A method and system for controlling oil well heating, wax removal and viscosity reduction

Abstract

The present invention provides a method and system for joint control of heating, wax removal and viscosity reduction of oil wells. The method mainly includes: taking the minimum fluctuation of total heating power and total oil return line pressure as the optimization target, selecting a target well according to a preset well selection rule; setting a new wellhead control temperature for the target well according to the current production situation, and outputting the heating power according to the new wellhead control temperature to generate the next generation of production data; obtaining the new total heating power fluctuation and total oil return line pressure fluctuation according to the new generation of production data, and judging whether the new total heating power fluctuation and total oil return line pressure fluctuation meet the preset fitness threshold, and if the stop condition is met, outputting the wellhead control temperature setting value of each single well in the current working condition as the best control scheme under the current working condition. The present invention provides the optimal control scheme adapted to the current production conditions through an adaptive algorithm, so that the overall energy consumption of an oil transfer station (or central processing station) is minimized.

Description

Technical Field

[0001] The present invention relates to a technical field for solving the wax removal and viscosity reduction problems involved in the lifting of heavy oil and high-condensate oil during oil well lifting, and more specifically, to an oil well heating wax removal and viscosity reduction joint control method and system. Background Art

[0002] In the field of oil production, the difficulty in lifting heavy oil (or waxy) wells has always restricted the improvement of production efficiency. High-viscosity crude oil increases energy consumption during the lifting process and creates a great burden on the power unit, making it difficult for the power unit to operate stably for a long time.

[0003] In order to solve the above problems, the common practice in the industry is to install a heating belt on the outside of the underground lifting pipeline, and continuously release heat to the lifting pipeline through the heating belt, thereby increasing the oil temperature in the pipeline and reducing the viscosity of the oil. However, continuous heating consumes a lot of energy, and too high oil temperature is not conducive to ensuring production safety. Therefore, the pipeline heating device is subjected to temperature closed-loop control, that is, a heating control system is designed for each single well, and the heating process is controlled with the preset output liquid temperature as the control target. Since the underground heating system in the existing solution is monotonous for a single well, there is a lack of joint adjustment between the single wells of the metering stations, which cannot meet the control requirements of large-scale oil production systems, cannot perform system-level power optimization, and it is difficult to further reduce energy consumption on the basis of the existing control system. Summary of the invention

[0004] According to the technical problem that the above-mentioned single-well monotonous heating system cannot realize the joint adjustment between metering stations, and thus cannot realize system-level power optimization, a method and system for joint control of oil well heating, wax removal and viscosity reduction is provided. The present invention takes the oil wells under the jurisdiction of a central processing station as the research object, establishes an oil well production situation database, takes each metering station as the control object, and gives the optimal control scheme that adapts to the current production conditions and has the lowest energy consumption through an adaptive algorithm.

[0005] The technical means adopted by the present invention are as follows:

[0006] A method for heating, removing wax and reducing viscosity of oil wells is applied to a three-level production control system. The three-level production control system includes a central processing station, which is under the jurisdiction of several metering stations. Any of the metering stations is under the jurisdiction of several single wells. A heating device, a power controller and a sensor system are provided in the single well. The power controller is used to adjust the heating of the sensor system for collecting production data of the single well. The joint control method includes the following steps:

[0007] S101, obtaining the initialization data of the single well under the jurisdiction of each metering station, wherein the initialization data includes the initial wellhead control temperature of the single well; controlling the heating device to perform heating according to the initial wellhead control temperature;

[0008] S102, obtaining production data of a single well, wherein the single well production data obtains total heating power fluctuation and total oil return line pressure fluctuation, wherein the total heating power fluctuation is used to characterize the change of total heating power in the metering station over time, and the total oil return line pressure fluctuation is used to characterize the change of total oil return line pressure in the metering station over time;

[0009] S103, calculating the total heating power fluctuation and the total oil return line pressure fluctuation and setting them as initial thresholds α and β respectively;

[0010] S104, selecting a target well according to a preset well selection rule, wherein the preset well selection rule is set to set a candidate priority of a single well according to liquid production, oil content, and shelving status;

[0011] S105, setting a new wellhead control temperature for the single well according to the production situation, and outputting heating power according to the new wellhead control temperature to generate next generation production data;

[0012] S106, obtaining new total heating power fluctuation and total oil return pipeline pressure fluctuation according to the new generation production data, and judging again whether the new total heating power fluctuation and total oil return pipeline pressure fluctuation meet the preset fitness threshold. If the preset fitness requirement is not met, judging again whether the stop condition is met. If the stop condition is met, outputting the wellhead control temperature setting value of each single well in the current working condition as the optimal control scheme, otherwise executing S107;

[0013] S107. Adjust the candidate priority of the single well according to the new generation production data, and execute S104.

[0014] Furthermore, the total heating power fluctuation is obtained according to the following method:

[0015] Obtain the heating power data of a single well based on the production data of the single well.

[0016] Calculate the single well heating power fluctuation data, where the single well heating power fluctuation data is the difference between the single well heating power data in a certain period and the single well heating power data in the previous period.

[0017] Calculate the variance of the heating power fluctuation data of each single well as the total heating power fluctuation in the metering station;

[0018] The total oil return line pressure fluctuation is obtained according to the following method:

[0019] Obtain the single well return oil pipeline pressure data based on the single well production data.

[0020] Calculate the single well return oil pipeline pressure fluctuation data, where the single well return oil pipeline pressure fluctuation data is the difference between the single well return oil pipeline pressure data in a certain period and the single well return oil pipeline pressure data in the previous period.

[0021] The variance of the return oil pipeline pressure fluctuation data of each single well is calculated as the total return oil pipeline pressure fluctuation in the metering station.

[0022] Furthermore, the target well is selected according to the preset well selection rules, including:

[0023] Sort the liquid production of the single wells under the metering station, and assign an initial value to the priority vector of the single well according to the sorting result;

[0024] The priority vector is screened based on a preset priority threshold, and the well selection vector of the screened single well is set to 1;

[0025] A round of adjustment is performed on all single wells. At this time, if the priority vector of a single well is not the highest level, it will be promoted one level. If a single well is selected more than the specified threshold, the priority of the single well is set to the lowest, and the well selection vector of this round is output.

[0026] Furthermore, a new wellhead control temperature is set for a single well according to production conditions, including:

[0027] Constructing a fitting prediction model of the wellhead control temperature of each single well under the metering station and the total oil return pipeline pressure fluctuation, wherein the fitting prediction model is used to describe the linear mapping relationship between the wellhead control temperature of each single well and the total oil return pipeline pressure fluctuation;

[0028] Obtaining historical observation data and bringing it into a fitting prediction model to obtain a coefficient equation group, wherein the historical observation data includes wellhead control temperature of a single well extracted in multiple time periods and total return oil pipeline pressure fluctuations;

[0029] Solving the coefficient equations and updating the coefficients of the fitted prediction model based on the results;

[0030] The wellhead control temperature under the current production conditions is brought into the fitting prediction model after the coefficient is updated to obtain the total return oil pipeline pressure fluctuation at this time;

[0031] Determine whether the current total return oil pipeline pressure fluctuation is smaller than the total return oil pipeline pressure fluctuation obtained by the wellhead control temperature set in the previous round. If so, output the current wellhead control temperature.

[0032] Furthermore, the joint control method comprises the following steps:

[0033] Classify the metering stations under the central processing station, and optimize the wellhead control temperature of each metering station according to the classification results; the classification of the metering stations under the central processing station specifically includes:

[0034] Read the production data of the single wells under the jurisdiction of each metering station, the production data including the power consumption of the single well, the output of the single well and the distance from the single well to the metering station; calculate the liquid production distance and power demand according to the power consumption of the single well, the output of the single well and the distance from the single well to the metering station, the liquid production distance is the weighted average of the liquid production of the single well multiplied by the distance from the well to the metering station, and the power demand is the weighted average of the power consumption of the single well and the liquid production;

[0035] Normalizing the production distance and power requirement, establishing a linear fitting function with the normalized production distance and power requirement as characteristic values ​​and bringing the linear fitting function into the activation function;

[0036] Perform two-class classification three times, calculate the regression coefficients of the corresponding categories, and finally output the updated classification regression coefficient matrix of the metering station;

[0037] The liquid production distance and power demand characteristic values ​​of the metering stations to be classified are processed according to the metering station classification regression coefficient matrix to obtain the classification results.

[0038] Furthermore, the heating device comprises a battery core, a core wire sheath and an induction steel armor, wherein the induction steel armor is a longitudinally wrapped structure, the battery core is arranged inside the induction steel armor, and the core wire sheath is filled between the induction steel armor and the battery core;

[0039] The blind end of the induction steel armor is set to a curved structure adapted to the specifications of the oil pipeline; a side opening end of the induction steel armor is arranged opposite to the blind end of the induction steel armor, and the side opening end of the induction steel armor is a double-stacked structure.

[0040] Furthermore, a plurality of parallel air gaps are laterally arranged on the double-stacked structure at the side opening end of the induction steel armor.

[0041] The present invention also discloses an oil well heating, wax removal and viscosity reduction joint control system, the system comprising:

[0042] An initialization unit, which is used to obtain the initialization data of the single well under the jurisdiction of each metering station, wherein the initialization data includes the initial wellhead control temperature of the single well; and control the heating device to perform heating according to the initial wellhead control temperature;

[0043] A production data acquisition unit, which is used to acquire production data of a single well, wherein the single well production data acquires total heating power fluctuation and total oil return line pressure fluctuation, wherein the total heating power fluctuation is used to characterize the change of total heating power in the metering station over time, and the total oil return line pressure fluctuation is used to characterize the change of total oil return line pressure in the metering station over time;

[0044] A first judgment unit, which is used to judge whether the total heating power fluctuation and the total oil return line pressure fluctuation meet a preset fitness threshold. If the preset fitness requirement is not met, a target well is selected according to a preset well selection rule, wherein the preset well selection rule is set to set a candidate priority of a single well according to liquid production, oil content and shelving status;

[0045] An optimization unit, which is used to set a new wellhead control temperature for a single well according to production conditions, and output heating power according to the new wellhead control temperature to generate next generation production data;

[0046] The second judgment unit is used to obtain new total heating power fluctuations and total oil return line pressure fluctuations according to the new generation of production data, and judge again whether the new total heating power fluctuations and total oil return line pressure fluctuations meet the preset fitness thresholds. If the preset fitness requirements are not met, it is judged whether the stop condition is met. If the stop condition is met, the wellhead control temperature setting value of each single well in the current working condition is output as the optimal control solution;

[0047] The priority adjustment unit is used to adjust the candidate priority of the single well according to the new generation production data.

[0048] The present invention also discloses an oil well heating, wax removal and viscosity reduction joint control device, the device comprising:

[0049] at least one processor; and,

[0050] a memory communicatively connected to the at least one processor; wherein,

[0051] The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to:

[0052] Acquire the single well initialization data under each metering station, wherein the initialization data includes the initial wellhead control temperature of the single well; control the heating device to perform heating according to the initial wellhead control temperature;

[0053] Acquire production data of a single well, wherein the single well production data acquires fluctuations in total heating power and total oil return line pressure, wherein the fluctuations in total heating power are used to characterize changes in total heating power over time in the metering station, and the fluctuations in total oil return line pressure are used to characterize changes in total oil return line pressure over time in the metering station;

[0054] Determine whether the total heating power fluctuation and the total oil return line pressure fluctuation meet the preset fitness threshold. If the preset fitness requirement is not met, select the target well according to the preset well selection rule, wherein the preset well selection rule is set to set the candidate priority of the single well according to the liquid production, oil content and shelving condition;

[0055] A new wellhead control temperature is set for a single well according to production conditions, and heating power is output according to the new wellhead control temperature to generate next generation production data;

[0056] According to the new generation of production data, the new total heating power fluctuation and total return oil pipeline pressure fluctuation are obtained, and it is judged again whether the new total heating power fluctuation and total return oil pipeline pressure fluctuation meet the preset fitness threshold. If the preset fitness requirement is not met, it is judged whether the stop condition is met. If the stop condition is met, the wellhead control temperature setting value of each single well in the current working condition is output as the optimal control solution.

[0057] The present invention also discloses an oil well heating wax removal and viscosity reduction joint control medium, which stores computer executable instructions, and the computer executable instructions are set as follows:

[0058] Acquire the single well initialization data under each metering station, wherein the initialization data includes the initial wellhead control temperature of the single well; control the heating device to perform heating according to the initial wellhead control temperature;

[0059] Acquire production data of a single well, wherein the single well production data acquires fluctuations in total heating power and total oil return line pressure, wherein the fluctuations in total heating power are used to characterize changes in total heating power over time in the metering station, and the fluctuations in total oil return line pressure are used to characterize changes in total oil return line pressure over time in the metering station;

[0060] Determine whether the total heating power fluctuation and the total oil return line pressure fluctuation meet the preset fitness threshold. If the preset fitness requirement is not met, select the target well according to the preset well selection rule, wherein the preset well selection rule is set to set the candidate priority of the single well according to the liquid production, oil content and shelving condition;

[0061] A new wellhead control temperature is set for a single well according to production conditions, and heating power is output according to the new wellhead control temperature to generate next generation production data;

[0062] According to the new generation of production data, the new total heating power fluctuation and the total return oil pipeline pressure fluctuation are obtained, and it is judged again whether the new total heating power fluctuation and the total return oil pipeline pressure fluctuation meet the preset fitness threshold. If the preset fitness requirement is not met, it is judged whether the stop condition is met. If the stop condition is met, the wellhead control temperature setting value of each single well in the current working condition is output as the optimal control solution.

[0063] Compared with the prior art, the present invention has the following advantages: the present invention not only solves the problems of heavy oil and wax deposition in the process of crude oil lifting, but also realizes system-level power optimization through single-well joint adjustment between various metering stations. At the same time, a classification scheme between metering stations is designed to facilitate the optimization and promotion of the control scheme. In addition, the heating device designed in the present invention can make heat transfer directional, effectively avoid energy waste, and further reduce the consumption of heating energy. Based on the above reasons, the present invention can be widely promoted in oil lifting or oil gathering and transportation systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0065] Figure 1 This is a control system architecture diagram provided in the embodiments of this specification.

[0066] Figure 2 A flow chart of a method for controlling oil well heating, wax removal and viscosity reduction provided in an embodiment of this specification.

[0067] Figure 3 This is a fitness calculation flow chart provided in the embodiments of this specification.

[0068] Figure 4 A flow chart of target well selection provided for an embodiment of this specification.

[0069] Figure 5 A flow chart for updating the target well set temperature provided in the embodiments of this specification.

[0070] Figure 6 This is a flow chart of metering station classification provided in the embodiments of this specification.

[0071] Figure 7 This is a flow chart for calculating the regression coefficient vector provided in the embodiments of this specification.

[0072] Figure 8 This is a schematic diagram of the structure of the heating device provided in the embodiment of this specification.

[0073] Fig. 9 This is a schematic diagram of the terminal structure provided in the embodiments of this specification.

[0074] In the figure: 1. Battery core; 2. Core wire sheath; 3. Induction armor; 3.1. Blind end; 3.2. Side opening end; 3.3. Air gap; 4. Electric heating component body; 5. Terminal protection cover; 6. Transition adapter; 7. Casting agent. DETAILED DESCRIPTION

[0075] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail with reference to the accompanying drawings and in combination with the embodiments. In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described in combination with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present invention and its application or use. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0076] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0077] A method for heating, removing wax and reducing viscosity of oil wells is applied to a three-level production control system. Its architecture is as follows: Figure 1 As shown, the three-level production control system includes a central processing station, which is under the jurisdiction of several metering stations. Any metering station is under the jurisdiction of several single wells. A heating device, a power controller and a sensor system are set in the single well. The power controller is used to adjust the heating of the sensor system for collecting production data of the single well. The joint control method first initializes the data, and sets the wellhead control temperature of the single well according to the established strategy based on the current production conditions of the single well under the jurisdiction of the metering station. The single well control cabinet will generate the first generation of production data (G=0) according to the set target, and calculate the initial generation α, β, that is, the fluctuation of the current total heating power and the pressure fluctuation of the return oil manifold of the metering station (between) are recorded as α=δW, β=δP. Secondly, a batch of target wells are selected for optimization: wells with stable liquid production and oil content are given priority for adjustment, and long-term shelved wells that have not been selected for more than N rounds will also be given priority as the selection category. Next, set a new wellhead control temperature for the selected target well to generate the next generation of production data (G=G+1), and calculate the fitness after this parameter adjustment, calculate the fluctuation of the total heating power and the fluctuation range of the return oil manifold pressure of the metering station (room) in this cycle, if δW<α and δP<β are not satisfied, until the expected value is reached or the iteration cycle ΔT is reached. Finally, output the best solution under the current working conditions. Specifically, if Figure 2As shown, the method mainly includes the following steps:

[0078] S101, obtaining the initialization data of the single well under the jurisdiction of each metering station, wherein the initialization data includes the initial wellhead control temperature of the single well; and controlling the heating device to perform heating according to the initial wellhead control temperature.

[0079] This step is mainly used to read the relevant data of a single well under the jurisdiction of a metering station (room): the heating power of a single well W[i][j] and the return oil pipeline pressure of a single well P[i][j] as a record; the meaning of this record is the power and return oil pressure of the single wells numbered from 0 to j under the jurisdiction of the metering station (room) in the i-th time period.

[0080] S102. Acquire the production data of a single well. The single well production data acquires the total heating power fluctuation and the total return oil pipeline pressure fluctuation. The total heating power fluctuation is used to characterize the change of the total heating power in the metering station over time. The total return oil pipeline pressure fluctuation is used to characterize the change of the total return oil pipeline pressure in the metering station over time.

[0081] Furthermore, the total heating power fluctuation is obtained according to the following method:

[0082] a. Obtain single well heating power data based on single well production data;

[0083] b. Calculate the single well heating power fluctuation data, where the single well heating power fluctuation data is the difference between the single well heating power data in a certain period and the single well heating power data in the previous period;

[0084] c. Calculate the variance of the heating power fluctuation data of each single well as the total heating power fluctuation in the metering station.

[0085] The total return oil line pressure fluctuation is obtained as follows:

[0086] d. Obtain the single well return oil pipeline pressure data based on the single well production data;

[0087] e. Calculate the single well return oil pipeline pressure fluctuation data, the single well return oil pipeline pressure fluctuation data is a single well return oil pipeline pressure data for a period of time and the difference between the single well return oil pipeline pressure data for the previous period;

[0088] f. Calculate the variance of the return oil pipeline pressure fluctuation data of each single well as the total return oil pipeline pressure fluctuation in the metering station.

[0089] Specifically, if Figure 3 The calculation process of fitness is shown in the figure. First, the single well heating power fluctuation dW[i][j] and the return oil pipeline pressure fluctuation dP[i][j] are calculated according to the following formula:

[0090] dW[i][j]=W[i][j]-W[i-1][j],

[0091] dP[i][j]=P[i][j]-P[i-1][j];

[0092] This step is used to obtain the fluctuation difference between the power in the current time period and the power in the previous time period, and the fluctuation difference between the return oil pipeline pressure in the current time period and the previous time period for the well numbered j in the i-th time period.

[0093] Secondly, the variance of heating power fluctuation S2dW[] and the variance of return oil pipeline pressure fluctuation S2dP[] are calculated according to the following formula:

[0094]

[0095]

[0096] This step is used to obtain the variance of the power fluctuations of all single wells in the metering station and the variance of the fluctuations of the return oil pipeline pressures of all single wells in the i time period.

[0097] Finally, δW=S2dW[i], δP=S2dP[i] are output, that is, the total heating power fluctuation and pressure fluctuation in time period i are obtained as the adaptability value.

[0098] S103, calculating the current total heating power fluctuation and the total oil return line pressure fluctuation and setting them as the initial fitness thresholds α=δW, β=δP.

[0099] S104, selecting a target well according to a preset well selection rule, wherein the preset well selection rule is configured to set a candidate priority of a single well according to liquid production, oil content, and shelving status.

[0100] Furthermore, the target well is selected according to the preset well selection rules, including:

[0101] a. Sort the liquid production of the single wells under the metering station, and assign an initial value to the priority vector of the single well according to the sorting result;

[0102] b. Filter the priority vector based on the preset priority threshold, and set the well selection vector of the filtered single well to 1;

[0103] c. Perform a round of adjustments on all single wells. If the priority vector of a single well is not the highest level, it will be promoted one level. If the number of rounds of selection of a single well exceeds the specified threshold, the priority of the single well is set to the lowest, and the well selection vector of this round is output.

[0104] Specifically, if Figure 4 The figure shows the process of single well selection, which includes:

[0105] The preprocessing process is to sort the liquid production of the single wells under the jurisdiction of a certain metering station (room) when the system is started for the first time, and assign an initial value to the priority vector C[] according to the sorting result.

[0106] The first step is to set the well selection vector according to the well selection criteria; the algorithm for this step is: select wells with priority C[i]≥C0. If the condition is met, the well selection vector SW[i]=1, otherwise SW[i]=0. In the present invention, C0 is a priority constant. For example, if the priority is set to 1, 2, 3, ..., 10, 10 priorities, the priority constant C0=5, then the single well with priority ≥5 is the selection target. The initial physical meaning of C0 is the dividing point of the liquid production, that is, the classification of the liquid production. However, in order to avoid some wells from being unable to be selected for a long time and unable to participate in the system-level adjustment, a priority rotation mechanism is set: for the selected well, the well selection round vector is added by 1, that is, SC[i]=SC[i]+1; if the reset round number is reached, that is, SC[i]≥N, then the priority vector C[i]=0, that is, the priority is set to the lowest. Repeat this process until all the single wells under the jurisdiction of the metering station are circulated once according to this rule.

[0107] Finally, when this round of selection ends, if C[i] is not the highest priority, the priority vector C[i]=C[i]+1 is promoted one level, and the well selection vector result SW[] of this round is output.

[0108] S105, setting a new wellhead control temperature for the single well according to the production situation, and outputting heating power according to the new wellhead control temperature to generate next generation production data;

[0109] Furthermore, a new wellhead control temperature is set for a single well according to production conditions, including:

[0110] a. Construct a fitting prediction model of the wellhead control temperature of each single well under the metering station and the total return oil pipeline pressure fluctuation, wherein the fitting prediction model is used to describe the linear mapping relationship between the wellhead control temperature of each single well and the total return oil pipeline pressure fluctuation;

[0111] b. Obtaining historical observation data and bringing it into the fitting prediction model to obtain a coefficient equation group, wherein the historical observation data includes the wellhead control temperature and total return oil pipeline pressure fluctuations of a single well extracted in multiple time periods;

[0112] c. solving the coefficient equations and updating the coefficients of the fitted prediction model based on the results;

[0113] d. Bring the wellhead control temperature under the current production conditions into the fitting prediction model after the coefficient is updated to obtain the total return oil pipeline pressure fluctuation at this time;

[0114] e. Determine whether the current total return oil pipeline pressure fluctuation is smaller than the total return oil pipeline pressure fluctuation obtained by the wellhead control temperature set in the previous round. If so, output the current wellhead control temperature.

[0115] Specifically, if Figure 5 The figure shows the process of setting the temperature of a single well, which includes:

[0116] The first step is to read the number of wells m under the metering station (room) and retrieve the corresponding fitting prediction model function (1) of δP and set temperature T[]:

[0117] δP=a[0]T[0]+a[1]T[1]+…+a[m-1]T[m-1]+a[m], where the coefficient vector A[] already has an initial value.

[0118] The second step is to read n groups of observation data records (the set temperature T[] of all wells and the corresponding return oil pipeline pressure fluctuation δP[] during this period are a group of record data). At this time, the set temperature data matrix TC[][] is obtained. For example: TC[i][j] means: the set temperature of the well numbered i at the jth moment:

[0119]

[0120] The third step is to perform Cholesky decomposition on the set temperature matrix TC[][]. If the decomposition fails, the coefficient vector A[] will not be updated; if the decomposition is not normal, the equation is solved:

[0121] The numerical (analytical) solution of is used to update the coefficient vector A[].

[0122] The fourth step is to generate a set of set temperature data T[] according to the current production conditions and bring them into the prediction model function (1) to predict whether the change trend of δP at this time is smaller than that of the previous round. If it is satisfied, this set of set temperature data T[] is output; in addition, each iteration makes a small step correction to the set temperature data T[] until the iteration cycle T is reached, and the last set temperature data T[] is output.

[0123] S106, obtaining new total heating power fluctuation and total oil return pipeline pressure fluctuation according to the new generation production data, and judging again whether the new total heating power fluctuation and total oil return pipeline pressure fluctuation meet the preset fitness threshold. If the preset fitness requirement is not met, judging again whether the stop condition is met. If the stop condition is met, outputting the wellhead control temperature setting value of each single well in the current working condition as the optimal control scheme, otherwise executing S107;

[0124] S107. Adjust the candidate priority of the single well according to the new generation production data, and execute S104.

[0125] Furthermore, the joint control method comprises the following steps:

[0126] S108, classifying each metering station under the jurisdiction of the central processing station, and optimizing the wellhead control temperature of each metering station according to the classification result; the classification of each metering station under the jurisdiction of the central processing station specifically includes:

[0127] a. Read the production data of the single wells under the jurisdiction of each metering station, the production data including the power consumption of the single well, the production of the single well and the distance from the single well to the metering station; calculate the liquid production distance and power demand according to the power consumption of the single well, the production of the single well and the distance from the single well to the metering station, the liquid production distance is the weighted average of the liquid production of the single well multiplied by the distance from the well to the metering station, and the power demand is the weighted average of the power consumption of the single well and the liquid production;

[0128] b. normalizing the production distance and power demand, establishing a linear fitting function with the normalized production distance and power demand as characteristic values ​​and bringing it into the activation function;

[0129] c. Perform two-class classification three times, calculate the regression coefficients of the corresponding categories, and finally output the updated classification regression coefficient matrix of the metering station;

[0130] d. According to the classification regression coefficient matrix of the metering station, the characteristic values ​​of the liquid production distance and power demand of the metering station to be classified are processed to obtain the classification results.

[0131] The scheme of this embodiment is suitable for medium and large central processing stations (CPF). Since the management level of CPF is higher, its dispatchable system resources will be more abundant. Therefore, the universality of the control scheme generated by the system will also be higher, and the control scheme library established by it can better guide the management of metering stations (rooms). First, the scale of the metering station (OGM) is classified into three levels of "large, medium and small". Classifying OGM in this way can shorten the iteration cycle and determine the optimal solution as soon as possible: for example, different control schemes can be used when adjusting OGMs of the same scale, or the same scheme can be used for control in OGMs of different scales. In this way, N schemes can be carried out in parallel at one time, effectively reducing the time cost required for control. Secondly, extract the characteristic values ​​of the single wells under the jurisdiction of the same OGM: they are the production distance and power demand, and perform data normalization processing on them, establish a fitting correlation function to classify OGMs, establish a model function, and continuously correct the coefficient vector, so as to accurately classify and archive OGMs with similar working conditions. Finally, the optimized selected control scheme can be set as the initial scheme for the same type of OGM control and participate in the iteration of a new round of control schemes, which can effectively shorten the iteration time of control schemes for similar working conditions and continuously optimize the existing control scheme library.

[0132] Specifically, Figure 6 A flow chart of metering station classification is given, and the main processes include:

[0133] The first step is to read the production data and the number of wells m under the jurisdiction of a metering station;

[0134] Extract the single well production Pd[] and the distance to the metering station Ds[] to calculate the production distance Pd_Ds[] and power demand PW_Dm[] respectively:

[0135]

[0136] Sum the liquid production, and the liquid production distance function is: Its meaning is: the liquid production of a single well multiplied by the distance from the well to the metering station (room) and the weighted average of the liquid production.

[0137] The power demand function is

[0138] Its meaning is: the power consumption of a single well is weighted to the liquid production and averaged. Based on this method, the liquid production distance Pd_Ds[] and power demand PW_Dm[] of all metering stations (rooms) are calculated.

[0139] The second step is to process the data of the production distance Pd_Ds[] and the power demand PW_Dm[]; the data of the production distance Pd_Ds[] and the power demand PW_Dm[] are normalized:

[0140]

[0141] Taking the production distance as an example, first, calculate the maximum value MAX(Pd_Ds[]) and the minimum value MIN(Pd_Ds[]) of the production distance, and then use the increment between Pd_Ds[i] and the minimum value to divide the data by the difference between the maximum and minimum values ​​to normalize the data.

[0142] The third step is to use the liquid production distance Pd_Ds_norm[] and the power demand PW_Dm_norm[] as the characteristic values ​​to establish a fitting function and bring it into the activation function; the fitting related function (2) is:

[0143] Z[i]=w1·Pd_Ds_norm[i]+w2·PW_Dm_norm[i]+w0,

[0144] The activation function (3) is:

[0145]

[0146] The fourth step is to perform three binary classifications and call the regression coefficient calculation subroutine of the corresponding category, and finally output the updated regression coefficient matrix w[] of the metering station classification (0, 1, 2).

[0147] like Figure 7 As shown in the figure, it is a flow chart for calculating the regression coefficient vector. The main process includes:

[0148] The first step is to call the corresponding Loss[x] function according to the metering station type (x=0, 1, 2):

[0149]

[0150] The second step is to use an iterative method to numerically solve the coefficient vector w[x][]: First, correct the coefficient vector w[i]: W[i] = W[i]-λ·W[i], and use a numerical method to calculate the gradient of w[i]:

[0151]

[0152] If the gradient converges downward, it means that the correction direction of λ is correct (otherwise, change the correction direction), and then use the correction vector to calculate Loss[x] until the output value of Loss[x] meets the error requirement (ERR) or reaches the iteration cycle, and outputs the current type of regression variable w[x][].

[0153] After that, as long as the characteristic values ​​of the production distance and power demand of the wells under the control of the metering room are normalized, it can be judged according to the regression coefficient matrix whether it can be classified into (0, 1, 2), and then the corresponding control plan can be conveniently called.

[0154] In addition, the heating belt used in the prior art is installed on the outside of the oil pipe, so there are the following problems: ① The existing solution requires the use of cable ties and protective covers to fix the heating belt on the oil pipe. Due to the large number of cable ties and protective covers, the installation efficiency is low, and there is a great risk of falling into the well when installing in inclined wells, horizontal wells, etc.; ② With the deepening of unconventional oil and gas development such as water gas and shale oil and gas, the requirements for pressurized operations are increasing day by day, and the installation process of the existing solution is difficult to safely achieve pressurized operations; ③ Since the heating mechanism of the existing solution is resistive heating, heating is carried out by heat conduction, the energy transfer is non-directional, more energy is dissipated, the temperature field establishment time is long, and the energy consumption is high.

[0155] In order to solve the above problems, the present application optimizes the hardware structure of the heating device. Figure 8-9 As shown, the heating device includes a battery core, a core wire sheath and an induction steel armor, wherein the induction steel armor is a longitudinally wrapped structure, the battery core is arranged inside the induction steel armor, and the core wire sheath is filled between the induction steel armor and the battery core; the blind end of the induction steel armor is arranged to be a curved structure adapted to the specifications of the oil pipeline; the side opening end of the induction steel armor is arranged opposite to the blind end, and the side opening end is a double-stacked structure. A plurality of parallel air gaps are laterally engraved on the double-stacked structure of the side opening end.

[0156] Specifically, the blind end of the induction steel armor is designed as a curved structure with a radius R Tube Designed according to the specifications of the installed oil pipe, as shown in Table 1, it can effectively fit the oil pipe. In addition, this curved structure also increases the rigidity of the induction steel armor, which can prevent the electric heating component from bending in the direction away from the oil pipe. Therefore, it can effectively reduce the number of binding steel belts, improve installation efficiency, and solve the problem of too many binding steel belts and high risk of falling into the well in the existing solution. The open end of the induction steel armor is designed as a double-stack structure, which can effectively reduce the risk of mechanical damage caused by impact, collision, etc. during the process of going down the well. It can replace the installation of the protective cover in the existing solution. During pressure operation, it can effectively avoid accumulation and pressure holding caused by the falling of the protective cover, and can also greatly reduce the risk of failure of the slip rubber core.

[0157] Table 1 Reference table of circular curvature radius and common oil pipe nominal size

[0158]

[0159] The induction steel armor is provided with a blind end and an open end, and an air gap, and is designed as shown in Table 2: In order to reduce the skin effect of the battery cell when working at a medium frequency, the battery cell adopts a multi-strand twisted wire and is designed to be multi-core parallel power supply, and the appropriate size is selected according to the working frequency In addition, the induction armor should also select the appropriate thickness (δ) and air gap width (σ) according to the designed working frequency; when an alternating current is passed through the battery core, an alternating magnetic field will be generated around it, and then an induced current will be generated in the induction steel armor. Since there is an air gap on the open end, the thermal effect of part of the induced current will be blocked, which is similar to the role of transformer core laminations. In this way, the heat dissipated by the electric heating component to the surrounding environment can be effectively reduced, and the heat energy can be effectively applied to the oil pipe, thereby saving energy consumption.

[0160] Table 2 Comparison table of heating component design parameters and main operating frequencies

[0161]

[0162] Fig. 9 It is a schematic diagram of the terminal structure of the present invention, wherein the electric heating component body and the terminal protection cover are sealed by injection molding, and the battery core and the induction armor are reliably connected by a transition adapter.

[0163] Figure 1 This is the system architecture diagram used in this embodiment. The system takes all oil wells under the jurisdiction of a joint station as the research object, establishes an oil well production status database, takes each metering station as the control object, and uses a set of adaptive algorithms to provide the optimal solution with the lowest energy consumption to adapt to the current production conditions.

[0164] In addition to participating in the closed-loop control of the temperature of the single-well output fluid, the single-well control cabinet can also summarize the remaining production metering data of the well, package it into a data message and transmit it back to the data center (the central control computer in the station). In addition to collecting the production metering data of the single well, the central control computer in the station also uses an adaptive algorithm to output control instructions according to the set control target, intervene in the set parameters of the single-well control cabinet, and coordinate the allocation of power output requirements so that the return oil pressure of the manifold meets the safety production requirements.

[0165] A specific implementation example is given below: the main components in the single well control cabinet are selected as follows: the temperature controller uses AI-719P produced by Xiamen Yudian Automation Technology Co., Ltd., the frequency converter uses MF100-180A-4 produced by Shenzhen Yingwei Electric Co., Ltd., the capacitor uses MKP-LS type produced by Foshan Shunde Chuangge Electronic Industrial Co., Ltd., the medium frequency transformer is a self-made toroidal transformer, and the iron core is an iron-based nano-amorphous alloy (working frequency band 0.8~2.5kHz) customized by Foshan Zhongyan Amorphous Technology Co., Ltd., and the RTU module uses CPU401-1202 produced by Aoto Technology Co., Ltd.; the data acquisition and monitoring control system (SCADA) of the hollow machine in the station uses NAControl cross-platform software of Aoto Technology Co., Ltd., which can be perfectly combined with domestic operating systems (such as Kylin series) and domestic hardware (CPU represented by Loongson, Feiteng, Zhaoxin, etc.), which can greatly broaden the application field of the system.

[0166] The present invention also discloses an oil well heating, wax removal and viscosity reduction joint control system, the system comprising:

[0167] An initialization unit, which is used to obtain the initialization data of the single well under the jurisdiction of each metering station, wherein the initialization data includes the initial wellhead control temperature of the single well; and control the heating device to perform heating according to the initial wellhead control temperature;

[0168] A production data acquisition unit, which is used to acquire production data of a single well, wherein the single well production data acquires total heating power fluctuation and total oil return line pressure fluctuation, wherein the total heating power fluctuation is used to characterize the change of total heating power in the metering station over time, and the total oil return line pressure fluctuation is used to characterize the change of total oil return line pressure in the metering station over time;

[0169] A first judgment unit, which is used to judge whether the total heating power fluctuation and the total oil return line pressure fluctuation meet a preset fitness threshold. If the preset fitness requirement is not met, a target well is selected according to a preset well selection rule, wherein the preset well selection rule is set to set a candidate priority of a single well according to liquid production, oil content and shelving status;

[0170] An optimization unit, which is used to set a new wellhead control temperature for a single well according to production conditions, and output heating power according to the new wellhead control temperature to generate next generation production data;

[0171] The second judgment unit is used to obtain new total heating power fluctuations and total oil return line pressure fluctuations according to the new generation of production data, and judge again whether the new total heating power fluctuations and total oil return line pressure fluctuations meet the preset fitness thresholds. If the preset fitness requirements are not met, it is judged whether the stop condition is met. If the stop condition is met, the wellhead control temperature setting value of each single well in the current working condition is output as the optimal control solution;

[0172] The priority adjustment unit is used to adjust the candidate priority of the single well according to the new generation production data.

[0173] As for the embodiment of the joint adjustment and control device of the oil well heating system of the present invention, since it corresponds to the embodiment of the joint adjustment and control method of the oil well heating system above, the description is relatively simple. For the relevant similarities, please refer to the partial description in the embodiment of the joint adjustment and control method of the oil well heating system above, which will not be described in detail here.

[0174] The present invention also discloses an oil well heating, wax removal and viscosity reduction joint control device, the device comprising:

[0175] at least one processor; and,

[0176] a memory communicatively connected to the at least one processor; wherein,

[0177] The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to:

[0178] Acquire the single well initialization data under each metering station, wherein the initialization data includes the initial wellhead control temperature of the single well; control the heating device to perform heating according to the initial wellhead control temperature;

[0179] Acquire production data of a single well, wherein the single well production data acquires fluctuations in total heating power and total oil return line pressure, wherein the fluctuations in total heating power are used to characterize changes in total heating power over time in the metering station, and the fluctuations in total oil return line pressure are used to characterize changes in total oil return line pressure over time in the metering station;

[0180] Determine whether the total heating power fluctuation and the total oil return line pressure fluctuation meet the preset fitness threshold. If the preset fitness requirement is not met, select the target well according to the preset well selection rule, wherein the preset well selection rule is set to set the candidate priority of the single well according to the liquid production, oil content and shelving condition;

[0181] A new wellhead control temperature is set for a single well according to production conditions, and heating power is output according to the new wellhead control temperature to generate next generation production data;

[0182] According to the new generation of production data, the new total heating power fluctuation and the total return oil pipeline pressure fluctuation are obtained, and it is judged again whether the new total heating power fluctuation and the total return oil pipeline pressure fluctuation meet the preset fitness threshold. If the preset fitness requirement is not met, it is judged whether the stop condition is met. If the stop condition is met, the wellhead control temperature setting value of each single well in the current working condition is output as the optimal control solution.

[0183] As for the embodiment of the joint adjustment and control device of the oil well heating system of the present invention, since it corresponds to the embodiment of the joint adjustment and control method of the oil well heating system above, the description is relatively simple. For relevant similarities, please refer to the partial description in the embodiment of the joint adjustment and control method of the oil well heating system above, which will not be described in detail here.

[0184] The present invention also discloses an oil well heating wax removal and viscosity reduction joint control medium, which stores computer executable instructions, and the computer executable instructions are set as follows:

[0185] Acquire the single well initialization data under each metering station, wherein the initialization data includes the initial wellhead control temperature of the single well; control the heating device to perform heating according to the initial wellhead control temperature;

[0186] Acquire production data of a single well, wherein the single well production data acquires fluctuations in total heating power and total oil return line pressure, wherein the fluctuations in total heating power are used to characterize changes in total heating power over time in the metering station, and the fluctuations in total oil return line pressure are used to characterize changes in total oil return line pressure over time in the metering station;

[0187] Determine whether the total heating power fluctuation and the total oil return line pressure fluctuation meet the preset fitness threshold. If the preset fitness requirement is not met, select the target well according to the preset well selection rule, wherein the preset well selection rule is set to set the candidate priority of the single well according to the liquid production, oil content and shelving condition;

[0188] A new wellhead control temperature is set for a single well according to production conditions, and heating power is output according to the new wellhead control temperature to generate next generation production data;

[0189] According to the new generation of production data, the new total heating power fluctuation and the total return oil pipeline pressure fluctuation are obtained, and it is judged again whether the new total heating power fluctuation and the total return oil pipeline pressure fluctuation meet the preset fitness threshold. If the preset fitness requirement is not met, it is judged whether the stop condition is met. If the stop condition is met, the wellhead control temperature setting value of each single well in the current working condition is output as the optimal control solution.

[0190] As for the embodiment of the joint regulation and control medium of the oil well heating system of the present invention, since it corresponds to the embodiment of the joint regulation and control method of the oil well heating system above, the description is relatively simple. For the relevant similarities, please refer to the partial description in the embodiment of the joint regulation and control method of the oil well heating system above, which will not be described in detail here.

[0191] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0192] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0193] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0194] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0195] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling oil well heating, wax removal and viscosity reduction, applied to a three-level production control system, wherein the three-level production control system includes a central processing station, wherein the central processing station has a plurality of metering stations under its jurisdiction, and any of the metering stations has a plurality of single wells under its jurisdiction, wherein a heating device, a power controller and a sensor system are provided in the single well, wherein the power controller is used to adjust the heating power, and the sensor system is used to collect production data of the single well, and wherein: The joint control method comprises the following steps: S101, obtaining the initialization data of the single well under the jurisdiction of each metering station, wherein the initialization data includes the initial wellhead control temperature of the single well; controlling the heating device to perform heating according to the initial wellhead control temperature; S102, obtaining production data of a single well, wherein the single well production data obtains total heating power fluctuation and total oil return line pressure fluctuation, wherein the total heating power fluctuation is used to characterize the change of total heating power in the metering station over time, and the total oil return line pressure fluctuation is used to characterize the change of total oil return line pressure in the metering station over time; S103, calculating the total heating power fluctuation and the total oil return line pressure fluctuation, and setting them as initial thresholds α and β respectively; S104, selecting a target well according to a preset well selection rule, wherein the preset well selection rule is set to set a candidate priority of a single well according to liquid production, oil content, and shelving status; S105, setting a new wellhead control temperature for the single well according to the production situation, and outputting heating power according to the new wellhead control temperature to generate next generation production data; S106, obtaining new total heating power fluctuation and total oil return line pressure fluctuation according to the next generation production data, and judging again whether the new total heating power fluctuation and total oil return line pressure fluctuation meet the preset fitness threshold. If the preset fitness requirement is not met, judging again whether the stop condition is met. If the stop condition is met, outputting the wellhead control temperature setting value of each single well in the current working condition as the optimal control scheme, otherwise executing S107; S107. Adjust the candidate priority of the single well according to the next generation production data, and execute S104.

2. The oil well heating, wax removal and viscosity reduction joint control method according to claim 1 is characterized in that: The total heating power fluctuation is obtained according to the following method: Obtain the heating power data of a single well based on the production data of the single well. Calculate the single well heating power fluctuation data, where the single well heating power fluctuation data is the difference between the single well heating power data in a certain period and the single well heating power data in the previous period. Calculate the variance of the heating power fluctuation data of each single well as the total heating power fluctuation in the metering station; The total oil return line pressure fluctuation is obtained according to the following method: Obtain the single well return oil pipeline pressure data based on the single well production data. Calculate the single well return oil pipeline pressure fluctuation data, where the single well return oil pipeline pressure fluctuation data is the difference between the single well return oil pipeline pressure data in a certain period and the single well return oil pipeline pressure data in the previous period. The variance of the return oil pipeline pressure fluctuation data of each single well is calculated as the total return oil pipeline pressure fluctuation in the metering station.

3. The oil well heating, wax removal and viscosity reduction joint control method according to claim 1, characterized in that: Select target wells according to preset well selection rules, including: Sort the liquid production of the single wells under the metering station, and assign an initial value to the priority vector of the single well according to the sorting result; The priority vector is screened based on a preset priority threshold, and the well selection vector of the screened single well is set to 1; A round of adjustment is performed on all single wells. At this time, if the priority vector of a single well is not the highest level, it will be promoted one level. If a single well is selected more than the specified threshold, the priority of the single well is set to the lowest, and the well selection vector of this round is output.

4. The oil well heating, wax removal and viscosity reduction joint control method according to claim 1, characterized in that: Set a new wellhead control temperature for a single well according to production conditions, including: Constructing a fitting prediction model of the wellhead control temperature of each single well under the metering station and the total oil return pipeline pressure fluctuation, wherein the fitting prediction model is used to describe the linear mapping relationship between the wellhead control temperature of each single well and the total oil return pipeline pressure fluctuation; Obtaining historical observation data and bringing it into a fitting prediction model to obtain a coefficient equation group, wherein the historical observation data includes wellhead control temperature of a single well extracted in multiple time periods and total return oil pipeline pressure fluctuations; Solving the coefficient equations and updating the coefficients of the fitted prediction model based on the results; The wellhead control temperature under the current production conditions is brought into the fitting prediction model after the coefficient is updated to obtain the total return oil pipeline pressure fluctuation at this time; Determine whether the current total return oil pipeline pressure fluctuation is less than the total return oil pipeline pressure fluctuation obtained by the wellhead control temperature set in the previous round. If so, output the current wellhead control temperature.

5. The oil well heating, wax removal and viscosity reduction joint control method according to claim 1, characterized in that: The joint control method comprises the following steps: Classify the metering stations under the central processing station, and optimize the wellhead control temperature of each metering station according to the classification results; the classification of the metering stations under the central processing station specifically includes: Read the production data of the single wells under the jurisdiction of each metering station, the production data including the power consumption of the single well, the output of the single well and the distance from the single well to the metering station; calculate the liquid production distance and power demand according to the power consumption of the single well, the output of the single well and the distance from the single well to the metering station, the liquid production distance is the weighted average of the liquid production of the single well multiplied by the distance from the well to the metering station, and the power demand is the weighted average of the power consumption of the single well and the liquid production; Normalizing the production distance and power requirement, establishing a linear fitting function with the normalized production distance and power requirement as characteristic values ​​and bringing the linear fitting function into the activation function; Perform two-class classification three times, calculate the regression coefficients of the corresponding categories, and finally output the updated classification regression coefficient matrix of the metering station; The liquid production distance and power demand characteristic values ​​of the metering stations to be classified are processed according to the metering station classification regression coefficient matrix to obtain the classification results.

6. The oil well heating, wax removal and viscosity reduction joint control method according to claim 1, characterized in that: The heating device comprises a battery core, a core wire sheath and an induction steel armor, wherein the induction steel armor is a longitudinally wrapped structure, the battery core is arranged inside the induction steel armor, and the core wire sheath is filled between the induction steel armor and the battery core; The blind end of the induction steel armor is set to a curved structure adapted to the specifications of the oil pipeline; a side opening end of the induction steel armor is arranged opposite to the blind end of the induction steel armor, and the side opening end of the induction steel armor is a double-stacked structure.

7. The oil well heating, wax removal and viscosity reduction joint control method according to claim 6, characterized in that: A plurality of parallel air gaps are laterally arranged on the double-stacked structure at the side opening end of the induction steel armor.

8. An oil well heating, wax removal and viscosity reduction joint control system, characterized in that: The system comprises: An initialization unit, which is used to obtain the initialization data of the single well under the jurisdiction of each metering station, wherein the initialization data includes the initial wellhead control temperature of the single well; and control the heating device to perform heating according to the initial wellhead control temperature; A production data acquisition unit, which is used to acquire production data of a single well, wherein the single well production data acquires total heating power fluctuation and total oil return line pressure fluctuation, wherein the total heating power fluctuation is used to characterize the change of total heating power in the metering station over time, and the total oil return line pressure fluctuation is used to characterize the change of total oil return line pressure in the metering station over time; A first judgment unit, which is used to judge whether the total heating power fluctuation and the total oil return line pressure fluctuation meet a preset fitness threshold. If the preset fitness requirement is not met, a target well is selected according to a preset well selection rule, wherein the preset well selection rule is set to set a candidate priority of a single well according to liquid production, oil content and shelving status; An optimization unit, which is used to set a new wellhead control temperature for a single well according to production conditions, and output heating power according to the new wellhead control temperature to generate next generation production data; The second judgment unit is used to obtain new total heating power fluctuations and total oil return line pressure fluctuations according to the next generation production data, and judge again whether the new total heating power fluctuations and total oil return line pressure fluctuations meet the preset fitness threshold. If the preset fitness requirements are not met, it is judged whether the stop condition is met. If the stop condition is met, the wellhead control temperature setting value of each single well in the current working condition is output as the optimal control solution; A priority adjustment unit is used to adjust the candidate priority of a single well according to the next generation production data.

9. An oil well heating, wax removal and viscosity reduction joint control equipment, characterized in that: The device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to: Acquire the single well initialization data under each metering station, wherein the initialization data includes the initial wellhead control temperature of the single well; control the heating device to perform heating according to the initial wellhead control temperature; Acquire production data of a single well, wherein the single well production data acquires fluctuations in total heating power and total oil return line pressure, wherein the fluctuations in total heating power are used to characterize changes in total heating power over time in the metering station, and the fluctuations in total oil return line pressure are used to characterize changes in total oil return line pressure over time in the metering station; Determine whether the total heating power fluctuation and the total oil return line pressure fluctuation meet the preset fitness threshold. If the preset fitness requirement is not met, select the target well according to the preset well selection rule, wherein the preset well selection rule is set to set the candidate priority of the single well according to the liquid production, oil content and shelving condition; A new wellhead control temperature is set for a single well according to production conditions, and heating power is output according to the new wellhead control temperature to generate next generation production data; According to the next generation of production data, new total heating power fluctuations and total return oil pipeline pressure fluctuations are obtained, and it is judged again whether the new total heating power fluctuations and total return oil pipeline pressure fluctuations meet the preset fitness thresholds. If the preset fitness requirements are not met, it is judged whether the stop conditions are met. If the stop conditions are met, the wellhead control temperature setting value of each single well in the current working condition is output as the optimal control solution.

10. An oil well heating wax removal and viscosity reduction joint control medium, storing computer executable instructions, characterized in that: The computer executable instructions are configured to: Acquire the single well initialization data under each metering station, wherein the initialization data includes the initial wellhead control temperature of the single well; control the heating device to perform heating according to the initial wellhead control temperature; Acquire production data of a single well, wherein the single well production data acquires fluctuations in total heating power and total oil return line pressure, wherein the fluctuations in total heating power are used to characterize changes in total heating power over time in the metering station, and the fluctuations in total oil return line pressure are used to characterize changes in total oil return line pressure over time in the metering station; Determine whether the total heating power fluctuation and the total oil return line pressure fluctuation meet the preset fitness threshold. If the preset fitness requirement is not met, select the target well according to the preset well selection rule, wherein the preset well selection rule is set to set the candidate priority of the single well according to the liquid production, oil content and shelving condition; A new wellhead control temperature is set for a single well according to production conditions, and heating power is output according to the new wellhead control temperature to generate next generation production data; According to the next generation of production data, new total heating power fluctuations and total return oil pipeline pressure fluctuations are obtained, and it is judged again whether the new total heating power fluctuations and total return oil pipeline pressure fluctuations meet the preset fitness thresholds. If the preset fitness requirements are not met, it is judged whether the stop conditions are met. If the stop conditions are met, the wellhead control temperature setting value of each single well in the current working condition is output as the optimal control solution.

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