation of steps / components can be combined into new steps / components to achieve the purpose of this invention.

[0095] The order of the steps in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0096] It should be understood that those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A method for analyzing salt crystallization dynamic plugging experiment under real pore network, characterized in that, The method comprises the following steps: S1, constructing a heterogeneous microfluidic chip based on real core pore structure; S2, installing and connecting the microfluidic experimental equipment; S3, obtaining the differential pressure-normalized time curve of the chip in the CO2 injection process when saturated with pure water, and the specific experimental method comprises: S31, setting experimental parameters before the experiment, including temperature, system pressure and CO2 injection rate; S32, after the experimental parameter setting is completed, the degassed pure water is injected into the microfluidic chip in a constant pressure manner to ensure that the pore space is completely saturated and no bubbles are left; S33, start CO2 injection program to displace pure water in the pore at a preset constant flow rate, in the process, the inlet pressure is synchronously collected by the pressure sensor arranged at the inlet and outlet P in and outlet pressure P out , the differential pressure is calculated in real time P 0 = P in - P out , and a dynamic differential pressure-normalized time curve is drawn P 0- t / t 0max , t t is time, t 0max tmaxis the time when P 0 reaches the maximum value P 0max . S4, obtaining the differential pressure-normalized time curve of the chip in the CO2 injection process when saturated with salt water, and the specific experimental method comprises: S41, setting the same experimental parameters as in S3 stage; S42, after the pre-configured salt water solution is heated to the same experimental temperature as in S3 stage, it is injected into the microfluidic chip at a constant pressure until the pore space is completely saturated; S43, start CO2 injection program to displace salt water in the pore with a preset constant flow rate, in the process, the inlet pressure is synchronously collected by the pressure sensor set at the inlet and outlet P’ in and outlet pressure P’ out , real-time calculation of pressure difference P s = P’ in - P ’ out , and draw dynamic pressure difference-normalized time curve P s - t / t smax , t smax the time when P s reaches the maximum value P smax ; simultaneously start the high-speed microscopic camera system to continuously record the gas-liquid two-phase flow behavior, salt crystal nucleation, crystal growth and deposition process in the microchannel of the microfluidic chip; all pressure data and image data are synchronized at the millisecond level; S5, quantitative calculation of pore volume plugging rate based on image analysis, normalization processing and quantitative characterization of pressure contribution item, and finally combination of pore volume plugging rate and pressure contribution item to calculate the final comprehensive plugging index; The quantitative calculation method for pore volume blockage rate is as follows: preprocess each frame of image, segment the salt crystallization blockage region using an adaptive threshold algorithm, and calculate the blockage area at each time step. A b The pore volume blockage rate is systematically calculated at fixed time intervals. Φ c ,draw Φ c With normalization time t / t smax Changing curve Φ c - t / t smax Record the maximum value throughout the entire experiment. Φ cmax ; The normalization process and quantitative characterization method of the pressure contribution term are: to eliminate the influence of experimental condition fluctuation and highlight the additional flow resistance caused by salt crystallization, a dimensionless pressure contribution term is defined Φ p : Φ p =1- P 0 / P s wherein P 0 is the pressure difference during CO2 displacement in saturated pure water, representing the reference flow resistance under salt-free conditions; P s is the pressure difference during CO2 displacement in saturated salt water. The method for calculating the final comprehensive plugging index is to construct a comprehensive plugging index wherein Φ c is the pore volume blockage rate, Φ p is the pressure contribution term; The experimental results are divided into different values to evaluate the degree of clogging. S6, change the experimental conditions and repeat the experiment to obtain the salting-out plugging data under different conditions.

2. The method according to claim 1, wherein, The microfluidic experimental equipment comprises a CO2 injection pump, a constant temperature holder, a microfluidic chip, a constant pressure tracking pump, a high-speed microscopic camera system and a workstation; the microfluidic chip is integrated in the constant temperature holder, the CO2 injection pump is connected with the inlet of the microfluidic chip through an inlet pipeline, the outlet of the microfluidic chip is connected with the constant pressure tracking pump through an outlet pipeline, an inlet pressure sensor is arranged on the inlet pipeline, and an outlet pressure sensor is arranged on the outlet pipeline; the high-speed microscopic camera system is arranged on the side of the constant temperature holder and is integrated with a microscope lens and a high-speed camera; the inlet pressure sensor, the outlet pressure sensor and the high-speed microscopic camera system are connected with the workstation through signal lines respectively.

3. The method according to claim 2, wherein, Valves are further arranged on the inlet pipeline; back pressure valves are further arranged on the outlet pipeline.

4. The method of claim 1, wherein, different The degree of clogging was evaluated as follows: No blockage; 2, weak jam; , strong clogging; 0.4, complete blockage.

5. The method of claim 1, wherein, In S6, the full factorial experimental design method is adopted to systematically change the combination of four key variables, temperature, pressure, injection rate and salt concentration, 3-5 levels are set for each variable, and a total of 50-80 groups of experiments are completed; each group of experiments is repeated 3 times to ensure data repeatability, and experimental data is automatically stored as a structured database.

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