A system for measuring phase parameters of hydrocarbon substances in situ converted from shale in different formation environments

Abstract

The present invention provides a system for measuring phase parameters of hydrocarbon substances in shale in-situ conversion in different formation environments, belonging to the technical field of shale in-situ conversion pyrolysis products, including: shale pyrolysis and product injection system, PVT experiment and heating system, drive and rotation system and integrated control system. The shale pyrolysis and product injection system controls the heating conditions of shale and collects products, the PVT experiment and heating system provides the experimental environment and heats the substances, the drive and rotation system controls the volume of the PVT cylinder and achieves full mixing, and the integrated control system tests the temperature and pressure and controls the experimental conditions. At the same time, the system is also equipped with a microscopic observation and data acquisition system, which can perform microscopic observation of samples and collect data. The integrated system of the present invention can simulate the pyrolysis process of shale under different formation environments and heating conditions, solving the technical problems in the prior art that the in-situ conversion heating conditions are difficult to achieve and the influence of organic matter and heating medium cannot be considered.

Description

Technical Field

[0001] The invention belongs to the technical field of shale in-situ conversion pyrolysis products, and in particular relates to a system for measuring phase parameters of hydrocarbon substances in shale in-situ conversion in different formation environments. Background Art

[0002] In-situ conversion heating mining technology has become one of the most effective means of developing shale reservoirs. The heating methods mainly include heat conduction (electric heating) and convection heating (fluid heating). By heating the organic matter in the shale, the organic kerogen is converted into light oil and natural gas on a large scale, and then the pyrolysis oil and gas products are discharged to achieve the effective development of shale reservoirs. The composition of hydrocarbon substances produced by pyrolysis under different heating conditions is different, and hydrocarbon substances of different compositions have different phase characteristics under different temperatures, pressures and spaces. The phase parameters determine the flow law of the fluid. Clarifying the phase characteristics of hydrocarbon substances produced by pyrolysis is of great significance to the production prediction of oil fields.

[0003] To solve such problems, the existing experimental methods are mainly pyrolysis oil and gas phase state experiments. The devices are mainly piston-type PVT cylinders, and the sealing method is rubber ring sealing. The high temperature resistance is poor, and the maximum temperature generally does not exceed 200°C, which is difficult to cover all temperature ranges of oil and gas phase state tests; most of the experimental devices cannot consider the influence of rock reservoir characteristics. Nano-scale pores are widely developed in shales. The confined space under the nano-scale pores will affect the value of the phase state parameters. Considering the reservoir pore structure characteristics can be more accurate and meet the actual fluid phase state parameter testing needs; some experimental methods cannot consider the influence of heating medium and organic matter. The injected hot fluid and the original retained hydrocarbons and kerogen in the shale will also affect the phase state characteristics of the hydrocarbon substances produced by pyrolysis. Such devices and test methods have the problems that the in-situ conversion heating conditions are difficult to achieve, and the influence of organic matter and heating medium cannot be considered, resulting in the inability to fully obtain the hydrocarbon phase state characteristic parameters that best reflect the characteristics of the in-situ conversion process of shale.

[0004] Therefore, in order to comprehensively carry out the determination of phase characteristic parameters of hydrocarbon substances in shale in-situ conversion, it is necessary to design and construct a new phase state device. Not only should the complex shale reservoir characteristics be considered, but also accurate data and a wide range of data should be obtained, and the influence of different heating conditions and environments on hydrocarbon substances should be considered as much as possible, so as to obtain the phase characteristic parameters of hydrocarbon substances that best reflect the characteristics of the shale in-situ conversion process. Summary of the invention

[0005] In view of this, the present invention provides a system for measuring phase parameters of hydrocarbon substances in situ converted from shale in different formation environments, which can solve the technical problems in the prior art that heating conditions for in-situ conversion are difficult to achieve and the influence of organic matter and heating medium cannot be considered.

[0006] The present invention is achieved in that:

[0007] The present invention provides a system for measuring phase parameters of hydrocarbon substances in situ converted from shale in different formation environments, which includes a shale pyrolysis and product injection system, a PVT experiment and heating system, a drive and rotation system, an integrated control system, and a microscopic observation and data acquisition system. The shale pyrolysis and product injection system includes a pyrolysis reactor, a conical flask, an injection pump, an intermediate container, a first valve, a metal pipeline, a measuring cylinder, and a second valve. The outlet end of the pyrolysis reactor is connected to the conical flask and the intermediate container in sequence through a pipeline, which are used to collect pyrolysis oil and store pyrolysis gas respectively. The output end of the intermediate container is connected to the conical flask and the intermediate container through a pipeline. The metal pipeline is connected to the second valve, the vacuum pump, the first valve and the PVT cylinder in sequence. The measuring cylinder is filled with pyrolysis oil from a conical flask and is connected to the PVT cylinder. The PVT experiment and heating system includes a PVT cylinder, a heating sleeve, a graphite ring, a copper sleeve, a visual glass window, a cylinder cover, a plunger and a plunger seal. The PVT cylinder and the visual glass window are sealed in sequence by a graphite ring and a copper sleeve. The PVT cylinder is used to place shale cores to provide a reservoir environment for phase state experiments. The other end of the PVT cylinder is blocked by a plunger and sealed by a plunger seal. The PVT cylinder is wrapped by a heating sleeve on all sides. for heating and connected to the integrated control cabinet through a data line; the driving and rotation system includes a fixed platform, a rotating rod, an angle adjustment system, a driving column, a driver, a transmission, a support frame and a movable base, the fixed platform is connected to the outside of the PVT cylinder, and is connected to the angle adjustment system through a rotating rod for controlling the rotation angle of the PVT cylinder, the fixed platform is connected to the driver through a driving column for controlling the movement of the plunger, the driver is equipped with a transmission for controlling the movement speed of the plunger, and the driver and the angle adjustment system are both connected to the integrated control cabinet; the integrated control system includes an integrated control cabinet, a touch screen, a temperature sensor and a pressure sensor, the integrated control cabinet is connected to the inner cavity of the PVT cylinder through a temperature sensor and a pressure sensor respectively for testing temperature and pressure, the integrated control cabinet is connected to a computer, both of which can realize the control of the experimental conditions of the PVT cylinder; the microscopic observation and image acquisition system includes a microscope, a microscope adjustment frame and a computer, the microscope is fixed on the fixed platform through a microscope adjustment frame, the microscope is connected to the computer through a data line, and the computer is installed with image acquisition and analysis software, temperature and pressure data recording software and control cabinet synchronization control software.

[0008] On the basis of the above technical solution, the system for measuring phase parameters of hydrocarbon substances in situ converted from shale in different formation environments of the present invention can also be improved as follows:

[0009] Wherein, the image acquisition and analysis software includes the following modules:

[0010] Image acquisition module: controls the microscope to capture images of the fluid state in the PVT cylinder in real time;

[0011] Image preprocessing module: noise reduction and enhancement processing of the collected original images;

[0012] Phase recognition module: identifies gas, liquid and solid phase areas in the image;

[0013] Interface tracking module: track and measure the position and shape changes of the phase interface;

[0014] Particle size analysis module: measure the size distribution of droplets or bubbles;

[0015] Flow visualization module: analyze the flow pattern of fluid through continuous images;

[0016] Data storage module: save images and analysis results in a retrievable format.

[0017] Further, the temperature and pressure data recording software includes the following modules:

[0018] Data acquisition module: collects data from temperature sensors and pressure sensors in real time;

[0019] Data display module: real-time display of temperature and pressure changes in the form of graphs;

[0020] Data calibration module: calibrate and correct sensor data;

[0021] Alarm module: issues an alarm when the temperature or pressure exceeds the preset range;

[0022] Data storage module: save temperature and pressure data in the form of time series;

[0023] Data analysis module: calculate the statistics of mean and standard deviation;

[0024] Data export module: export data to Excel format for further analysis;

[0025] Historical query module: view and compare temperature and pressure data of different time periods.

[0026] Furthermore, the control cabinet synchronization control software includes the following modules:

[0027] Temperature control module: set and adjust the heating temperature of the PVT cylinder;

[0028] Pressure control module: adjusts the pressure inside the PVT cylinder by controlling the plunger;

[0029] Angle control module: set and adjust the rotation angle of the PVT cylinder;

[0030] Drive control module: controls the speed and displacement of the drive;

[0031] Parameter synchronization module: ensure parameter synchronization and coordination among systems;

[0032] Remote control module: allows remote control of devices via the network;

[0033] System diagnosis module: monitors the equipment operation status and provides fault diagnosis;

[0034] Data integration module: integrates temperature, pressure and image data and stores them.

[0035] Among them, the inner diameter of the PVT tube is 21 mm, and the maximum tube depth is 216.5 mm. Core models with different characteristics can be placed in the tube to study the influence of rock pore structure and mineral composition on phase state.

[0036] Furthermore, the visible glass window and the PVT cylinder are sealed by a graphite ring and a copper sleeve. The visible glass window is made of sapphire and has a cylindrical shape. After sealing, the maximum pressure resistance is 25 MPa and the maximum temperature resistance is 300°C.

[0037] Furthermore, the angle adjustment system is connected to the fixed platform and transmits angle information through the grating, which is used to mix fluids and adjust fluid angles, and can achieve angle positioning and automatic rotation, with a rotation angle range of -120°~120°.

[0038] Furthermore, the pyrolysis reactor can obtain hydrocarbon products under different heating conditions, with a maximum experimental temperature of 600°C and a maximum pressure of 40 MPa. The product release end is directly connected to the PVT cylinder through a pipeline and a second valve for directly collecting pyrolysis products and performing phase parameter testing.

[0039] The heating conditions include: heating temperature, heating time, and heating medium.

[0040] Furthermore, both the pyrolysis reactor and the PVT cylinder can be injected with a heating medium to study the phase characteristic parameters of hydrocarbon substances under the action of the heating medium.

[0041] The heating medium includes water, nitrogen, carbon dioxide and the like.

[0042] Furthermore, the integrated control cabinet is connected to the heating sleeve, temperature sensor, pressure sensor, angle adjustment system and driver to collect and control the pressure, temperature, volume, angle and driving plunger speed in the PVT cylinder in real time.

[0043] The operating steps of this system are as follows:

[0044] S1, basic setup: Place shales of different conditions to be studied in the PVT cylinder, including shale cores, rock blocks, powder, etc. before and after pyrolysis. Before placing the shale, its pore structure characteristics can be clarified by nuclear magnetic resonance testing and other methods. After the rock is placed, the maximum compressible depth is calculated, and then the PVT cylinder is sealed;

[0045] S2, pyrolysis product collection and output ratio calculation: shale is pyrolyzed using a pyrolysis reactor, and pyrolysis conversion hydrocarbon materials under different heating medium environments are obtained by controlling the pyrolysis time and pyrolysis temperature, including pyrolysis liquid and pyrolysis gas. The pyrolysis gas volume is calculated based on the reactor pressure and gas volume at the end of the experiment (reactor volume minus the residue volume, the volume occupied in the reactor, and the pyrolysis liquid volume). The pyrolysis liquid volume is obtained by weighing the liquid collected in the conical flask after the product is released after the experiment, and the liquid volume is recorded separately to calculate the output ratio of pyrolysis oil and gas. The oil and gas products produced by shale pyrolysis are collected for phase state experiments. The pyrolysis gas is collected in an intermediate container, and the pyrolysis oil is transferred to a measuring cylinder. For special heating medium conditions, the water volume is obtained by subtracting the oil volume from the liquid volume during supercritical water heating, and the pyrolysis gas is directly injected through the output gas;

[0046] S3, equipment debugging: turn on the computer, microscope and supporting software, adjust the position of the observation window and the magnification in the screen, turn on the integrated control cabinet, computer integrated control supporting software and adjust the port settings, and obtain the real-time pressure, temperature and volume data in the PVT cylinder;

[0047] S4, vacuuming and airtightness check: vacuum the PVT cylinder and experimental pipeline until the pressure in the PVT cylinder is -0.1 MPa and continue for 10 min, close the valve of the vacuum pump, and observe the pressure in the PVT cylinder. If the pressure in the cylinder remains unchanged, the airtightness is good;

[0048] S5, liquid suction: the pyrolysis oil in the measuring cylinder is sucked in by the negative pressure in the cylinder, and the volume of the pyrolysis oil in the PVT cylinder is determined according to the volume of the pyrolysis oil in the measuring cylinder before and after the suction. After the suction is completed, the first valve is closed and the plunger is withdrawn to the bottom of the PVT cylinder. At this time, the cylinder volume is the largest. If the influence of solid organic matter is considered, the kerogen can be ground into powder and inhaled, and the kerogen suction amount can be obtained by calculating the mass difference before and after the suction;

[0049] S6, gas injection: the volume of pyrolysis gas is calculated according to the volume of injected pyrolysis oil and the oil-gas output ratio, the pressure of the PVT cylinder after gas injection is calculated based on the cylinder volume and the volume of injected oil, and the gas in the intermediate container is pre-pressurized to the pressure using a syringe pump. After the pressurization is completed, the valve of the intermediate container is opened to quickly inject the gas into the PVT cylinder and pressurize it to the set pressure;

[0050] S7, instrument heating: Use the touch screen or computer to set the heating temperature of the PVT cylinder. At the same time, you can turn on the rotation button and set the automatic rotation angle range to fully mix the fluid in the cylinder;

[0051] S8, phase state experiment: Taking the constant mass expansion experiment as an example, after the temperature in the PVT cylinder reaches the target temperature and stabilizes, a series of values ​​can be obtained by setting the constant pressure of the PVT cylinder and recording the volume value of the PVT cylinder when the pressure is stable. At the same time, the rotation angle of the PVT cylinder can be adjusted to observe and record the state of the mixed fluid;

[0052] S9, adjusting the temperature, after the experiment is completed at the temperature, further adjusting the experimental temperature, repeating steps S7-S8, and obtaining experimental values ​​and microscopic images at different temperatures;

[0053] S10, instrument cleaning and data processing: after the experiments at different temperatures are completed, turn off the heating button, adjust the angle of the PVT cylinder to reset it, and discharge the experimental fluid after the temperature drops to room temperature. Since the volume of the PVT cylinder is small, in order to prevent fluid leakage from affecting the next experiment, the PVT cylinder is disassembled for cleaning and drying, the graphite ring is replaced and other parts are checked for damage. After cleaning and replacement, the instrument is installed and wait for the next experiment; among them, data processing can obtain a series of pressure and volume values ​​according to the constant mass expansion experiment at the same temperature, draw a PV relationship diagram to obtain the bubble point pressure of the experimental fluid, obtain the dew point pressure of the experimental fluid by observing the existing pressure of the liquid, and draw a fluid phase diagram based on the bubble point and dew point pressures. In addition, based on the pressure and volume values ​​at different temperatures, the thermal expansion coefficient, compression coefficient and other phase parameters of the pyrolysis oil can also be calculated.

[0054] Compared with the prior art, the beneficial effects of the system for measuring phase parameters of hydrocarbon substances for in-situ conversion of shale in different formation environments provided by the present invention are: it can meet a wider range of experimental temperature requirements (300°C), and the experimental research conditions can fully consider the reservoir characteristics and heating conditions, which is more in line with the actual situation during in-situ conversion of shale. The system and equipment can not only accurately measure the phase characteristic parameters of hydrocarbon substances but also observe and record the state of fluids in real time, and can also consider the influence of kerogen organic matter and heating medium, and can better meet the actual development needs of in-situ conversion of shale under different conditions.

[0055] Specifically, the present invention can realize the research on the phase characteristics of shale in-situ conversion of hydrocarbon substances under 300°C, and can obtain more extensive phase data of shale in-situ conversion of hydrocarbon substances. The present invention can also consider the phase characteristics of hydrocarbon substances under the influence of shale rocks, obtain the phase data under the influence of shale nanopore confined space and rock minerals, and control the temperature, pressure and volume in the PVT cylinder by adjusting the temperature of the heating sleeve and the movement of the plunger to complete different phase experiments. A visual window is installed on the outside of the PVT cylinder, and the fluid conditions in the cylinder can be observed and recorded with the help of a microscope. The angle adjustment system can not only realize the fluid interface at different angles, but also can realize the phase characteristics of shale in-situ conversion of hydrocarbon substances under 300°C. Observation can also control the automatic rotation of the PVT cylinder to achieve sufficient mixing of the fluid. The invention can also consider the effects of different heating media and incompletely pyrolyzed organic matter, and is widely applicable to different in-situ conversion engineering conditions. The present invention is simple to operate, and the temperature, pressure, volume and angle of the PVT cylinder are integrated, all displayed, controlled and recorded on the same interface, with low resource consumption, small size of the PVT cylinder, and parameter measurement can be completed with a small amount of product. The degree of reduction is high, which solves the problems of difficult to achieve in-situ conversion heating conditions and the inability to consider the effects of organic matter and heating media, and can better provide theoretical guidance for the development of actual shale oil reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 A schematic diagram of the composition of the system provided by the present invention;

[0057] Figure 2 The curve of pressure-volume variation of hydrocarbon produced by pyrolysis of shale in a certain area at 375℃ and at 120℃;

[0058] Figure 3 This is a comparison curve of the bubble point pressure experimental results of hydrocarbon substances produced by pyrolysis of shale in a certain block at 375℃ and the calculation results of the PR state equation;

[0059] Figure 4 The state diagram of hydrocarbons produced by pyrolysis of shale in a certain area at 375°C at different pressures at 30°C: (a) is the fluid image at a pressure of 5 MPa; (b) is the fluid image at a pressure of 10 MPa;

[0060] The figure marks in the accompanying drawings are: 1. integrated control cabinet; 2. touch display screen; 3. computer; 4. microscope; 5. microscope adjustment frame; 6. cylinder cover; 7. copper sleeve; 8. graphite ring; 9. visual glass window; 10. PVT cylinder; 11. heating sleeve; 12. plunger seal; 13. plunger; 14. data cable; 15. temperature sensor; 16. pressure sensor; 17. rotating rod; 18. fixed table; 19. angle adjustment system; 20. drive column; 21. drive; 22. support frame; 23. transmission; 24. movable base; 25. first valve; 26. metal pipeline; 27. measuring cylinder; 28. vacuum pump; 29. ​​second valve; 30. intermediate container; 31. injection pump; 32. conical flask; 33. pyrolysis reactor; 34. shale core. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0062] See attached Figure 1As shown, a system for measuring phase parameters of shale in-situ conversion hydrocarbon materials in different formation environments provided by the present invention includes a shale pyrolysis and product injection system, a PVT experiment and heating system, a drive and rotation system, an integrated control system, and a microscopic observation and data acquisition system. The shale pyrolysis and product injection system includes a pyrolysis reactor 33, a conical flask 32, an injection pump 31, an intermediate container 30, a first valve 25, a metal pipeline 26, a vacuum pump 28, a measuring cylinder 27, and a second valve 29. The outlet end of the pyrolysis reactor 33 is connected to the conical flask 32 and the intermediate container 30 in sequence through pipelines, which are used to collect pyrolysis oil and store pyrolysis gas, respectively. The output end of the intermediate container 30 is connected to the second valve 29, the vacuum pump 28, the first valve 25 and the PVT cylinder 10 in sequence through the metal pipeline 26, wherein the first valve 25 is a three-way valve, the measuring cylinder 27 is filled with pyrolysis oil from the conical flask 32 and is connected to the PVT cylinder 10; the PVT experiment and heating system includes the PVT cylinder 10, the heating sleeve 11, the graphite ring 8, the copper sleeve 7, the visual glass window 9, the cylinder cover 6, the plunger 13 and the plunger seal 12, the PVT cylinder 10 and the visual glass window 9 are sealed by the graphite ring 8 and the copper sleeve 7 in sequence, the material of the visual glass window 9 is sapphire glass, and the maximum pressure resistance after sealing is 25 MPa and the maximum temperature resistance is 300°C, the other end of the PVT cylinder 10 is blocked by the plunger 13 and sealed by the plunger seal 12, the outer diameter of the plunger 13 is 20 mm, and the inner diameter of the PVT cylinder 10 is 21 mm, the PVT cylinder 10 is used to place the shale core 34 to provide a reservoir environment for phase state experiments. The PVT cylinder 10 is wrapped by a heating sleeve for heating and is connected to the integrated control cabinet 1 through a data line 14; the driving and rotating system includes a fixed platform 18, a rotating rod 17, an angle adjustment system 19, a driving column 20, a driver 21, a transmission 23, a support frame 22 and a movable base 24. The fixed platform 18 is connected to the outside of the PVT cylinder 10 and is connected to the angle adjustment system 19 through the rotating rod 17. The angle adjustment system 19 transmits angle information through a grating, which is used to mix fluids and adjust fluid angles, and can achieve angle positioning and automatic rotation. The rotation angle range is -120 °~120°, the fixed platform 18 is connected to the driver 21 through the driving column 20 to control the movement of the plunger 13, and the driver 21 is equipped with a transmission 23 to control the movement speed of the plunger 13. The driver 21 and the angle adjustment system 19 are both connected to the integrated control cabinet 1; the integrated control system includes an integrated control cabinet 1, a touch screen 2, a temperature sensor 15 and a pressure sensor 16. The integrated control cabinet 1 is connected to the inner cavity of the PVT cylinder 10 through the temperature sensor 15 and the pressure sensor 16 respectively for testing the temperature and pressure. The integrated control cabinet 1 is connected to the computer 3, both of which can collect and control the pressure, temperature, volume, angle and driving plunger speed in the PVT cylinder 10 in real time;The microscopic observation and image acquisition system includes a microscope 4, a microscope adjustment frame 5 and a computer 3. The microscope 4 is fixed on a fixed platform 18 through the microscope adjustment frame 5. The microscope 4 is connected to the computer 3 through a data line. The computer 3 is installed with integrated control supporting software, including: image acquisition and analysis software, temperature and pressure data recording software and control cabinet synchronization control software. The present invention has rich functions, simple operation, accurate measurement, and high temperature and pressure resistance of the sealing and observation parts, so that the shale in-situ conversion hydrocarbon material phase characteristic parameter measurement device has the characteristics of wide experimental test range, high reduction degree, visualization, etc.;

[0063] The following is a detailed description of the three software-related modules:

[0064] 1. Implementation of image acquisition and analysis software module

[0065] 1.1 Image acquisition module

[0066] This module realizes real-time communication and image acquisition with the microscope based on the OpenCV development library. Data is transmitted with the microscope camera through the USB3.0 or HDMI interface, supporting up to 4K resolution and 60fps acquisition rate. Multi-threading technology is used to separate image acquisition and display to ensure the real-time nature of the acquisition process. An integrated autofocus algorithm is used to calculate the image clarity through the evaluation function and control the microscope motor to achieve precise focus. ROI area setting function is provided to support simultaneous acquisition and observation of multiple areas. Adaptive exposure control is implemented to automatically adjust the exposure parameters according to the image histogram distribution to ensure moderate image brightness. A ring buffer management mechanism is used to prevent data loss.

[0067] 1.2 Image Preprocessing Module

[0068] The image preprocessing module adopts a multi-level processing flow. First, noise evaluation and adaptive noise reduction are performed. Combined with algorithms such as Gaussian filtering, median filtering and bilateral filtering, the optimal noise reduction scheme is automatically selected according to the noise characteristics. Then, contrast enhancement is performed through histogram analysis, and adaptive histogram equalization technology is used to maintain image details while improving the overall observation effect. For the distortion caused by the microscope, a distortion model is established for correction to eliminate edge deformation. Finally, automatic registration of image sequences is achieved. By extracting and matching feature points, the transformation matrix is ​​calculated for image alignment to ensure the accuracy of subsequent analysis.

[0069] 1.3 Phase identification module

[0070] The phase recognition module uses a method that combines deep learning with traditional image processing. First, the improved U-Net network is used to perform semantic segmentation on the image to identify the gas, liquid and solid phase regions. The network training adopts a transfer learning strategy and uses a pre-labeled data set for model optimization. At the same time, the traditional edge detection and region growing algorithms are used as auxiliary to improve recognition accuracy. The automatic extraction of phase features is achieved, including multi-dimensional feature vectors such as color distribution, texture features and shape features, and a multi-layer classifier is constructed for phase discrimination. Finally, the phase distribution diagram and the proportion of each phase are output.

[0071] 1.4 Interface Tracking Module

[0072] The interface tracking module implements multi-scale edge detection and dynamic contour tracking functions. First, the improved Canny algorithm is used for edge detection, and the robustness of edge detection is improved by adaptive threshold selection. The active contour model (Snake algorithm) is used to accurately extract the interface contour, and elastic potential energy and external force field constraints are introduced to ensure the accuracy of contour fitting. In the dynamic tracking process, the optical flow method and Kalman filter are combined to realize interface motion prediction, and the tracking stability is improved by multi-frame information fusion. At the same time, the interface position and shape changes are recorded to generate time series data for subsequent analysis.

[0073] 1.5 Particle Size Analysis Module

[0074] The particle size analysis module integrates a variety of particle detection and measurement algorithms. The improved Hough transform is used to detect circular droplets, and the watershed algorithm is used to handle the segmentation of adherent particles. The mapping relationship between pixels and actual sizes is established, and spatial calibration is completed through the calibration plate. The shape parameters of particles are calculated, including characteristic parameters such as area, perimeter, and roundness. The kernel density estimation method is used to generate the particle size distribution curve, calculate the characteristic particle size and distribution width. Batch processing is supported, and the image sequence can be automatically analyzed to obtain the particle size evolution law and output statistical reports.

[0075] 1.6 Flow Visualization Module

[0076] The flow visualization module uses particle image velocimetry (PIV) technology to realize flow field analysis. The displacement field of the image sequence is calculated by the cross-correlation algorithm, and the velocity field distribution is obtained by combining the time interval. The adaptive window deformation technology is used to improve the accuracy of velocity field calculation and support multi-resolution analysis. Automatic generation and rendering of streamlines are realized, and trajectory integration is performed using the fourth-order Runge-Kutta method. Typical flow patterns are identified through cluster analysis, and a flow type classification library is established. A variety of visualization methods are provided, including vector diagrams, streamline diagrams, and vorticity distribution diagrams, supporting dynamic demonstration and exporting high-quality pictures.

[0077] 1.7 Data Storage Module

[0078] The data storage module adopts a layered architecture design to achieve systematic management of experimental data. A three-level storage structure is established, including experimental batches, sample numbers, and test sequences. The original images are stored using lossless compression, supporting PNG and TIFF formats. The analysis results are stored in HDF5 format to achieve efficient compression and fast access. A data indexing mechanism is established to support multi-dimensional retrieval by time, sample characteristics, experimental conditions, etc. A data integrity check function is provided to automatically back up important data. A data export interface is implemented to support multiple format conversions for easy subsequent processing and analysis.

[0079] 2. Implementation of temperature and pressure data recording software module

[0080] 2.1 Data Acquisition Module

[0081] The data acquisition module implements multi-protocol sensor access and data acquisition functions. It supports multiple communication methods such as RS485, 4-20mA and TCP / IP, and uses multi-threading technology to achieve parallel acquisition. The data sampling frequency can be adjusted in the range of 0.1-100Hz, supporting two modes: triggered sampling and continuous sampling. It implements data preprocessing functions, including digital filtering, zero drift compensation and linear calibration, to ensure data quality. It uses a double buffer mechanism to manage the collected data to ensure that data is not lost during high-speed acquisition. It provides sensor status monitoring function, automatically detects sensor failures and alarms.

[0082] 2.2 Data Display Module

[0083] The data display module adopts a multi-view design to achieve real-time visualization of data. Use OpenGL to draw real-time curves, support multi-channel synchronous display, and realize curve translation, scaling and local magnification. The large font numerical display adopts an adaptive layout to ensure the display effect at different resolutions. Integrated statistical information calculation function, real-time update of maximum, minimum, average and standard deviation statistics. Provide a variety of curve styles and color schemes, support user-defined display parameters. Implement curve export function, support image and data export.

[0084] 2.3 Data calibration module

[0085] The data calibration module implements the comprehensive calibration function of the sensor and the system. It supports the multi-point calibration method and obtains the calibration curve through the least squares method. It implements the temperature compensation algorithm and automatically corrects the measured value according to the ambient temperature. It provides dead zone compensation and hysteresis correction functions to improve the measurement accuracy. It establishes a calibration data management system to record the calibration history and realize the automatic generation of calibration certificates. It supports the calibration cycle reminder function to ensure the calibration on schedule. It integrates the calibration process auxiliary tool to guide the operator to complete the calibration steps.

[0086] 2.4 Alarm Module

[0087] The alarm module adopts a multi-level alarm strategy to achieve comprehensive security monitoring. It supports upper and lower limit alarms, change rate alarms and combined condition alarms, and the alarm threshold can be adjusted dynamically. It realizes sound and light alarms and remote notification functions, and supports SMS and email push. It adopts an alarm classification management mechanism and takes different treatment measures according to the severity. It provides alarm confirmation and elimination functions, and records the operator and the treatment process. It establishes an alarm history database, supports alarm statistical analysis, and helps to discover potential problems in the system. It realizes alarm linkage control and can trigger preset safety protection actions.

[0088] 2.5 Data Storage Module

[0089] The data storage module adopts a hybrid storage architecture to achieve efficient data management. Use SQLite database to store structured data and binary files to store raw data. Implement data compression storage strategy and use lossless compression algorithm to reduce storage space. Support multiple storage triggering methods, including timed storage, conditional storage and manual storage. Provide data integrity verification function to ensure that data is not damaged during storage. Implement automatic data backup mechanism to regularly back up important data to a specified location. Establish data cleanup strategy to automatically delete expired data and optimize storage space.

[0090] 2.6 Data Analysis Module

[0091] The data analysis module integrates a variety of statistical analysis and data mining methods. It implements basic statistical analysis functions, including descriptive statistics, correlation analysis, and regression analysis. It uses a sliding window algorithm to perform trend analysis and predict parameter change trends. It integrates anomaly detection algorithms to identify abnormal data based on statistical methods and machine learning models. It provides data visualization tools and supports a variety of chart types. It implements automatic report generation, which can automatically generate analysis reports based on templates and supports output in Word and PDF formats.

[0092] 2.7 Data export module

[0093] The data export module provides flexible data export functions. It supports export in multiple formats such as Excel, CSV and JSON, and realizes automatic conversion of data formats. It provides data filtering function, and can select export content by time period, data type and channel. It implements batch export function, supports exporting multiple files at the same time, and automatically generates file names. It integrates data compression function, and can package and compress export files. It provides export log records to record detailed information of export operations. It supports breakpoint resumption of export tasks to ensure the reliability of large data volume export.

[0094] 2.8 History Query Module

[0095] The historical query module implements multi-dimensional data retrieval and analysis functions. It provides flexible query condition settings and supports multiple condition combination queries such as time range, data type and alarm records. It implements a fast data indexing mechanism to improve query efficiency. It supports multiple data display methods, including trend charts, data tables and statistical charts. It provides data comparison and analysis functions, which can display multiple curves at the same time and perform historical comparisons. It implements data export functions and supports batch export of query results. It integrates data analysis tools and supports simple statistical analysis.

[0096] 3. Implementation of control cabinet synchronous control software module

[0097] 3.1 Temperature Control Module

[0098] The temperature control module adopts intelligent control strategy to achieve precise temperature regulation. It integrates PID control algorithm and fuzzy controller to automatically optimize control parameters according to temperature response characteristics. It realizes step heating and program heating functions, and supports multi-stage temperature curve control. It provides temperature over-limit protection function and sets multi-level protection thresholds to ensure system safety. It realizes sensor fault diagnosis and automatically switches to the backup channel when the sensor is abnormal. It adopts heating power limitation strategy to prevent heater overload. It supports temperature control process recording and real-time recording of temperature change curve and control parameters.

[0099] 3.2 Pressure Control Module

[0100] The pressure control module realizes precise pressure control based on the plunger position. It adopts a cascade control structure, with the inner loop as position control and the outer loop as pressure control, to achieve fast response and stable control. It provides multiple control modes, including pressure setting, flow control and program control. It realizes the pressure fluctuation compensation function and reduces the pressure fluctuation through feedforward control. It integrates safety protection functions, including overpressure protection, pressure relief control and emergency stop. It supports pressure control process recording, recording pressure changes and plunger position data. It realizes system fault diagnosis and monitors the sealing performance and drive system status.

[0101] 3.3 Angle Control Module

[0102] The angle control module realizes the precise rotation control of the PVT cylinder. It adopts the position-speed-torque three-loop control structure to ensure the smoothness of the rotation process. It supports multiple rotation modes, including continuous rotation, reciprocating rotation and stepping rotation. It realizes soft start and soft stop functions, and reduces shock through acceleration planning. It provides position memory function to store multiple common positions. It integrates the origin return function to ensure the accuracy of the position reference. It realizes the angle calibration function to compensate for mechanical errors and gaps. It supports the rotation process recording, recording angle, speed and torque data.

[0103] 3.4 Drive control module

[0104] The drive control module uses high-precision motion control technology to achieve precise control of the motor. It supports three modes: speed control, position control and torque control, and achieves seamless mode switching. It uses a trapezoidal speed planning algorithm to generate a smooth motion trajectory. It realizes multi-axis synchronous control function to ensure coordinated motion of multiple actuators. It provides motor status monitoring function to monitor current, temperature and position information in real time. It integrates fault diagnosis function to identify motor stall, overcurrent and other faults. It supports parameter self-tuning function to optimize control performance.

[0105] 3.5 Parameter Synchronization Module

[0106] The parameter synchronization module uses the publish-subscribe design pattern to achieve real-time data synchronization between systems. The module sets up an independent parameter synchronization server, which is responsible for receiving and distributing the status data of each subsystem. During the synchronization process, subsystems such as temperature control, pressure control, angle control and drive control act as publishers and send their parameter changes to the synchronization server in real time through the TCP / IP protocol. After receiving the data, the synchronization server performs data verification and timestamp alignment according to the preset synchronization strategy to ensure data consistency and timing. The processed data is pushed to other subsystems that need the data through the subscription mechanism. The module also contains a parameter conflict detection mechanism. When a potential conflict between control parameters is detected, it automatically adjusts or warns the operator according to the preset priority rules. At the same time, the module maintains a parameter synchronization log to record all synchronization operations and abnormal conditions for later analysis and fault tracking.

[0107] 3.6 Remote Control Module

[0108] The remote control module realizes remote monitoring and operation of the equipment based on the WebSocket protocol. The module adopts C / S architecture, the server is deployed locally in the control cabinet, and the client supports Web browser access. Remote users access the system through HTTPS encrypted connection, and a two-factor authentication mechanism is used to ensure operational security. After successful login, the remote control interface maintains real-time two-way communication with the server through WebSocket, and can display the equipment operation status and various sensor data in real time. After multiple security checks, the operation instructions are executed in sequence through the message queue to ensure the reliability and timing of the instruction execution. The module sets up a three-level operation authority system, and users of different levels have different operation authorities. To ensure the safety of the experiment, the module integrates a remote operation safety protection mechanism, including automatic disconnection when the operation timeouts, confirmation of dangerous operations, emergency stop and other functions, and records all remote operation logs in real time.

[0109] 3.7 System Diagnosis Module

[0110] The system diagnosis module adopts a multi-level fault detection and diagnosis strategy to achieve real-time monitoring of the equipment's operating status and fault warning. The module collects the operating parameters of each sensor and actuator, and combines it with the preset normal operating parameter range of the equipment to establish an equipment health status assessment model. At the data acquisition level, the module preprocesses and extracts features from the collected data, and analyzes the changing trends of characteristic parameters such as equipment vibration and temperature through algorithms such as Fourier transform. The diagnostic algorithm adopts a combination of rule-based and machine learning methods. By learning from historical fault data, a fault feature library is established to achieve accurate fault location and prediction. When an abnormality is detected, the system automatically generates a fault diagnosis report, which includes the fault type, severity, possible causes and handling suggestions, and issues real-time alarms through preset notification methods.

[0111] 3.8 Data Integration Module

[0112] The data integration module adopts a distributed data processing architecture to achieve unified management and analysis of multi-source heterogeneous data. The module designs a unified data interface standard and converts different types of data such as temperature, pressure, and images into a standard format through a data adapter. The data storage adopts a hybrid storage strategy, with real-time data stored in an in-memory database to provide fast access, and historical data is regularly archived to a relational database to ensure data persistence. The module provides a data query and analysis interface, supports multi-dimensional data association analysis, and discovers potential associations between data through data mining algorithms. To ensure the integrity and traceability of the data, the module implements a data version control mechanism to record the change history of the data. At the same time, the module supports data export, which can export the integrated data into a standard format to facilitate subsequent analysis by external systems.

[0113] The interface tracking module performs the following steps:

[0114] S11, obtaining the original image data collected by the microscope and performing image preprocessing;

[0115] S12, using the improved Canny algorithm to perform edge detection on the preprocessed image;

[0116] S13, extracting the interface contour using an active contour model according to the edge detection result;

[0117] S14, calculating the interface position change between adjacent frames using an optical flow algorithm;

[0118] S15, using Kalman filter to predict the interface motion trajectory;

[0119] S16. Record the interface position and shape parameters.

[0120] Specifically:

[0121] The specific implementation of step S11 is to collect image sequences through a microscope CCD camera with a sampling frequency of 30 frames per second. Gaussian filtering is performed on the acquired original image to eliminate noise, and the filter kernel size is , standard deviation Then histogram equalization is performed to enhance the image contrast, and finally median filtering is used (window size is ) to remove salt and pepper noise. Image preprocessing uses grayscale image processing, and the pixel value range is The grayscale difference threshold between adjacent pixels is set to 12, and pixels below this threshold are considered to belong to the same region.

[0122] The specific implementation of step S12 is to use the improved Canny operator for edge detection. First, calculate the image gradient. Suppose the image At the point The gradient size at is and direction : , .in and are the first-order partial derivatives in the x and y directions respectively. Adaptive dual threshold method is used for edge connection, and the high threshold Take the 85th percentile of the image gradient magnitude and the low threshold .

[0123] The specific implementation of step S13 is to extract the interface contour based on the geometric active contour model. Define the level set function , the interface consists of a zero level set The evolution equation is: ,in Stop function for edge: , is the curvature: , is the bubble expansion coefficient, which is set to 1.5. The iteration step is 0.1, and the maximum number of iterations is 200.

[0124] The specific implementation of step S14 is to use the Lucas-Kanade optical flow method to calculate the interface motion. is a point in the image sequence at time The gray value of , assuming that the gray value remains unchanged in a small time interval: . Expand to get the optical flow equation: ,in , is the velocity component to be determined, , , are the spatial and temporal partial derivatives of the image respectively. The velocity field is obtained by solving the least squares problem with a window.

[0125] The specific implementation of step S15 is to use a Kalman filter to predict the interface motion trajectory. The state vector is the position and velocity of the interface feature point: . State transfer equation: ,in is the state transfer matrix, is the process noise, the covariance matrix . Measurement equation: ,in is the measurement matrix, is the measurement noise, the covariance matrix .

[0126] The specific implementation of step S16 is to record the geometric characteristic parameters of the interface contour. Including the interface perimeter : ,area : , roundness : , and the barycentric coordinates : , .

[0127] The particle size analysis module performs the following steps:

[0128] S21, collecting microscopic images and performing spatial calibration;

[0129] S22, detecting circular droplets using improved Hough transform;

[0130] S23, using watershed algorithm to process adhesion droplet segmentation;

[0131] S24, calculating the area and perimeter of each droplet;

[0132] S25, establishing a mapping relationship between pixel size and actual size;

[0133] S26, calculating the droplet roundness and shape coefficient;

[0134] S27. Generate particle size distribution statistics.

[0135] Specifically:

[0136] The specific implementation of step S21 is to perform spatial calibration according to a standard ruler. Place a standard ruler in the microscope field of view, calculate the corresponding relationship between the number of pixels and the actual length, and obtain the proportionality coefficient. (micrometers / pixel). The image resolution collected is Pixels, field of view The spatial resolution is about 0.42 microns / pixel. Bilinear interpolation is used to resample the image to ensure processing accuracy.

[0137] The specific implementation of step S22 is to use the improved Hough transform to detect circular droplets. In the parameter space, the circle can be represented by the center coordinates and radius express: To improve computational efficiency, we first use the gradient information to determine the search range. Set the minimum radius Pixels, maximum radius The accumulator threshold is set to 15% of the image height, and circles with votes greater than this threshold are considered valid droplets.

[0138] The specific implementation of step S23 is to use the watershed algorithm to segment the adhesion droplets. First, the Euclidean distance transform is calculated to obtain the distance map , and then find the local maximum as the mark point. Take the negative value of the distance map and submerge the mark point. Let the submerged height be , then at time The flooded area at the moment is: When two flooded areas meet, a watershed is created at the junction. The height threshold of the watershed line is set to 60% of the maximum distance value.

[0139] The specific implementation of step S24 is to calculate the area and perimeter of each segmented region. The area is obtained by pixel counting: ,in is the number of pixels in the area, is the spatial resolution. The perimeter is calculated using a boundary tracking algorithm: ,in is the number of boundary pixels. To improve accuracy, sub-pixel edge detection is used for the boundary, with the minimum resolvable area being 25 pixels and the minimum resolvable perimeter being 18 pixels.

[0140] The specific implementation of step S25 is to establish a mapping relationship between pixel size and actual size. Considering optical distortion, a quadratic polynomial is used for correction: , ,in is the distorted image coordinate, is the corrected coordinate, , and is the distortion coefficient, which is obtained by calibration with the calibration plate.

[0141] The specific implementation of step S26 is to calculate the drop shape parameters. Roundness is defined as: , when the perfect circle The shape factor is defined as: ,in is the maximum Feyre diameter. When the droplet deviates from a circular shape, the shape factor threshold is set to 0.85, and the droplet below this value is marked as non-spherical. The flattening is defined as the ratio of the major axis to the minor axis, and the threshold is set to 1.2.

[0142] The specific implementation of step S27 is to generate the particle size distribution statistics. The equal-proportional logarithmic grouping method is adopted, and the group interval ratio is . Calculate the number distribution function and volume distribution function : , ,in For the Number of droplets in a group, is the total number of droplets, is the total volume, is the median diameter of the group. Calculate the characteristic diameter (Sauter mean diameter): .

[0143] The flow visualization module performs the following steps:

[0144] S31, collecting continuous image sequences;

[0145] S32, performing cross-correlation operation on the image sequence;

[0146] S33, calculating velocity field distribution data;

[0147] S34, the fourth-order Runge-Kutta method is used to calculate streamlines;

[0148] S35, performing flow pattern identification and classification;

[0149] S36, generating vector field display data;

[0150] S37. Output flow field analysis results.

[0151] Specifically:

[0152] The specific implementation of step S31 is to collect a high-speed continuous image sequence. A high-speed camera is used with a sampling frequency of 1000 frames per second and an exposure time of 100 microseconds. The image resolution is Pixels, grayscale level is 256. To ensure image quality, coaxial LED light source is used for illumination, light intensity is adjustable, and the maximum illumination is 50000 lux. The length of the acquired sequence is 2048 frames to ensure that the complete flow cycle is captured.

[0153] The specific implementation of step S32 is to perform a cross-correlation operation on the image sequence. Assume that the grayscale distributions of the two frames of images are and , and its cross-correlation function is: . Use Fast Fourier Transform to speed up calculations: The search window size is The pixels were overlapped by 50%, and the correlation peak signal-to-noise ratio threshold was set to 2.5.

[0154] The specific implementation of step S33 is to calculate the velocity field distribution. The velocity vector is calculated based on the cross-correlation peak displacement and time interval: The velocity field is median filtered to remove abnormal vectors, and the filter window is The velocity field is smoothed using Gaussian weights: ,in For distance, is a smoothing parameter with a value of 1.5. The minimum measurable speed is 0.1 mm / s and the maximum measurable speed is 100 mm / s.

[0155] The specific implementation of step S34 is to use the fourth-order Runge-Kutta method to calculate the streamline. and velocity field , the streamlines are described by a system of ordinary differential equations: , The fourth-order Runge-Kutta format is: , , , , ,in is the step size, and its value is 0.1.

[0156] The specific implementation of step S35 is to perform flow pattern recognition and classification. Calculation of characteristic parameters: Reynolds number , Weber number ,in is the density, is the characteristic speed, is the characteristic length, is the viscosity, is the surface tension. According to the dimensionless parameters, the flow type is divided into laminar flow ( )、Transition Flow( ) and turbulence ( ). For gas-liquid two-phase flow, the flow pattern is further subdivided according to the Weber number: When it is a trickle flow, For slug flow, is a film flow. Introducing dimensionless numbers Describe the droplet breakup mechanism, when Shear crushing occurs when The confidence threshold for flow pattern judgment is set to 85%.

[0157] The specific implementation of step S36 is to generate vector field display data. The velocity vector is represented by an arrow, and the length of the arrow is proportional to the velocity: ,in is the proportional coefficient, and its value is 0.5. The color of the arrow indicates the speed, and the HSV color space is used. Linear mapping with velocity magnitude: The minimum displayed speed is 5% of the overall average speed, and the maximum displayed speed is 200% of the overall average speed. The speed direction is indicated by an arrow, and the direction resolution is 5 degrees.

[0158] The specific implementation of step S37 is to output the flow field analysis results. Calculate flow field statistics: average velocity , speed pulsation intensity , turbulent kinetic energy . Calculate the vorticity field: . Identify the vortex center location: The vortex core intensity threshold is 20% of the local maximum value.

[0159] The angle control module performs the following steps:

[0160] S41, receiving an angle control instruction;

[0161] S42, reading the current angle position;

[0162] S43, calculating the deviation between the target angle and the current angle;

[0163] S44, generating an angle motion trajectory;

[0164] S45, executing position loop control;

[0165] S46, execute speed loop control;

[0166] S47: Execute torque loop control.

[0167] Specifically:

[0168] The specific implementation of step S41 is to receive an angle control instruction. The control instruction includes a target angle , maximum angular velocity , maximum angular acceleration , motion mode (point to point, continuous trajectory), etc. The angular resolution is 0.01 degrees, the angular velocity resolution is 0.1 degrees per second, and the angular acceleration resolution is 1 degree per square second. The instructions are transmitted via the CAN bus with a baud rate of 1 megabit per second and a standard frame format.

[0169] The specific implementation of step S42 is to read the current angle position. A 17-bit absolute photoelectric encoder is used with a resolution of 0.00275 degrees. The encoder output format is Gray code, which is converted to binary to obtain the angle value: ,in is the encoder reading. The sampling period is 1 millisecond, sliding mean filtering is used, and the window length is 10. The reading error is less than ±1 minimum resolution, and the repeatability is better than ±0.005 degrees.

[0170] The specific implementation of step S43 is to calculate the angle deviation. , angular velocity deviation ,in and are the target angle and angular velocity respectively, and is the current angle and angular velocity. Considering the periodicity of angle, the deviation calculation adopts the minimum path principle: when hour, The position error band is set to ±0.02 degrees and the speed error band is set to ±0.05 degrees per second.

[0171] The specific implementation of step S44 is to generate an angle motion trajectory. S-curve planning is adopted, and the acceleration is a constant value. The motion process is divided into 7 sections: uniform acceleration, uniform acceleration, uniform deceleration, uniform speed, uniform acceleration and deceleration, uniform deceleration, and uniform deceleration and deceleration. The time and displacement of each section meet the following requirements: , . Maximum angular acceleration Take 5000 degrees per square second, the maximum acceleration Take 50,000 degrees per cubic second.

[0172] The specific implementation of step S45 is to perform position loop control. A composite control strategy of feedforward and PID control is adopted: ,in , , are proportional, integral, and differential gains respectively, is the feedforward gain. The parameter setting adopts the Ziegler Nichols method, and the critical proportional gain , critical period seconds, get , , .

[0173] The specific implementation of step S46 is to perform speed loop control. Using PI controller: ,in and They are the proportional and integral gains of the speed loop respectively. The gain parameters are adjusted by trial and error. , The integral term sets the saturation limit, and the limit value is 80% of the rated torque. The speed feedback uses the encoder position differential and low-pass filtering: ,in is the cut-off frequency, take 100 Hz, is the sampling period.

[0174] The specific implementation of step S47 is to perform torque loop control. Proportional control is adopted: ,in For a given current, is the actual current, is the torque coefficient. The current given value is calculated through the speed loop output: The current feedback is measured by Hall sensor with a sampling frequency of 20 kHz and a resolution of 0.1A. The current control uses space vector PWM modulation with a switching frequency of 10 kHz and a dead time of 2 microseconds.

[0175] Optionally, step S48 is further included. The specific implementation of step S48 is to record the angle control process data. The record items include: target angle , the actual angle , angular deviation , target speed , actual speed , speed deviation , motor current , control output , , The data sampling period is 1 millisecond, stored in binary format, and each data occupies 4 bytes. The data cache size is 1 megabyte, using a circular cache method.

[0176] The drive control module has the following steps:

[0177] S51, receiving a drive control instruction;

[0178] S52, selecting a motor control mode;

[0179] S53, generating a motion trajectory curve;

[0180] S54, executing multi-axis synchronous control;

[0181] S55, monitoring the motor running status;

[0182] S56. Record drive control parameters.

[0183] Specifically:

[0184] The specific implementation of step S51 is to receive a drive control instruction. The instruction includes a motion mode (point, straight line, arc), a target position , Movement speed , acceleration The position resolution is 0.1 micron, the velocity resolution is 0.1 mm / s, and the acceleration resolution is 1 mm / s2. The instructions are transmitted using the Modbus-TCP protocol, with a communication cycle of 10 milliseconds and a timeout of 100 milliseconds. The instruction cache depth is 128, and a first-in-first-out queue management is used.

[0185] The specific implementation of step S52 is to select the motor control mode. According to the load characteristics and accuracy requirements, position control, speed control or torque control mode can be selected. Position control is used for precise positioning, and the control accuracy is better than ±1 micron; speed control is used for constant speed movement, and the speed fluctuation is less than ±0.1%; torque control is used for constant force control, and the torque accuracy is better than ±1%. The mode switching adopts a disturbance-free switching strategy to keep the output continuous. The control parameters of each mode are independently stored in the EEPROM.

[0186] The specific implementation of step S53 is to generate a motion trajectory curve. Use cubic spline interpolation to ensure the continuity of position and speed. and end point , the interpolation polynomial is: , the coefficient is determined by the boundary conditions. The speed curve is: , the acceleration curve is: The interpolation point interval is 1 millisecond, and the generated trajectory satisfies the maximum velocity and acceleration constraints.

[0187] The specific implementation of step S54 is to perform multi-axis synchronous control. A master-slave synchronization strategy is adopted, one axis is defined as the main axis, and the other axes follow the main axis. The synchronization error is defined as: ,in is the slave axis position, is the spindle position, is the synchronization ratio. The output of the synchronization controller is: The synchronization accuracy is better than ±0.5 microns, and the dynamic following error is less than ±2 microns.

[0188] The specific implementation of step S55 is to monitor the motor running state. The monitoring items include: motor temperature , winding current , bus voltage , encoder signal quality, etc. The temperature is measured by a PT100 sensor, the sampling period is 100 milliseconds, and the alarm threshold is 85 degrees Celsius; the current is measured by a Hall sensor, the sampling frequency is 20 kHz, and the overcurrent threshold is 150% of the rated current; the voltage is measured by voltage division, the sampling frequency is 1 kHz, and the undervoltage threshold is 85% of the normal value. When any parameter exceeds the threshold, the system enters the protection state.

[0189] The specific implementation of step S56 is to record the drive control parameters. The recorded content includes: actual position ,speed , acceleration , motor current , bus voltage , controller output , synchronization error The data sampling period is 1 millisecond, and the compressed storage format is used. The position data occupies 4 bytes, the speed and acceleration each occupies 2 bytes, and the other parameters each occupies 1 byte. The data file is named by the timestamp, and a new file is generated every hour. The file is managed in a cyclic overwrite mode to save the data of the last 24 hours.

[0190] The operating steps of this system are as follows:

[0191] S1, selection of reservoir model and installation of PVT equipment. Unpyrolyzed shale is placed in the PVT cylinder 10. The diameter of the shale core is 20 mm and the length is 30 mm. After the rock is placed, the maximum compressible depth is calculated to be 18.65 cm. Then the PVT cylinder 10 is sealed.

[0192] S2, pyrolysis product collection and output ratio calculation, using the pyrolysis reactor 33 at 375 ° C to pyrolyze 500g of low-maturity shale powder for 2 hours to obtain pyrolysis hydrocarbons, the pyrolysis gas yield is calculated based on the pressure and gas volume of the pyrolysis reactor 33 at the end of the experiment (the reactor volume minus the residue volume, pyrolysis oil volume and the volume occupied in the reactor), the pyrolysis oil volume is obtained by weighing the oil collected in the conical flask after the product is released after the experiment, and then the output ratio of pyrolysis oil and gas is calculated. The yield of pyrolysis oil and gas under this condition is shown in Table 1. The oil and gas products produced by pyrolysis are collected for phase state experiments, the pyrolysis gas is collected in the intermediate container 30, and the pyrolysis oil is transferred to the measuring cylinder 27;

[0193] S3, equipment debugging, open the computer 3, microscope 4 and integrated control supporting software, adjust the position and magnification of the microscope, make the visual glass window 9 located at the center of the image, open the integrated control cabinet 1 and the integrated control supporting software on the computer 3 and adjust the port settings, and obtain the real-time pressure, temperature and volume data in the PVT cylinder 10;

[0194] S4, vacuuming and airtightness inspection, vacuuming the PVT cylinder 10 and the experimental pipeline until the pressure in the PVT cylinder 10 is -0.1 MPa and then continuing for 10 min, closing the valve of the vacuum pump 28, and observing the pressure in the PVT cylinder 10. If the pressure in the cylinder remains unchanged, the airtightness is good;

[0195] S5, liquid suction, the pyrolysis oil in the measuring cylinder 27 is sucked in by controlling the negative pressure in the cylinder, and the volume of the pyrolysis oil in the measuring cylinder 27 before and after the suction is determined to be 5.5 mL. After the suction is completed, the first valve 25 is closed and the plunger 13 is withdrawn to the bottom of the PVT cylinder 10, at which time the volume in the cylinder is the largest;

[0196] S6, gas injection, calculate the volume of pyrolysis gas according to the volume of injected pyrolysis oil and the oil-gas output ratio, and calculate the pressure of PVT cylinder 10 after gas injection based on the cylinder volume and the volume of injected pyrolysis oil. The pressure of pyrolysis gas should reach 5.00 MPa (P ge ), the value is calculated according to the following formula, and the specific experimental data are shown in Table 1:

[0197] ;

[0198] Where: V oi is the initial oil volume produced by pyrolysis; V oe V is the volume of oil required for phase state experiment; gi is the volume of gas produced by pyrolysis; V ge is the gas volume required for phase experiment; P gi P is the pressure of the pyrolysis gas in the reactor; ge is the pressure of the gas in the reactor required for the phase experiment; it should be noted that P gi and P ge is the value at the same volume.

[0199] ;

[0200] ;

[0201] ;

[0202] Where: P gPVT V is the pressure of the gas in the phase device; gPVT V is the volume occupied by the gas in the phase device; 釜 is the total volume of the reactor; V r is the volume of the pyrolysis residue, calculated by the drainage method; V d V is the occupied volume in the reactor, mainly the sample cup; PVT is the total volume of the PVT cylinder.

[0203] Table 1 Pyrolysis product results and phase state experimental calculation values

[0204] parameter <![CDATA[V oi ]]> <![CDATA[V oe ]]> <![CDATA[P gi ]]> <![CDATA[V 釜 ]]> <![CDATA[V r ]]> <![CDATA[V d ]]> <![CDATA[V PVT ]]> value 6.15mL 5.5mL 0.67MPa 670mL 124.78mL 58mL 63.425mL

[0205] The gas in the intermediate container 30 is pre-pressurized to 5.00 MPa by using the injection pump 31. After the pressurization is completed, the second valve 29 is opened to quickly inject the gas into the PVT cylinder 10 and pressurize it to 5.00 MPa;

[0206] S7, the instrument is heated up, the temperature of the PVT cylinder 10 is set to 30°C using the touch screen 2, the rotation button is turned on, and the automatic rotation angle range is set to 0-120°, so that the fluid in the cylinder is fully mixed;

[0207] S8, phase state experiment, taking the constant mass expansion experiment as an example, after the temperature in the PVT cylinder 10 reaches 30°C and stabilizes, set a constant pressure of 16MPa for injection, record the volume of the PVT cylinder 10 after the pressure stabilizes, then reduce the pressure by 0.5MPa and record the volume, when the pressure is 5.00MPa, the PVT cylinder 10 reaches the maximum volume, and this group of experiments is completed. In addition, when each system is stable, adjust the rotation angle of the PVT cylinder 10 to 100° to shoot the fluid interface;

[0208] S9, adjust the temperature. After the experiment at 30°C is completed, adjust the experimental temperature to 70, 120, 160, 200 and 230°C respectively for experiments. Repeat steps S7-S8 to obtain experimental values ​​and images at different temperatures. The fluid images of hydrocarbon substances at 30°C under pressures of 5.00 MPa and 10.00 MPa are as follows: Figure 4 As shown;

[0209] S10, instrument cleaning and data processing. After the experiments at 5 temperatures are completed, turn off the heating button, adjust the angle of the PVT cylinder 10 to reset it, and drain the experimental fluid after the temperature drops to room temperature. Disassemble the PVT cylinder 10 for cleaning and drying, replace the graphite ring 8 and check whether other parts are damaged. After cleaning and replacement, install the instrument and wait for the next experiment. According to the constant mass expansion experiment at 5 temperatures, a series of pressure and volume values ​​are obtained, and a PV relationship diagram is drawn. The curve can be fitted into two intersecting straight lines. The curve at 120°C is as follows: Figure 2 As shown, the intersection point is the bubble point pressure of the hydrocarbon material at this temperature. The fluid phase diagram is drawn based on the five bubble point pressures as shown in Figure 3 shown.

[0210] It should be noted that the specific models and specifications of the injection pump 31, the intermediate container 30, the pyrolysis reactor 33, the temperature sensor 15, the pressure sensor 16, the microscope 4 and the computer 3 need to be selected and determined according to the actual specifications of the device, etc. The specific selection and calculation method adopts the existing technology in the field, so it will not be described in detail.

[0211] Specifically, the principles of the present invention mainly include the following aspects:

[0212] 1. Basic principles of shale in-situ conversion

[0213] The present invention measures phase parameters in the in-situ conversion process in shale oil and gas development. Organic matter (mainly kerogen) in shale undergoes pyrolysis reaction under high temperature conditions, converting macromolecular organic matter into small molecular hydrocarbons. The phase characteristics of hydrocarbon substances produced in this process have an important influence on the development effect. Factors such as temperature, pressure, pore structure, etc. in the in-situ conversion process will affect the phase characteristics of the product.

[0214] 2. Core design principles of the experimental system

[0215] High temperature and high pressure environment simulation: Using a special PVT cylinder and sealing system (sapphire glass window, graphite ring, copper sleeve, etc.), it can withstand high temperature of 300℃ and high pressure of 25MPa, far exceeding the 200℃ limit of traditional rubber ring seals.

[0216] Simulation of nanopore effect: Shale samples with different pore structure characteristics can be placed in the PVT cylinder to simulate the influence of nanoscale confined space on the fluid phase state.

[0217] Multiphase mixing system: The angle adjustment system (-120°~120°) is used to achieve full mixing of the fluid and ensure the accuracy of the test results.

[0218] Real-time observation system: Real-time observation and recording of fluid phase changes are achieved through a microscope and a visual window.

[0219] 3. Measurement principle

[0220] Constant mass expansion method: By controlling the system temperature, changing the piston position to adjust the volume, and recording the pressure changes, the PV relationship curve is obtained, and then the bubble point pressure is obtained.

[0221] Phase transition point determination: Determine the dew point pressure by observing the changes in the liquid-gas interface.

[0222] Calculation of thermal physical parameters: Calculate thermal expansion coefficient, compression coefficient and other parameters based on PVT data at different temperatures and pressures.

[0223] 4. Innovative technical principles

[0224] Comprehensive environmental simulation: The effects of temperature, pressure, pore structure, heating medium (water, nitrogen, carbon dioxide, etc.) and organic matter can be considered simultaneously.

[0225] In-situ product testing: The pyrolysis reactor is directly connected to the PVT cylinder to achieve instant phase testing of the pyrolysis products.

[0226] Integrated control: integrated control and data collection of temperature, pressure, volume, angle and other parameters.

[0227] This system breaks through the temperature limit of traditional phase state testing through innovative design principles, and realizes a more comprehensive simulation and characterization of the in-situ conversion process of shale. Its core lies in the ability to consider multiple influencing factors at the same time under high temperature and high pressure conditions to obtain phase state parameter data that is closer to actual development conditions. The modular design and integrated control of the system ensure the reliability and convenience of the testing process, and provide an important theoretical basis for the in-situ conversion development of shale oil and gas.

[0228] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A system for measuring phase parameters of hydrocarbon substances in situ converted from shale in different formation environments, characterized in that: The invention comprises a shale pyrolysis and product injection system, a PVT experiment and heating system, a drive and rotation system, an integrated control system, and a microscopic observation and data acquisition system. The shale pyrolysis and product injection system comprises a pyrolysis reactor, a conical flask, an injection pump, an intermediate container, a first valve, a metal pipeline, a measuring cylinder, and a second valve. The outlet end of the pyrolysis reactor is connected to the conical flask and the intermediate container in sequence through pipelines, which are used to collect pyrolysis oil and store pyrolysis gas respectively. The output end of the intermediate container is connected to the second valve, the vacuum pump, the first valve, and the PVT cylinder in sequence through a metal pipeline. The pyrolysis oil from the conical flask is placed in the measuring cylinder and connected to the PVT cylinder; the PVT experiment and heating system includes a PVT cylinder, a heating sleeve, a graphite ring, a copper sleeve, a visual glass window, a cylinder cover, a plunger and a plunger seal. The PVT cylinder and the visual glass window are sealed in turn by a graphite ring and a copper sleeve. The PVT cylinder is used to place shale cores to provide a reservoir environment for phase state experiments. The other end of the PVT cylinder is blocked by a plunger and sealed by a plunger seal. The PVT cylinder is wrapped by a heating sleeve for heating and is connected to an integrated control cabinet via a data cable. The drive and rotation The system includes a fixed platform, a rotating rod, an angle adjustment system, a driving column, a driver, a transmission, a support frame and a movable base. The fixed platform is connected to the outside of the PVT cylinder and is connected to the angle adjustment system through the rotating rod to control the rotation angle of the PVT cylinder. The fixed platform is connected to the driver through the driving column to control the movement of the plunger. The driver is equipped with a transmission to control the movement speed of the plunger. The driver and the angle adjustment system are both connected to an integrated control cabinet; the integrated control system includes an integrated control cabinet, a touch screen, a temperature sensor and a pressure sensor. The integrated control cabinet is connected to the inner cavity of the PVT cylinder through the temperature sensor and the pressure sensor respectively to test the temperature and pressure. The integrated control cabinet is connected to a computer, and both are used to control the experimental conditions of the PVT cylinder; the microscopic observation and image acquisition system includes a microscope, a microscope adjustment frame and a computer. The microscope is fixed on the fixed platform through the microscope adjustment frame, and the microscope is connected to the computer through a data cable. The computer is installed with image acquisition and analysis software, temperature and pressure data recording software and control cabinet synchronization control software; wherein the inner diameter of the PVT cylinder is 21 mm, and the maximum cylinder depth is 216.5 mm, and core models with different characteristics are placed in the cylinder to study the influence of rock pore structure and mineral composition on phase state; the visual glass window and the PVT cylinder are sealed by a graphite ring and a copper sleeve. The material of the visual glass window is sapphire and the shape is cylindrical. After sealing, the maximum pressure resistance is 25 MPa and the maximum temperature resistance is 300°C; the angle adjustment system is connected to the fixed platform, and the angle information is transmitted through the grating. It is used to mix the fluid and adjust the fluid angle, realize angle positioning and automatic rotation, and the rotation angle range is -120°~120°; the pyrolysis reactor is used to obtain hydrocarbon products under different heating conditions, and the maximum experimental temperature is 600°C and the maximum pressure is 40 MPa, the product release end is directly connected to the PVT cylinder through a pipeline and a second valve, which is used to directly collect the pyrolysis products and perform phase parameter testing; the pyrolysis reactor and the PVT cylinder are both used to inject heating medium to study the phase characteristic parameters of hydrocarbon substances under the action of the heating medium; the integrated control cabinet is connected to the heating jacket, temperature sensor, pressure sensor, angle adjustment system and driver, and real-time acquisition and control of the pressure, temperature, volume, angle and driving plunger speed in the PVT cylinder;. Wherein, the image acquisition and analysis software includes the following modules: Image acquisition module: controls the microscope to capture images of the fluid state in the PVT cylinder in real time; Image preprocessing module: performs noise reduction and enhancement processing on the collected original images; Phase recognition module: identifies the gas, liquid and solid phase areas in the image; Interface tracking module: track and measure the position and shape changes of the phase interface; Particle size analysis module: measure the size distribution of droplets or bubbles; Flow visualization module: analyze the flow pattern of fluid through continuous images; Data storage module: save images and analysis results in a retrievable format; The interface tracking module performs the following steps: S11, obtaining the original image data collected by the microscope and performing image preprocessing; S12, using the improved Canny algorithm to perform edge detection on the preprocessed image; S13, extracting the interface contour using an active contour model according to the edge detection result; S14, calculating the interface position change between adjacent frames using an optical flow algorithm; S15, using Kalman filter to predict the interface motion trajectory; S16, recording interface position and shape parameters; Specifically: The specific implementation of step S11 is to collect image sequences through a microscope CCD camera with a sampling frequency of 30 frames per second; Gaussian filtering is performed on the acquired original image to eliminate noise, and the filter kernel size is , standard deviation ; Then histogram equalization is performed to enhance the image contrast, and finally median filtering is used to remove salt and pepper noise; grayscale image processing is used for image preprocessing, and the pixel value range is ; The grayscale difference threshold between adjacent pixels is set to 12, and pixels below this threshold are considered to belong to the same area; The specific implementation method of step S12 is to use the improved Canny operator to perform edge detection; first calculate the image gradient, assuming that the image At the point The gradient size at is and direction : , ;in and are the first-order partial derivatives in the x and y directions respectively; an adaptive double threshold method is used for edge connection, with a high threshold Take the 85th percentile of the image gradient magnitude and the low threshold ; The specific implementation method of step S13 is to extract the interface contour based on the geometric active contour model; define the level set function , the interface consists of a zero level set Expressed; the evolution equation is: ,in Stop function for edge: , is the curvature: , is the bubble expansion coefficient, which is set to 1.5; the iteration step is 0.1, and the maximum number of iterations is 200; The specific implementation of step S14 is to use the Lucas-Kanade optical flow method to calculate the interface motion; is a point in the image sequence at time The gray value of , assuming that the gray value remains unchanged in a small time interval: ; Expand to get the optical flow equation: ,in , is the velocity component to be determined, , , are the spatial and temporal partial derivatives of the image respectively; The velocity field is obtained by solving the least squares problem with the window of The specific implementation of step S15 is to use a Kalman filter to predict the interface motion trajectory; the state vector is the position and velocity of the interface feature point: ; State transfer equation: ,in is the state transfer matrix, is the process noise, the covariance matrix ; Measurement equation: ,in is the measurement matrix, is the measurement noise, the covariance matrix ; The specific implementation of step S16 is to record the geometric characteristic parameters of the interface contour; including the interface perimeter : ,area : , roundness : , and the barycentric coordinates : , ; The particle size analysis module performs the following steps: S21, collecting microscopic images and performing spatial calibration; S22, detecting circular droplets using improved Hough transform; S23, using watershed algorithm to process adhesion droplet segmentation; S24, calculating the area and perimeter of each droplet; S25, establishing a mapping relationship between pixel size and actual size; S26, calculating the droplet roundness and shape coefficient; S27, generating particle size distribution statistics; Specifically: The specific implementation of step S21 is to perform spatial calibration according to a standard ruler; place a standard ruler in the microscope field of view, calculate the corresponding relationship between the number of pixels and the actual length, and obtain the proportionality coefficient The image resolution is Pixels, field of view Micrometer, the spatial resolution is 0.42 micrometer / pixel; bilinear interpolation is used to resample the image to ensure processing accuracy; The specific implementation of step S22 is to use the improved Hough transform to detect circular droplets; in the parameter space, the circle is represented by the center coordinates and radius express: ; To improve computational efficiency, first use the gradient information to determine the search range; set the minimum radius Pixels, maximum radius pixels; the accumulator threshold is set to 15% of the image height, and circles with votes greater than this threshold are considered valid droplets; The specific implementation method of step S23 is to use the watershed algorithm to segment the adhesion droplets; firstly, the Euclidean distance transform is calculated to obtain the distance map , then find the local maximum as the mark point; take the negative value of the distance map and submerge the mark point; set the submerged height to , then at time The flooded area at the moment is: ; When two flooded areas meet, a watershed is established at the junction; the height threshold of the watershed line is set to 60% of the maximum distance value; The specific implementation of step S24 is to calculate the area and perimeter of each segmented region; the area is obtained by pixel counting: ,in is the number of pixels in the area, is the spatial resolution; the perimeter is calculated using a boundary tracing algorithm: ,in is the number of boundary pixels; to improve accuracy, sub-pixel edge detection is used for the boundary, the minimum resolvable area is 25 pixels, and the minimum resolvable perimeter is 18 pixels; The specific implementation of step S25 is to establish a mapping relationship between the pixel size and the actual size; taking into account the optical distortion, a quadratic polynomial is used for correction: , ,in are the distorted image coordinates, is the corrected coordinate, , and is the distortion coefficient, obtained by calibration with the calibration plate; The specific implementation of step S26 is to calculate the drop shape parameters; the roundness is defined as: , when the perfect circle ; The shape factor is defined as: ,in is the maximum Feyre diameter; when the droplet deviates from the circular shape, the shape factor threshold is set to 0.85, and the droplet below this value is marked as non-spherical; the flattening is defined as the ratio of the major axis to the minor axis, and the threshold is set to 1.2; The specific implementation of step S27 is to generate particle size distribution statistics; using the equal-proportional logarithmic grouping method, the group interval ratio is ; Calculate the number distribution function and volume distribution function : , ,in For the Number of droplets in a group, is the total number of droplets, is the total volume, is the group median diameter; calculate the characteristic diameter : .

2. The system for measuring phase parameters of hydrocarbon substances in situ converted from shale in different formation environments according to claim 1 is characterized in that: The temperature and pressure data recording software includes the following modules: Data acquisition module: collects data from temperature sensors and pressure sensors in real time; Data display module: real-time display of temperature and pressure changes in the form of charts; Data calibration module: calibrate and correct sensor data; Alarm module: issues an alarm when the temperature or pressure exceeds the preset range; Data storage module: save temperature and pressure data in the form of time series; Data analysis module: calculate the statistics of mean and standard deviation; Data export module: export data to Excel format for further analysis; Historical query module: view and compare temperature and pressure data of different time periods.

3. The system for measuring phase parameters of hydrocarbon substances in situ converted from shale in different formation environments according to claim 2 is characterized in that: The control cabinet synchronous control software includes the following modules: Temperature control module: set and adjust the heating temperature of the PVT cylinder; Pressure control module: adjusts the pressure inside the PVT cylinder by controlling the plunger; Angle control module: set and adjust the rotation angle of the PVT cylinder; Drive control module: controls the speed and displacement of the drive; Parameter synchronization module: ensure parameter synchronization and coordination among systems; Remote control module: allows remote control of devices via the network; System diagnosis module: monitors the equipment operation status and provides fault diagnosis; Data integration module: integrates temperature, pressure and image data and stores them.

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