Method and system for determining optimal compounding ratio of binary compound oil displacement system

Abstract

The invention relates to the technical field of intelligent sensors, in particular to a method and system for determining the optimal compounding ratio of a binary compound oil displacement system.The method comprises the steps that the binary compound oil displacement system of octylphenol polyoxyethylene ether and polyacrylamide is subjected to an emulsification experiment; analyzing the change degree and the change difference of the temperature peak values of the upper and lower bottoms of the inner wall of the oven collected by the intelligent sensor to obtain the local peak position abnormity degree, and combining the discrete condition of the temperature difference change between the upper and lower bottoms to obtain the disturbed confusion degree; a high-frequency interference characteristic value is obtained according to the high-frequency change characteristic of the disturbed confusion degree in the frequency domain in the emulsification process, then the proportionality coefficient of a PID controller in the drying oven is adjusted so as to control the temperature in the drying oven, and the optimal compounding ratio of the binary compound oil displacement system is determined according to the bleeding rate of the binary compound oil displacement system in the emulsification process. The temperature control precision of the drying oven in the emulsification process of the binary composite oil displacement system can be improved, so that the determination precision of the optimal compounding ratio is improved.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of intelligent sensors, in particular to a method and system for determining the optimal compounding ratio of a binary composite oil displacement system. BACKGROUND

[0002] At present, the optimal compounding ratio of a binary composite oil displacement system can be quickly determined through emulsification experiments on octylphenol polyoxyethylene ether and a polymer system. During the emulsification experiments, a PID controller (Proportion Integration Differentiation) is used to control the temperature in an oven to simulate the heat settling process and observe the water separation rate of the binary composite oil displacement system.

[0003] However, the traditional PID controller uses a fixed proportional parameter to control the temperature in the oven, which cannot timely respond to the change in the temperature in the oven affected by the external environment temperature, resulting in poor accuracy in controlling the temperature in the oven and affecting the determination of the optimal compounding ratio of the binary composite oil displacement system. SUMMARY

[0004] To solve the above technical problems, the purpose of the application is to provide a method and system for determining the optimal compounding ratio of a binary composite oil displacement system, and the technical solution adopted is as follows:

[0005] The application provides a method for determining the optimal compounding ratio of a binary composite oil displacement system, which comprises the following steps:

[0006] An emulsification experiment is performed on a binary composite oil displacement system of octylphenol polyoxyethylene ether and polyacrylamide, and an intelligent sensor is used to obtain the upper and lower bottom temperatures of the inner wall of the oven during the emulsification experiment;

[0007] The peak value change degree and change difference of the upper and lower bottom temperatures of the inner wall of the oven collected by the intelligent sensor are analyzed to obtain the local peak abnormality degree at each collection time, and the disturbance chaos degree at each collection time is obtained in combination with the dispersion of the temperature difference between the upper and lower bottoms;

[0008] According to the high-frequency change characteristics of the disturbance chaos degree in the frequency domain during the emulsification process, and in combination with the disturbance chaos degree, the high-frequency interference eigenvalue at each collection time is obtained, the proportional coefficient of the PID controller in the oven is adjusted through the change of the high-frequency interference eigenvalue to control the temperature in the oven, and then the optimal compounding ratio of the binary composite oil displacement system is determined through the water separation rate data of the binary composite oil displacement system during the emulsification process.

[0009] Preferably, the process of obtaining the local peak abnormality degree at each collection time is as follows: ; wherein, is the local peak position abnormality degree of the tth acquisition time, is the DTW distance between the upper and lower bottom peak position sequences of the tth acquisition time, and are respectively the element mean of the first-order difference sequence of the upper and lower bottom peak position sequences of the tth acquisition time.

[0010] Preferably, the multiple acquisition times closest to each acquisition time in time interval are recorded as the local acquisition times of each acquisition time, and the upper and lower bottom temperatures collected by the intelligent sensor at each acquisition time and its local acquisition time are arranged in time sequence to form the upper and lower bottom temperature sequences of each acquisition time, and the positions of all peak values in the upper and lower bottom temperature sequences are extracted to form the upper and lower bottom peak position sequences of each acquisition time in ascending order.

[0011] Preferably, the process of obtaining the interference chaos degree of each acquisition time is: ; in the formula, is the interference chaos degree of the tth acquisition time, is the local peak position abnormality degree of the tth acquisition time, is the discrete degree of all elements in the temperature difference step change sequence of the tth acquisition time.

[0012] Preferably, the upper and lower bottom temperature sequences of each acquisition time are subtracted, and the first-order difference sequence of the subtracted sequence is taken as the temperature difference step change sequence of each acquisition time.

[0013] Preferably, the interference chaos degrees of each acquisition time and its local acquisition time are arranged in time sequence to obtain the interference feature sequence of each acquisition time, the amplitude spectrum of the positive frequency part is extracted through frequency domain transformation, and the frequencies corresponding to all amplitudes not equal to 0 in the amplitude spectrum of the positive frequency part form the local frequency set of each acquisition time.

[0014] Preferably, the local frequency set of each acquisition time is respectively threshold segmented, and the frequencies greater than the corresponding segmentation threshold in the local frequency set form the local high frequency set of each acquisition time.

[0015] Preferably, the process of obtaining the high-frequency interference feature value of each acquisition time is: the normalized result of the product between the number of elements in the local high-frequency set of each acquisition time and the interference chaos degree is taken as the high-frequency interference feature value of each acquisition time.

[0016] Preferably, the process of adjusting the proportional coefficient of the PID controller in the oven is: ; in the formula, is the expected proportional coefficient of the current acquisition time, is the preset initial proportional coefficient, and are high-frequency interference eigenvalues of the current acquisition moment and the last acquisition moment of the current acquisition moment, respectively.

[0017] The embodiment of the application further provides a system for determining an optimal compounding ratio of a binary composite oil displacement system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, and the processor implements the steps of the method for determining the optimal compounding ratio of the binary composite oil displacement system according to any one of the preceding embodiments when running the computer program.

[0018] As can be seen from the above, the method and system for determining the optimal compounding ratio of the binary composite oil displacement system provided by the application have at least the following beneficial effects:

[0019] The emulsifying capacity of the non-ionic surfactant octylphenol polyoxyethylene ether is deeply researched in the application, and the emulsifying capacity is positively correlated with the improvement of the oil displacement effect. It is found from the oil displacement experiment data that the octylphenol polyoxyethylene ether and the polymer system can improve the recovery by 7.95 percent points compared with the single polymer system. The octylphenol polyoxyethylene ether can be widely used in the oil displacement capacity after being compounded with the polymer in addition to the washing and decontamination;

[0020] In the application, the abnormal degree of the local peak in the temperature change of the upper and lower bottoms of the oven is analyzed in the emulsification experiment process, and the step change characteristics of the temperature difference between the upper and lower bottoms of the oven are combined to accurately measure the non-steady-state abnormal chaotic characteristics of the temperature in the oven caused by the serious interference of the external environment temperature, which more clearly reflects the severity of the temperature in the oven affected by the external environment temperature, and is beneficial to the subsequent real-time fine tuning of the proportional parameter of the PID controller;

[0021] The application extracts the high-frequency change component of the interference chaos degree in the emulsification process by Fourier transform, and accurately measures the high-frequency interference characteristics of the temperature in the oven affected by the environment temperature by combining the non-steady-state abnormal chaotic characteristics of the temperature in the oven, and accurately fine tunes the proportional parameter of the PID controller through the change of the high-frequency interference characteristics, so that the adjusted PID controller can timely respond to the temperature change in the oven affected by the external environment temperature, and can ensure the stability of the temperature control system, thereby avoiding affecting the emulsification effect of the binary composite oil displacement system. BRIEF DESCRIPTION OF DRAWINGS

[0022] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort.

[0023] Figure 1 A step flow chart of a method for determining the optimal compounding ratio of a binary composite oil displacement system provided by the present application. DETAILED DESCRIPTION

[0024] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the specific embodiments, structure, features and effects of the method and system for determining the optimal compounding ratio of a binary composite oil displacement system according to the present application are described in detail as follows. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0025] Unless otherwise defined and limited, such as the terms "comprise", "include" or any other variants thereof, are intended to cover non-exclusive inclusion, so that the circuit structure, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such article or device. Without more limitation, the element limited by the statement "including one" does not exclude the presence of another identical element in the article or device including the element. In addition, the term "and / or" used herein includes any and all combinations of one or more related listed items. All technical and scientific terms used herein have the same meaning as understood by those skilled in the art of the technology to which the present application belongs.

[0026] The specific scheme of the method and system for determining the optimal compounding ratio of a binary composite oil displacement system provided by the present application is described in detail below with reference to the drawings.

[0027] Please refer to Figure 1 which shows a step flow chart of a method for determining the optimal compounding ratio of a binary composite oil displacement system provided by one embodiment of the present application, including the following steps:

[0028] Step 1: Emulsification experiment is performed on the binary composite oil displacement system of octylphenol polyoxyethylene ether and polyacrylamide, and the upper and lower bottom temperatures of the oven inner wall during the emulsification experiment process are obtained by intelligent sensors.

[0029] In this embodiment, the concentration of non-ionic surfactant octylphenol polyoxyethylene ether is 0.05%, 0.1% and 0.2% respectively, and is compounded with the polymer concentration of 1500 mg / L, the solution after sufficient mixing is subjected to hand shaking emulsification experiment, and the volume of water phase is read to calculate the water separation rate, the calculation process is the prior art, which is not described in detail in this embodiment. The emulsification effect of different concentrations of octylphenol polyoxyethylene ether is evaluated by the water separation rate, wherein the polymer is polyacrylamide. The water separation rate data table of different concentrations is shown in Table 1.

[0030] Table 1

[0031]

[0032] According to the above table, it is found from the experimental data of the hand shaking emulsification experiment that when the concentration of octylphenol polyoxyethylene ether is 0.1%, the water separation rate is the lowest, and therefore the emulsification effect under this concentration is the best, which is the best binary combination flooding system.

[0033] Further, the binary combination flooding system of octylphenol polyoxyethylene ether (0.1%) and polymer is subjected to emulsification experiment with oil-water ratio of 1:1, 3:7 and 1:9. Among them, the dehydrated crude oil and the prepared system solution are placed in a 100 mL graduated cylinder with a stopper, shaken vigorously, then placed in an oven to simulate the heat settling process, and the interface between the oil and the combined system is observed. In this embodiment, the preset temperature in the oven is 45°C.

[0034] In order to reduce the interference of the temperature in the oven by the external environment temperature, the temperature in the oven needs to be accurately adjusted and controlled by a PID controller (Proportion Integration Differentiation, PID controller) during the emulsification experiment, so as to avoid affecting the determination of the best compounding ratio in the subsequent binary combination flooding system.

[0035] In order to adjust and control the temperature in the oven by the PID controller, the upper and lower bottom temperatures of the inner wall of the oven need to be monitored in real time by an intelligent sensor, which includes a sensing unit, a micro-processing unit and a communication unit. The sensing unit of the intelligent sensor senses the temperature of the upper and lower bottoms of the inner wall of the oven through a thermocouple temperature sensor, the micro-processing unit of the intelligent sensor adopts a Savitzky-Golay filtering algorithm to filter the upper and lower bottom temperature data, and the communication unit of the intelligent sensor transmits the filtered upper and lower bottom temperature data to a data storage unit in real time through a wireless Bluetooth module for further data storage and analysis.

[0036] Therefore, the upper bottom temperature data and the lower bottom temperature data of the inner wall of the oven in the emulsification experiment process are collected by the intelligent sensor, the collection frequency of the intelligent sensor in the embodiment is 1 Hz, and the upper bottom temperature data and the lower bottom temperature data of the inner wall of the oven at each collection time in the emulsification experiment process are obtained.

[0037] In step 2, the peak value change degree and the change difference of the upper bottom temperature and the lower bottom temperature of the inner wall of the oven collected by the intelligent sensor are analyzed to obtain the local peak position abnormality degree at each collection time, and then the disturbance confusion degree at each collection time is obtained by combining the dispersion of the temperature difference between the upper bottom and the lower bottom.

[0038] The conventional PID controller uses a fixed proportional parameter to control the temperature in the oven, and cannot respond to the change of the temperature in the oven affected by the external environment temperature in time, so that the stability of the temperature in the oven cannot be effectively ensured, and the determination of the optimal compounding ratio in the subsequent binary composite oil displacement system is easily affected. Therefore, in order to accurately determine the optimal compounding ratio of the binary composite oil displacement system, it is necessary to accurately fine-tune the proportional parameter in the PID controller in real time, so as to improve the accuracy of controlling the temperature in the oven and avoid affecting the emulsification effect of the binary composite oil displacement system.

[0039] In order to analyze the interference of the upper bottom temperature and the lower bottom temperature of the oven in a short time by the external environment temperature, K collection time points closest to each collection time are recorded as K local collection time points of each collection time in the emulsification experiment process, wherein K is 60; then, the upper bottom temperature data and the lower bottom temperature data collected by the intelligent sensor at each collection time and K local collection time points are arranged in time sequence respectively, and the upper bottom temperature sequence and the lower bottom temperature sequence of each collection time are obtained.

[0040] Further, the upper bottom temperature sequence and the lower bottom temperature sequence of each collection time are respectively taken as the input of the AMPD peak detection algorithm (Automatic Multiscale Peak Detection), and all peak position sequences in the upper bottom temperature sequence and the lower bottom temperature sequence are respectively obtained by the AMPD peak detection algorithm. The sequence composed of all peak position sequences in the upper bottom temperature sequence and the lower bottom temperature sequence in the order from small to large is recorded as the upper bottom peak position sequence and the lower bottom peak position sequence of each collection time, which reflects the peak position change characteristics of the upper bottom temperature and the lower bottom temperature collected by the intelligent sensor affected by the external environment temperature interference.

[0041] Generally, if the difference between adjacent elements in the upper bottom peak position sequence or the lower bottom peak position sequence is smaller, the peak fluctuation of the upper bottom temperature or the lower bottom temperature collected by the intelligent sensor due to the interference of the external environment temperature is more frequent. If the difference between the upper bottom peak position sequence and the lower bottom peak position sequence is larger, the abnormality degree of the peak position in the upper bottom temperature and the lower bottom temperature collected by the intelligent sensor in a short time is higher, which reflects that the upper bottom temperature and the lower bottom temperature of the inner wall of the oven are more seriously interfered by the external environment temperature. At this time, the stability of the temperature at different positions in the oven cannot be effectively ensured, which will affect the emulsification effect of the binary composite oil displacement system.

[0042] Based on the above analysis, the local peak abnormality degree at each collection time is calculated: In the formula, is the local peak abnormality degree at the tth collection time, is the DTW distance (Dynamic Time Warping) between the upper bottom peak position sequence and the lower bottom peak position sequence at the tth collection time, and are the element mean values in the first-order difference sequence of the upper bottom peak position sequence and the lower bottom peak position sequence at the tth collection time, respectively. The calculation of the DTW dynamic programming distance and the first-order difference sequence are known technologies, and the specific process is not described again.

[0043] The local peak abnormality degree reflects the abnormality degree of the local peak in the upper bottom temperature and the lower bottom temperature collected by the intelligent sensor. The larger the local peak abnormality degree is, the more seriously the upper bottom temperature and the lower bottom temperature of the inner wall of the oven are interfered by the external temperature. At this time, it is more necessary to effectively adjust and control the temperature in the oven through the PID controller, so as to timely respond to the change of the temperature in the oven affected by the external environment temperature, and avoid affecting the emulsification effect of the binary composite oil displacement system.

[0044] At the same time, in order to enable the PID controller to timely respond to the complex change of the upper bottom temperature and the lower bottom temperature in the oven, it is necessary to combine the complex change characteristics of the upper bottom temperature and the lower bottom temperature in the oven, so as to more accurately fine-tune the proportional parameter of the PID controller. Therefore, the first-order difference sequence of the sequence after the difference between the upper bottom temperature sequence and the lower bottom temperature sequence at each collection time is recorded as the temperature difference step change sequence at each collection time, which reflects the step change characteristics of the temperature difference change affected by the external environment temperature.

[0045] Generally, the higher the abnormal degree of the local peak in the upper and lower bottom temperature change collected by the intelligent sensor, and the more complex the step change characteristics of the temperature difference between the upper and lower bottoms in the oven, the more reliably it can be explained that the temperature in the oven is disturbed by the external environment temperature, causing non-steady abnormal changes in the temperature in the oven, and the more accurate the proportional parameter in the PID controller needs to be adjusted, so that the PID controller can respond more quickly to the non-steady abnormal temperature change in the oven, thereby avoiding affecting the emulsification effect of the binary composite oil displacement system.

[0046] Based on the above analysis, the disturbance chaos degree at each collection time is calculated: ; In the formula, is the disturbance chaos degree at the tth collection time, is the dispersion degree of all elements in the temperature difference step change sequence at the tth collection time, and the dispersion degree measurement method includes variance, standard deviation, or coefficient of variation, etc. In this embodiment, the coefficient of variation is used to measure the dispersion degree.

[0047] According to the above process, it can be understood that the disturbance chaos degree reflects the non-steady abnormal chaotic characteristics of the temperature in the oven disturbed by the external environment temperature, and the greater the disturbance chaos degree, the more significant the non-steady abnormal chaotic characteristics of the temperature in the oven disturbed by the external environment temperature, and the more likely the temperature in the oven is out of control, so the proportional parameter in the PID controller needs to be accurately adjusted to timely and accurately adjust and control the temperature in the oven, thereby avoiding affecting the emulsification effect of the binary composite oil displacement system.

[0048] Step 3: According to the high-frequency change characteristics of the disturbance chaos degree in the frequency domain during the emulsification process, and combining the disturbance chaos degree to obtain the high-frequency interference characteristic value at each collection time, the proportional coefficient of the PID controller in the oven is adjusted through the change of the high-frequency interference characteristic value to control the temperature in the oven, and then the best compounding ratio of the binary composite oil displacement system is determined through the water separation rate data of the binary composite oil displacement system during the emulsification process.

[0049] In order to accurately analyze the disturbance characteristics of the temperature data collected by the intelligent sensor affected by the external environment, and more accurately adjust the proportional parameter in the PID controller, the disturbance chaos degrees at each collection time and its K local collection times are arranged in time sequence to obtain the disturbance characteristic sequence at each collection time, reflecting the non-steady abnormal chaotic change characteristics of the oven in a short time.

[0050] Further, the frequency components in the disturbed feature sequence are analyzed, and the disturbed feature sequence at each collection time is taken as the input of Fourier transform, which can be fast Fourier transform or discrete Fourier transform. In this embodiment, the discrete Fourier transform is used to obtain the amplitude spectrum of the positive frequency part of the disturbed feature sequence at each collection time, and a set composed of the frequencies corresponding to all amplitudes not equal to 0 in the amplitude spectrum of the positive frequency part is recorded as a local frequency set at each collection time, which reflects the frequency characteristics of the non-steady-state abnormal chaotic changes in the temperature data collected by the intelligent sensor in a short time.

[0051] Generally, the more high-frequency components in the local frequency set at a certain collection time, and the greater the non-steady-state abnormal chaotic characteristics of the temperature collected by the intelligent sensor at this time, the more it can reflect the high-frequency change characteristics of the disturbed chaos degree in the emulsification process, indicating that the non-steady-state high-frequency change of the temperature in the oven is more significant at this time, and the proportional parameter in the PID controller should be increased at this time, so that the PID controller can respond to the high-frequency change affected by the external environment temperature in time.

[0052] Therefore, the local frequency set at each collection time is taken as the input of the maximum inter-class variance algorithm, and the segmentation threshold is obtained by the maximum inter-class variance algorithm. A set composed of the frequencies greater than the segmentation threshold in the local frequency set is recorded as a local high-frequency set at each collection time, which reflects the high-frequency change components of the disturbed chaos degree in the emulsification process. The maximum inter-class variance algorithm is a known technology, and the specific process will not be repeated.

[0053] Further, in this embodiment, the Min-Max normalized result of the product of the number of elements in the local high-frequency set at each collection time and the disturbed chaos degree is recorded as a high-frequency interference feature value at each collection time, to reflect the high-frequency interference feature of the temperature in the oven affected by the environment temperature in the emulsification process. If the change of the high-frequency interference feature value between adjacent collection times increases, it indicates that the high-frequency interference of the temperature in the oven affected by the environment temperature is more serious at this time, and the proportional parameter in the PID controller should be increased at this time, so as to respond to the temperature change in the oven affected by the external environment temperature in time; otherwise, if the change of the high-frequency interference feature value between adjacent collection times decreases, it indicates that the high-frequency interference of the temperature in the oven affected by the environment temperature is weakening at this time, in order to avoid that the too large proportional parameter affects the stability of the temperature control system, the proportional parameter in the PID controller should be decreased at this time, so as to improve the stability of the temperature control system.

[0054] Based on the above analysis, the expected proportional coefficient at the current collection time is calculated as follows: ; in the formula, is the expected proportional coefficient at the current collection time, The preset initial proportional coefficient is 12 in the range of (10, 15) in this embodiment. and are high-frequency interference eigenvalues of the current acquisition time and the last acquisition time of the current acquisition time, respectively.

[0055] By fine-tuning the proportional coefficient of the PID controller in the oven, the adjusted PID controller can respond to the temperature change in the oven affected by the external environment temperature in a timely manner, and can ensure the stability of the temperature control system, thereby improving the accuracy of controlling the temperature in the oven.

[0056] Therefore, the real-time fine-tuned expected proportional coefficient is used as the proportional parameter of the PID controller in the oven, and the integral parameter and the differential parameter of the PID controller in the oven are in the range of (0, 2), and in this embodiment, the preset integral parameter and differential parameter are 1.2 and 1.5, respectively. The actual temperature of the inner wall of the oven collected by the intelligent sensor and the preset temperature in the oven are transmitted to the PID controller, the PID calculates the control signal through the temperature error between the actual temperature and the preset temperature value, and transmits the control signal to the heating unit in the oven, to realize real-time adjustment and control of the temperature in the oven, avoiding affecting the emulsification process of the binary composite oil displacement system. The actual temperature is the average of the upper and lower bottom temperatures.

[0057] Therefore, by adjusting and controlling the temperature in the oven through the PID controller, the emulsification experiment of the binary composite oil displacement system is more effectively realized, and the interface of oil and the compound system is observed to read the volume and calculate the water separation rate. The data of the water separation rate of the octylphenol polyoxyethylene ether binary system is shown in Table 2.

[0058] Table 2

[0059]

[0060] From the experimental data, it can be seen that the emulsification effect of the octylphenol polyoxyethylene ether / polymer binary composite oil displacement system is better than that without adding the binary composite oil displacement system, and the emulsion of the octylphenol polyoxyethylene ether / polymer binary composite oil displacement system is most stable and the emulsification effect is best when the oil-water ratio is 1:1, and the 4-hour water separation rate is 4%. When the oil-water ratio is 1:9, the 4-hour water separation rate is 67.67%, and the emulsion system is unstable, but through the experiment, it can be seen that the area of the transition layer in the compound system is large, so when the water content in the oil layer is large, the system can still improve the oil washing efficiency and increase the flow ability of the system within a certain time range, thereby improving the recovery efficiency.

[0061] Therefore, the best complexing system is nonylphenol polyoxyethylene ether (0.1%), the polymer concentration is 1500 mg / L, the oil-water ratio is 1:1, and the complexing ratio of the best complexing system is the best complexing ratio of the binary composite oil displacement system.

[0062] The best complexing system of nonylphenol polyoxyethylene ether (0.1%) and the polymer is subjected to indoor core displacement experiments and compared with the polymer system alone. The oil displacement experiment data are shown in Table 3.

[0063] Table 3

[0064]

[0065] As can be seen from Table 3, the recovery efficiency of the best complexing system in the embodiment is increased by 7.95 percentage points compared with the polymer system alone. Through analysis of the experimental research in the embodiment, when the nonionic surfactant nonylphenol polyoxyethylene ether concentration is 0.1%, it has strong emulsifying effect, and can achieve certain emulsifying effect for different water-containing oil layers, thereby improving the oil displacement effect.

[0066] Based on the same inventive concept as the above method, the embodiment of the present application also provides a system for determining the best complexing ratio of a binary composite oil displacement system, which comprises a memory, a processor, and a computer program stored in the memory and running on the processor, and the processor implements the steps of the best complexing ratio determination method of the binary composite oil displacement system according to any one of the above embodiments when executing the computer program.

[0067] It can be understood that the above-mentioned sequence of the embodiments is only for description, and does not represent the advantages and disadvantages of the embodiments. The above describes the specific embodiments of the present application. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are possible or can be advantageous.

[0068] Each embodiment in the present specification is described in a progressive manner, and the same or similar parts between each embodiment can be referred to each other. Each embodiment mainly describes the differences from other embodiments.

[0069] The above is only an embodiment of the present application, and is not used to limit the scope of the present application. Any equivalent structure or equivalent process conversion using the contents of the present application specification and drawings, or direct or indirect application in other related technical fields, are also included in the protection scope of the present application.

Claims

1. A method for determining the optimum matching ratio of a binary combination of oil displacement system, characterized in that, The method comprises the following steps: The emulsification experiment is conducted on a binary complex oil displacement system of octylphenol polyoxyethylene and polyacrylamide, and the upper and lower bottom temperatures of the inner wall of an oven during the emulsification experiment are obtained by an intelligent sensor; The peak value change degree and difference of the upper and lower bottom temperatures of the inner wall of the oven collected by the intelligent sensor are analyzed to obtain the local peak abnormality degree at each collection time, and the interference chaos degree at each collection time is obtained by combining the dispersion of the temperature difference between the upper and lower bottoms; According to the high-frequency change characteristics of the interference chaos degree in the frequency domain during the emulsification process, and combining the interference chaos degree, the high-frequency interference characteristic value at each collection time is obtained, the proportional coefficient of the PID controller in the oven is adjusted through the change of the high-frequency interference characteristic value to control the temperature in the oven, and then the best compounding ratio of the binary complex oil displacement system is determined through the water separation rate data of the binary complex oil displacement system during the emulsification process.

2. The method for determining the optimum matching ratio of a binary composite oil displacement system according to claim 1, characterized in that, The acquisition process of the local peak position anomaly degree of each acquisition moment is as follows: In the formula, is the local peak position anomaly degree of the tth acquisition moment, is the DTW distance between the upper bottom peak position sequence and the lower bottom peak position sequence of the tth acquisition moment, and are respectively the element mean values in the first-order difference sequences of the upper bottom peak position sequence and the lower bottom peak position sequence of the tth acquisition moment.

3. The method for determining the optimum matching ratio of a binary composite oil displacement system according to claim 2, characterized in that, The collection time interval of the nearest multiple collection times to each collection time is recorded as the local collection time of each collection time, and the upper and lower bottom temperatures collected by the intelligent sensor at each collection time and its local collection time are arranged in time sequence to form the upper and lower bottom temperature sequences of each collection time, and the bit sequence of all peak values in the upper and lower bottom temperature sequences is extracted and arranged in ascending order to form the upper bottom peak sequence and the lower bottom peak sequence of each collection time.

4. The method for determining the optimum matching ratio of a binary composite oil displacement system according to claim 1, characterized in that, The acquisition process of the disturbed chaos degree of each acquisition time is as follows: ; in the formula, is the disturbed chaos degree of the tth acquisition time, is the local peak anomaly degree of the tth acquisition time, is the dispersion degree of all elements in the temperature difference step change sequence at the tth acquisition time.

5. The method for determining the optimum matching ratio of a binary composite oil displacement system according to claim 4, characterized in that, The upper and lower bottom temperature sequences of each collection time are subtracted, and the first-order difference sequence of the subtracted sequence is taken as the temperature difference step sequence of each collection time.

6. The method for determining the optimum matching ratio of a binary composite oil displacement system according to claim 1, characterized in that, The interference chaos degrees of each collection time and its local collection time are arranged in time sequence to obtain the interference feature sequence of each collection time, the amplitude spectrum of the positive frequency part is extracted through frequency domain transformation, and the frequencies corresponding to all amplitudes not equal to 0 in the amplitude spectrum of the positive frequency part form the local frequency set of each collection time.

7. The method for determining the optimum matching ratio of a binary composite oil displacement system according to claim 6, characterized in that, The local frequency set of each collection time is respectively subjected to threshold segmentation, and the frequencies greater than the corresponding segmentation threshold in the local frequency set form the local high-frequency set of each collection time.

8. The method for determining the optimum matching ratio of a binary composite oil displacement system according to claim 7, characterized in that, The acquisition process of the high-frequency interference characteristic value of each collection time is that the normalized result of the product of the number of elements in the local high-frequency set of each collection time and the interference chaos degree is taken as the high-frequency interference characteristic value of each collection time.

9. The method for determining the optimum matching ratio of a binary composite oil displacement system according to claim 1, characterized in that, The process of adjusting the proportional coefficient of the PID controller in the conditioning oven is: ; wherein, is the expected proportional coefficient at the current acquisition time, is the preset initial proportional coefficient, and are the high-frequency interference eigenvalues at the current acquisition time and the last acquisition time of the current acquisition time, respectively. 10.A system for determining the optimum matching ratio of a binary combination flooding system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein, The processor executes the computer program to realize the steps of the method for determining the best compounding ratio of the binary complex oil displacement system according to any one of claims 1-9.

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