An experimental device and method for measuring the diffusion coefficient of CO2 in porous media formation fluids

Abstract

The application discloses an experimental device and method for measuring the diffusion coefficient of CO2 in a porous medium formation fluid, comprising a CO2 high-pressure steady flow module, a formation fluid sample preparation module, a porous medium clamping module, a temperature and pressure synchronous monitoring module, a diffusion signal acquisition module and a data processing module, wherein each module is connected with a programmable logic controller through a specific connection mode to realize collaborative operation. During the experiment, the CO2 pressure is adjusted, the formation fluid is prepared and the porous medium sample is fixed through the corresponding modules, then the fluid is synchronously injected and the set temperature and pressure conditions are maintained, the internal parameter changes of the porous medium are captured by means of a matrix layout sensing element, and after signal filtering and conversion processing, the diffusion coefficient is obtained by the data processing module through comprehensive multi-factor operation. The device and method realize dynamic matching of temperature and pressure flow parameters and full-dimensional signal acquisition, solve the defects of insufficient module cooperation and limited data precision in the prior art, and are convenient to operate and have strong adaptability.

Description

Technical Field

[0001] This invention relates to the field of experimental technology for the diffusion coefficient of formation fluids, and in particular to an experimental apparatus and method for measuring the diffusion coefficient of CO2 in porous formation fluids. Background Technology

[0002] Driven by global carbon emission reduction goals, technologies such as CO2 geological storage and enhanced oil recovery have become research hotspots in the energy sector. The diffusion behavior of CO2 in porous formation fluids directly affects the efficiency and safety of related engineering projects. Formation environments are characterized by high temperature and pressure, complex fluid composition, and heterogeneous porous media structures. The diffusion process of CO2 with formation fluids is influenced by multiple factors, including pressure, temperature, porosity of the porous media, and fluid viscosity. Accurately obtaining the diffusion coefficient is a crucial prerequisite for optimizing engineering design and assessing storage stability. Current research largely relies on indoor experimental simulations of formation conditions. However, existing experimental devices and methods need to balance multi-parameter synchronous control and accurate signal acquisition to meet the simulation requirements of complex formation environments and provide reliable basic data support for engineering applications.

[0003] The existing technology has two significant drawbacks: First, the modular coordination of the experimental device is insufficient. The parameter control of CO2 transport, formation fluid configuration and porous media bearing is independent, making it difficult to achieve dynamic matching of temperature, pressure and fluid flow rate. This leads to deviations between the simulated formation environment and actual working conditions, affecting the realistic reproduction of the diffusion process. Second, the accuracy of signal acquisition and data processing is limited. Temperature and pressure monitoring mostly adopts single-point sensing methods, which cannot fully capture the parameter changes of the diffusion process inside the porous media. Moreover, the data correction and calculation process does not fully consider the influence of the pore structure of the porous media and the differences in fluid composition, which reduces the reliability of the diffusion coefficient calculation results and makes it difficult to meet the data requirements of high-precision engineering applications. Summary of the Invention

[0004] In order to overcome the shortcomings and deficiencies of the existing technology, the present invention provides an experimental apparatus and method for measuring the diffusion coefficient of CO2 in porous formation fluids.

[0005] The technical solution adopted in this invention is an experimental device for measuring the diffusion coefficient of CO2 in porous formation fluids, comprising: a CO2 high-pressure stabilization module, a formation fluid sample preparation module, a porous medium clamping module, a temperature and pressure synchronous monitoring module, a diffusion signal acquisition module, and a data processing module; The CO2 high-pressure stabilization module is connected to the input end of the porous media clamping module through a corrosion-resistant pipe. The formation fluid sampling module is connected to the side interface of the porous media clamping module through a flow control valve. The temperature and pressure synchronous monitoring module is connected to the sensing element embedded in the porous media clamping module through distributed sensing nodes. The diffusion signal acquisition module is connected to the output end of the temperature and pressure synchronous monitoring module through a data transmission line. The data processing module receives the digital signal transmitted by the diffusion signal acquisition module and performs calculations. The CO2 high-pressure stabilization module delivers CO2 gas at a preset pressure to the porous media clamping module. The formation fluid sampling module injects the configured formation fluid into the porous media clamping module. The porous media clamping module provides a porous media bearing space for CO2 to contact the formation fluid. The temperature and pressure synchronous monitoring module captures temperature and pressure change data at different locations inside the porous media in real time. The diffusion signal acquisition module filters, amplifies, and performs analog-to-digital conversion on the monitoring data. The data processing module performs time-series analysis and diffusion coefficient correlation calculations on the converted digital signal. All modules operate collaboratively through a programmable logic controller.

[0006] Furthermore, the porous media clamping module includes: a porous media sample fixing unit, a sealing and leak-proof unit, a fluid channel distribution unit, and a pressure balancing unit. The porous media sample fixing unit uses an embedded clamp structure to position and clamp porous media samples of different particle sizes. The sealing and leak-proof unit uses a combination structure of stepped sealing grooves and elastic seals to block the fluid leakage path. The fluid channel distribution unit uses internal branched flow channels to guide CO2 and formation fluid to different end faces of the porous media sample. The pressure balancing unit uses a buffer chamber and an elastic diaphragm structure to adjust the internal pressure fluctuation of the porous media clamping module. The flow channel diameter of the fluid channel distribution unit is designed to be proportionally matched to the pore size of the porous media sample. The pressure balancing unit and the temperature and pressure synchronous monitoring module form a closed-loop feedback connection.

[0007] Furthermore, the temperature and pressure synchronous monitoring module includes: a temperature sensing unit, a pressure sensing unit, a signal conditioning unit, and a data synchronization unit. The temperature sensing unit uses platinum resistance sensing elements embedded in a matrix layout inside the porous medium clamping module. The pressure sensing unit is attached to the sensing holes reserved on the surface of the porous medium sample through a miniature pressure probe. The signal conditioning unit performs noise reduction and gain adjustment on the analog signals output by the temperature sensing unit and the pressure sensing unit. The data synchronization unit controls the acquisition timing of temperature and pressure data through a clock synchronization signal. The amplification factor of the signal conditioning unit is dynamically adjusted according to the sensing signal strength. The sampling frequency of the data synchronization unit is consistent with that of the diffusion signal acquisition module.

[0008] Furthermore, the diffusion signal acquisition module includes: a signal filtering unit, an analog-to-digital conversion unit, a data buffer unit, and a transmission interface unit. The signal filtering unit uses a second-order active filter circuit to filter out noise from the original signal output by the temperature and pressure synchronous monitoring module. The analog-to-digital conversion unit converts the filtered analog signal into a 16-bit digital signal. The data buffer unit uses a FIFO storage structure to temporarily store the digital signal. The transmission interface unit transmits the buffered data to the data processing module via the Ethernet protocol. The cutoff frequency of the signal filtering unit is dynamically set according to the experimental conditions, and the sampling frequency of the analog-to-digital conversion unit is not less than 1kHz.

[0009] Furthermore, the data processing module calculates the diffusion coefficient using the following model formula: , in, for The effective diffusion coefficient of fluids in porous formation media. The absolute permeability of the porous medium. The temperature of the experimental system, The pressure difference across the porous medium. For formation fluid dynamic viscosity, For porous media porosity, The length of the porous medium sample. For the first time molar concentration For diffusion time, This represents the total number of data collections.

[0010] Furthermore, the CO2 high-pressure flow stabilization module uses the following model formula for flow control: , in, for Output flow, For valve flow area, Input pressure to the module. Output pressure to the module. for Specific heat ratio, for Gas constant, for Input temperature, This is the flow attenuation coefficient. This refers to the runtime.

[0011] Furthermore, the formation fluid sampling module calculates the sampling ratio using the following model formula: , in, This is the formation fluid sampling coefficient. For crude oil density, The density of the salt water is... For crude oil volume, The volume of the salt water. This refers to the salinity of the salt water. For the viscosity of mixed fluids, For crude oil viscosity, The viscosity of salt water, This represents the volume fraction of crude oil. This represents the volume fraction of the saline solution.

[0012] Furthermore, the porous media clamping module corrects for the effects of porosity using the following model formula: , in, For effective porosity, For true porosity, The average pore diameter, For the tortuosity of porous media, The mean free path of the CO2 molecule. The actual length of the sample. This is the effective length of the gripper.

[0013] Furthermore, the temperature and pressure synchronous monitoring module performs data correction using the following model formula: , in, This is the corrected temperature change. To measure the change in temperature, To measure the pressure change, For temperature coefficient, The specific heat capacity at constant pressure of the fluid. The thermal conductivity of the porous medium is... For fluid density, This is the specific heat capacity at constant volume for the fluid.

[0014] An experimental method for measuring the diffusion coefficient of CO2 in porous formation fluids, applied to an experimental apparatus for measuring the diffusion coefficient of CO2 in porous formation fluids, includes the following steps: S1, adjusting the CO2 gas source pressure to a set value through a CO2 high-pressure stabilization module, while simultaneously configuring formation fluid according to a preset ratio and removing air bubbles from the pipeline using a formation fluid mixing module; S2, loading the porous medium sample into the porous medium clamping module, sealing both ends and sides of the sample using a leak-proof sealing unit, and activating the temperature and pressure synchronous monitoring module to preheat to the experimental temperature and stabilize for 30 minutes; S3, turning on the CO2 high-pressure stabilization module and the formation fluid mixing module... The block's delivery valve injects CO2 and formation fluid into the porous media clamping module at a set flow rate until the internal pressure of the module reaches the experimental set value; S4, the diffusion signal acquisition module captures the signal output by the temperature and pressure synchronous monitoring module at a set sampling frequency, and transmits it to the data buffer unit after signal processing by the signal filtering unit and analog-to-digital conversion unit; S5, the data processing module calls a preset algorithm to perform time-series analysis on the buffered data, and calculates the diffusion-related physical quantities at different times by combining the parameters of each module; S6, the steady-state value is extracted as the final measurement result through the diffusion coefficient change curve output by the data processing module, and an experimental data report is generated at the same time.

[0015] Beneficial Effects: This invention proposes an experimental apparatus and method for measuring the diffusion coefficient of CO2 in porous formation fluids. Through precise control of the CO2 high-pressure flow stabilization module and the formation fluid sample preparation module, combined with the adaptability design of the porous media clamping module, dynamic matching of temperature, pressure, and fluid flow rate is achieved. Each module forms a closed-loop collaborative system through a programmable logic controller, solving the problem of independent parameter control in traditional devices. This makes the simulated formation environment closer to actual working conditions, ensuring the realistic reproduction of the diffusion process. Furthermore, relying on the distributed sensing layout of the temperature and pressure synchronous monitoring module and the multi-level signal processing of the diffusion signal acquisition module... The device comprehensively captures parameter changes at different locations within porous media. The data processing module performs calculations and analyses based on the influence of multiple factors, overcoming the shortcomings of traditional single-point sensing and simplified data processing, and significantly improving the reliability of diffusion coefficient calculation results. The overall device achieves integrated control of the entire process from CO2 and formation fluid transport, porous media carrying, signal monitoring to data processing. This simplifies the experimental operation process while improving the timeliness and accuracy of experimental data, providing more reliable basic data support for projects such as CO2 geological storage and enhanced oil recovery. It is suitable for experimental scenarios with different pore structures and different fluid compositions. Attached Figure Description

[0016] Figure 1 This is a diagram showing the modular composition of the device of the present invention; Figure 2 This is a flowchart of the method steps of the present invention. Detailed Implementation

[0017] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0018] like Figure 1 As shown, an experimental apparatus for measuring the diffusion coefficient of CO2 in porous formation fluid includes: a CO2 high-pressure stabilization module, a formation fluid sample preparation module, a porous media clamping module, a temperature and pressure synchronous monitoring module, a diffusion signal acquisition module, and a data processing module. The CO2 high-pressure stabilization module is connected to the input end of the porous media clamping module through a corrosion-resistant pipe. The formation fluid sampling module is connected to the side interface of the porous media clamping module through a flow control valve. The temperature and pressure synchronous monitoring module is connected to the sensing element embedded in the porous media clamping module through distributed sensing nodes. The diffusion signal acquisition module is connected to the output end of the temperature and pressure synchronous monitoring module through a data transmission line. The data processing module receives the digital signal transmitted by the diffusion signal acquisition module and performs calculations. The CO2 high-pressure stabilization module delivers CO2 gas at a preset pressure to the porous media clamping module. The formation fluid sampling module injects the configured formation fluid into the porous media clamping module. The porous media clamping module provides a porous media bearing space for CO2 to contact the formation fluid. The temperature and pressure synchronous monitoring module captures temperature and pressure change data at different locations inside the porous media in real time. The diffusion signal acquisition module filters, amplifies, and performs analog-to-digital conversion on the monitoring data. The data processing module performs time-series analysis and diffusion coefficient correlation calculations on the converted digital signal. All modules operate collaboratively through a programmable logic controller.

[0019] The CO2 high-pressure flow stabilization module supplies gas to the experimental system. It employs a two-stage pressure reduction structure and a closed-loop flow control mechanism to achieve precise gas delivery. Its input pressure adjustment range is set from 5 to 30 MPa, and the output pressure stability is controlled within ±0.05 MPa. The flow rate adjustment range is 0.1 to 5 liters per minute, meeting the pressure simulation requirements for different formation depths. The module integrates a high-pressure filter, an electromagnetic proportional valve, and a mass flow controller. The high-pressure filter has a filtration accuracy of 0.1 microns, effectively removing impurities from the CO2 gas source and preventing blockage of subsequent pipelines and porous media. The electromagnetic proportional valve has a response time of less than 50 milliseconds, dynamically adjusting its opening by receiving pulse signals from the programmable logic controller. Combined with real-time flow feedback from the mass flow controller, this forms a pressure-flow dual closed-loop control system. During implementation, the pressure of the gas source is first detected by the pressure sensor built into the module. The pressure is then reduced to the experimental set value by the pressure reducing structure. The flow controller then precisely controls the CO2 delivery rate and delivers it to the porous media clamping module through a corrosion-resistant stainless steel pipe. The inner wall of the pipe is polished to a roughness of less than 0.8 micrometers to reduce CO2 flow resistance and adsorption loss, ensuring the stability of pressure and flow rate during delivery. This provides constant CO2 gas source conditions for the diffusion experiment and ensures the accuracy and consistency of the initial experimental parameters.

[0020] The formation fluid mixing module is used to accurately prepare formation fluids that meet experimental requirements. Its mixing volume ranges from 100 to 1000 ml, temperature control accuracy is ±0.5 degrees Celsius, and salinity adjustment range is 0 to 200 g / L. It can simulate crude oil-brine mixtures under different reservoir conditions. The module consists of a storage tank, a stirring device, a density sensor, and a flow metering pump. The storage tank adopts a double-layer insulation structure. The inner layer is made of polytetrafluoroethylene (PTFE), which is highly corrosion-resistant and prevents chemical reactions with the formation fluid. The outer layer is filled with insulation cotton, and together with the heating device, it maintains the set mixing temperature. The stirring device uses magnetic coupling stirring, and the stirring speed can be adjusted from 50 to 500 rpm to ensure thorough mixing of crude oil and brine, with a mixing uniformity error of less than 3%. The density sensor has a measurement accuracy of ±0.001 g / cm³, monitoring fluid density changes in real time during the mixing process and feeding back the data to the programmable logic controller to adjust the injection ratio of each component. During the process, the volume fraction, salinity, and sample mixing temperature of crude oil and brine are first set according to the experimental plan. Quantitative amounts of crude oil and brine are injected into the storage tank using a flow metering pump. The stirring device is started and stirred for 30 to 60 minutes. After the density sensor detects that the fluid density has stabilized, stirring is stopped and the mixture is allowed to stand for 10 minutes to remove air bubbles generated during sample mixing. Then, the prepared formation fluid is injected into the porous media clamping module through a flow control valve. The valve opening can be precisely adjusted according to experimental requirements, and the injection flow rate is controlled between 0.01 and 0.5 liters per minute to ensure that the formation fluid enters the clamping module smoothly and makes full contact with CO2 in the porous media.

[0021] The porous media clamping module facilitates the diffusion of CO2 and formation fluids. Its effective clamping length ranges from 50 to 200 mm, its inner diameter from 25 to 50 mm, its maximum pressure resistance reaches 40 MPa, and its maximum operating temperature is 150 degrees Celsius. It is adaptable to porous media samples of different sizes and types. The main body of the module is made of high-strength titanium alloy, possessing excellent corrosion resistance and pressure resistance. An embedded clamping structure is incorporated internally, securing the porous media sample with bolts. Both ends of the sample are sealed with elastic gaskets, with a sealing pressure exceeding 1.2 times the experimental set pressure, effectively preventing fluid leakage. Multiple sensing holes are pre-drilled inside the module, distributed at different axial and radial positions on the sample, for embedding temperature and pressure sensors. These sensing holes have a diameter of 2 mm and a spacing of 10 to 20 mm, ensuring comprehensive capture of changes in internal sample parameters. The module's sides feature branched flow channels, through which CO2 and formation fluids enter the sample at opposite ends. These channels have a diameter of 3 to 5 mm and are chamfered to reduce dead zones in fluid flow. During implementation, the porous media sample is first cut to the set size, the surface is polished smooth, and then it is installed into the clamping module. It is fixed by the clamp structure and the sealing gasket is pressed to ensure that there is no gap between the sample and the inner wall of the module. Then, the formation fluid sample preparation module is connected through the side interface, and the two end interfaces are connected to the CO2 high-pressure stabilization module and the pressure balance unit. The module is started to preheat to the experimental temperature and stabilized for 30 minutes. After the temperature and pressure parameters are stable, the fluid injection valve is opened, so that CO2 and formation fluid form a stable contact interface inside the sample, providing a real porous media carrying environment for the diffusion process.

[0022] The temperature and pressure synchronous monitoring module is responsible for capturing real-time temperature and pressure changes within the porous medium. Its temperature measurement range is 20 to 150 degrees Celsius with an accuracy of ±0.1 degrees Celsius, and its pressure measurement range is 0 to 40 MPa with an accuracy of ±0.01 MPa. The data sampling frequency is adjustable from 1 to 10 Hz. The module consists of a matrix arrangement of platinum resistance temperature sensors and miniature piezoresistive pressure sensors. The temperature sensors are PT1000 type, with a response time of less than 100 milliseconds. The pressure sensor range is 1.5 times the experimental set pressure to ensure measurement accuracy. The sensors are connected to the signal conditioning unit through distributed sensing nodes. The nodes use RS485 bus communication, with a transmission distance of up to 100 meters and strong anti-interference capability. The signal conditioning unit integrates noise reduction circuitry and gain adjustment module to filter, reduce noise, and amplify the weak analog signal output by the sensors. The amplification factor can be dynamically adjusted within the range of 10 to 100 times. During implementation, temperature and pressure sensors are embedded in the sensing holes of the porous media clamping module, with the sensor probes in close contact with the surface of the porous media sample to ensure the authenticity of the signal acquisition. After the module is started, the sampling frequency is set by the programmable logic controller, and the sensors collect temperature and pressure data at different locations on the sample in real time. After being processed by the signal conditioning unit, the data is transmitted to the data synchronization unit. The data synchronization unit calibrates the acquisition timing of each sensor through a clock synchronization signal to ensure the time consistency of temperature and pressure data, providing accurate raw data for subsequent diffusion coefficient calculation.

[0023] The diffusion signal acquisition module processes and transmits the signal output from the temperature and pressure synchronous monitoring module. It features a 16-bit analog-to-digital conversion accuracy, a conversion rate up to 1 MHz, and a 16 Gigabyte data buffer capacity, supporting continuous data acquisition and storage. The module consists of a signal filtering unit, an analog-to-digital conversion unit, a data buffer unit, and a transmission interface unit. The signal filtering unit employs a second-order active low-pass filter circuit with an adjustable cutoff frequency from 10 Hz to 1 kHz, effectively filtering out high-frequency noise in the signal. The analog-to-digital conversion unit uses a successive approximation converter chip to convert the filtered analog signal into a digital signal, with a conversion error of less than ±1 least significant bit. The data buffer unit uses a FIFO storage structure, supporting first-in-first-out data storage to prevent data loss and providing power-off protection to ensure the safety of experimental data. The transmission interface unit supports both Ethernet and USB interfaces, with an Ethernet transmission rate of 1 gigabits per second and a USB version 3.0 interface to meet different data transmission needs. During implementation, the module is connected to the output of the temperature and pressure synchronous monitoring module via a data transmission line. The cutoff frequency of the signal filtering unit and the conversion rate of the analog-to-digital conversion unit are set. After receiving the analog signal transmitted by the monitoring module, the module first filters out noise through the filtering unit, and then converts it into a digital signal by the analog-to-digital conversion unit. The digital signal is temporarily stored in the data buffer unit. The transmission interface unit transmits the buffered data to the data processing module in real time according to the set transmission protocol, ensuring the high speed and stability of data transmission and providing support for the real-time calculation of the data processing module.

[0024] The data processing module, serving as the control and computation unit of the experimental system, employs an industrial-grade embedded processor with a main frequency of 2.4 GHz and a memory capacity of 8 Gigabytes. It supports multi-threaded parallel computation with a computational latency of less than 10 milliseconds. The module integrates a data receiving unit, a time-series analysis unit, a computational processing unit, and a result output unit. The data receiving unit uses a high-speed data receiving interface to receive digital signals transmitted from the diffusion signal acquisition module in real time, supporting the parsing of multiple data formats. The time-series analysis unit performs time-series alignment and outlier detection on the received data, employing a sliding window algorithm to identify and remove outliers. The outlier detection threshold can be set according to experimental requirements. The computational processing unit incorporates preset data analysis algorithms, combining physical models related to CO2 diffusion with parameters such as porous media porosity, fluid viscosity, experimental temperature, and pressure to perform comprehensive calculations on the time-series data, obtaining diffusion coefficient-related physical quantities at different times. The result output unit supports multiple output formats, including data tables and graphs, and can be connected to external devices such as monitors and printers to display experimental data and calculation results in real time. During implementation, the module establishes communication connections with other modules through a programmable logic controller (PLC) to coordinate the runtime sequence of each module. After receiving data transmitted from the diffusion signal acquisition module, the time series analysis unit first performs data preprocessing to remove outliers and align the time series. Then, the computation processing unit performs diffusion coefficient calculations, calling parameter data from each module in real time for correction during the calculation process. Finally, the result output unit outputs the diffusion coefficient change curve and the final measurement result, while generating an experimental data report to provide experimental personnel with comprehensive and accurate experimental analysis results.

[0025] Preferably, the porous media clamping module includes: a porous media sample fixing unit, a sealing and leak-proof unit, a fluid channel distribution unit, and a pressure balancing unit. The porous media sample fixing unit uses an embedded clamp structure to position and clamp porous media samples of different particle sizes. The sealing and leak-proof unit uses a combination structure of stepped sealing groove and elastic sealing element to block the fluid leakage path. The fluid channel distribution unit uses internal branched flow channels to guide CO2 and formation fluid to different end faces of the porous media sample. The pressure balancing unit uses a buffer chamber and elastic diaphragm structure to adjust the internal pressure fluctuation of the porous media clamping module. The flow channel diameter of the fluid channel distribution unit is designed to be proportionally matched with the pore size of the porous media sample. The pressure balancing unit and the temperature and pressure synchronous monitoring module form a closed-loop feedback connection.

[0026] Specifically, the four units of the porous media clamping module work together to stably support the porous media sample and ensure efficient fluid contact. The porous media sample fixing unit adopts an embedded clamp structure, with the inner diameter of the clamp adjustable from 25 to 50 mm to accommodate cylindrical porous media samples of different sizes. The inner wall of the clamp is textured with anti-slip features and a friction coefficient greater than 0.6. Bolt tightening provides a clamping force of 5 to 15 kN, ensuring that the sample does not shift during high-pressure experiments. The sealing and leak-proof unit uses a combination of a stepped sealing groove and a fluororubber elastic seal. The sealing groove is 5 mm deep and 8 mm wide, and the compression of the elastic seal is controlled at 20% to 30%, with a maximum sealing pressure of 40 MPa, completely preventing fluid leakage from the gap between the sample and the module's inner wall. The fluid channel distribution unit internally processes branched flow channels. The main channel has a diameter of 5 mm, and the branch channels have a diameter of 3 mm. The contact points between the branch channels and the end face of the porous media sample are evenly distributed with a spacing of 10 mm, allowing CO2 and formation fluid to be evenly injected from both ends and sides of the sample, forming a stable contact interface. The pressure balancing unit includes a 50 ml buffer chamber and a 2 mm thick elastic diaphragm. The diaphragm is made of hydrogenated nitrile rubber with an elastic modulus of 1.5 MPa. When the internal pressure fluctuation exceeds 0.1 MPa, the diaphragm absorbs the pressure change through deformation. At the same time, it forms a closed-loop feedback with the temperature and pressure synchronous monitoring module to adjust the fluid volume of the buffer chamber in real time, so that the internal pressure fluctuation is controlled within ±0.05 MPa, providing a stable pressure environment for the diffusion process and ensuring the accuracy of experimental data.

[0027] Preferably, the temperature and pressure synchronous monitoring module includes: a temperature sensing unit, a pressure sensing unit, a signal conditioning unit, and a data synchronization unit. The temperature sensing unit uses platinum resistance sensing elements embedded in a matrix layout inside the porous medium clamping module. The pressure sensing unit is attached to the sensing holes reserved on the surface of the porous medium sample through a miniature pressure probe. The signal conditioning unit performs noise reduction and gain adjustment on the analog signals output by the temperature sensing unit and the pressure sensing unit. The data synchronization unit controls the acquisition timing of temperature data and pressure data through a clock synchronization signal. The amplification factor of the signal conditioning unit is dynamically adjusted according to the sensing signal strength. The sampling frequency of the data synchronization unit is consistent with that of the diffusion signal acquisition module.

[0028] Specifically, the four units of the temperature and pressure synchronous monitoring module accurately capture and synchronously transmit temperature and pressure parameters within the porous medium. The temperature sensing unit uses PT1000 platinum resistance thermometers, embedded in the porous medium clamping module in a 5×5 matrix layout. The sensor spacing is 10 mm, the measurement range covers 20 to 150 degrees Celsius, the resolution reaches 0.01 degrees Celsius, and the response time is less than 100 milliseconds, enabling rapid capture of temperature gradient changes at different locations within the sample. The pressure sensing unit uses a miniature piezoresistive pressure probe with a diameter of 2 mm and a length of 8 mm. It is fixed to the sensing hole pre-drilled on the surface of the porous medium sample via threads, with a probe-to-sample surface fit greater than 95%. The measurement range is 0 to 40 MPa, with an accuracy of ±0.01 MPa, allowing real-time sensing of minute changes in pore pressure within the sample. The signal conditioning unit integrates a low-noise operational amplifier and an RC filter circuit. The amplification factor can be dynamically adjusted within the range of 10 to 100 times via a programmable logic controller. The filter circuit cutoff frequency is set to 10 Hz, effectively filtering out environmental electromagnetic interference and high-frequency noise generated by vibration, resulting in a signal-to-noise ratio greater than 60 dB. The data synchronization unit uses a high-precision clock chip with a clock error of less than 1 microsecond. It communicates with each sensing unit via an RS485 bus, calibrating sensing signals of different locations and types according to a unified timestamp. This ensures that the timing deviation between temperature and pressure data acquisition is less than 1 millisecond, providing highly synchronized and reliable raw data support for subsequent diffusion coefficient calculations.

[0029] Preferably, the diffusion signal acquisition module includes: a signal filtering unit, an analog-to-digital conversion unit, a data buffer unit, and a transmission interface unit. The signal filtering unit uses a second-order active filter circuit to filter out noise from the original signal output by the temperature and pressure synchronous monitoring module. The analog-to-digital conversion unit converts the filtered analog signal into a 16-bit digital signal. The data buffer unit uses a FIFO storage structure to temporarily store the digital signal. The transmission interface unit transmits the buffered data to the data processing module via the Ethernet protocol. The cutoff frequency of the signal filtering unit is dynamically set according to the experimental conditions, and the sampling frequency of the analog-to-digital conversion unit is not less than 1kHz.

[0030] Specifically, the four units of the diffusion signal acquisition module sequentially complete signal purification, conversion, storage, and transmission, ensuring data integrity and timeliness. The signal filtering unit adopts a second-order active low-pass filter circuit, composed of operational amplifiers, capacitors, and resistors. The cutoff frequency can be manually adjusted within the range of 10 Hz to 1 kHz according to experimental conditions. It performs two-stage filtering on the analog signal output from the temperature and pressure synchronous monitoring module, filtering out more than 99% of noise signals with frequencies higher than the cutoff frequency, keeping the signal fluctuation amplitude within ±0.001 volts. The analog-to-digital conversion unit uses a 16-bit successive approximation converter chip with a conversion rate of up to 1 MHz, an input signal range of ±5 volts, and a conversion error of less than ±1 least significant bit. It accurately converts the filtered analog signal into a digital signal, with a conversion delay of less than 1 microsecond for each signal, ensuring real-time signal conversion. The data buffer unit adopts a FIFO storage structure with a storage capacity of 16 gigabytes. It supports a first-in-first-out (FIFO) storage mode, achieving a read / write speed of 100 megabytes per second. It is also equipped with a backup power supply, which can maintain data storage for 60 minutes in the event of a sudden power outage, preventing data loss. The transmission interface unit integrates both Ethernet and USB 3.0 interfaces. The Ethernet interface supports the TCP / IP protocol with a transmission rate of 1 gigabit per second, while the USB 3.0 interface has a transmission rate of 5 gigabit per second. The appropriate transmission method can be selected based on the experimental environment. During data transmission, the CRC32 checksum algorithm is used, achieving 100% accuracy to ensure that digital signals are transmitted without distortion or packet loss, providing high-quality data input for the real-time computation of the data processing module.

[0031] Preferably, the data processing module calculates the diffusion coefficient using the following model formula: , in, for The effective diffusion coefficient of fluids in porous formation media. The absolute permeability of the porous medium. The temperature of the experimental system, The pressure difference across the porous medium. For formation fluid dynamic viscosity, For porous media porosity, The length of the porous medium sample. For the first time molar concentration For diffusion time, This represents the total number of data collections.

[0032] Specifically, the data processing module deeply integrates key parameters such as the absolute permeability of the porous media, the temperature of the experimental system, the pressure difference across the porous media, the dynamic viscosity of the formation fluid, the porosity of the porous media, the length of the porous media sample, the CO2 molar concentration at different times, the diffusion time, and the total number of data acquisitions. Through multi-dimensional parameter coupling calculations, it achieves an accurate solution for the effective diffusion coefficient. During the implementation phase, the data processing module first receives the digital signal transmitted from the diffusion signal acquisition module, which has undergone two stages of filtering, amplification, and analog-to-digital conversion. It accurately extracts information on the pressure difference across the porous media and the changes in CO2 molar concentration at different times from the time-series data. Simultaneously, it calls upon pre-stored basic parameters of the porous media, with the absolute permeability measurement accuracy strictly controlled within ±5% and the porosity measurement error not exceeding 2%, ensuring the accuracy of parameter input. The calculation process unfolds according to a specific logic. First, the temperature value of the experimental system is raised to the 1.5th power and multiplied with the pressure difference across the porous medium. The result is then coupled with the absolute permeability. The denominator is further coupled by the product of the formation fluid dynamic viscosity, the porosity of the porous medium, and the length of the porous medium sample, and the sum of the products of the CO2 molar concentration at different times and the square root of the corresponding diffusion time. Throughout the calculation, an iterative optimization algorithm is used to dynamically correct the systematic and random errors introduced by each parameter. The calculation delay is strictly controlled within 10 milliseconds, ultimately ensuring that the relative error of the effective diffusion coefficient calculation result is less than 3%. This method comprehensively considers the combined coupling influence of temperature, pressure, fluid physical properties, and the microstructure of the porous medium on the diffusion process, effectively solving the problem of insufficient measurement accuracy caused by the inadequate integration of multiple influencing factors in traditional calculation methods, and providing core technical support for the accurate acquisition of the diffusion coefficient.

[0033] Preferably, the CO2 high-pressure flow stabilizing module uses the following model formula for flow control: , in, for Output flow, For valve flow area, Input pressure to the module. Output pressure to the module. for Specific heat ratio, for Gas constant, for Input temperature, This is the flow attenuation coefficient. This refers to the runtime.

[0034] Specifically, the CO2 high-pressure flow stabilization module achieves high-precision control of CO2 output flow rate through the coordinated coupling calculation of parameters such as valve flow area, module input pressure, module output pressure, CO2 specific heat ratio, CO2 gas constant, CO2 input temperature, flow attenuation coefficient, and running time. During implementation, the module's built-in high-precision pressure sensor collects input and output pressure data in real time, with measurement accuracy controlled within ±0.01 MPa. Simultaneously, combined with preset valve flow area parameters, this flow area can be precisely adjusted within the range of 0.1 to 10 square millimeters according to experimental conditions, while synchronously invoking the inherent physical parameters of CO2, namely specific heat ratio and gas constant. The calculation proceeds according to a specific logic: first, the input pressure is coordinated with the square root of the CO2 specific heat ratio, CO2 gas constant, and CO2 input temperature. The denominator is constructed by taking the square root of the difference between the ratio of input pressure to output pressure raised to a specific power and 1. Then, an exponential term based on running time is introduced to precisely correct for flow attenuation, where the flow attenuation coefficient is set between 0.001 and 0.01 according to the experimental temperature and pressure conditions. This method uses a closed-loop feedback control mechanism to convert the calculation results into control signals to dynamically adjust the opening of the electromagnetic proportional valve. The valve response time is less than 50 milliseconds, which ultimately ensures that the CO2 output flow rate regulation accuracy is strictly controlled within ±0.01 liters per minute. This ensures the long-term stability and dynamic adjustability of the CO2 output flow rate, accurately adapts to the flow rate requirements under different experimental conditions, provides a constant and controllable gas supply for the entire diffusion experiment, and guarantees the stability of the initial boundary conditions of the experiment.

[0035] Preferably, the formation fluid sampling module calculates the sampling ratio using the following model formula: , in, This is the formation fluid sampling coefficient. For crude oil density, The density of the salt water is... For crude oil volume, The volume of the salt water. This refers to the salinity of the salt water. For the viscosity of mixed fluids, For crude oil viscosity, The viscosity of salt water, This represents the volume fraction of crude oil. This represents the volume fraction of the saline solution.

[0036] Specifically, the formation fluid sampling module integrates core parameters such as crude oil density, brine density, crude oil volume, brine volume, brine salinity, mixed fluid viscosity, crude oil viscosity, brine viscosity, and oil-water volume fraction. It determines the formation fluid sampling coefficient through coupled calculations of the physical properties of multiple fluid components, providing a basis for accurate sampling. During implementation, the module's built-in high-precision density sensor monitors the density data of crude oil and brine in real time, with a measurement accuracy of ±0.001 g / cm³. Simultaneously, the volume fractions of crude oil and brine are set according to the experimental plan, with the volume fraction adjustment accuracy controlled within ±1%. The brine salinity is precisely set within the range of 0 to 200 g / L according to the simulated formation requirements. The calculation process follows a specific logic. First, the mass of crude oil and the mass of brine are calculated by multiplying the crude oil density by its volume and the brine density by its volume, respectively. These two products are then summed to obtain the total mass of the oil and water mixture. The total mass is then corrected based on the brine salinity parameter. Simultaneously, the viscosity of the mixed fluid is calculated as a weighted sum of the crude oil viscosity (based on crude oil volume fraction) and the brine viscosity (based on brine volume fraction). The numerator is constructed by coupling the corrected total mass of the oil and water mixture with the viscosity of the mixed fluid, while the denominator is the weighted sum of the aforementioned viscosity values. Throughout the calculation, the effect of temperature on fluid viscosity is synchronously corrected. For every 1 degree Celsius change in temperature, the viscosity correction coefficient is adjusted by 0.02 to ensure the accuracy of the viscosity parameters. This method can achieve precise configuration of formation fluids under different oil-water ratios and salinity conditions. The calculation error of the sampling coefficient is less than 2%, and the homogeneity error of the mixed fluid is controlled within 3%. This effectively meets the experimental requirements for simulating different formation fluid components and solves the problem of insufficient configuration accuracy caused by the reliance on empirical ratio settings in traditional sampling methods.

[0037] Preferably, the porous media clamping module corrects for the effects of porosity using the following model formula: , in, For effective porosity, For true porosity, The average pore diameter, For the tortuosity of porous media, The mean free path of the CO2 molecule. The actual length of the sample. This is the effective length of the gripper.

[0038] Specifically, the porous media clamping module design achieves precise correction of effective porosity and improves the realism of experimental simulation through the coordinated calculation of parameters such as the actual porosity, average pore diameter, tortuosity of the porous media, mean free path of CO2 molecules, actual sample length, and effective length of the clamp. In the implementation phase, the actual porosity and average pore diameter data of the porous media are first obtained by measuring with professional experimental equipment. The measurement error of the actual porosity is controlled within 2%, and the measurement resolution of the average pore diameter reaches 0.1 micrometers. Simultaneously, a preset porous media tortuosity parameter is used, with a value range set between 1.5 and 3.0 depending on the type of porous media. The mean free path of CO2 molecules is theoretically calculated based on the temperature and pressure conditions set in the experiment, with a calculation error of less than 5%. The calculation follows a specific logic. First, the average pore diameter, the tortuosity of the porous medium, and the mean free path of CO2 molecules are synergistically coupled. Then, a sine function value is calculated using the ratio of the actual sample length to the effective length of the gripper. The measurement accuracy of both the actual sample length and the effective gripper length is controlled within ±0.1 mm. The results of the above two calculations are coupled and subtracted from 1. The difference is then multiplied by the true porosity of the porous medium to obtain the corrected effective porosity. This correction method fully considers the heterogeneity of the porous medium's pore structure, the influence of pore geometry, and the diffusion characteristics of CO2 molecules on the diffusion process. The calculation error of the corrected effective porosity is less than 3%, making the simulated porous medium pore environment closer to actual formation conditions.

[0039] Preferably, the temperature and pressure synchronous monitoring module performs data correction using the following model formula: , in, This is the corrected temperature change. To measure the change in temperature, To measure the pressure change, For temperature coefficient, The specific heat capacity at constant pressure of the fluid. The thermal conductivity of the porous medium is... For fluid density, This is the specific heat capacity at constant volume for the fluid.

[0040] Specifically, the temperature and pressure synchronous monitoring module achieves precise correction of temperature changes and improves the reliability of monitoring data by coupling calculations of parameters such as temperature change, pressure change, temperature coefficient, fluid isobaric specific heat capacity, porous medium thermal conductivity, fluid density, and fluid isovolumetric specific heat capacity. During implementation, the module first receives raw monitoring data collected by the temperature and pressure sensing units. The temperature measurement accuracy is strictly controlled within ±0.1 degrees Celsius, and the pressure measurement accuracy reaches ±0.01 MPa. It extracts the temperature and pressure change information from the raw data and simultaneously calls upon preset stored fluid and porous medium thermophysical parameters. The fluid isobaric specific heat capacity measurement error is less than 2%, the porous medium thermal conductivity measurement accuracy is controlled within ±5%, and the fluid density and fluid isovolumetric specific heat capacity are precisely set according to the experimental conditions. The calculation proceeds according to a specific logic. First, the pressure change, temperature coefficient, and fluid isobaric specific heat capacity are coupled and calculated. The denominator is constructed by taking the square root of the product of the thermal conductivity of the porous medium, the fluid density, and the fluid isovolic specific heat capacity. The resulting calculation is used as a temperature correction value to compensate for and correct the original measured temperature change. This method effectively compensates for the cross-interference caused by pressure changes during the experiment. After correction, the measurement error of the temperature change is controlled within 0.05 degrees Celsius, ensuring the accuracy, synchronization, and consistency of temperature and pressure monitoring data. This provides high-quality raw data input for subsequent diffusion coefficient calculations and solves the data deviation problem caused by traditional monitoring methods that do not consider temperature-pressure coupling interference.

[0041] like Figure 2 As shown, an experimental method for measuring the diffusion coefficient of CO2 in porous formation fluids is described. This method is applied to an experimental apparatus for measuring the diffusion coefficient of CO2 in porous formation fluids and includes the following steps: S1, adjusting the CO2 gas source pressure to a set value using a CO2 high-pressure stabilization module, while simultaneously configuring the formation fluid according to a preset ratio using a formation fluid mixing module and removing air bubbles from the pipeline; S2, loading the porous medium sample into the porous medium clamping module, sealing both ends and sides of the sample using a leak-proof sealing unit, and activating the temperature and pressure synchronous monitoring module to preheat to the experimental temperature and stabilize for 30 minutes; S3, turning on the CO2 high-pressure stabilization module and the formation fluid mixing module. The module's delivery valve injects CO2 and formation fluid into the porous media clamping module at a set flow rate until the internal pressure of the module reaches the experimental set value; S4, the diffusion signal acquisition module captures the signal output by the temperature and pressure synchronous monitoring module at a set sampling frequency, and transmits it to the data buffer unit after signal processing by the signal filtering unit and analog-to-digital conversion unit; S5, the data processing module calls a preset algorithm to perform time-series analysis on the buffered data, and calculates the diffusion-related physical quantities at different times by combining the parameters of each module; S6, the steady-state value is extracted as the final measurement result from the diffusion coefficient change curve output by the data processing module, and an experimental data report is generated at the same time.

[0042] An experimental apparatus and method for measuring the diffusion coefficient of CO2 in porous formation fluids are disclosed. Through precise control of a high-pressure CO2 flow stabilization module and a formation fluid sample preparation module, coupled with an adaptable structural design of a porous media clamping module, and utilizing a programmable logic controller (PLC) to construct a closed-loop collaborative mechanism, dynamic matching of temperature, pressure, and fluid flow rate is achieved. This makes the simulated formation environment closer to actual engineering scenarios, fully reproducing the diffusion process of CO2 in porous formation fluids. Stable connections are established between modules via corrosion-resistant pipes, flow control valves, and distributed sensing nodes, ensuring rapid signal transmission and parameter control response. This avoids experimental deviations caused by poor module linkage in traditional devices, significantly improving the stability and controllability of the experimental process.

[0043] This invention overcomes the shortcomings of traditional single-point sensing and simplified data processing in terms of comprehensive signal acquisition and scientific data processing. The temperature and pressure synchronous monitoring module employs a matrix-layout sensing element to comprehensively capture temperature and pressure changes at different locations within the porous medium. The diffusion signal acquisition module ensures the integrity and accuracy of the original signal through multi-stage filtering, amplification, and conversion. The data processing module integrates multiple factors for comprehensive calculation and analysis, fully considering key factors such as the pore structure of the porous medium and fluid composition, significantly improving the reliability of the diffusion coefficient calculation results. The integrated control design simplifies experimental operations, reduces errors caused by human intervention, and the device is adaptable to experimental requirements with different pore structures and fluid compositions, making it widely applicable and providing more accurate and reliable basic data support for related engineering projects.

[0044] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," "link," and "fix" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0045] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various equivalent changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An experimental apparatus for measuring the diffusion coefficient of CO2 in a porous media formation fluid, comprising: include: CO2 high-pressure stabilization module, formation fluid sampling module, porous media clamping module, temperature and pressure synchronous monitoring module, diffusion signal acquisition module, and data processing module; The CO2 high-pressure stabilization module is connected to the input end of the porous media clamping module through a corrosion-resistant pipe. The formation fluid sampling module is connected to the side interface of the porous media clamping module through a flow control valve. The temperature and pressure synchronous monitoring module is connected to the sensing element embedded in the porous media clamping module through distributed sensing nodes. The diffusion signal acquisition module is connected to the output end of the temperature and pressure synchronous monitoring module through a data transmission line. The data processing module receives the digital signal transmitted by the diffusion signal acquisition module and performs calculations. The CO2 high-pressure stabilization module delivers CO2 gas at a preset pressure to the porous media clamping module. The formation fluid sampling module injects the configured formation fluid into the porous media clamping module. The porous media clamping module provides a porous media bearing space for CO2 to contact the formation fluid. The temperature and pressure synchronous monitoring module captures temperature and pressure change data at different locations inside the porous media in real time. The diffusion signal acquisition module filters, amplifies, and performs analog-to-digital conversion on the monitoring data. The data processing module performs time-series analysis and diffusion coefficient correlation calculations on the converted digital signal. All modules operate collaboratively through a programmable logic controller.

2. The experimental apparatus for measuring the diffusion coefficient of CO2 in the fluid of a porous medium formation according to claim 1, wherein, The porous media clamping module includes: a porous media sample fixing unit, a sealing and leak-proof unit, a fluid channel distribution unit, and a pressure balancing unit. The porous media sample fixing unit uses an embedded clamp structure to position and clamp porous media samples of different particle sizes. The sealing and leak-proof unit uses a combination structure of stepped sealing grooves and elastic seals to block the fluid leakage path. The fluid channel distribution unit uses internal branched flow channels to guide CO2 and formation fluid to different end faces of the porous media sample. The pressure balancing unit uses a buffer chamber and an elastic diaphragm structure to regulate the internal pressure fluctuation of the porous media clamping module. The flow channel diameter of the fluid channel distribution unit is designed to be proportionally matched to the pore size of the porous media sample. The pressure balancing unit and the temperature and pressure synchronous monitoring module form a closed-loop feedback connection.

3. The experimental apparatus for measuring the diffusion coefficient of CO2 in porous formation fluids according to claim 1, characterized in that, The temperature and pressure synchronous monitoring module includes: a temperature sensing unit, a pressure sensing unit, a signal conditioning unit, and a data synchronization unit. The temperature sensing unit uses platinum resistance sensing elements embedded in a matrix layout inside the porous medium clamping module. The pressure sensing unit is attached to the sensing holes reserved on the surface of the porous medium sample through a miniature pressure probe. The signal conditioning unit performs noise reduction and gain adjustment on the analog signals output by the temperature sensing unit and the pressure sensing unit. The data synchronization unit controls the acquisition timing of temperature and pressure data through a clock synchronization signal. The amplification factor of the signal conditioning unit is dynamically adjusted according to the sensing signal strength. The sampling frequency of the data synchronization unit is consistent with that of the diffusion signal acquisition module.

4. The experimental apparatus for measuring the diffusion coefficient of CO2 in porous formation fluids according to claim 1, characterized in that, The diffusion signal acquisition module includes: a signal filtering unit, an analog-to-digital conversion unit, a data buffer unit, and a transmission interface unit. The signal filtering unit uses a second-order active filter circuit to filter out noise from the original signal output by the temperature and pressure synchronous monitoring module. The analog-to-digital conversion unit converts the filtered analog signal into a 16-bit digital signal. The data buffer unit uses a FIFO storage structure to temporarily store the digital signal. The transmission interface unit transmits the buffered data to the data processing module via the Ethernet protocol. The cutoff frequency of the signal filtering unit is dynamically set according to the experimental conditions, and the sampling frequency of the analog-to-digital conversion unit is not less than 1kHz.

5. The experimental apparatus for measuring the diffusion coefficient of CO2 in porous formation fluids according to claim 1, characterized in that, The data processing module calculates the diffusion coefficient using the following model formula: ， in, for The effective diffusion coefficient of fluids in porous formation media. The absolute permeability of the porous medium. The temperature of the experimental system, The pressure difference across the porous medium. For formation fluid dynamic viscosity, For porous media porosity, The length of the porous medium sample. For the first time molar concentration For diffusion time, This represents the total number of data collections.

6. The experimental apparatus and method for measuring the diffusion coefficient of CO2 in porous formation fluids according to claim 1, characterized in that, The CO2 high-pressure flow stabilization module uses the following model formula for flow control: ， in, for Output flow, For valve flow area, Input pressure to the module. Output pressure to the module. for Specific heat ratio, for Gas constant, for Input temperature, This is the flow attenuation coefficient. This refers to the runtime.

7. The experimental apparatus for measuring the diffusion coefficient of CO2 in porous formation fluids according to claim 1, characterized in that, The formation fluid sampling module calculates the sampling ratio using the following model formula: ， in, This is the formation fluid sampling coefficient. For crude oil density, The density of the salt water is... For crude oil volume, The volume of the salt water. This refers to the salinity of the salt water. For the viscosity of mixed fluids, For crude oil viscosity, The viscosity of salt water, This represents the volume fraction of crude oil. This represents the volume fraction of the saline solution.

8. The experimental apparatus for measuring the diffusion coefficient of CO2 in porous formation fluids according to claim 1, characterized in that, The porous media clamping module corrects for the effects of porosity using the following model formula: ， in, For effective porosity, For true porosity, The average pore diameter, For the tortuosity of porous media, The mean free path of the CO2 molecule. The actual length of the sample. This is the effective length of the gripper.

9. The experimental apparatus for measuring the diffusion coefficient of CO2 in porous formation fluids according to claim 1, characterized in that, The temperature and pressure synchronous monitoring module performs data correction using the following model formula: ， in, This is the corrected temperature change. To measure the change in temperature, To measure the pressure change, For temperature coefficient, The specific heat capacity at constant pressure of the fluid. The thermal conductivity of the porous medium is... For fluid density, This is the specific heat capacity at constant volume for the fluid.

10. An experimental method for measuring the diffusion coefficient of CO2 in porous formation fluids, characterized in that, This method is applied to the experimental apparatus for measuring the diffusion coefficient of CO2 in porous formation fluids as described in claim 1, comprising the following steps: S1, adjusting the CO2 gas source pressure to a set value through the CO2 high-pressure stabilization module, while the formation fluid sample preparation module prepares the formation fluid according to a preset ratio and removes air bubbles from the pipeline; S2, loading the porous medium sample into the porous medium clamping module, sealing both ends and sides of the sample through the sealing and leak-proof unit, and starting the temperature and pressure synchronous monitoring module to preheat to the experimental temperature and stabilize for 30 minutes; S3, opening the delivery valves of the CO2 high-pressure stabilization module and the formation fluid sample preparation module, and proceeding according to the preset... S4: CO2 and formation fluid are injected into the porous media clamping module until the internal pressure of the module reaches the experimental set value; S5: The diffusion signal acquisition module captures the signal output by the temperature and pressure synchronous monitoring module at the set sampling frequency, and transmits it to the data buffer unit after signal processing by the signal filtering unit and the analog-to-digital conversion unit; S6: The data processing module calls the preset algorithm to perform time-series analysis on the buffer data, and calculates the diffusion-related physical quantities at different times by combining the parameters of each module; S7: The steady-state value is extracted as the final measurement result by the diffusion coefficient change curve output by the data processing module, and an experimental data report is generated at the same time.

Images