A high-temperature, high-pressure CO2 huff and puff test apparatus and method for full-diameter shale formation

Abstract

The application relates to the technical field of oil and gas field development, in particular to a full-diameter shale high-temperature high-pressure CO2 throughput experimental device and method, which comprises the following steps: acquiring monitoring data of each monitoring parameter corresponding to each sampling point in a CO2 reaction kettle in a well-sealing reaction process at each moment in real time; determining an instantaneous difference amount of each monitoring parameter at each moment; obtaining a trend deviation amount, a continuous deviation coefficient, a continuous characteristic difference degree and a deviation response coefficient of any monitoring parameter corresponding to each sampling point at each monitoring period; determining an error coefficient; and controlling each monitoring parameter in the CO2 reaction kettle in real time. According to the application, each monitoring parameter in the CO2 reaction kettle can be kept in a stable state, chemical reactions and fluid properties in the CO2 oil displacement process are ensured from being affected by changes of each monitoring parameter in the CO2 reaction kettle, and the accuracy and reliability of experimental results in the CO2 oil displacement experiment process are improved.

Description

Technical Field

[0001] This application relates to the field of oil and gas field development technology, specifically to a full-diameter shale high-temperature and high-pressure CO2 huff and puff experimental device and method. Background Technology

[0002] Due to the high mud content of shale, drilling small-pump cores from full-diameter shale cores is extremely difficult. The small-pump cores are prone to breakage during drilling, making it difficult to obtain cores suitable for scientific research and production. This severely hinders the advancement of CO2 flooding technology in shale core experimental research. Secondly, drilling small-pump cores from frozen, pressurized, sealed full-diameter cores is a lengthy process, requiring the cores to be brought back to room temperature before drilling can begin. During this time, some light components in the core are lost, failing to maintain the original oil and gas composition of the reservoir, thus reducing the accuracy of experimental data related to CO2 flooding technology. Therefore, using small-pump cores for high-temperature, high-pressure CO2 huff and puff experiments in CO2 flooding technology cannot meet the demands of scientific research and production for accurate data and effective experimental results. There is a need to develop a CO2 huff and puff testing device for full-diameter shale cores to improve the experimental level and data reliability of CO2 flooding technology in shale core research.

[0003] In existing technologies, CO2 huff and puff experiments are conducted using small plunger shale cores. However, this process can easily lead to core breakage and insufficient volatilization of light components within the core during the core drilling process. Therefore, by placing cryogenically sealed cores directly into a high-temperature, high-pressure CO2-resistant reactor, it is possible to conduct experiments without drilling small plunger cores from a full-diameter core. However, the chemical reactions and fluid properties during the CO2 flooding process are affected by the temperature and pressure changes within the CO2 reactor, which can impact the oil removal efficiency of the CO2 flooding technology and thus affect the accuracy and reliability of the experimental results. Summary of the Invention

[0004] To address the aforementioned technical problems, a high-temperature, high-pressure CO2 huff and puff test apparatus and method for full-diameter shale is provided to solve the existing issues.

[0005] The solution to the technical problem presented in this application is to provide a high-temperature, high-pressure CO2 huff and puff test apparatus and method for full-diameter shale formation, comprising the following steps:

[0006] In a first aspect, embodiments of this application provide a method for high-temperature and high-pressure CO2 huff and puff testing of full-diameter shale, the method comprising the following steps:

[0007] Real-time acquisition of monitoring data for each monitoring parameter at each sampling point inside the CO2 reactor during the well-sealing reaction process;

[0008] Analyze the differences in monitoring data of all sampling points at each time point under each monitoring parameter and the remaining time points to determine the instantaneous difference of each monitoring parameter at each time point; based on the instantaneous difference, divide all time points corresponding to each monitoring parameter into multiple monitoring periods;

[0009] By analyzing the trend changes of all monitoring data for any monitoring parameter corresponding to each sampling point during each monitoring period, and the trend changes of all instantaneous differences of the monitoring parameter during each monitoring period, the trend deviation of the monitoring parameter corresponding to each sampling point during each monitoring period can be obtained.

[0010] Analyze the monitoring data of each sampling point and the other sampling points for any one of the monitoring parameters in each monitoring period, as well as the differences in the trend deviation; determine the continuous deviation coefficient of the monitoring parameter corresponding to each sampling point in each monitoring period; and combine the trend deviation and the continuous deviation coefficient to determine the continuous characteristic difference degree of the monitoring parameter corresponding to each sampling point in each monitoring period.

[0011] Based on the difference in the degree of continuous characteristic difference of any monitoring parameter corresponding to each sampling point between each monitoring period and other monitoring periods, the deviation response coefficient of any monitoring parameter corresponding to each sampling point in each monitoring period is determined.

[0012] Based on the monitoring data of any monitoring parameter corresponding to different sampling points at the current time, and the deviation response coefficient of the monitoring period to which the current time belongs, the error coefficient of any monitoring parameter at the current time is determined, and in conjunction with the controller, each monitoring parameter in the CO2 reactor is controlled in real time.

[0013] Preferably, the monitoring parameters include temperature and pressure.

[0014] Preferably, the instantaneous difference of each monitoring parameter at each time is the average of the differences between the monitoring data of all sampling points at each time and the monitoring data of all sampling points at all other times for each monitoring parameter.

[0015] Preferably, the step of dividing all times corresponding to each monitoring parameter into multiple monitoring time periods includes:

[0016] Obtain the extreme points of the instantaneous difference of each monitoring parameter at all times, and use the extreme points as dividing points to divide all times corresponding to each monitoring parameter into multiple monitoring periods.

[0017] Preferably, determining the trend deviation of any monitoring parameter corresponding to each sampling point in each monitoring period includes:

[0018] Calculate the trend statistics of the monitoring data of any monitoring parameter corresponding to each sampling point at all times in each monitoring period, and denot it as the first trend quantity;

[0019] Calculate the trend statistic of the instantaneous difference of any monitoring parameter at all times within each monitoring period, and denot it as the second trend quantity;

[0020] The difference between the first trend quantity and the second trend quantity is used as the trend deviation of any monitoring parameter corresponding to each sampling point in each monitoring period.

[0021] Preferably, obtaining the continuous deviation coefficient of any monitoring parameter corresponding to each sampling point in each monitoring period includes:

[0022] The difference between the monitoring data of any one monitoring parameter corresponding to each sampling point at all times in each monitoring period and the monitoring data of any one monitoring parameter corresponding to the other sampling points at all times in the same monitoring period is denoted as the first difference.

[0023] The difference in the trend deviation between any monitoring parameter corresponding to each sampling point in each monitoring period and any monitoring parameter corresponding to the other sampling points in the same monitoring period is denoted as the second difference;

[0024] Calculate the product of the first difference and the second difference, and take the mean of the product between each sampling point and all other sampling points for each monitoring parameter in each monitoring period as the continuous deviation coefficient of the monitoring parameter corresponding to each sampling point in each monitoring period.

[0025] Preferably, the degree of continuous characteristic difference of any monitoring parameter corresponding to each sampling point in each monitoring period is the product of the trend deviation and the continuous deviation coefficient.

[0026] Preferably, the deviation response coefficient of the monitoring parameter corresponding to each sampling point in each monitoring period is the normalized result of the mean of the difference in the degree of difference of the continuous characteristics between the monitoring parameter corresponding to each sampling point in each monitoring period and all other monitoring periods.

[0027] Preferably, the error coefficient ρ of the r-th monitoring parameter at the current time t is... r,t The calculation method is as follows: Among them, v n,r,t Let g be the deviation response coefficient of the r-th monitoring parameter corresponding to the n-th sampling point at the current time t within the monitoring period. n,r,t G represents the monitoring data of the r-th monitoring parameter corresponding to the n-th sampling point at the current time t. rLet be the preset standard value corresponding to the r-th monitoring parameter, and N be the number of all sampling points.

[0028] Preferably, the real-time control of each monitoring parameter in the CO2 reactor includes: based on the error coefficient, controlling each monitoring parameter in the CO2 reactor in real time via a PLC controller.

[0029] Secondly, this application also provides a full-diameter shale high-temperature and high-pressure CO2 huff and puff experimental device. The experimental device is implemented based on the steps of any of the above-described methods for a full-diameter shale high-temperature and high-pressure CO2 huff and puff experimental device. The experimental device includes an air compressor, a gas booster pump, an injection pump, a first piston container, a second piston container, a constant temperature chamber, a data recording system, a first high-definition camera, a high-temperature and high-pressure CO2 resistant reactor, a back pressure valve, a hand-cranked pump, a second high-definition camera, a metering tube, a gas flow meter, a gas chromatograph, a vacuum system, pressure and temperature sensors, a first backplate light source, a second backplate light source, and valves.

[0030] Preferably, the high-temperature and high-pressure CO2 resistant reactor includes an outlet plug, a viewing window, a metering glass tube, a glass collection funnel, a rock sample, a pressure-resistant reactor body, a magnetic stirrer, a quick-release half-ring, a lower plug, a stirring motor, a viewing window pressure plate, a lower oil drain hole, an upper plug, and an upper oil drain hole.

[0031] Preferably, the quick-opening locking half-ring includes a left locking half-ring, a rotating fixing bracket, a right locking half-ring, a pressure-resistant vessel body, a locking half-ring rotating shaft, a safety lock, and a handle.

[0032] This application has at least the following beneficial effects:

[0033] This application analyzes the differences in monitoring data from all sampling points at each time step and other times for each monitoring parameter, determining the instantaneous difference of each monitoring parameter at each time step. Its beneficial effect lies in considering the fluctuations of each monitoring parameter at different times, reflecting the fluctuations in temperature and pressure within the CO2 reactor. Based on the instantaneous difference, all times corresponding to each monitoring parameter are divided into multiple monitoring periods. By analyzing the trend changes of all monitoring data for each monitoring parameter at each sampling point within each monitoring period, and the trend changes of all instantaneous differences for each monitoring parameter within each monitoring period, the trend deviation of each monitoring parameter at each sampling point within each monitoring period is obtained. Its beneficial effect lies in analyzing the differences in the changing trends of each monitoring parameter across different monitoring periods, reflecting the degree of deviation in different monitoring periods, and thus explaining the significance of the continuous deviation response trend within different monitoring periods during the well-sealing reaction process, and the possibility of feedback difference deviations occurring during the control of each monitoring parameter. The analysis also examines the monitoring data between each sampling point and other sampling points within each monitoring period for each monitoring parameter, as well as the trend deviation. The method involves determining the continuous deviation coefficient of each monitoring parameter at each sampling point during each monitoring period. This is beneficial because it addresses the continuous deviation of the same monitoring parameter between different sampling points within the same monitoring period. By integrating the trend deviation and the continuous deviation coefficient, the continuous characteristic difference of each monitoring parameter at each sampling point during each monitoring period is determined. This is beneficial because it considers the degree of continuous deviation response of each monitoring parameter at different sampling points during the CO2 reactor's well-sealing reaction process. Based on the difference in the continuous characteristic difference between each monitoring parameter at each sampling point and other monitoring periods, the deviation response coefficient of each monitoring parameter at each sampling point during each monitoring period is determined. This is beneficial because it analyzes the differences in continuous deviation characteristics between different monitoring periods, illustrating the degree of difference in deviation response at different monitoring periods under the same sampling point, reflecting the possibility of continuous deviation of each monitoring parameter under fluctuations during each monitoring period, and the accuracy of the error response of each sampling point's location to fluctuations of each monitoring parameter within the CO2 reactor.Based on the monitoring data of any monitoring parameter corresponding to different sampling points at the current moment, and the deviation response coefficient of the monitoring period to which the current moment belongs, the error coefficient of any monitoring parameter at the current moment is determined. Real-time control of each monitoring parameter within the CO2 reactor is then implemented. The beneficial effect lies in considering the deviation response of each monitoring parameter at each sampling point, and the difference between the current monitoring data and the preset standard value. This clarifies the error situation of each monitoring parameter within the CO2 reactor, enabling real-time control and adjustment of each parameter. This ensures that each monitoring parameter within the CO2 reactor remains stable, guaranteeing that the chemical reaction and fluid properties during CO2 flooding are not disturbed by temperature and pressure changes. This effectively improves the contact and interaction between shale and the experimental medium within the reactor, and also provides reliable experimental conditions for accurately evaluating the CO2 flooding effect. This effectively improves the accuracy and reliability of experimental results in the research and application of CO2 flooding technology. Attached Figure Description

[0034] The following is a detailed description of a high-temperature, high-pressure CO2 huff and puff test method for full-diameter shale, based on the accompanying drawings.

[0035] Figure 1 An experimental apparatus for high-temperature and high-pressure CO2 huff and puff testing of full-diameter shale rocks, provided in this application embodiment;

[0036] Figure 2 This is a schematic diagram of the structure of the high-temperature and high-pressure CO2-resistant reactor provided in the embodiments of this application;

[0037] Figure 3 This is a schematic diagram of the structure of the quick-opening card semi-ring provided in the embodiments of this application;

[0038] Figure 4 A flowchart illustrating the steps of a method for controlling temperature and pressure in a high-temperature, high-pressure CO2-resistant reactor provided in this application embodiment;

[0039] Figure 5 A flowchart illustrating the steps of a method for obtaining the trend deviation of each monitoring parameter corresponding to each sampling point during each monitoring period, as provided in the embodiments of this application.

[0040] Figure 6 A flowchart illustrating the steps of a method for obtaining the continuous characteristic difference of any monitoring parameter corresponding to each sampling point in each monitoring period, as provided in the embodiments of this application. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description, in conjunction with the accompanying drawings and embodiments, provides a comprehensive explanation of the experimental apparatus and method for high-temperature, high-pressure CO2 huff and puff testing of full-diameter shale. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0042] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0043] This application provides a full-diameter shale high-temperature and high-pressure CO2 huff and puff experimental device, the schematic diagram of which is shown below. Figure 1 As shown, 1 is an air compressor, 2 is a gas booster pump, 3 is an injection pump, 4 is a first piston container, 5 is a second piston container, 6 is a constant temperature chamber, 7 is a data recording system, 8 is a first high-definition camera, 9 is a high-temperature and high-pressure CO2-resistant reactor, 10 is a back pressure valve, 11 is a hand-cranked pump, 12 is a second high-definition camera, 13 is a metering tube, 14 is a gas flow meter, 15 is a gas chromatograph, 16 is a vacuum system, 17 is a pressure and temperature sensor, 18 is a first backplane light source, 19 is a second backplane light source, and V1-V9 are all valves.

[0044] A schematic diagram of the high-temperature, high-pressure, CO2-resistant reactor is shown below. Figure 2 As shown, 20 is the outlet plug, 21 is the viewing window glass, 22 is the metering glass tube, 23 is the glass collection funnel, 24 is the rock sample, 25 is the pressure vessel body, 26 is the magnetic stirring paddle, 27 is the quick-opening half-ring, 28 is the lower plug, 29 is the stirring motor, 30 is the viewing window glass pressure plate, 31 is the lower oil drain hole, 32 is the upper plug, and 33 is the upper oil drain hole;

[0045] The structural diagram of the quick-opening card semi-ring is shown below. Figure 3 As shown, 34 is the left locking half ring, 35 is the rotating fixed bracket, 36 is the right locking half ring, 37 is the pressure vessel body, 38 is the locking half ring rotating shaft, 39 is the safety lock, and 40 is the handle.

[0046] The full-diameter shale high-temperature and high-pressure CO2-resistant experimental device uses a magnetic stirring paddle to rapidly stir the oil adsorbed on the surface of the full-diameter core, allowing the separated crude oil to enter the metering glass tube through a glass collection funnel. Furthermore, the dynamic changes in oil and water production can be observed and automatically recorded in real time through the viewing window and a high-definition camera.

[0047] The high-definition camera is positioned opposite a backlight panel for clear observation of the metering tube's scale. Pressure and temperature sensors automatically record temperature and pressure data within the high-temperature, high-pressure CO2-resistant reactor, enabling real-time monitoring and control of temperature and pressure changes. Furthermore, the experimental setup automatically records the cumulative gas production using a wet flow meter. The maximum experimental temperature is 150°C, and the maximum experimental pressure is 70 MPa. It can be used for high-temperature, high-pressure huff and puff experiments with gaseous media such as methane and carbon dioxide, as well as liquid media such as slickwater and fracturing fluid. If the huff and puff medium is gaseous, the core product is discharged from the lower oil drain port of the high-temperature, high-pressure CO2-resistant reactor; if the huff and puff medium is liquid, the core product is discharged from the upper oil drain port of the reactor.

[0048] Based on the same inventive concept as the above method, this application also provides a method for high-temperature and high-pressure CO2 huff and puff testing of full-diameter shale, the operation flow of which is as follows:

[0049] (1) Measure the weight of the full-diameter shale and test the nuclear magnetic resonance T2 spectrum of the full-diameter shale;

[0050] (2) Open the quick-release half ring of the high-temperature and high-pressure CO2 resistant reactor, and slowly lower the lower plug to a certain height using the stirring motor, and place the full-diameter core on the magnetic stirring paddle; in this embodiment, the lower plug is slowly lowered to a height of 25cm. As for other implementation methods, the implementer can set it according to the experimental requirements.

[0051] (3) The core is fed into the reactor body by the motor, the quick-opening half ring of the high temperature and high pressure CO2 resistant reactor is closed, and the quick-opening half ring of the high temperature and high pressure CO2 resistant reactor is locked with the safety lock.

[0052] (4) Close valves V1, V3, V4, V5, and V6, and open valves V2, V7, and V9. Use a vacuum system to evacuate the high-temperature and high-pressure CO2 resistant reactor and the first piston container.

[0053] (5) Close valves V9 and V2, open valve V1, use an air compressor to inject the experimental gas medium into the first piston container, and quickly pressurize it to the predetermined experimental pressure. In this embodiment, the predetermined experimental pressure is 40MPa. As other implementation methods, the implementer can set it according to the experimental requirements.

[0054] (6) Close valve V1, open valve V4, set the injection pump to constant pressure mode, and set the injection pressure to the experimental pressure. In this embodiment, the experimental pressure is set to 40MPa. As other implementation methods, the implementer can set it according to the experimental requirements. Set the temperature of the constant temperature chamber and the temperature of the high temperature and high pressure CO2 resistant reactor to the experimental temperature. In this embodiment, the experimental temperature is set to 110℃. As other implementation methods, the implementer can set it according to the experimental requirements.

[0055] (7) Open valves V2 and V7 to inject the gas medium in the first piston container into the high temperature and high pressure CO2 resistant reactor at constant pressure; after injection, perform the well-sealing reaction.

[0056] (8) After the preset well shut-in time is reached, close valve V7 and open valve V8. Use a hand pump to control the back pressure valve to slowly discharge the oil and gas in the reactor. Record the cumulative oil production using a high-definition camera. Analyze the composition of the produced gas using gas chromatography. In this embodiment, the preset well shut-in time is 24 hours. As for other implementation methods, the implementer can set the time according to the experimental requirements.

[0057] (9) Take out the full-diameter shale from the high-temperature and high-pressure CO2 resistant reactor, measure the weight of the core, and test the core nuclear magnetic resonance T2 spectrum. The mobilization of shale oil in different pores can be judged by the changes in the T2 spectrum before and after the shale oil is spun out.

[0058] (10) Repeat steps (1)-(9) to perform multiple rounds of core loading and unloading.

[0059] In step (7), when the well is sealed, it is necessary to maintain the stability of the temperature and pressure of the high-temperature and high-pressure CO2 reactor. It is necessary to control the temperature and pressure in the high-temperature and high-pressure CO2 reactor in real time to ensure that the chemical reaction and fluid properties in the CO2 oil displacement process are not affected by the temperature and pressure changes, and at the same time provide reliable experimental conditions for accurately evaluating the oil displacement effect.

[0060] To better control the temperature and pressure of the high-temperature, high-pressure CO2-resistant reactor, temperature and pressure data are monitored in real time using pressure and temperature sensors, allowing for adjustment of the reactor's temperature and pressure. The flowchart of the temperature and pressure control method in the high-temperature, high-pressure CO2-resistant reactor provided in this embodiment is shown below. Figure 4 As shown, it specifically includes:

[0061] Step 1: Real-time acquisition of monitoring data for each monitoring parameter at each sampling point inside the CO2 reactor during the well-sealing reaction process.

[0062] After the gas medium in the first piston container is injected into the high-temperature and high-pressure CO2 reactor, the temperature data inside the CO2 reactor is collected in real time by a temperature sensor and the pressure data inside the CO2 reactor is collected in real time by a pressure sensor under the set experimental pressure and temperature. Specifically, a sensor group consisting of one temperature sensor and one pressure sensor is used. Multiple locations are evenly selected from top to bottom inside the CO2 reactor as sampling points. Multiple sensor groups are installed at different sampling points inside the CO2 reactor to collect the temperature and pressure data of each sampling point inside the CO2 reactor at various times during the sealing process. The collected data is then filtered to remove noise.

[0063] In this embodiment, six locations are selected as sampling points inside the CO2 reactor. Three sensor groups are installed on each side of the CO2 reactor. As for other implementation methods, the implementer can set them according to the actual situation. Secondly, a Wiener filter is used for filtering. The Wiener filter is a well-known technology and will not be described in detail here. As for other implementation methods, the implementer can use other methods of the prior art, such as mean filtering algorithms. This embodiment does not impose any special restrictions on this.

[0064] Therefore, the monitoring data of each monitoring parameter at each sampling point in the CO2 reactor during the well sealing process are obtained at each time point. Each monitoring parameter includes temperature and pressure.

[0065] In this embodiment, all sensor groups collect data synchronously at a time interval of 2 seconds. As for other implementation methods, the implementer can set the time interval according to the actual situation.

[0066] Thus, the monitoring data of each monitoring parameter at each sampling point inside the CO2 reactor during the well sealing process were obtained at each time point.

[0067] Step 2: Analyze the differences in monitoring data of all sampling points at each time point under each monitoring parameter and the remaining time points to determine the instantaneous difference of each monitoring parameter at each time point; based on the instantaneous difference, divide all time points corresponding to each monitoring parameter into multiple monitoring periods; by the trend changes of all monitoring data of any monitoring parameter corresponding to each sampling point in each monitoring period, and the trend changes of all instantaneous differences of any monitoring parameter in each monitoring period, obtain the trend deviation of any monitoring parameter corresponding to each sampling point in each monitoring period.

[0068] During experiments in a high-temperature, high-pressure CO2 reactor, after the gas medium is injected, it is crucial to ensure that the temperature and pressure within the reactor remain precisely constant at the set values. Temperature fluctuations can cause uneven changes in the internal structure of the shale, interfering with the adsorption, desorption, and percolation processes of the experimental medium within the shale pores, ultimately leading to deviations in the experimental results. Pressure fluctuations, on the other hand, can alter the flow state of the experimental medium, affecting its contact efficiency and interaction with the shale. Therefore, during the initial shut-in phase of the CO2 reactor, real-time control based on collected monitoring data is essential.

[0069] Secondly, during the experimental stage of the closed-well reaction in the CO2 reactor, changes in the stability of the external environment, the internal thermal effect of the CO2 reactor, and the state of the gas medium all induce fluctuations in temperature and pressure. These fluctuations affect the pore structure of shale, causing changes in the adsorption, desorption, and permeation states of the shale pores. Because the reaction equilibrium between shale and the gas medium is disrupted, the temperature changes during the monitoring period of the CO2 reactor exhibit regional continuous fluctuations.

[0070] Based on the above analysis, by monitoring the changes in reaction conditions caused by temperature and pressure fluctuations during the CO2 reactor monitoring process, the trend characteristics of continuous changes within the reactor are analyzed to determine the trend deviation. The flowchart of the method for obtaining the trend deviation of each monitoring parameter at each sampling point during each monitoring period, as provided in this application embodiment, is shown below. Figure 5 As shown, it specifically includes:

[0071] First, analyze the trend differences in monitoring data from sampling points at different times to determine the trend deviation, which reflects the occurrence of continuous deviation response trends in the monitored data. Specifically:

[0072] The mean of the differences between the monitoring data of all sampling points at each time point under each monitoring parameter and the monitoring data of all sampling points at all other times is taken as the instantaneous difference of each monitoring parameter at each time point.

[0073] In this embodiment, the average DTW distance between the monitoring data of all sampling points at each time under each monitoring parameter and the monitoring data of all sampling points at all other times is used as the instantaneous difference of each monitoring parameter at each time. The DTW distance is a well-known technology and will not be described in detail here. As other implementation methods, implementers may use other methods of the prior art, such as Manhattan distance, Euclidean distance, etc. This embodiment does not impose any special restrictions on this.

[0074] Obtain the extreme points of the instantaneous difference of each monitoring parameter at all times, and use the extreme points as dividing points to divide all times corresponding to each monitoring parameter into multiple monitoring periods;

[0075] In this embodiment, the extreme points of the instantaneous difference of each monitoring parameter at all times are obtained by the finite difference method. The finite difference method is a well-known technique and will not be described in detail here.

[0076] Calculate the trend statistics of the monitoring data of each monitoring parameter corresponding to each sampling point at all times in each monitoring period, and record it as the first trend quantity;

[0077] Calculate the trend statistic of the instantaneous difference of each monitoring parameter at all times within each monitoring period, and denote it as the second trend quantity;

[0078] In this embodiment, the Mann-Kendall trend test algorithm is used to calculate the trend statistics. The Mann-Kendall trend test algorithm is a well-known technology and will not be described in detail here.

[0079] The difference between the first trend quantity and the second trend quantity is used as the trend deviation of each monitoring parameter corresponding to each sampling point in each monitoring period.

[0080] It should be noted that the larger the trend deviation, the more significant the continuous deviation response trend is in different monitoring periods during the well closure reaction process, and the greater the possibility of feedback difference deviations occurring during the adjustment of monitoring parameters.

[0081] Thus, the trend deviation of each monitoring parameter corresponding to each sampling point in each monitoring period is obtained.

[0082] Step 3: Analyze the differences between the monitoring data of each sampling point and the other sampling points for each type of monitoring parameter in each monitoring period, as well as the differences in the trend deviation, and determine the continuous deviation coefficient of the monitoring parameter corresponding to each sampling point in each monitoring period; combine the trend deviation and the continuous deviation coefficient to determine the continuous characteristic difference degree of the monitoring parameter corresponding to each sampling point in each monitoring period.

[0083] Furthermore, the differences in monitoring data from different sampling points within the same monitoring period are analyzed, and the degree of continuous characteristic difference is determined in conjunction with the trend deviation. The flowchart of the method for obtaining the degree of continuous characteristic difference of any monitoring parameter corresponding to each sampling point in each monitoring period, as provided in this application embodiment, is shown below. Figure 6 As shown, it specifically includes:

[0084] The difference between the monitoring data of any monitoring parameter corresponding to each sampling point at all times in each monitoring period and the monitoring data of the same monitoring parameter corresponding to the other sampling points at all times in the same monitoring period is denoted as the first difference.

[0085] In this embodiment, the Hausdorff distance between the monitoring data of any monitoring parameter corresponding to each sampling point at all times within each monitoring period and the monitoring data of the same monitoring parameter corresponding to the other sampling points at all times within the same monitoring period is denoted as the first difference. The calculation of the Hausdorff distance is a well-known technique and will not be described in detail here. As other implementation methods, implementers may use other methods of the prior art, such as DTW distance, Euclidean distance, etc. This embodiment does not impose any special restrictions on this.

[0086] The difference in the trend deviation between any monitoring parameter corresponding to each sampling point in each monitoring period and any monitoring parameter corresponding to the other sampling points in the same monitoring period is denoted as the second difference;

[0087] In this embodiment, the absolute value of the difference between the trend deviation of any monitoring parameter corresponding to each sampling point in each monitoring period and the trend deviation of any monitoring parameter corresponding to the other sampling points in the same monitoring period is denoted as the second difference.

[0088] The mean of the product of the first difference and the second difference between each sampling point and all other sampling points of any one of the monitoring parameters in each monitoring period is used as the continuous deviation coefficient of the monitoring parameter corresponding to each sampling point in each monitoring period.

[0089] The product of the trend deviation and the continuous deviation coefficient is used as the continuous characteristic difference of each monitoring parameter corresponding to each sampling point in each monitoring period.

[0090] In this embodiment, the formula for calculating the continuous characteristic difference of each monitoring parameter corresponding to each sampling point in each monitoring period is as follows: Among them, B n,r,k Let d be the degree of continuous characteristic difference of the r-th monitoring parameter corresponding to the n-th sampling point during the k-th monitoring period. n,r,k Let be the trend deviation of the r-th monitoring parameter corresponding to the n-th sampling point during the k-th monitoring period. Let r be the first difference between the nth sampling point and the mth sampling point during the kth monitoring period for the rth monitoring parameter. Let N be the second difference between the nth and mth sampling points of the rth monitoring parameter during the kth monitoring period, where N is the total number of sampling points; secondly, This is the continuous deviation coefficient.

[0091] It should be noted that the larger the continuous deviation coefficient, the greater the difference in the data of the corresponding monitoring parameters between the location of the corresponding sampling point and the location of other sampling points in each monitoring period, and the more severe the continuous deviation. The larger the continuous characteristic difference degree, the more significant the continuous deviation response of the monitoring parameters at different locations during the CO2 reactor's well-sealing reaction.

[0092] Thus, the continuous characteristic difference of each monitoring parameter corresponding to each sampling point in each monitoring period is obtained.

[0093] Step 4: Based on the difference in the degree of continuous characteristic difference of each monitoring parameter corresponding to each sampling point between each monitoring period and other monitoring periods, determine the deviation response coefficient of each monitoring parameter corresponding to each sampling point in each monitoring period; based on the monitoring data of each monitoring parameter corresponding to different sampling points at the current time and the deviation response coefficient of the monitoring period to which the current time belongs, determine the error coefficient of each monitoring parameter at the current time, and perform real-time control of each monitoring parameter in the CO2 reactor.

[0094] Furthermore, during the control of the CO2 reactor, if a deviation occurs in its feedback control process, the monitoring data at different monitoring periods will be affected differently by the response of this deviation. Therefore, in order to accurately reflect the deviation of the monitoring parameters at different times during the CO2 reactor's shut-off process, the deviation response coefficient is determined by analyzing the changes in the degree of difference of the continuous characteristics of any monitoring parameter corresponding to each sampling point between different monitoring periods. Specifically:

[0095] The mean normalized result of the difference in the degree of continuous feature difference between each monitoring parameter corresponding to each sampling point and all other monitoring periods is used as the deviation response coefficient of each monitoring parameter corresponding to each sampling point in each monitoring period.

[0096] In this embodiment, Among them, h r,n,k Let B be the deviation response coefficient of the r-th monitoring parameter corresponding to the n-th sampling point during the k-th monitoring period. n,r,k B represents the continuous characteristic difference of the r-th monitoring parameter corresponding to the n-th sampling point during the k-th monitoring period. n,r,s T represents the continuous characteristic difference of the r-th monitoring parameter corresponding to the n-th sampling point during the s-th monitoring period. r Let be the number of all monitoring periods under the r-th monitoring parameter, and norm() be the normalization function. In this embodiment, the Softmax function is used for normalization. The Softmax function is a well-known technique and will not be described in detail here.

[0097] It should be noted that by analyzing the differences in continuous characteristics between different monitoring periods, the deviation response of the sampling point location under different monitoring periods can be reflected. The larger the obtained deviation response coefficient, the greater the possibility that the corresponding monitoring parameter under the corresponding monitoring period will be affected by fluctuations and have continuous deviations during the well-sealing reaction process. In this case, the error response of the corresponding sampling point location to the fluctuations of the monitoring parameters in the CO2 reactor is more accurate.

[0098] Furthermore, based on the monitoring data of any monitoring parameter corresponding to each sampling point at the current time, and the difference between the preset standard value of the corresponding monitoring parameter, and in conjunction with the deviation response coefficient of the monitoring period to which the current time belongs, an error coefficient is determined to adjust and control each monitoring parameter, specifically as follows:

[0099] The method for calculating the error coefficient of any monitoring parameter at the current moment is as follows: Where, ρ r,t Let v be the error coefficient of the r-th monitoring parameter at the current time t. n,r,t Let g be the deviation response coefficient of the r-th monitoring parameter corresponding to the n-th sampling point at the current time t within the monitoring period. n,r,t G represents the monitoring data of the r-th monitoring parameter corresponding to the n-th sampling point at the current time t. r Let be the preset standard value corresponding to the r-th monitoring parameter, and N be the number of all sampling points.

[0100] In this embodiment, each monitoring parameter corresponds to temperature and pressure. Therefore, the preset standard value for temperature is 110°C and the preset standard value for pressure is 40MPa. In other implementation methods, the implementer can set the values ​​according to the experimental requirements.

[0101] The error coefficient is used as the input of the PLC (Programmable Logic Controller). The PLC controller controls the temperature and pressure inside the CO2 reactor in real time, so that the temperature and pressure inside the CO2 reactor remain stable. The PLC controller is a well-known technology and will not be described in detail here.

[0102] Furthermore, the experimental procedure of this application is not only applicable to CO2 gas, but can also be used for huff and puff experiments with liquid media such as fracturing fluid, simulated formation water, and chemical solutions. The specific experimental procedure includes:

[0103] (1) Open the quick-release half ring of the high temperature and high pressure CO2 resistant reactor, and slowly lower the lower plug to a certain height of 25cm by using the stirring motor, and place the full diameter core on the magnetic stirring paddle;

[0104] (2) The core is fed into the pressure vessel by the motor, the quick-opening half ring of the high temperature and high pressure CO2 resistant reactor is closed, and the quick-opening half ring of the high temperature and high pressure CO2 resistant reactor is locked with the safety lock.

[0105] (3) Close valves V1, V2, V4, V5, V6, and V8, and open valves V3, V7, and V9. Use a vacuum system to evacuate the high-temperature and high-pressure CO2 resistant reactor and piston container. Set the temperature of the constant temperature chamber and the high-temperature and high-pressure CO2 resistant reactor to the experimental temperature of 110℃.

[0106] (4) Open valve V5 and close valve V9. Use injection pump 3 to inject the liquid medium in piston container 5 into high temperature and high pressure CO2 resistant reactor and set the pressure to the experimental pressure of 40MPa.

[0107] (5) The well stagnation time is set to 72 hours. The change in crude oil production in the metering glass tube 3 of the high-temperature and high-pressure CO2 resistant reactor 9 is observed through the viewing window glass 2 by the first high-definition camera 8.

[0108] (6) After the well is shut down, turn off injection pump 3, close valves V5, V3, and V7, open valve V6, and slowly reduce the pressure in the reactor using hand pump 11. Open valve V8 to slowly discharge the liquid medium from the reactor, thus ending the churn process.

[0109] (7) Repeat steps (1)-(6) above to perform multiple rounds of inhalation and exhalation on the full-diameter shale core.

[0110] It should be understood that, although Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0111] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0112] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application. Therefore, any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of this application, without departing from the content of the technical solution of this application, shall fall within the protection scope of the technical solution of this application.

Claims

1. A method for high-temperature and high-pressure CO2 huff and puff testing of full-diameter shale, characterized in that, The method includes the following steps: Real-time acquisition of monitoring data for each monitoring parameter at each sampling point inside the CO2 reactor during the well-sealing reaction process; Analyze the differences in monitoring data of all sampling points at each time point under each monitoring parameter and the remaining time points to determine the instantaneous difference of each monitoring parameter at each time point; based on the instantaneous difference, divide all time points corresponding to each monitoring parameter into multiple monitoring periods; By analyzing the trend changes of all monitoring data for any monitoring parameter corresponding to each sampling point during each monitoring period, and the trend changes of all instantaneous differences of the monitoring parameter during each monitoring period, the trend deviation of the monitoring parameter corresponding to each sampling point during each monitoring period can be obtained. Analyze the monitoring data of each sampling point and the other sampling points for any one of the monitoring parameters in each monitoring period, as well as the differences in the trend deviation; determine the continuous deviation coefficient of the monitoring parameter corresponding to each sampling point in each monitoring period; and combine the trend deviation and the continuous deviation coefficient to determine the continuous characteristic difference degree of the monitoring parameter corresponding to each sampling point in each monitoring period. Based on the difference in the degree of continuous characteristic difference of any monitoring parameter corresponding to each sampling point between each monitoring period and other monitoring periods, the deviation response coefficient of any monitoring parameter corresponding to each sampling point in each monitoring period is determined. Based on the monitoring data of any monitoring parameter corresponding to different sampling points at the current time, and the deviation response coefficient of the monitoring period to which the current time belongs, the error coefficient of any monitoring parameter at the current time is determined, and in conjunction with the controller, each monitoring parameter in the CO2 reactor is controlled in real time.

2. The experimental method for high-temperature and high-pressure CO2 huff and puff testing of full-diameter shale as described in claim 1, characterized in that, The monitoring parameters include temperature and pressure.

3. The experimental method for high-temperature and high-pressure CO2 huff and puff testing of full-diameter shale as described in claim 1, characterized in that, The instantaneous difference of each monitoring parameter at each time point is the average difference between the monitoring data of all sampling points at each time point under each monitoring parameter and the monitoring data of all sampling points at all other times points.

4. The experimental method for high-temperature and high-pressure CO2 huff and puff testing of full-diameter shale as described in claim 1, characterized in that, The method of dividing all times corresponding to each monitoring parameter into multiple monitoring time periods includes: Obtain the extreme points of the instantaneous difference of each monitoring parameter at all times, and use the extreme points as dividing points to divide all times corresponding to each monitoring parameter into multiple monitoring periods.

5. The experimental method for high-temperature and high-pressure CO2 huff and puff testing of full-diameter shale as described in claim 1, characterized in that, Determining the trend deviation of any monitoring parameter corresponding to each sampling point in each monitoring period includes: Calculate the trend statistics of the monitoring data of any monitoring parameter corresponding to each sampling point at all times in each monitoring period, and denot it as the first trend quantity; Calculate the trend statistic of the instantaneous difference of any monitoring parameter at all times within each monitoring period, and denot it as the second trend quantity; The difference between the first trend quantity and the second trend quantity is used as the trend deviation of any monitoring parameter corresponding to each sampling point in each monitoring period.

6. The experimental method for high-temperature and high-pressure CO2 huff and puff testing of full-diameter shale as described in claim 1, characterized in that, The process of obtaining the continuous deviation coefficient of any monitoring parameter corresponding to each sampling point in each monitoring period includes: The difference between the monitoring data of any one monitoring parameter corresponding to each sampling point at all times in each monitoring period and the monitoring data of any one monitoring parameter corresponding to the other sampling points at all times in the same monitoring period is denoted as the first difference. The difference in the trend deviation between any monitoring parameter corresponding to each sampling point in each monitoring period and any monitoring parameter corresponding to the other sampling points in the same monitoring period is denoted as the second difference; Calculate the product of the first difference and the second difference, and take the mean of the product between each sampling point and all other sampling points for each monitoring parameter in each monitoring period as the continuous deviation coefficient of the monitoring parameter corresponding to each sampling point in each monitoring period.

7. The experimental method for high-temperature and high-pressure CO2 huff and puff testing of full-diameter shale as described in claim 1, characterized in that, The degree of continuous characteristic difference of any monitoring parameter corresponding to each sampling point in each monitoring period is the product of the trend deviation and the continuous deviation coefficient.

8. The experimental method for high-temperature and high-pressure CO2 huff and puff testing of full-diameter shale as described in claim 1, characterized in that, The deviation response coefficient of each sampling point for any monitoring parameter in each monitoring period is the normalized result of the mean of the difference in the degree of continuous characteristic difference between each sampling point for any monitoring parameter in each monitoring period and all other monitoring periods.

9. The experimental method for high-temperature and high-pressure CO2 huff and puff testing of full-diameter shale as described in claim 1, characterized in that, No. The monitoring parameters at the current moment error coefficient The calculation method is as follows: ,in, For the first The corresponding sampling point of the th sampling point The monitoring parameters at the current moment Deviation response coefficient for the monitoring period For the first The corresponding sampling point of the th sampling point The monitoring parameters at the current moment Monitoring data, For the first The preset standard values ​​corresponding to the monitoring parameters This represents the total number of sampling points.

10. The experimental method for high-temperature and high-pressure CO2 huff and puff testing of full-diameter shale as described in claim 1, characterized in that, The real-time control of each monitoring parameter in the CO2 reactor includes: based on the error coefficient, controlling each monitoring parameter in the CO2 reactor in real time through a PLC controller.

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