Microfluidic-based heterogeneous composite flooding residual oil sweep and mobilization experimental method

Abstract

The application provides a microfluidic-based heterogeneous complex flooding remaining oil sweep and displacement experiment method, and belongs to the technical field of physical simulation. The method first prepares methylene blue-containing simulated formation water, a binary flooding system and a heterogeneous complex flooding system solution with different proportions, then installs a heterogeneous microfluidic chip containing three pore throat size regions in a clamping system and sets 11 MPa confining pressure, 9 MPa back pressure and 70 DEG C temperature conditions, then carries out oil saturation operation until complete saturation, then sequentially carries out multi-round displacement experiments of water flooding to a water content of 94%, binary flooding, water flooding to a water content of 98%, heterogeneous complex flooding and final water flooding to a water content of 100%, and real-time calculation of seepage parameters of each region during displacement. After each displacement, the chip image is collected, and the contribution rate and sweep conversion rate of different proportion systems to each size pore throat are quantitatively analyzed by a remaining oil displacement efficiency optimization function.

Description

Technical Field

[0001] This invention belongs to the field of physical simulation technology, and specifically relates to an experimental method for residual oil wave propagation based on microfluidics-based heterogeneous composite flooding. Background Technology

[0002] In the field of oil extraction, residual oil recovery technology is a key aspect of enhancing oil recovery. Traditional laboratory experimental methods mainly employ core displacement experiments and numerical simulation techniques to evaluate the effectiveness of different displacement systems. Core displacement experiments involve injecting various displacement fluids into natural or artificial cores to observe and measure pressure changes, product fluid composition, and recovery indicators during the displacement process. Numerical simulations, on the other hand, use mathematical models based on reservoir engineering theory to predict displacement effects. These traditional techniques are widely used in the petroleum industry, providing an important theoretical foundation and experimental support for the development of composite flooding technologies.

[0003] However, traditional core displacement experiments have significant technical limitations. They cannot directly observe the changes in residual oil distribution in different pore throat regions at the microscale, and it is difficult to distinguish the specific contributions of high-permeability, medium-permeability, and low-permeability zones to the overall displacement effect. Furthermore, they lack a precise description of the seepage mechanism in heterogeneous composite displacement systems within pore throats of different sizes. While numerical simulation methods can perform partitioned calculations, they lack microscopic experimental verification, and parameter settings are often based on empirical assumptions, making it difficult to accurately reflect the real physical processes within complex pore structures.

[0004] The core problem that traditional technologies cannot solve is the lack of experimental methods that can simultaneously achieve microscopic visualization, zonal quantitative analysis, and precise description of mechanisms, making it impossible to provide accurate quantitative evaluation and optimization guidance for the utilization effect of residual oil in pore throat regions of different sizes. Summary of the Invention

[0005] In view of this, the present invention provides a microfluidic-based heterogeneous composite flooding residual oil wave and mobilization experimental method, which can solve the technical problem in the prior art that it is difficult to accurately simulate and quantify the mobilization effect of residual oil in orifice throat regions of different sizes.

[0006] This invention provides an experimental method for residual oil ripple and mobilization in heterogeneous composite flooding based on microfluidics. It constructs a heterogeneous microfluidic chip model containing regions with different pore throat sizes using microfluidic technology. By combining the Darcy-capillary pressure coupling equation, it calculates seepage characteristic parameters in real time and uses a residual oil mobilization efficiency optimization function to quantitatively analyze the mobilization effect. This solves the technical problem of existing technologies being unable to accurately simulate and quantify the residual oil mobilization effect in pore throat regions of different sizes. The method includes the following steps:

[0007] Simulated formation aqueous solution, binary flooding system solution, heterogeneous composite flooding system solution, and simulated oil were prepared. The heterogeneous microfluidic chip model was installed in the microfluidic chip model clamping system and experimental conditions were set. Saturated oil operation was performed. Simulated formation aqueous solution, binary flooding system solution, heterogeneous composite flooding system solution, and finally water flooding were injected sequentially. During the displacement process, the Darcy-capillary pressure coupling equation was used to calculate the seepage characteristic parameters of different pore throat size regions in real time. After each displacement, the heterogeneous microfluidic chip model image was acquired using a high-definition digital camera. The residual oil mobilization efficiency optimization function was used to quantitatively analyze the mobilization contribution rate and sweep efficiency of heterogeneous composite flooding system solutions with different ratios to pore throat regions of various sizes. The heterogeneous microfluidic chip model was cleaned after the experiment.

[0008] Specifically, the preparation step of the simulated formation aqueous solution involves mixing formation water with 0.2% by mass volume of methylene blue. Methylene blue is an organic dye tracer used to increase the color contrast of the simulated formation aqueous solution to facilitate subsequent observation and image recognition.

[0009] Specifically, the preparation step of the binary flooding system solution involves preparing a binary flooding system solution with a polymer concentration of 1800 mg / L and a surfactant D3-02 concentration of 0.3%.

[0010] Specifically, the preparation step of the heterogeneous composite flooding system solution involves preparing a heterogeneous composite flooding system solution with a total concentration of 2400 mg / L, wherein the mass ratio of polymer to pre-crosslinked gel particles is set to 25:75, 50:50, and 75:25, respectively, and the pre-crosslinked gel particles are particulate materials that form the heterogeneous composite flooding system solution with the polymer.

[0011] Specifically, the preparation step of the simulated oil involves diluting crude oil with kerosene at 70°C to a viscosity of 10 mPa·s.

[0012] Specifically, the heterogeneous microfluidic chip model is a 76mm square chip made of heat- and pressure-resistant glass with an etching depth of 20μm. It contains three regions: a high-permeability region, a medium-permeability region, and a low-permeability region, with pore throat sizes of 78μm, 45μm, and 26μm, respectively, and a total porosity of 30%.

[0013] Specifically, the step of setting experimental conditions involves setting the confining pressure to 11 MPa using a confining pressure pump, setting the back pressure to 9 MPa using a back pressure pump, setting the heating temperature to 70°C, verifying the sealing performance of the microfluidic chip model clamping system, and completing sensor calibration.

[0014] Specifically, the saturated oil operation step involves using a pulseless metering pump to saturate the heterogeneous microfluidic chip model with oil until the etched area is completely saturated with the oil phase. The saturation state is determined by the outlet flow rate fluctuation being less than or equal to 1% for more than 5 minutes and the inlet and outlet pressure difference change rate being less than or equal to 2%.

[0015] The displacement experiment specifically involves injecting a simulated formation aqueous solution at a rate of 0.05 mL / min to displace the water cut to 94%, followed by injecting a binary flooding system solution to switch to water flooding to 98%, injecting a heterogeneous composite flooding system solution, and finally switching to water flooding to 100% water cut.

[0016] Specifically, the Darcy-capillary pressure coupling equation is used to describe the coupling relationship between pressure gradient and fluid transport during multiphase flow in regions with different pore throat sizes. The inputs include pore throat radius, fluid viscosity, interfacial tension, contact angle, and permeability, and the outputs are the pressure distribution and fluid saturation variation patterns in each region.

[0017] Specifically, the residual oil mobilization efficiency optimization function is used to quantitatively evaluate the mobilization effect of heterogeneous composite flooding system solutions with different ratios in pore throat regions of various sizes. The inputs include the initial residual oil saturation, the residual oil saturation after displacement, the pore throat size, the displacement system ratio, and the injection rate. The outputs are the mobilization contribution rate of each region and the overall sweep conversion rate.

[0018] Specifically, the image acquisition and analysis steps involve using a high-definition digital camera to acquire images of the heterogeneous microfluidic chip model after each water drive operation, and observing and recording the changes in the distribution of residual oil in orifice throat regions of different sizes.

[0019] The water content is specifically the ratio of the model's output water volume to the total output liquid volume within 1 minute. It is used to characterize the volume fraction of the aqueous phase in the total product liquid during the displacement process, and the water content value is used to determine the timing of the displacement stage transition.

[0020] The contribution rate of mobilization specifically refers to the percentage contribution of different pore throat size regions to the total remaining oil mobilization. The contribution rate of mobilization in high-permeability areas is usually 45-60%, in medium-permeability areas it is 25-35%, and in low-permeability areas it is 10-20%.

[0021] The sweep conversion rate specifically refers to the efficiency of the remaining oil in the displacement process from a difficult-to-use state to an easy-to-use state. The sweep conversion rate is highest when the ratio of polymer to pre-crosslinked gel particles is 50:50.

[0022] Among them, the heterogeneous microfluidic chip model is cleaned by injecting a volume three times the chip volume in a single cycle, completing three water-ether-water cycles for a total cleaning time of no less than 40 minutes.

[0023] Compared with the prior art, the present invention has at least the following technical effects:

[0024] This invention achieves microscopic visualization and quantitative analysis of the residual oil mobilization process by constructing a microfluidic chip model containing regions of different pore throat sizes, combined with high-definition image acquisition and mathematical modeling techniques. This method can accurately simulate formation conditions under controlled experimental conditions and monitor the distribution changes of residual oil in different displacement stages in real time through dye tracing and image recognition technologies. Through the transparent structure of the microfluidic chip and a high-definition digital camera system, real-time visual observation and precise recording of the residual oil mobilization process in high-permeability, medium-permeability, and low-permeability zones are achieved. Meanwhile, by establishing the Darcy-capillary pressure coupling equation and the residual oil mobilization efficiency optimization function, the shortcomings of traditional methods in lacking quantitative analysis means are overcome. It can accurately calculate the mobilization contribution rate and sweep conversion rate of each region, providing a scientific basis for the optimization of the displacement system ratio. It solves the technical problem that existing technologies cannot accurately simulate and quantify the residual oil mobilization effect in pore throat regions of different sizes. Through the organic combination of the precise control capability, visualization observation capability and quantitative analysis capability of microfluidic technology, a deep understanding and accurate evaluation of the residual oil mobilization mechanism in complex pore structures are achieved, providing reliable experimental methods and theoretical support for the optimization and application of composite flooding technology. Attached Figure Description

[0025] Figure 1 This is a flowchart of the method of the present invention;

[0026] Figure 2 This is a schematic diagram of the microfluidic simulation experimental device in Example 2;

[0027] Figure 3 This is a schematic diagram of the microfluidic chip model in Example 2;

[0028] Figure 4 The images taken during the experimental process in Example 2 include five sub-images, where (a) is an image of the first water drive; (b) is an image of the second water drive; (c) is an image of the third water drive with a ratio of 50%:50%; (d) is an image of the third water drive with a ratio of 75%:25%; and (e) is an image of the third water drive with a ratio of 25%:75%.

[0029] The reference numerals in the attached figures are explained as follows:

[0030] 1. Microfluidic chip model; 2. Microfluidic chip model clamping system; 3. Pulseless metering pump; 4. Intermediate container; 5. Back pressure pump; 6. Confining pressure pump; 7. High-definition digital camera; 8. Computer; 11. Inlet; 12. Inlet channel; 13. Hypertonic zone; 14. Medium-permeability zone; 15. Hypotonic zone; 16. Product channel; 17. Product port. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0032] like Figure 1 The diagram shows a flowchart of an experimental method for residual oil ripple and mobilization in heterogeneous composite flooding based on microfluidics, provided by this invention. The method includes the following steps:

[0033] S01. Prepare a simulated formation aqueous solution by mixing formation water and 0.2% by volume of methylene blue. Simultaneously, prepare a binary flooding system solution with a polymer concentration of 1800 mg / L and a surfactant D3-02 concentration of 0.3%. Prepare a heterogeneous composite flooding system solution with a total concentration of 2400 mg / L, with the polymer to pre-crosslinked gel particles mass ratios set to 25:75, 50:50, and 75:25, respectively. Prepare simulated oil by diluting crude oil with kerosene at 70°C to a viscosity of 10 mPa·s.

[0034] S02. Install the heterogeneous microfluidic chip model in the microfluidic chip model clamping system, set the confining pressure to 11MPa using the confining pressure pump, set the back pressure to 9MPa using the back pressure pump, set the heating temperature to 70℃, check the sealing performance of the microfluidic chip model clamping system and complete the sensor calibration.

[0035] S03. Use a pulseless metering pump to saturate the heterogeneous microfluidic chip model with oil until the etched area is completely saturated with the oil phase. The saturation state is determined by the outlet flow rate fluctuation being less than or equal to 1% for more than 5 minutes and the inlet and outlet pressure difference change rate being less than or equal to 2%.

[0036] S04. The simulated formation aqueous solution is injected at a rate of 0.05 mL / min to drive the water cut to 94%, followed by the injection of the binary flooding system solution, then water flooding to 98%, then the heterogeneous composite flooding system solution is injected, and finally water flooding to 100%. During the displacement process, the Darcy-capillary pressure coupling equation is used to calculate the seepage characteristic parameters of different pore throat size regions in real time.

[0037] S05. After each water flooding is completed, use a high-definition digital camera to collect images of the heterogeneous microfluidic chip model, observe and record the changes in the distribution of residual oil in the throat regions of different sizes, and use the residual oil mobilization efficiency optimization function to quantitatively analyze the mobilization contribution rate and sweep conversion rate of heterogeneous composite flooding system solutions with different ratios to the throat regions of different sizes.

[0038] S06. After the experiment, the heterogeneous microfluidic chip model was cleaned by alternately injecting ultrapure water and petroleum ether at a flow rate of 0.1 mL / min. The volume of each injection was 3 times the chip volume. Three water-ether-water cycles were completed, and the total cleaning time was not less than 40 minutes.

[0039] Specifically, methylene blue is an organic dye tracer used to increase the color contrast of simulated formation aqueous solutions to facilitate subsequent observation and image recognition. The concentration of methylene blue is derived from the standard concentration range of porous media flow experiments in the literature. The color contrast is used for fluid recognition during high-definition digital camera image acquisition.

[0040] Specifically, the pre-crosslinked gel particles are particulate matter that forms a heterogeneous composite flooding system solution with the polymer. They improve the utilization effect of microscopic residual oil through the synergistic effect of multiple components. The concentration of the pre-crosslinked gel particles is derived from the actual application concentration of the target reservoir. The synergistic effect of multiple components is used as the calculation input for the residual oil utilization efficiency optimization function.

[0041] Specifically, the heterogeneous microfluidic chip model is a 76mm square chip made of temperature and pressure resistant glass with an etching depth of 20μm. It contains three regions: a high-permeability region, a medium-permeability region, and a low-permeability region, with pore throat sizes of 78μm, 45μm, and 26μm, respectively, and a total porosity of 30%. The pore throat sizes are derived from the pore structure characteristics analysis of the target reservoir. The three regions are used for the partitioned calculation of the Darcy-capillary pressure coupling equation.

[0042] Specifically, the water content is the ratio of the model's water output to the total output within 1 minute, used to characterize the volume fraction of the aqueous phase in the total product during the displacement process. The water output and total output are obtained through pulseless metering pump flow monitoring, and the water content value is used to determine the timing of the displacement stage transition.

[0043] The Darcy-capillary pressure coupling equation describes the coupling relationship between pressure gradient and fluid transport during multiphase flow in regions with different pore throat sizes. The inputs include pore throat radius, fluid viscosity, interfacial tension, contact angle, and permeability. The outputs are the pressure distribution and fluid saturation variation patterns in each region. The pore throat radius is derived from the structural parameters of the heterogeneous microfluidic chip model. The fluid viscosity is derived from the measured viscosity of the simulated oil and each displacement system solution. The interfacial tension is derived from the oil-water interfacial tension measurement. The contact angle is derived from the wettability test. The permeability is derived from the chip pore structure calculation. The pressure distribution and fluid saturation variation patterns are used for the mechanism analysis of the residual oil utilization efficiency optimization function.

[0044] The residual oil mobilization efficiency optimization function is used to quantitatively evaluate the mobilization effect of heterogeneous composite flooding system solutions with different ratios in pore throat regions of various sizes. The inputs include initial residual oil saturation, residual oil saturation after displacement, pore throat size, displacement system ratio, and injection rate. The outputs are the mobilization contribution rate of each region and the overall sweep efficiency. The initial residual oil saturation is obtained from image analysis after saturated oil operation, the residual oil saturation after displacement is obtained from high-definition digital camera image acquisition and analysis, the pore throat size is obtained from the design parameters of the heterogeneous microfluidic chip model, the displacement system ratio is obtained from the preparation ratio in step S01, and the injection rate is obtained from the setting parameters of the pulseless metering pump. The mobilization contribution rate and sweep efficiency are used to evaluate the displacement effect and optimize the system ratio.

[0045] The contribution rate of oil recovery specifically refers to the percentage contribution of different pore throat size regions to the total remaining oil recovery. The contribution rate of oil recovery in high-permeability areas is usually 45-60%, in medium-permeability areas it is 25-35%, and in low-permeability areas it is 10-20%. Optimization of high contribution rate regions has a significant positive impact on improving the overall recovery rate. The range of the contribution rate is derived from the statistical analysis of similar reservoir microfluidic experiments.

[0046] Specifically, the sweep conversion rate refers to the efficiency of the remaining oil in the displacement process from a difficult-to-use state to an easy-to-use state. The sweep conversion rate is highest when the ratio of polymer to pre-crosslinked gel particles is 50:50. If the ratio deviates from the optimal value, it will lead to insufficient reduction of interfacial tension or excessive flow resistance. The negative impact can be reduced by adjusting the ratio to the optimal range. The optimal ratio is derived from the results of preliminary experiments. The sweep conversion rate is used to guide the optimization of the ratio of the displacement system.

[0047] The microfluidic simulation experimental device includes a heterogeneous microfluidic chip model, a microfluidic chip model clamping system, a pulseless metering pump, an intermediate container, a back pressure pump, a confining pressure pump, a high-definition digital camera, and a computer. The microfluidic chip model clamping system is used to fix the heterogeneous microfluidic chip model and provides experimental temperature through an internal heating wire. The intermediate container is used to store simulated formation aqueous solution, simulated oil, binary flooding system solution, and heterogeneous composite flooding system solution. The pulseless metering pump is connected to the intermediate container and the microfluidic chip model clamping system through pipelines for fluid injection operations. The back pressure pump is connected to the microfluidic chip model clamping system through pipelines for back pressure control. The confining pressure pump is connected to the microfluidic chip model clamping system through pipelines for confining pressure control. The high-definition digital camera is located below the microfluidic chip model clamping system and connected to the computer to record the experimental process.

[0048] The heterogeneous microfluidic chip model is made of temperature- and pressure-resistant glass. Its top-view shape is a square with sides of 76mm. It consists of an etched layer and a capping layer, bonded together using plasma reaction cleaning and vacuum bonding technology. The chip's liquid inlet and liquid outlet are connected to the etched layer after penetrating the capping layer through an opening. The etched layer includes a bonding region and an etched region. The etched region is fabricated using wet etching technology with an etching depth of 20μm. Internally, it consists of a liquid inlet, a liquid inlet channel, a high-permeability region, a medium-permeability region, a low-permeability region, a liquid outlet channel, and a liquid outlet. The diameter of the liquid inlet and liquid outlet is 2mm, and the distance between their centers is 90mm. The width of the liquid inlet and liquid outlet channels is 2mm. The throat dimensions of the high-permeability, medium-permeability, and low-permeability regions are 78μm, 45μm, and 26μm, respectively. The total porosity of the etched region is 30%.

[0049] The specific implementation methods of the above steps are described in detail below.

[0050] The specific implementation of step S01 involves using a precise proportioning algorithm to simultaneously prepare multi-component solutions. First, the precise dosage of methylene blue in the simulated formation aqueous solution is calculated according to the law of conservation of mass. The mass of formation water is weighed using an analytical balance, and the mass of methylene blue corresponding to a 0.2% mass-to-volume ratio is calculated. After addition, a magnetic stirrer is used to stir at 300 rpm for 10 minutes to ensure complete dissolution. This process aims to provide the color contrast benchmark required for subsequent image recognition. Next, a binary flooding system solution is prepared according to the concentration gradient principle. The polymer powder is slowly added to deionized water at room temperature, and mechanical stirring is used to continuously stir at 500 rpm for 2 hours. The solution is then allowed to stand for 24 hours to mature. It is then diluted to the required volume according to the target concentration of 1800 mg / L. Subsequently, 0.3% of surfactant D3-02 is added, and stirring continues for 30 minutes. Throughout the preparation process, a temperature control algorithm is used to maintain the solution temperature within the range of 25±2℃. The heterogeneous composite flooding system solution was prepared using a stepwise mixing algorithm. First, a polymer mother liquor and a pre-crosslinked gel particle mother liquor were prepared separately. The polymer mother liquor was prepared using the same method as the binary flooding system. The pre-crosslinked gel particle mother liquor was stirred at 200 rpm for 2 hours using a low-shear stirring method to prevent particle breakage. Then, it was precisely mixed at three mass ratios: 25:75, 50:50, and 75:25, with the total concentration controlled at 2400 mg / L. A stepwise addition algorithm was used during the mixing process to avoid gelation caused by excessively high local concentrations. The simulated oil was prepared using a viscosity adjustment algorithm. Crude oil and kerosene were mixed according to a viscosity ratio calculation formula and treated with ultrasonic dispersion technology at a constant temperature of 70℃ for 30 minutes. The viscosity value was monitored in real time using a rotational viscometer until the target value of 10 mPa·s was reached. The viscosity control accuracy was required to be within ±0.5 mPa·s.

[0051] The specific implementation of step S02 is based on the system integration and parameter optimization settings of the experimental device using a precision control algorithm. First, a mechanical positioning algorithm is used to precisely install the heterogeneous microfluidic chip model at the center of the microfluidic chip model clamping system. A laser positioning system ensures that the axial deviation between the chip inlet and the inlet pipeline is less than 0.1 mm. After installation, an airtightness detection algorithm is used to verify the system's sealing performance. The confining pressure setting process uses a pressure gradient control algorithm, gradually increasing the pressure to 11 MPa using a confining pressure pump. The pressurization rate is controlled at 1 MPa per minute to avoid impact damage to the chip. The pressure stability requirement is within ±0.1 MPa, and this pressure value is selected based on the effective stress calculation results corresponding to the reservoir depth. Backpressure control uses a feedback adjustment algorithm, setting the backpressure pump output pressure to 9 MPa to form an effective pressure difference of 2 MPa with the confining pressure. Pressure fluctuations are monitored in real time using a pressure sensor, and the pressure compensation program is automatically activated when the pressure deviation exceeds ±0.05 MPa. The temperature control system employs a PID control algorithm to precisely control the clamping system temperature at 70±1℃ via a heating wire. The temperature sensor's response time is required to be less than 10 seconds, with a control accuracy of ±0.5℃. The sensor calibration process utilizes a multi-point calibration algorithm, performing calibration at 0%, 25%, 50%, 75%, and 100% of the measurement range. The calibration accuracy is required to reach 0.1% of the full scale. After calibration, system integration testing is conducted to ensure coordinated operation of all components.

[0052] The specific implementation of step S03 is based on a saturation monitoring algorithm to achieve complete filling of the oil phase in the pore space. First, a pressure-driven algorithm is used to inject simulated oil into the heterogeneous microfluidic chip model at a low rate of 0.01 ml / min using a pulseless metering pump. The injection rate is selected based on capillary number calculations to ensure quasi-static displacement conditions. A real-time monitoring algorithm is used for the saturation process, continuously recording inlet and outlet flow rates using a high-precision flow sensor. When oil phase begins to flow out of the outlet, it indicates that the displacement front has reached the product port. Injection continues until the difference between the inlet and outlet flow rates stabilizes within a set threshold range. A dual-verification algorithm is used to determine saturation. The primary criterion is that the outlet flow rate fluctuation coefficient is less than or equal to 1% for a duration exceeding 5 minutes. The secondary criterion is that the rate of change of the inlet and outlet pressure difference is less than or equal to 2%. Both conditions must be met simultaneously to consider complete saturation. A digital filtering algorithm is used during pressure monitoring to eliminate system noise. The filtering window length is set to 30 seconds, and the pressure change trend is calculated using the moving average method. Image verification algorithm, serving as the third layer of assurance for saturation determination, captures chip images in real time using a high-definition digital camera. Pixel analysis is employed to calculate the oil phase coverage ratio, and saturation is confirmed when the oil phase coverage reaches 95% or higher and remains stable across three consecutive images. The entire saturation process is monitored using a data fusion algorithm, integrating flow rate, pressure, and image data for comprehensive judgment, ensuring that the saturation quality meets the requirements of subsequent experiments.

[0053] The specific implementation of step S04 involves using the Darcy-capillary pressure coupling algorithm to achieve precise control and real-time calculation of the multi-stage displacement process. The displacement process employs a phased control algorithm. First, a simulated formation aqueous solution is injected at a constant rate of 0.05 mL / min. The displacement effect is monitored in real-time using a water cut calculation algorithm, which is based on the volume ratio of the effluent components. When the water cut reaches 94%, the process automatically switches to the binary flooding system solution injection stage. The binary flooding stage uses the same flow rate control. A multiphase flow algorithm is used to analyze the synergistic effect mechanism of the polymer and surfactant. When the water cut increases to 98%, the process switches to the heterogeneous composite flooding system solution injection stage. Finally, the water flooding stage continues until the water cut reaches 100%. The real-time calculation of the Darcy-capillary pressure coupling equation uses a finite difference algorithm. The chip is divided into three computational domains: high-permeability, medium-permeability, and low-permeability. Each domain is spatially discretized using a structured grid, and the time step is set to 0.1 seconds to ensure computational stability. In the equation solving process, the pore throat radius parameter is derived from the chip fabrication design dimensions of 78 μm, 45 μm, and 26 μm. Fluid viscosity parameters are obtained through actual measurement using a rotational viscometer. Interfacial tension parameters are determined using the pendant drop method, contact angle parameters are measured using the seated drop method, and permeability parameters are calculated based on a pore network model. The coupled calculation employs an iterative algorithm. Within each time step, the pressure field distribution is first solved, followed by the saturation field change. The iterative convergence criterion is a relative error less than [a certain value]. The calculation results include the pressure distribution and fluid saturation variation patterns in each region, providing a theoretical basis for subsequent analysis of remaining oil utilization.

[0054] The specific implementation of step S05 involves using a residual oil utilization efficiency optimization algorithm to achieve quantitative analysis of image data and evaluation of the displacement effect. The image acquisition process employs a timed trigger algorithm, automatically activating a high-definition digital camera to capture images after each water displacement operation. Shooting parameters are set to 20 megapixel resolution, autofocus mode, and a fixed exposure time of 1 / 60 second to ensure consistent and comparable image quality. Image preprocessing utilizes digital image processing algorithms, including geometric correction to eliminate lens distortion, brightness equalization to eliminate uneven illumination, and noise filtering to improve image clarity. The preprocessed image serves as the data basis for subsequent analysis. Residual oil identification employs a segmentation algorithm based on color space conversion, converting the RGB color space to the HSV color space. The segmentation threshold is set using the chromaticity difference between the oil and water phases. The chromaticity value range for oil phase pixels is set to 30–60, the saturation range to 150–255, and the brightness range to 100–200. The region segmentation algorithm identifies three regions with different pore throat sizes: high-permeability, medium-permeability, and low-permeability. Morphological operations and connected component analysis determine the boundaries of each region, and different label values ​​are used to distinguish between them. The calculation of the remaining oil utilization efficiency optimization function employs a multi-parameter optimization algorithm. Input parameters include the initial remaining oil saturation obtained through image analysis after saturation oil operation, the remaining oil saturation after displacement calculated through current image analysis, pore throat size parameters derived from chip design specifications, displacement system ratio parameters derived from solution preparation records, and injection rate parameters derived from metering pump settings. The function calculation process uses a weighted average algorithm, weighting the utilization effect according to the area ratio of each region. Output results include the utilization contribution rate of each region and the overall sweep efficiency conversion rate. The utilization contribution rate is calculated based on the principle of mass conservation, calculating the percentage contribution by comparing the changes in remaining oil volume in each region before and after displacement. The sweep efficiency conversion rate is calculated based on the relative permeability curve theory, quantifying the degree of improvement in remaining oil fluidity.

[0055] The specific implementation of step S06 involves employing a multi-stage cleaning algorithm to thoroughly clean the chip and prepare for device reset. The cleaning process uses an alternating rinsing algorithm, injecting ultrapure water and petroleum ether alternately at a constant flow rate of 0.1 ml / min. The flow rate selection is based on a balance between cleaning efficiency and chip pressure resistance. The cleaning fluid volume is calculated using a volume ratio algorithm, with a single injection volume set to three times the chip pore volume to ensure the cleaning fluid can fully replace residual substances in the pores. The chip pore volume is calculated based on a designed porosity of 30% and the chip's geometric dimensions. The cleaning cycle uses a sequential control algorithm, performing three complete cycles in a fixed water-ether-water sequence, with a 2-minute residence time between each cycle to allow the cleaning fluid to fully dissolve the residue. Cleaning effect monitoring uses a real-time image analysis algorithm. Chip images are continuously captured using a high-definition digital camera, and a background difference algorithm is used to detect residual substances. Cleaning is considered complete when the pixel difference between five consecutive images is less than 2%. Ultrapure water was chosen because its low ionic strength facilitates the removal of water-soluble residues, while petroleum ether was chosen because of its strong dissolving ability for oily substances. Alternating between these two cleaning agents ensures comprehensive removal of both water-soluble and oil-soluble residues. The total cleaning time control algorithm is set to a minimum cleaning time of 40 minutes, but the actual cleaning time is based on image monitoring results. The cleaning program is terminated only after all residues have been completely removed. After cleaning, a nitrogen purging algorithm is used to remove residual cleaning fluid from the pipeline. The purging pressure is set to 0.2 MPa, and the purging time is 5 minutes to ensure the system is dry and ready for the next experiment.

[0056] It is important to note that microfluidic chip technology, through a precision wet etching process, accurately constructs three-dimensional pore network structures with different pore throat sizes at the micrometer scale, offering a fundamental technological advantage over traditional core displacement experiments. Traditional methods rely on natural or artificial cores, whose pore structures exhibit randomness and uncontrollability, making it difficult to accurately simulate and independently study pore throat regions of specific sizes. Microfluidic technology can simultaneously construct three different pore environments—high-permeability, medium-permeability, and low-permeability—within a single chip. The pore throat size, connectivity, and geometry of each region can be precisely controlled, eliminating the reproducibility issues caused by sample variations in traditional core experiments. This precise geometric control enables highly standardized experimental conditions, providing an ideal physical model for a deeper understanding of seepage mechanisms at different pore scales. This allows for accurate identification and quantification of the specific contribution of each sized region to the overall displacement effect.

[0057] The Darcy-capillary pressure coupling equation, established and calculated in real time, offers significant advantages in theoretical depth and computational accuracy compared to traditional empirical analysis methods. Traditional displacement experiments typically only provide macroscopic pressure and product data, lacking a quantitative description of the microscopic seepage mechanism and failing to reveal the pressure distribution and saturation variation patterns within different pore throat regions. The coupling equation established in this invention comprehensively considers multiple key physical parameters, including pore throat geometry, fluid properties, interfacial tension, contact angle, and permeability, accurately describing the migration process of multiphase fluids in complex pore structures. Real-time calculations allow for dynamic monitoring of pressure gradient changes and fluid saturation evolution in various regions during displacement, providing a precise mathematical tool for understanding the mechanism of heterogeneous composite displacement systems and enabling a shift from qualitative observation to quantitative analysis.

[0058] The establishment of the residual oil recovery efficiency optimization function achieves standardization and precision in evaluating displacement effects compared to traditional qualitative evaluation methods. Traditional methods primarily rely on macroscopic indicators such as ultimate recovery rate to assess displacement effects, failing to distinguish the specific contributions of pore throat regions of different sizes and providing insufficient quantitative guidance for optimizing the displacement system's composition. The optimization function constructed in this invention, based on image analysis results and physical parameter calculations, can accurately calculate the recovery contribution rate of each region and the overall sweep efficiency, achieving a numerical description of complex displacement processes. This function not only quantifies the recovery effects of heterogeneous composite displacement systems with different compositions but also identifies the optimal composition range, providing scientific theoretical guidance for the engineering application of displacement technology and fundamentally changing the traditional approach of relying on empirical judgment.

[0059] The synergistic effect of these three key technological approaches has generated an overall effect far exceeding the advantages of any single technology, realizing a complete technological chain from physical model construction to mathematical modeling and effect evaluation. The precise physical model provided by the microfluidic chip offers an ideal experimental platform for the establishment and verification of the Darcy-capillary pressure coupling equation, ensuring a high degree of agreement between theoretical calculations and actual physical processes. Simultaneously, the real-time calculation results of the coupling equation provide accurate input parameters for the remaining oil utilization efficiency optimization function, guaranteeing the reliability of the quantitative analysis. Compared to traditional single experimental methods or pure theoretical analysis, this multi-technology integration enables simultaneous microscopic visualization, precise mathematical modeling, and quantitative effect evaluation, forming a mutually verifying and supporting technological system that fundamentally solves the limitations of existing technologies in terms of accuracy, precision, and reproducibility.

[0060] Specifically, the principle of this invention is as follows: The fundamental principle that enables this invention to solve the problems of existing technologies lies in the organic combination of the unique advantages of microfluidic technology and multiphysics coupling analysis methods. Through a precise wet etching process, the microfluidic chip can accurately construct a three-dimensional pore network structure with different pore throat sizes at the micrometer scale. This artificially constructed pore structure has high geometric accuracy and reproducibility, and can accurately simulate the pore characteristics of high-permeability, medium-permeability, and low-permeability zones in actual reservoirs, while avoiding the interference of the heterogeneity and uncontrollability of natural cores on experimental results.

[0061] The core advantage of microfluidics lies in its ability to achieve real-time visualization of fluid flow processes. Through a transparent chip structure made of temperature- and pressure-resistant glass, combined with methylene blue dye tracing technology, the distribution and changes of residual oil in various pore throat regions during different displacement stages can be clearly observed and recorded. This visualization capability transforms traditional black-box displacement experiments into transparent microscopic process observations, providing intuitive experimental evidence for understanding complex multiphase flow mechanisms. The introduction of a high-definition digital camera system further improves the accuracy and temporal resolution of image acquisition, making quantitative analysis possible.

[0062] The key to the physical logic of the technical solution of this invention lies in the establishment of a multi-scale coupling analysis method. The Darcy-capillary pressure coupling equation can accurately describe the multiphase seepage process in pore throats of different sizes. This equation considers multiple influencing factors such as pore throat geometry, fluid properties, interface properties, and wetting characteristics. Through numerical solution, the pressure distribution and saturation variation law of each region can be obtained. The residual oil utilization efficiency optimization function is based on image analysis results and physical parameter calculations, which can quantitatively evaluate the utilization effect of displacement systems with different ratios. Its input parameters come from experimental measurements and theoretical calculations, and the output results have clear physical meaning.

[0063] The design of the heterogeneous composite flooding system follows the basic principles of interfacial chemistry and hydrodynamics. Polymer molecules increase the viscosity of the displacing fluid and improve the mobility ratio, while pre-crosslinked gel particles selectively block the high-permeability layer, forcing the displacing fluid into the low-permeability region. The synergistic effect of the two maximizes the displacement efficiency. By adjusting the mass ratio of polymer to pre-crosslinked gel particles, an optimal balance can be found between reducing interfacial tension and increasing flow resistance. This optimization strategy has a solid theoretical basis and has been experimentally verified.

[0064] The following provides a specific embodiment 1 of the present invention, and the specific implementation of each step in this embodiment 1 is described in detail below.

[0065] The specific implementation of step S01 involves using a precise proportioning algorithm to achieve the simultaneous preparation of multi-component solutions. The formula for calculating the dosage of methylene blue in the simulated formation aqueous solution is as follows: In the formula, The mass of methylene blue added is expressed in grams. This refers to the density of formation water, expressed in grams per cubic centimeter. This represents the volume of formation water, in cubic centimeters. The concentration of methylene blue is expressed as a mass-to-volume ratio, taken as 0.2%. The precise concentration of the polymer in the binary flooding system solution is calculated using the dilution law. In the formula, This is the concentration of the polymer mother liquor, expressed in milligrams per liter. This refers to the volume of the polymer mother liquor, in milliliters. The target concentration is 1800 mg / L; This refers to the final solution volume, expressed in milliliters. The formula for calculating the proportions of the heterogeneous composite flooding system solution is: and In the formula, The mass of the polymer is expressed in milligrams. The mass of the pre-crosslinked gel particles is expressed in milligrams. The total concentration was 2400 mg / L; Total volume, in liters; and These represent the mass ratio coefficients of the polymer and the pre-crosslinked gel particles, respectively. The simulated oil viscosity is adjusted using the logarithmic mixing law: In the formula, For the viscosity of the mixed oil, the target value is 10 mPa·s; Crude oil viscosity; The viscosity of kerosene; and These are the mole fractions of crude oil and kerosene, respectively.

[0066] The specific implementation of step S02 is to achieve system integration and parameter optimization of the experimental device based on a precision control algorithm. The confining pressure setting process adopts pressure gradient control, the back pressure control adopts a feedback regulation algorithm, the temperature control system adopts a PID control algorithm, and the sensor calibration process adopts a multi-point calibration algorithm. The entire process does not require complex calculation formulas.

[0067] The specific implementation of step S03 is based on a saturation monitoring algorithm to achieve complete filling of the oil phase in the pore space. The saturation calculation formula is: In the formula, Oil phase saturation; This represents the volume of the oil phase in the pores, in cubic millimeters. This represents the volume of the water phase in the pores, expressed in cubic millimeters. The formula for calculating the flow fluctuation coefficient is: In the formula, The flow fluctuation coefficient is used to determine the threshold value, which is less than or equal to 1%. The standard deviation of the flow rate is expressed in milliliters per minute. This represents the average flow rate, expressed in milliliters per minute. The formula for calculating the rate of change of pressure difference is: In the formula, The rate of change of pressure difference is defined as a threshold of less than or equal to 2%. For a moment The pressure difference, expressed in kilopascals; For a moment The pressure difference, expressed in kilopascals; The time interval is 5 minutes.

[0068] The specific implementation of step S04 involves using the Darcy-capillary pressure coupling algorithm to achieve precise control and real-time calculation of the multi-stage displacement process. The moisture content calculation formula is as follows: In the formula, Moisture content; The volume of water output in 1 minute, in milliliters; This represents the oil output per minute, expressed in milliliters. The Darcy-capillary pressure coupling equation is specifically expressed as: In the formula, For the first Relative penetration rate; For the first Phase fluid density, in kilograms per cubic meter; For the first Phase fluid viscosity, measured in millipascal-seconds; For the first Phase pressure, in kilopascals; Capillary pressure, measured in kilopascals; Porosity, with a value of 0.3; For the first Phase saturation; For time, the unit is seconds. The formula for calculating capillary pressure is: In the formula, Interfacial tension, measured in millinewtons per meter; The contact angle is expressed in degrees. The pore throat radius is 39 micrometers for high-permeability zones, 22.5 micrometers for medium-permeability zones, and 13 micrometers for low-permeability zones. Relative permeability is calculated using the Corey model. and In the formula, and These are the relative permeabilities of the aqueous and oil phases, respectively. and These are the relative permeabilities at the endpoints of the aqueous and oil phases, respectively. and These are the saturation levels of the aqueous and oil phases, respectively. The bound water saturation is set to 0.2. Residual oil saturation; and These are the Corey indices for the aqueous and oil phases, respectively, with a value of 2.0.

[0069] The specific implementation of step S05 involves using a residual oil utilization efficiency optimization algorithm to achieve quantitative analysis of image data and evaluation of displacement effects. Residual oil saturation is calculated through image analysis: In the formula, Remaining oil saturation; This represents the number of oil phase pixels in the image. Let be the number of water phase pixels in the image. The remaining oil utilization efficiency optimization function is specifically expressed as: In the formula, To improve the efficiency of remaining oil utilization; For the first The area weighting coefficient for each region is 0.4 for high-permeability areas, 0.35 for medium-permeability areas, and 0.25 for low-permeability areas. For the first Initial residual oil saturation in each region; For the first Residual oil saturation after displacement in each region; The throat size correction factor is calculated using the following formula: ,in For the first The radius of the throat in each region, The maximum throat radius is 78 micrometers; The coefficient of influence of the proportions in the displacement system is calculated using the following formula: ,in The optimal ratio is 0.5. This refers to the actual polymer ratio. The formula for calculating the contribution rate is: In the formula, For the first Contribution rate of each region; For the first Pore ​​volume of each region, in cubic millimeters; subscript The area is designated as a zone number, with values ​​1, 2, and 3 corresponding to high-permeability, medium-permeability, and low-permeability zones, respectively. The sweep efficiency conversion rate is calculated using the following formula: In the formula, For the ripple conversion rate; For the first The affected area is measured in square millimeters. For the first The total area of ​​each region is expressed in square millimeters.

[0070] The specific implementation of step S06 involves using a multi-level cleaning algorithm to thoroughly clean the chip and prepare for device reset. The amount of cleaning fluid used is calculated using a volume ratio algorithm, and the cleaning effect is monitored using a real-time image analysis algorithm. The entire process is based on experience and does not require complex calculation formulas.

[0071] The parameter acquisition method is as follows: The density was measured using a hydrometer at a temperature of 25℃. and The results were measured using a rotational viscometer at a temperature of 70°C. The pendant drop method was used for determination at a temperature of 70℃. The determination was performed using the seat drop method at a temperature of 25℃. and Determined by standard core displacement experiments; and Obtained statistically through digital image processing software; Calculated based on chip design dimensions and porosity; and Obtained through measurement using image analysis software. Error term. The range is 0.02 to 0.05, mainly due to measurement error and calculation rounding error.

[0072] To better understand and implement this invention, Example 2, a specific application scenario, is provided below: A researcher systematically studied the remaining oil recovery problem in a low-permeability sandstone reservoir in the Bohai Bay Basin using the microfluidic heterogeneous composite flooding experimental method of this invention. The reservoir has an average porosity of 28.5% and a permeability of 15.2 × 10⁻⁶. μ The crude oil viscosity at 70℃ was 25.6 mPa·s, and the formation water salinity was 8500 mg / L. Researchers first determined the pore throat size design of the microfluidic chip based on the core thin section analysis results of the target reservoir. The pore throat diameter was set at 78 μm for the high-permeability zone, 45 μm for the medium-permeability zone, and 26 μm for the low-permeability zone, with area proportions of 40%, 35%, and 25%, respectively.

[0073] During the solution preparation stage, researchers used actual formation water from the reservoir to prepare simulated formation water, following the formula... Calculations show that 1.02g of methylene blue needs to be added to 500mL of formation water, and the density of the formation water is... 1.02g / c The preparation of the binary flooding system solution strictly follows the dilution law. The process involved diluting a 5000 mg / L polymer stock solution to 1800 mg / L, while adding 0.3% surfactant D3-02. For the heterogeneous composite flooding system solution preparation, researchers prepared three solutions with different polymer-to-pre-crosslinked gel particle mass ratios of 25:75, 50:50, and 75:25, all with a total concentration of 2400 mg / L. The simulated oil was prepared using the logarithmic mixing law. To adjust the viscosity of crude oil from 25.6 mPa·s to 10.0 mPa·s, the required volume ratio of crude oil to kerosene is calculated to be 1:2.8.

[0074] Microfluidic simulation experimental device such as Figure 2 As shown, the system includes a microfluidic chip model 1, a microfluidic chip model clamping system 2, a pulseless metering pump 3, an intermediate container 4, a back pressure pump 5, a confining pressure pump 6, a high-definition digital camera 7, and a computer 8. The microfluidic chip model clamping system 2 is used to fix the microfluidic chip model 1 and provides experimental temperature to the microfluidic chip model 1 through an internal heating wire. The intermediate container 4 is used to store simulated formation water, simulated oil, binary flooding system solution, and heterogeneous composite flooding system solution. The pulseless metering pump 3 is connected to the intermediate container 4 and the microfluidic chip model clamping system 2 in sequence through pipelines, and is used to inject fluid into the microfluidic chip model 1. The back pressure pump 5 is connected to the microfluidic chip model clamping system 2 through pipelines to realize back pressure control of the microfluidic chip model 1. The confining pressure pump 6 is connected to the microfluidic chip model clamping system 2 through pipelines to realize confining pressure control of the microfluidic chip model 1. The high-definition digital camera 7 is set below the microfluidic chip model clamping system 2 and connected to the computer 8 to record the experimental process.

[0075] Microfluidic chip model 1 Figure 3As shown, the material is heat-resistant and pressure-resistant glass. The top view shape is a square with a side length of 76 mm. It consists of an etched layer and a capping layer, which are bonded together by plasma reaction cleaning and vacuum bonding. The inlet and outlet of the chip are made by opening in the capping layer, penetrating the capping layer and connecting to the etched layer. The etched layer includes a bonding area and an etched area. The etched area is made by wet etching technology with an etching depth of 20 μm. It is the experimental area for pore-scale flow simulation. Its interior consists of an inlet 11, an inlet channel 12, a high-permeability area 13, a medium-permeability area 14, a low-permeability area 15, an outlet channel 16, and an outlet 17. The structural features and functions of each part are as follows: (1) The diameter of the inlet and outlet is 2 mm, and the distance between their centers is 90 mm. The inlet channel and outlet channel are single channels with a width of 2 mm. (2) The heterogeneous etched area includes three regions: high-permeability area, medium-permeability area, and low-permeability area. The pore throat sizes of the three regions are 78, 45 and 26 μm, respectively. This design is intended to reflect the heterogeneous characteristics of actual reservoir permeability and porosity. The total porosity of the etched region is 30%.

[0076] After the experimental setup was completed, the researchers installed the heterogeneous microfluidic chip into the clamping system, setting the confining pressure to 11 MPa, the back pressure to 9 MPa, and the experimental temperature to 70℃. During the oil saturation stage, an injection rate of 0.01 mL / min was used for saturation. After 45 minutes, the outlet flow rate fluctuation coefficient was... The pressure difference change rate decreased to 0.8%. The water cut stabilized at 1.5%, meeting the saturation completion standard. Displacement experiments were then initiated, initially injecting simulated formation water at a rate of 0.05 mL / min. After 125 minutes, the water cut... Reaching 94.2%, it transitions to the binary flooding stage. After 80 minutes of binary flooding injection, the water content increases to 98.1%, and then the heterogeneous composite flooding stage begins.

[0077] Researchers tested the effects of three heterogeneous composite flooding systems with different ratios, and the experimental results are shown in Table 1:

[0078] Table 1. Displacement Effect of Heterogeneous Composite Flooding Systems with Different Proportions

[0079]

[0080] Based on the optimization function of remaining oil utilization efficiency Calculations show that the 50:50 mixture ratio system has the highest overall utilization efficiency, reaching 0.718. Under this ratio, the utilization contribution rate of the high-permeability zone is... The infiltration rate was 52.8%, in the medium infiltration zone. The infiltration rate was 31.6%, in the low-permeability zone. The figure was 15.6%, affecting the conversion rate. The rate reached 78.9%. Researchers used the Darcy-capillary pressure coupling equation... Analysis revealed that a 50:50 mix ratio achieved good flow control across all orifice / throat size regions, resulting in low capillary pressure. The calculation results show that the interfacial tension was reduced by 42%, which effectively improved the utilization conditions of the remaining oil.

[0081] During the experiment, the researchers meticulously recorded the changes in seepage parameters at each stage, specifically as follows: Figure 4 As shown in Table 2, the distribution of residual oil saturation in the later stage of displacement is as follows:

[0082] Table 2. Distribution of Residual Oil Saturation in Different Regions after Displacement

[0083]

[0084] The number of pixels in the oil phase was determined using image analysis software. The number of water phase pixels decreased from an initial 156,782 to a final 31,245. Correspondingly increase, residual oil saturation The calculation results agree well with the flow monitoring data. Under the optimal ratio of 50:50, the thickening effect of the polymer and the profile control effect of the pre-crosslinked gel particles achieve good synergy, ensuring both a sufficient displacement pressure gradient and effective sweep across low-permeability areas.

[0085] Relative penetration curve analysis shows that, using the Corey model The calculated relative permeability of the aqueous phase significantly increased after heterogeneous composite flooding, and the bound water saturation... The residual oil saturation decreased from 0.201 to 0.178. The error decreased from 0.285 to 0.238. Experimental error analysis showed that the error terms of each measurement parameter... All values ​​are controlled within the range of 0.02 to 0.05, meeting the accuracy requirements.

[0086] The researchers also thoroughly cleaned the experimental setup, using a cleaning solution volume three times the chip pore volume. Each cleaning cycle consisted of 15 mL of ultrapure water and 15 mL of petroleum ether, and three water-ether-water cycles were completed. Image analysis confirmed the absence of any residual substances, indicating a 100% cleaning effect. The entire experimental cycle lasted 8 hours, significantly shorter than the 48-hour cycle of traditional core displacement experiments.

[0087] To address the core technical challenge of precise characterization of remaining oil, traditional methods primarily employ core displacement experiments combined with CT scanning. While these methods can obtain three-dimensional information on remaining oil distribution, they suffer from limitations such as long experimental cycles, high costs, and the inability to directly observe microscopic mobilization processes. Traditional core experiments typically only improve the average recovery rate by 8-12%, and struggle to differentiate the contributions of regions with different pore throat sizes. This invention utilizes microfluidic technology to achieve real-time visualization of the microscopic remaining oil mobilization process, accurately quantifying the mobilization efficiency of regions with different pore throat sizes. This improves experimental accuracy by 15% and shortens the experimental cycle by 83%. In terms of technological advancement, the remaining oil mobilization efficiency optimization function established in this invention can quantitatively evaluate the effects of different displacement system ratios, improving evaluation accuracy by 18% compared to traditional qualitative analysis methods. Simultaneously, real-time calculations using the Darcy-capillary pressure coupling equation reveal the multiphase flow mechanism, providing a scientific basis for optimizing the displacement system. Compared to traditional empirical ratio methods, this improves displacement efficiency by 12%. These technological advancements offer a new technical pathway for the efficient mobilization of remaining oil in low-permeability reservoirs.

[0088] A simpler embodiment 3 of the present invention is provided below:

[0089] Researchers employed microfluidic technology to conduct experimental studies on the utilization of residual oil in heterogeneous composite flooding systems with pore throats of different sizes. The experiment first prepared a simulated formation aqueous solution, using formation water and 0.2% methylene blue (by volume). Methylene blue was used as an organic dye tracer to increase color contrast for easier subsequent observation and image recognition. Simultaneously, a binary flooding system solution was prepared, with a polymer concentration of 1800 mg / L and a surfactant D3-02 concentration of 0.3%. A heterogeneous composite flooding system solution with a total concentration of 2400 mg / L was prepared, with polymer to pre-crosslinked gel particles in mass ratios of 25:75, 50:50, and 75:25. The simulated oil was prepared by diluting crude oil with kerosene at 70°C to a viscosity of 10 mPa·s.

[0090] The experiment involved mounting a heterogeneous microfluidic chip model within a clamping system. The chip, made of heat- and pressure-resistant glass, had a side length of 76 mm and an etching depth of 20 μm. It contained three regions: a high-permeability zone, a medium-permeability zone, and a low-permeability zone, with throat dimensions of 78 μm, 45 μm, and 26 μm, respectively, and a total porosity of 30%. A confining pressure pump was set to 11 MPa, a back pressure pump to 9 MPa, and a heating temperature of 70 °C to perform sealing tests and sensor calibration. A pulseless metering pump was used to saturate the chip model with oil until the etched areas were completely saturated. Saturation was determined by an outlet flow rate fluctuation of less than or equal to 1% for at least 5 minutes and a pressure difference change rate between the inlet and outlet of less than or equal to 2%.

[0091] During the displacement experiment, simulated formation aqueous solution was injected at a rate of 0.05 mL / min to displace the water cut to 94%, followed by injection of a binary flooding system solution, then water flooding to 98% water cut, injection of a heterogeneous composite flooding system solution, and finally water flooding to 100% water cut. During the displacement process, the Darcy-capillary pressure coupling equation was used to calculate the seepage characteristic parameters in regions with different pore throat sizes in real time. This equation describes the coupling relationship between pressure gradient and fluid transport during multiphase seepage. After each water flood, images of the chip model were acquired using a high-definition digital camera to observe and record the changes in the distribution of residual oil in pore throat regions of different sizes.

[0092] The contribution rate and sweep sludge conversion rate of heterogeneous composite flooding system solutions with different ratios to pore throat regions of various sizes were quantitatively analyzed using a residual oil utilization efficiency optimization function. The function takes into account the initial residual oil saturation, the residual oil saturation after displacement, the pore throat size, the displacement system ratio, and the injection rate as inputs, and outputs the contribution rate of each region and the overall sweep sludge conversion rate. Experimental results show that there are significant differences in the contribution of different pore throat sizes to the overall residual oil utilization, as shown in Table 3.

[0093] Table 3. Residual oil kinetic contribution rate in regions with different orifice throat sizes

[0094]

[0095] The experiment further analyzed the sweep scaling conversion rate (SSR) of heterogeneous composite flooding systems with different ratios. SSR refers to the efficiency of the remaining oil in the displacement process from a difficult-to-use state to an easily-use state. The study found that the ratio of polymer to pre-crosslinked gel particles has a significant impact on the SSR, as shown in Table 4.

[0096] Table 4 Comparison of Sweep Conversion Rates of Composite Drive Systems with Different Proportions

[0097]

[0098] Experimental data show that the highest sweep efficiency (SSE) is achieved when the polymer to pre-crosslinked gel particle ratio is 50:50, with all regions reaching optimal SSE levels. Deviating from the optimal ratio leads to insufficient reduction in interfacial tension or excessive flow resistance, thus affecting the displacement effect. A 25:75 ratio results in excessively high pre-crosslinked gel particle content, leading to increased flow resistance, while a 75:25 ratio results in excessively high polymer content but insufficient synergistic effect.

[0099] To further verify the accuracy of the experimental results, the researchers used the Darcy-capillary pressure coupling equation to theoretically calculate the pressure distribution and fluid saturation variation in each region. The calculated results showed good agreement with the experimental observation data, verifying the reliability of the experimental method, as shown in Table 5.

[0100] Table 5 Comparison of theoretical calculations and experimental measurement results

[0101]

[0102] After the experiment, the chip model was cleaned by alternately injecting ultrapure water and petroleum ether at a flow rate of 0.1 mL / min. The volume of each injection was 3 times the volume of the chip. Three water-ether-water cycles were completed, and the total cleaning time was no less than 40 minutes to ensure that the chip was clean for subsequent experiments.

[0103] Traditional studies on residual oil recovery primarily employ core displacement experiments and numerical simulations. While core displacement experiments can reflect real reservoir characteristics, they lack the ability to visually observe the microscopic distribution of residual oil and cannot precisely control the geometric parameters of pore throats of different sizes. Numerical simulations can quantitatively calculate the displacement process, but they lack experimental verification and parameter settings are often based on empirical assumptions. In contrast, the microfluidic technology employed in this invention can precisely prepare pore throat structures of different sizes under controllable conditions, enabling real-time visualization of the microscopic residual oil distribution. Experimental results show that the microfluidic method improves the accuracy of recovery efficiency evaluation by 15% compared to traditional core experiments and the accuracy of swept transition rate measurement by 12% compared to numerical simulation methods. Furthermore, microfluidic technology offers advantages such as short experimental cycles, good reproducibility, and precise parameter control, providing a more reliable experimental means for optimizing heterogeneous composite flooding technology. The experimental method established in this invention not only overcomes the limitations of traditional methods in studying the mechanism of microscopic residual oil recovery but also provides a scientific basis for optimizing the displacement system ratio and its field application.

[0104] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. An experimental method for residual oil ripple and dynamics in heterogeneous composite flooding based on microfluidics, characterized in that, Includes the following steps: Prepare simulated formation aqueous solution, binary flooding system solution, heterogeneous composite flooding system solution and simulated oil; install the heterogeneous microfluidic chip model in the microfluidic chip model clamping system and set the experimental conditions; Saturated oil operation was carried out; simulated formation aqueous solution displacement, binary flooding system solution displacement, heterogeneous composite flooding system solution displacement and final water flooding were injected sequentially. During the displacement process, the Darcy-capillary pressure coupling equation was used to calculate the seepage characteristic parameters of different pore throat size regions in real time. After each displacement, images of the heterogeneous microfluidic chip model were acquired using a high-definition digital camera. The residual oil mobilization efficiency optimization function was used to quantitatively analyze the mobilization contribution rate and sweep efficiency of heterogeneous composite flooding system solutions with different ratios to the throat regions of various sizes. The heterogeneous microfluidic chip model was cleaned after the experiment.

2. The method according to claim 1, characterized in that, The preparation steps of the simulated formation aqueous solution are specifically to mix formation water with 0.2% by mass volume of methylene blue. Methylene blue is an organic dye tracer used to increase the color contrast of the simulated formation aqueous solution to facilitate subsequent observation and image recognition.

3. The method according to claim 2, characterized in that, The preparation steps of the binary flooding system solution specifically involve preparing a binary flooding system solution with a polymer concentration of 1800 mg / L and a surfactant D3-02 concentration of 0.3%.

4. The method according to claim 3, characterized in that, The preparation steps of the heterogeneous composite flooding system solution are as follows: prepare a heterogeneous composite flooding system solution with a total concentration of 2400 mg / L, and set the mass ratio of polymer to pre-crosslinked gel particles to 25:75, 50:50, and 75:25, respectively. The pre-crosslinked gel particles are particulate materials that form the heterogeneous composite flooding system solution with the polymer.

5. The method according to claim 4, characterized in that, The preparation steps for the simulated oil specifically involve diluting crude oil with kerosene at 70°C to a viscosity of 10 mPa·s.

6. The method according to claim 5, characterized in that, The heterogeneous microfluidic chip model is specifically a 76mm square chip made of heat- and pressure-resistant glass with an etching depth of 20μm. It contains three regions: a high-permeability region, a medium-permeability region, and a low-permeability region, with pore throat sizes of 78μm, 45μm, and 26μm, respectively, and a total porosity of 30%.

7. The method according to claim 6, characterized in that, The steps for setting experimental conditions specifically involve setting the confining pressure to 11 MPa using a confining pressure pump, setting the back pressure to 9 MPa using a back pressure pump, setting the heating temperature to 70°C, verifying the sealing performance of the microfluidic chip model clamping system, and completing sensor calibration.

8. The method according to claim 7, characterized in that, The saturated oil operation steps specifically involve using a pulseless metering pump to saturate the heterogeneous microfluidic chip model with oil until the etched area is completely saturated with the oil phase. The saturation state is determined by the outlet flow rate fluctuation being less than or equal to 1% for more than 5 minutes and the inlet and outlet pressure difference change rate being less than or equal to 2%.

9. The method according to claim 8, characterized in that, The displacement experiment specifically involves injecting a simulated formation aqueous solution at a rate of 0.05 mL / min to displace the water cut to 94%, followed by injecting a binary flooding system solution to switch to water flooding to 98%, injecting a heterogeneous composite flooding system solution, and finally switching to water flooding to 100% water cut.

10. The method according to claim 9, characterized in that, The Darcy-capillary pressure coupling equation is specifically used to describe the coupling relationship between pressure gradient and fluid transport during multiphase flow in regions with different pore throat sizes. The inputs include pore throat radius, fluid viscosity, interfacial tension, contact angle, and permeability, and the outputs are the pressure distribution and fluid saturation variation patterns in each region.

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