Composite plugging removing agent for oil and gas field and preparation method thereof

Abstract

This invention discloses a composite unblocking agent for oil and gas fields and its preparation method, belonging to the field of chemical unblocking agent production technology in petrochemicals. This method aims to solve the technical problem of large batch-to-batch variations in product performance caused by the crude control of key parameters and reliance on manual experience in traditional preparation processes. The key to its technical solution lies in achieving precise preparation through step-by-step dynamic control: firstly, the chelating agent is pretreated with alkali in a first reactor while simultaneously controlling the temperature and stirring speed; then, the pretreated mixture is transferred to a second reactor, and a penetrant is added sequentially under controlled conditions to obtain a first mixture; next, a scale inhibitor and dispersant is added under controlled weight loss balance to obtain a second mixture; finally, a programmed segmented heating reaction is performed to obtain the final product. This method is mainly used for the efficient and stable preparation of a composite unblocking agent for removing inorganic scale from pipelines and equipment in oil and gas fields.

Description

Technical Field

[0001] This invention relates to the field of chemical unblocking agent production technology in petrochemicals. More specifically, this invention relates to composite unblocking agents for oil and gas fields and their preparation methods. Background Technology

[0002] In the oil and gas extraction and transportation processes in the petrochemical industry, inorganic salt scale, such as calcium carbonate and calcium sulfate, often forms in the formations and pipelines. The accumulation of this scale can severely clog pipelines and equipment, reduce transmission efficiency, exacerbate corrosion risks, and even pose safety hazards. Therefore, using chemical unblocking agents is an important technical means to maintain the normal operation of production systems.

[0003] Traditional descaling agent manufacturing processes typically focus on developing new effective chemical components to enhance scale-dissolving capabilities. However, in the process of transforming these laboratory formulations into stable and reliable industrial products, some fundamental process challenges have long existed that affect the consistency of product performance and the controllability of production. These challenges have constrained the large-scale, high-quality production of highly efficient descaling agents.

[0004] Firstly, in the pretreatment stage of the core raw materials for unblocking agents, especially in the compounding and activation process involving multiple chelating agents, the reaction efficiency is highly dependent on the pH and temperature of the mixed system. Conventional production methods often use a one-time addition of alkali solution for rough adjustment, followed by overall heating via steam or coils. Due to the lack of real-time, precise control over the pH and temperature within the reactor, the reaction environment is actually in a fluctuating state. This leads to inconsistent activation levels of chelating agents in different batches, directly affecting the chemical activity and uniformity of the core components of the final product, becoming one of the main sources of batch-to-batch performance differences. The difficulty in achieving such precise control lies in the fact that acid-base reactions themselves have nonlinear and hysteretic characteristics. Simple on / off or proportional adjustments can easily cause pH over-adjustment or oscillations, and the reaction temperature and pH value are mutually influential, making the stable control of a dynamic chemical reaction environment complex.

[0005] Secondly, the compounding stage of the unblocking agent involves the sequential addition and mixing of various functional additives such as penetrants and scale inhibitors / dispersants. This process not only requires the precise proportions of each component to be added, but more importantly, it requires control of the physical conditions of the addition process itself. For example, if the addition rate of solid scale inhibitors / dispersants is not properly controlled, it may lead to uneven dispersion in the system, forming local agglomerates and affecting its full functionality. Traditional production methods rely on the operator's experience to manually control the feeding or use simple mechanical feeding devices, making it difficult to guarantee a high degree of repeatability of the feeding rate and real-time matching of the rate and stirring intensity. The difficulty lies in achieving continuous, stable, and repeatable control of minute mass flow rates and immediate detection of abnormal conditions (such as blockage or flow interruption). This requires high-precision integration and linkage of weighing, control, and execution units, which places higher demands on conventional chemical equipment.

[0006] Furthermore, during the pH fine-tuning and maturation reaction stages before final product shaping, process conditions significantly impact the final product state. The final pH adjustment needs to reach a narrow target range (e.g., 8.0 to 9.0) and remain stable within this range. The traditional manual "add-measure-add again" approach is inefficient and struggles to achieve precise stability. Subsequent maturation reactions often require following specific temperature programs, such as staged heating to control the reaction process. In conventional production, achieving this programmed heating process and ensuring consistent duration and mixing intensity at each temperature plateau also relies on manual operation and monitoring, making it difficult to avoid human error and environmental interference. The core challenge here is how to transform multiple discrete process parameters (pH value, heating curve, stirring speed) that depend on manual judgment and operation into a continuously executed, closed-loop feedback process with rigorous logic.

[0007] In summary, the main challenge in producing composite unblocking agents for oil and gas fields using existing technologies is not entirely finding new chemical formulations, but rather how to stably reproduce known effective formulations on an industrial scale through a highly controllable, repeatable, and adaptive process. The core difficulties lie in: 1) achieving high-precision dynamic stability control of key chemical reaction environments (pH, temperature); 2) achieving precise rate program control of solid material addition; 3) achieving programmed condition management and coordination of multi-step processes; and 4) enabling the automated control system itself to adapt to process nonlinearity, overcome its own limitations (such as integral saturation), and intelligently respond to different operating conditions. These challenges lead to uncertainties in the performance consistency and reliability of the produced unblocking agents, potentially affecting the prediction and evaluation of unblocking effects in field applications. Summary of the Invention

[0008] This invention provides a method for preparing a composite unblocking agent for oil and gas fields, which uses the following control system to achieve multi-parameter coordinated dynamic control: the control system includes a first reaction vessel, a second reaction vessel, a first pH sensor, a second pH sensor, a temperature control unit, an automatic sodium hydroxide solution replenishment unit, a loss-in-weight balance, a metering pump, and a controller; The method includes the following steps: S1. The chelating agent and a sodium hydroxide solution with a mass concentration of 5% to 10% are mixed in a first reactor at a mass ratio of 1:2 to 1:4. The pH value of the mixture in the first reactor is monitored in real time by a first pH sensor, and the automatic sodium hydroxide solution replenishment unit is controlled in a closed-loop control manner based on the monitoring signal to dynamically control the pH value of the mixture within the range of 10.0 to 11.0. At the same time, the reaction temperature in the first reactor is dynamically controlled at 50°C to 60°C by a temperature control unit. Under these pH and temperature conditions, the mixture is stirred at a stirring speed of 200 rpm to 300 rpm for 20 min to 30 min to obtain a pretreated chelating agent mixture. S2. The pretreated chelating agent mixture and deionized water are pumped into the second reactor at a mass ratio of 1:5 to 1:10. In the second reactor, the mixture is stirred at a stirring speed of 250 rpm to 350 rpm for 15 min to 25 min to form a uniform chelating agent solution. A penetrant for reducing surface tension is added, wherein the mass ratio of the penetrant to the chelating agent is 0.1:1 to 0.5:1. The temperature in the second reactor is dynamically controlled at 35°C to 45°C by a temperature control unit, and the mixture is stirred at a stirring speed of 250 rpm to 350 rpm for 25 min to 35 min to obtain the first mixture. S3. Through the linkage between the loss-in-weight balance and the control system, the scale inhibitor and dispersant used for complexation and solubilization are gradually added to the first mixture in the second reactor at a rate of 5 g / min to 10 g / min. The total mass ratio of the scale inhibitor and dispersant to the chelating agent is 0.05:1 to 0.2:1. During this feeding process, the stirring speed in the second reactor is dynamically maintained at 250 rpm to 350 rpm to obtain the second mixture. The pH value of the mixture in the second reaction vessel is monitored in real time using a second pH sensor, and a 5% sodium hydroxide solution or hydrochloric acid solution is automatically added by a metering pump to dynamically adjust and stabilize the pH value of the mixture in the range of 8.0 to 9.0; then a solubilizer to improve solubility is added, and the volume ratio of the solubilizer to the total mixture is 1:100 to 5:100. S4. The temperature of the mixture in the second reactor is raised to 45°C to 50°C within 10 minutes using a temperature control unit, and the mixture is reacted at a stirring speed of 150 rpm to 250 rpm within this temperature range for 40 minutes to 60 minutes. Subsequently, the temperature is raised to 55°C to 60°C within 10 minutes again using a temperature control unit, and the mixture is reacted at a stirring speed of 150 rpm to 250 rpm within this temperature range for 50 minutes to 70 minutes to obtain the composite unblocking agent.

[0009] Preferably, the chelating agent is composed of aminotriacetic acid and disodium ethylenediaminetetraacetate, and the mass ratio of the two is 1:1.5 to 1:2.5; the particle size distribution D90 of the aminotriacetic acid is not greater than 75 μm, and the free acid content of the disodium ethylenediaminetetraacetate is not greater than 0.5%.

[0010] Preferably, the penetrant is sodium dodecylbenzenesulfonate, the scale inhibitor and dispersant is sodium hexametaphosphate, and the solubilizer is isopropanol.

[0011] Preferably, in step S3, the process of dynamically adjusting and stabilizing the pH value of the mixture within the range of 8.0 to 9.0 by the control system specifically includes: monitoring the pH value of the mixture in real time by the second pH sensor, and the controller driving the metering pump to automatically add sodium hydroxide solution or hydrochloric acid solution with a mass concentration of 5% according to the monitoring signal, so as to quickly adjust the pH value to the range of 8.5±0.3. Subsequently, the controller switches to fine-tuning mode and uses a PID algorithm to fine-tune the pH value to maintain it within the target range of 8.0 to 9.0 for at least 5 minutes, with fluctuations of less than ±0.05.

[0012] Preferably, the automatic sodium hydroxide solution replenishment unit includes a controller, a metering pump, and a high-precision flow meter; the controller receives the signal from the first pH sensor, calculates the replenishment flow rate according to a preset PID control algorithm to drive the metering pump, and receives the feedback signal from the flow meter for closed-loop correction.

[0013] Preferably, the supplementary flow rate is calculated based on a preset PID control algorithm, specifically including the following steps: The current pH value of the mixture monitored by the first pH sensor is acquired in real time; The current pH value is compared with the preset pH target value of 10.5, and the deviation value e(t) is calculated, where e(t) = 10.5 - current pH value; Based on the deviation value e(t), the supplementary flow command u(t) is calculated using the PID control algorithm. The expression of the PID control algorithm is: u(t) = Kp × e(t) + Ki × ∫e(t)dt + Kd × de(t) / dt; where Kp is the proportional coefficient, with a value of 0.8 to 1.2; Ki is the integral coefficient, with a value of 0.02 to 0.05; and Kd is the derivative coefficient, with a value of 0.1 to 0.3. The supplementary flow command u(t) is converted into an analog signal of 4 mA to 20 mA or a corresponding pulse frequency signal, which is used as a control signal to drive the metering pump to run at the corresponding speed. The flow rate of the metering pump is linearly related to the control signal. During the replenishment process, the temperature of the mixture inside the first reaction vessel is monitored in real time, and the current pH value measured by the first pH sensor is corrected by a temperature compensation unit. The correction formula is: pH c =pH m +α×(T-25), where pH c The corrected pH value, pH m The value measured by the sensor is T, which is the real-time temperature, and α is the temperature compensation coefficient, which is 0.003 pH / ℃. The corrected pH value is used as the current pH value for calculating the deviation value of the PID control algorithm.

[0014] Preferably, the PID control algorithm is a variable parameter algorithm with anti-integral saturation and parameter self-tuning functions: When the calculated value of the supplementary flow command u(t) exceeds the operating range of the metering pump, the integral term is locked; Furthermore, the proportional coefficient Kp, integral coefficient Ki, and derivative coefficient Kd are adjusted in segments according to the absolute value of the real-time deviation e(t): When |e(t)|>0.5, the first set of parameters is used, where Kp=1.2, Ki=0.02, and Kd=0.3; When 0.1 < |e(t)| ≤ 0.5, the second set of parameters is used, where Kp = 1.0, Ki = 0.035, and Kd = 0.2; When |e(t)|≤0.1, the third set of parameters is used, where Kp=0.8, Ki=0.05, and Kd=0.1.

[0015] Preferably, the segmented adjustment employs a method of adjusting the hysteresis width based on the rate of change of deviation; Set the first switching boundary B1 to 0.5 and the second switching boundary B2 to 0.1; set the deviation change rate threshold R to 0.01 pH / min; determine the real-time hysteresis width through the following steps: Calculate the change rate |Δe| of the absolute value |e(t)| of the real-time deviation; Determine the first hysteresis width W1 and the second hysteresis width W2 according to the comparison result between the change rate |Δe| and the threshold R: if |Δe| ≥ R, then W1 = 0.1 and W2 = 0.08; if |Δe| < R, then W1 = 0.05 and W2 = 0.04.

[0016] Preferably, the switching of parameter groups is performed by the following method: When the system starts or resets, determine the initial parameter group according to the range where the absolute value of the initial deviation |e(t)| is located: If B2 + W2 ≤ |e(t)| ≤ B1 - W1, initially adopt the second group of parameters; If |e(t)| > B1 - W1, initially adopt the first group of parameters; If |e(t)| < B2 + W2, initially adopt the third group of parameters; During the operation process, update the adopted parameter group according to the absolute value of the current deviation |e(t)| and the current hysteresis width by the following steps: If the first group of parameters is currently adopted and |e(t)| ≤ B1 - W1, change to adopt the second group of parameters; If the third group of parameters is currently adopted and |e(t)| ≥ B2 + W2, change to adopt the second group of parameters; If the second group of parameters is currently adopted and |e(t)| > B1, change to adopt the first group of parameters; If the second group of parameters is currently adopted and |e(t)| < B2, change to adopt the third group of parameters.

[0017] The present invention also provides a composite plugging removal agent for oil and gas fields, which is made by the above preparation method.

[0018] The present invention at least includes the following beneficial effects: The composite plugging removal agent for oil and gas fields and its preparation method of the present invention realize the high-precision dynamic control of the pH value of the reaction system by constructing a closed-loop feedback control system including a pH sensor, a controller, a metering pump, and a flowmeter, and overcome the overshoot and oscillation problems caused by traditional open-loop control or manual adjustment. Through the linkage of the loss-in-weight scale and the controller, the precise rate addition of the scale inhibitor is realized, avoiding local agglomeration and ensuring the uniform dispersion of the functional additives. Through the variable parameter PID algorithm and the adaptive hysteresis switching logic, the control system can maintain a stable and precise adjustment quality under different working conditions (fast disturbance / slow disturbance), and the ineffective switching rate is reduced by more than 86.5%. The comprehensive application of the above control system reduces the batch-to-batch variation coefficient of the key performance of the composite plugging removal agent by more than 80%, and fundamentally solves the batch consistency problem in the industrial production of the plugging removal agent.

[0019] Other advantages, objectives and features of the present invention will become apparent in part from the following description, and in part from those skilled in the art through study and practice of the invention. Detailed Implementation

[0020] The present invention will now be described in further detail with reference to specific embodiments, so that those skilled in the art can implement it based on the description.

[0021] It should be understood that terms such as “having,” “comprising,” and “including” as used herein do not exclude the presence or addition of one or more other elements or combinations thereof.

[0022] It should be noted that, unless otherwise specified, the experimental methods described in the following implementation plan are all conventional methods, and the reagents and materials described are all commercially available unless otherwise specified.

[0023] Example 1 The automated control system used in this embodiment includes: a first reaction vessel, a second reaction vessel, a first pH sensor, a second pH sensor, a temperature control unit, an automatic sodium hydroxide solution replenishment unit, a loss-in-weight scale, a metering pump, and a controller. The controller is a Siemens S7-1200 series PLC, and each sensor and actuator is connected to the controller via an analog input / output module.

[0024] A method for preparing a composite unblocking agent for oil and gas fields, under the control of the control system, includes the following specific steps: 1. Dynamic Control of Alkali Pretreatment: In a 1000L first reactor, 80kg of aminotriacetic acid (D90 of 65μm) and 120kg of disodium ethylenediaminetetraacetate (free acid content of 0.3%) were added, followed by 800kg of 8% sodium hydroxide solution. The pH value of the mixture in the first reactor was monitored in real time by a first pH sensor, and the monitoring signal was transmitted to the controller. The controller, based on the monitoring signal, used a closed-loop control method to link the automatic sodium hydroxide solution replenishment unit, dynamically controlling the pH value of the mixture within the range of 10.5±0.2. Simultaneously, the reaction temperature was controlled at 55±1℃ by the temperature control unit. Under these pH and temperature conditions, the mixture was stirred at 250 rpm for 25 min to obtain the pretreated chelating agent mixture.

[0025] 2. Control of Penetrant Addition: Pump all the pretreated mixtures into a 2000L second reactor, add deionized water to a total mass of approximately 1800kg, and stir at 300 rpm for 20 min to form a homogeneous solution. Then add 40kg of sodium dodecylbenzenesulfonate as a penetrant, with a penetrant-to-chelating agent mass ratio of 0.2:1. Control the temperature inside the second reactor at 40±1℃ using a temperature control unit, and continue stirring at 300 rpm for 30 min to obtain the first mixture.

[0026] 3. Precise Dosing of Scale Inhibitor and Dispersant and Fine pH Adjustment: The weight loss rate of sodium hexametaphosphate is monitored in real time using a loss-in-weight scale and the signal is fed back to the controller. The controller then adjusts the feeding mechanism to gradually add 20 kg of sodium hexametaphosphate to the first mixture at a constant rate of 8 g / min. The total mass ratio of the scale inhibitor / dispersant to the chelating agent is 0.1:1. During this feeding process, the stirring speed is dynamically maintained at 300 rpm to obtain the second mixture.

[0027] A second pH sensor was used to monitor the pH value of the mixture in the second reactor in real time, and a 5% hydrochloric acid solution was automatically added via a metering pump to dynamically adjust and stabilize the pH value of the mixture within the range of 8.5 ± 0.2. During the adjustment process, a two-stage fine adjustment was achieved through the control system: first, the pH value was rapidly adjusted to the range of 8.5 ± 0.3, and then switched to fine adjustment mode to keep the pH value stable within the target range of 8.5 ± 0.2 for at least 6 minutes. Finally, 15 L of isopropanol was added as a solubilizer, with a volume ratio of solubilizer to total mixture of 0.83:100.

[0028] 4. Programmed segmented heating reaction: The temperature of the mixture in the second reactor is raised from approximately 40°C to 48°C within 10 minutes using a temperature control unit, and then stirred at 200 rpm for 50 minutes at 48±1°C. Subsequently, the temperature is raised to 58°C again within 10 minutes, and stirring continues at 200 rpm for 60 minutes at 58±1°C. After the reaction is completed, the mixture is cooled to room temperature to obtain approximately 1800 kg of the composite unblocking agent.

[0029] Example 2 Based on Example 1, the automatic sodium hydroxide solution replenishment unit and its control logic in step 1 are further specified.

[0030] The automatic sodium hydroxide solution replenishment unit includes a controller, a diaphragm metering pump, and a Coriolis mass flow meter. The controller receives a signal from a first pH sensor, calculates the replenishment flow rate based on a preset PID control algorithm to drive the metering pump, and receives feedback signals from the flow meter for closed-loop correction. The specific control process is as follows: a. Temperature compensation correction: Read the raw pH value from the first pH sensor. m And the temperature T inside the reactor (measured by PT100), according to the formula pH c =pH m Calculate the temperature-compensated pH value using +0.003×(T-25). c .

[0031] b. Deviation calculation: The pH value... c The deviation e(t) is calculated as follows: e(t) = 10.5 - pH, compared with the preset pH target value of 10.5. c .

[0032] c. PID Calculation: The output u(t) is calculated using a variable-parameter PID algorithm to resist integral saturation: u(t) = Kp × e(t) + Ki × ∫e(t)dt + Kd × de(t) / dt. The parameters are dynamically selected based on |e(t)|. When |e(t)|>0.5, the first set of parameters is used: Kp=1.2, Ki=0.02, Kd=0.3.

[0033] When 0.1 < |e(t)| ≤ 0.5, the second set of parameters is used: Kp = 1.0, Ki = 0.035, Kd = 0.2.

[0034] When |e(t)|≤0.1, the third set of parameters is used: Kp=0.8, Ki=0.05, Kd=0.1.

[0035] When the calculated u(t) exceeds the metering pump range (0-100%), the integral term is locked and no longer accumulated.

[0036] d. Command Output and Feedback Correction: The controller converts u(t) into a 4-20 mA analog signal to drive the metering pump, while simultaneously receiving feedback signals from the mass flow meter. If the deviation between the commanded flow rate and the feedback flow rate continuously exceeds a set threshold, the controller will issue an alarm.

[0037] The other steps are the same as in Example 1.

[0038] The variable parameter PID algorithm used in this invention works as follows: When the deviation is large (|e(t)|>0.5), the system is far from the target value. At this time, a fast response is needed to shorten the settling time. Therefore, the proportional action is strengthened (Kp=1.2) and the integral action is weakened (Ki=0.02) to avoid integral overshoot. When the deviation is small (|e(t)|≤0.1), the system is close to the target value. At this time, fine adjustment is needed to eliminate steady-state error and improve steady-state accuracy. Therefore, the proportional action is weakened (Kp=0.8) and the integral action is strengthened (Ki=0.05). At the same time, the derivative action (Kd=0.1) suppresses overshoot.

[0039] Example 3 On the basis of Example 2, the adaptive logic for parameter group switching in the variable parameter PID algorithm is further refined.

[0040] When performing the variable parameter PID control in Example 2, the parameter switching adopts the method of adjusting the hysteresis width based on the deviation change rate. Set the first switching boundary B1 = 0.5, the second switching boundary B2 = 0.1, and the deviation change rate threshold R = 0.01 pH / min.

[0041] The hysteresis width is determined in real time according to the deviation change rate: calculate the change rate |Δe| of the absolute value of the real-time deviation |e(t)|. If |Δe|≥R, set the hysteresis width W1 = 0.1, W2 = 0.08; if |Δe|<R, set W1 = 0.05, W2 = 0.04.

[0042] The parameter group switching is executed according to the following rules: At system startup, determine the initial parameter group according to the range where the absolute value of the initial deviation |e(t)| is located. If |e(t)|>B1 - W1, initially adopt the first group of parameters; if |e(t)|<B2 + W2, initially adopt the third group of parameters; otherwise, initially adopt the second group of parameters.

[0043] During operation, update the parameter group adopted according to the absolute value of the current deviation |e(t)| and the current hysteresis width: If the first group of parameters is currently adopted and |e(t)|≤B1 - W1, switch to the second group of parameters; If the third group of parameters is currently adopted and |e(t)|≥B2 + W2, switch to the second group of parameters; If the second group of parameters is currently adopted and |e(t)|>B1, switch to the first group of parameters; If the second group of parameters is currently adopted and |e(t)|<B2, switch to the third group of parameters.

[0044] Through the above adaptive hysteresis switching logic, the control system automatically adopts a wider hysteresis width under fast disturbance conditions to avoid frequent jumps of the parameter group near the boundary; under slow disturbance conditions, it automatically adopts a narrower hysteresis width to maintain the sensitivity of regulation.

[0045] Other steps are the same as those in Example 2.

[0046] The automatic sodium hydroxide solution supplementary addition unit can be implemented by adopting the general reaction kettle automation control system architecture in the field.

[0047] The hardware configuration is as follows: (1) Controller selection: This controller employs a Siemens S7-1200 series PLC (such as CPU 1214C) or an equivalent industrial programmable logic controller, with a built-in PID control function block (such as FB1130 "PID_Compact"), supporting floating-point operations and 4-20mA analog I / O. It is widely used for closed-loop control of process quantities such as temperature and pH in chemical reactors.

[0048] (2) Sensors and actuators: pH sensor: Uses high-temperature resistant glass electrode (such as Mettler Toledo InPro4501VP), range 0-14 pH, accuracy ±0.01 pH, with Pt100 temperature sensor, supports automatic temperature compensation; output signal 4-20mA, response time T90≤10s.

[0049] Metering pump: The diaphragm electromagnetic drive metering pump (such as SEKO TPR series) is adopted, with a flow range of 0-20 L / h, a control signal of 4-20mA, and a linearity of flow rate and control signal of ≤±0.5%; the pump head material is PVDF, which is suitable for 5%-10% sodium hydroxide solution.

[0050] Flow feedback element: A Coriolis mass flow meter (such as Siemens SITRANS FC430) is used, with an accuracy of ±0.1% and an output of 4-20mA instantaneous flow signal for closed-loop calibration.

[0051] (3) System integration: The controller acquires signals from the pH sensor and flow meter via an analog input module (such as the SM1231 AI 8×13bit); and sends speed commands to the metering pump via an analog output module (such as the SM1232 AQ 4×14bit). The system supports the OPCUA protocol and can be connected to an enterprise SCADA system for monitoring and data recording.

[0052] Engineering implementation of PID control algorithm Commonly used PLC platforms in this field (such as Siemens TIA Portal V16 and above) have built-in standard PID control function blocks, supporting user-defined proportional, integral, and derivative coefficients, as well as integral term locking logic. The control algorithm described in this invention can be implemented in a PLC through the following steps: (1) Implementation of temperature compensation correction: Execute periodically in the PLC program (sampling period Ts = 1s): pH m := “pH_AI_Channel”; / / Read the converted value of the raw current signal from the pH sensor; T curr:= "Temp_AI_Channel"; / / Read temperature sensor value; pH c := pH m + 0.003 * (T curr - 25.0); / / Linear temperature compensation; This compensation formula is an engineering approximation method for pH electrode temperature compensation, applicable to the 50-60℃ operating range, and the compensation coefficient of 0.003 pH / ℃ is a commonly used empirical value in this field.

[0053] (2) Deviation calculation and PID instruction call: e := 10.5-pH c / / Calculate the deviation (target pH=10.5); "PID_Compact_1".Setpoint := 10.5; / / Set the target value for the PID; "PID_Compact_1".Input := pH_c; / / Input process value; "PID_Compact_1".ManualValue := 0.0; / / Disable manual mode; "PID_Compact_1".Mode := 3; / / Enable automatic mode; "PID_Compact_1"(); / / Call the PID function block; u := “PID_Compact_1”.Output; / / Read output instructions (0-100%); The internal algorithm of the PID function block is implemented in accordance with the IEC 61131-3 standard.

[0054] (3) Implementation of anti-integral saturation (integral term locking): Add integral lock logic outside the PID function block: IF u>= 100.0 OR u<= 0.0 THEN / / Output exceeds the metering pump's operating range (0-100%) "PID_Compact_1".Reset_Integral := TRUE; / / Lock the integral term (stop accumulation) ELSE “PID_Compact_1”.Reset_Integral := FALSE; / / Normal integration END_IF; This logic is executed before each call to the PID function block, which can effectively prevent control lag caused by integral saturation.

[0055] Segmented tuning and switching logic of PID parameters (1) Method for obtaining parameter sets in engineering: The three sets of PID parameters (Kp=1.2 / 1.0 / 0.8, Ki=0.02 / 0.035 / 0.05, Kd=0.3 / 0.2 / 0.1) can be automatically tuned using a relay feedback method well-known in the art. The specific steps are as follows: ① The system is connected to a relay characteristic circuit near the target pH=10.5 to cause the pH value to oscillate with constant amplitude; ② Measure the oscillation period Tu and the critical gain Ku (Ku=4d / πa, where d is the relay output amplitude and a is the fundamental frequency amplitude of the oscillation). ③ Calculate the basic PID parameters according to the Ziegler-Nichols tuning formula: Kc=0.6Ku, Ti=0.5Tu, Td=0.125Tu; ④ Convert the basic parameters into positional PID coefficients, and adjust the proportional gain in segments according to the magnitude of the deviation: Large deviation (|e|>0.5): strengthens the proportional effect (Kp=1.2×Kc_base), weakens the integral (Ki=0.5×Ki_base); Medium deviation (0.1 < |e| ≤ 0.5): Keep the tuning parameters (Kp = 1.0 × Kc_base, Ki = 1.0 × Ki_base); Small deviation (|e|≤0.1): weakening ratio (Kp=0.8×Kc_base), reinforcement integral (Ki=1.4×Ki_base).

[0056] (2) PLC implementation of parameter switching logic: CASE e_abs OF / / e_abs = ABS(e) 0.0 TO 0.1: param_group := 3; / / Third group of parameters (small deviation) 0.1 TO 0.5: param_group := 2; / / Second group of parameters (median deviation) >= 0.5: param_group := 1; / / First group of parameters (large deviation) END_CASE; CASE param_group OF 1: Kp := 1.2; Ki := 0.02; Kd := 0.3; 2: Kp := 1.0; Ki := 0.035; Kd := 0.2; 3: Kp := 0.8; Ki := 0.05; Kd := 0.1; END_CASE; "PID_Compact_1".Gain := Kp; / / Proportional gain "PID_Compact_1".Ti := Ki; / / Integration time (converted to seconds) “PID_Compact_1”.Td := Kd; / / Differential time Hysteresis adaptive logic based on deviation change rate Hysteresis adaptive switching logic aims to avoid frequent jumps in parameter sets near their boundaries. A typical implementation of this logic in industrial control systems is as follows: (1) Calculation of the rate of change of deviation: e_prev := e_curr; / / Store the deviation from the previous cycle e_curr := e; / / Current deviation delta_e := ABS(e_curr - e_prev); / / Absolute value of deviation change IF delta_e>= 0.01 THEN / / Deviation change rate threshold R=0.01 pH / min (converted to sampling period) W1 := 0.1; W2 := 0.08; / / Fast disturbance condition: wide hysteresis loop ELSE W1 := 0.05; W2 := 0.04; / / Slow disturbance condition: narrow hysteresis loop END_IF; When the sampling period is set to 1 second, the deviation change threshold of 0.01 pH / min is equivalent to 0.000167 pH / s. In this embodiment, the absolute value of the deviation change within the sampling period is ≥0.0002 as the judgment criterion.

[0057] (2) Engineering implementation of hysteresis switching logic: CASE param_group OF 1: / / Currently using the first set of parameters IF e_abs<= (0.5 - W1) THEN param_group := 2; / / Downgrade to the second group END_IF; 2: / / Currently using the second set of parameters IF e_abs>0.5 THEN param_group := 1; / / Move up to the first group ELSIF e_abs<0.1 THEN param_group := 3; / / Downgrade to the third group END_IF; 3: / / Currently using the third set of parameters IF e_abs>= (0.1 + W2) THEN param_group := 2; / / Upgrade to the second group END_IF; END_CASE; This logic is executed in each PID calculation cycle to ensure that parameter group switching has hysteresis characteristics and avoid invalid switching caused by measurement noise.

[0058] System step response characteristics and parameter adaptability description The control algorithm described in this invention does not require a complete remodeling for each reactor. Based on process control theory, for a first-order inertial plus pure time delay (FOPDT) reactor, the PID controller parameters can adapt to changes in the reactor gain K, time constant T, and pure time delay τ within a certain range. The transfer function model of the 1000L reactor used in this embodiment, identified through step response testing, is approximately: ; Under this model, the three sets of PID parameters have been verified to meet the following dynamic indices: Large deviation range: fast response (rise time <60s), moderate overshoot is allowed; Medium deviation range: balancing response speed and stability; Small deviation range: steady-state accuracy meets production requirements (pH fluctuation less than ±0.1).

[0059] Comparative Example 1 This comparative example provides a method for preparing a composite unblocking agent for oil and gas fields. Its core process steps are basically the same as in Example 1, except that all technical features in Example 1 involving "dynamic control," "real-time monitoring," "automatic replenishment," and "programmed temperature rise" are replaced with conventional manual operation or open-loop control. Specifically: In step S1, no pH sensor or automatic replenishment unit is used. A theoretically calculated amount of sodium hydroxide solution is added at once, mixed thoroughly, and then a single pH test is performed. If the pH value deviates, alkali solution is manually added and stirred. The reaction temperature is adjusted manually using a valve, with an allowable fluctuation range of ±5℃. In step S3, the scale inhibitor / dispersant is manually weighed and poured into the reactor at once, without real-time flow feedback. pH adjustment is achieved through manual sampling, offline pH meter measurement, and batch addition, repeated until the pH value falls within the 8.0-9.0 range. In step S4, a single-stage isothermal reaction is used: the material is heated to 50±3℃ at once and stirred for 120-150 minutes. The proportions of other raw materials, stirring speed, and reaction time are all consistent with those in Example 1.

[0060] Comparative Example 2 The basic process steps of this comparative example are exactly the same as those in Example 2. The difference is that the variable parameter PID control algorithm used in step S1 is replaced with a conventional fixed parameter PID control algorithm, and the function of adjusting parameters in segments based on the magnitude of the deviation is not set, nor is the integral term locking logic set. Specifically: a set of fixed PID parameters (Kp=1.0, Ki=0.035, Kd=0.2) is used for calculation and output, and no parameter switching is performed regardless of the magnitude of the deviation; the integral term is continuously accumulated, and no anti-integral saturation logic is set.

[0061] Comparative Example 3 The basic process steps of this comparative example are basically the same as those in Example 3, except that the variable parameter PID control with adaptive hysteresis width in step S3 is replaced with a control mode with fixed hysteresis width. Specifically: the hysteresis widths W1 and W2 are both fixed values ​​(W1=0.05, W2=0.04) and are not dynamically adjusted with the rate of change of deviation; no initialization rules based on the initial deviation are set when the system starts up, and the second set of parameters is used by default; parameter group switching is only performed based on the relationship between the absolute value of the deviation and the fixed boundary, and the strategy of maintaining the original parameter group within the hysteresis is not adopted.

[0062] The following comparative tests were conducted on Examples 1-3 and Comparative Examples 1-3. All tests were carried out in the same production environment, and irrelevant variables such as raw material batches, equipment models, and ambient temperature were kept consistent.

[0063] 1. Product batch consistency testing Ten independent batches of the composite unblocking agent were prepared consecutively according to the methods described in Example 1 and Comparative Example 1, respectively.

[0064] Chelation capacity determination: Take 10.0g of each batch of finished product, dilute with deionized water to 100mL, add excess calcium carbonate standard solution, and shake at 25℃ for 30min. After filtration, take the filtrate and determine the residual calcium ion concentration using EDTA complexometric titration. Calculate the number of milligrams of chelated calcium carbonate per gram of product (mg CaCO3 / g). Perform three parallel determinations for each batch and take the average value.

[0065] Surface tension measurement: Dilute each batch of finished product to 1.0 wt% with deionized water and measure the surface tension at 25°C using a fully automatic surface tension meter (platinum plate method). Perform 5 parallel measurements for each batch and take the average value.

[0066] Scale dissolution rate determination: Typical barium sulfate scale samples collected from the oilfield were crushed, sieved (80 mesh), and dried at 105℃ to constant weight. 2.0g of the scale sample was placed in a 100mL Erlenmeyer flask, and 50mL of the tested unblocking agent was added. The mixture was reacted in a 60℃ constant temperature water bath for 4 hours. After filtration, washing, and drying, the mass of the residual scale sample was weighed, and the scale dissolution rate was calculated. Each batch was measured in triplicate, and the average value was taken.

[0067] Data statistics: Calculate the arithmetic mean, standard deviation, and coefficient of variation (CV = standard deviation / mean × 100%) of chelation capacity, surface tension, and scale dissolution rate for 10 batches.

[0068] The test results are shown in Table 1: Table 1 As shown in Table 1, the unblocking agent prepared using the method of Example 1 of this invention exhibits significantly smaller batch-to-batch standard deviations in chelating capacity, surface tension, and scale dissolution rate compared to Comparative Example 1. The coefficient of variation decreased from 6.82%–8.88% in Comparative Example 1 to 1.28%–1.43%, a reduction of over 80%. This reflects that this invention, by constructing a complete automated closed-loop control system, achieves coordinated dynamic control of multiple parameters, fundamentally solving the batch consistency problem in the industrial production of unblocking agents.

[0069] 2. pH dynamic control performance test Following the methods described in Example 2 and Comparative Example 2, automatic sodium hydroxide solution replenishment units and control systems were configured and connected to the same 1000L first reactor, using the same chelating agent and alkali solution ratio. A calibrated online pH meter and a Pt100 temperature sensor were installed inside the reactor.

[0070] The standard pretreatment procedure was performed, with the target pH value set at 10.5 and the reaction temperature at 55°C. The control system of Example 2 (variable parameter PID + anti-integral saturation) and the control system of Comparative Example 2 (fixed parameter PID, no anti-integral saturation) were run respectively, with each control mode being run 5 times.

[0071] Test result comparison: Compared with the conventional fixed-parameter PID control used in Comparative Example 2, the variable-parameter PID control strategy used in Embodiment 2 of the present invention exhibits the following significant advantages: Response speed: The time for both to rise to the target value is basically the same, and both can meet the process requirements; Overshoot control: The pH overshoot in Example 2 was significantly reduced, effectively avoiding drastic pH fluctuations in the system caused by excessive addition of alkali solution; Adjustment efficiency: In Example 2, the adjustment time to reach steady state is significantly shortened, and the system enters a stable working state more quickly; Steady-state accuracy: The pH fluctuation amplitude after entering steady state in Example 2 was significantly reduced, and the control accuracy was significantly better than that in Comparative Example 2.

[0072] The above comparison results show that the variable parameter PID control strategy of the present invention effectively suppresses overshoot, shortens the settling time, and improves the steady-state control quality while maintaining fast response, thus achieving high-precision and high-stability dynamic control of the pH environment in the reactor.

[0073] 3. Parameter switching stability and adaptive capability test Following the methods described in Example 3 and Comparative Example 3, a loss-in-weight balance and a control system were configured and connected to the second reactor to simulate the variable-parameter PID execution process of the pH control system of the first reactor in step S1 (since parameter switching occurs in the pH control of the first reactor in actual production, this test uses hardware-in-the-loop simulation, which is equivalent to the actual pH adjustment process).

[0074] Two typical operating conditions are set up to simulate different disturbance rates: Operating Condition A (Rapid Disturbance): A sinusoidal disturbance signal with an amplitude of 0.2 and a frequency of 0.05 Hz is injected into the pH control system through the program to simulate uneven stirring or fluctuations in feeding.

[0075] Condition B (Slow Disturbance): Inject a sinusoidal disturbance signal with an amplitude of 0.2 and a frequency of 0.005 Hz to simulate the slow drift or natural changes in the sensor's response process.

[0076] The pH control system was run under the adaptive hysteresis logic of Example 3 and the fixed hysteresis logic of Comparative Example 3, respectively, for 10 minutes under each condition. The deviation signal |e(t)| and the parameter group currently used by the controller (Group 1 / Group 2 / Group 3) were recorded.

[0077] Test metrics: Parameter group switching count: The total number of parameter group switching events within 10 minutes.

[0078] Boundary crossing count: Count the number of times |e(t)| crosses the switching boundaries B1=0.5 and B2=0.1 (regardless of whether it is accompanied by parameter switching).

[0079] Invalid switching rate: The percentage of times a parameter group switches back to its original group within 3 seconds after switching to another parameter group out of the total number of switching operations.

[0080] Hysteresis width dynamic change record: For Example 3, record the real-time values ​​of |Δe| and the corresponding W1 and W2 to verify whether they adaptively adjust with the deviation change rate.

[0081] The test results are shown in Table 2: Table 2 As shown in Table 2, under rapid disturbance conditions, Comparative Example 3, due to its narrow fixed hysteresis width, experienced 52 parameter group switching times per 10 minutes, resulting in an ineffective switching rate as high as 38.5%. Example 3, employing the adaptive switching method based on the deviation change rate to adjust the hysteresis width as described in this invention, automatically increased the hysteresis width to W1=0.1 and W2=0.08 due to the larger |Δe|, reducing the number of parameter group switching times by 86.5% and lowering the ineffective switching rate to 2.9%. Under slow disturbance conditions, Example 3 automatically reduced the hysteresis width to W1=0.05 and W2=0.04, achieving an ineffective switching rate of 0%, while Comparative Example 3 still had an ineffective switching rate of 21.4%. The results demonstrate that the variable parameter PID algorithm and adaptive hysteresis switching logic described in this invention enable the control system to maintain stable and accurate regulation quality under different disturbance characteristics.

[0082] In summary, the above comparative tests systematically verified the significant advantages of the embodiments of the present invention compared to the comparative examples from three dimensions: product batch consistency, dynamic control performance, and algorithm stability and adaptability. Product Consistency: By constructing a complete automated closed-loop control system, this invention reduces the batch-to-batch variation coefficient of key performance of composite unblocking agents by more than 80%, completely solving the technical problems of highly dispersed product performance and poor batch stability under traditional manual / open-loop control processes.

[0083] Control accuracy: The variable parameter PID algorithm with anti-integral saturation and parameter self-tuning functions adopted in this invention significantly reduces pH control overshoot, significantly shortens settling time, effectively improves steady-state control accuracy, and completely eliminates the control failure problem caused by integral saturation of the fixed PID algorithm while maintaining fast response.

[0084] Algorithm robustness: This invention uses a switching method based on adaptive adjustment of hysteresis width according to the rate of change of deviation. It reduces invalid parameter switching by 86.5% under rapid disturbance conditions and achieves zero invalid switching under slow disturbance conditions, enabling the control system to maintain stable and accurate adjustment quality under different disturbance characteristics.

[0085] Although embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. They can be applied to various fields suitable for the present invention. For those skilled in the art, other modifications can be easily made. Therefore, without departing from the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details and embodiments shown and described herein.

Claims

1. A method for preparing a composite unblocking agent for oil and gas fields, characterized in that, The following control system is used to achieve multi-parameter collaborative dynamic control: the control system includes a first reaction vessel, a second reaction vessel, a first pH sensor, a second pH sensor, a temperature control unit, an automatic sodium hydroxide solution replenishment unit, a loss-in-weight balance, a metering pump, and a controller; The method includes the following steps: S1. A chelating agent and a sodium hydroxide solution with a mass concentration of 5% to 10% are mixed in a first reaction vessel at a mass ratio of 1:2 to 1:

4. The pH value of the mixture in the first reaction vessel is monitored in real time by a first pH sensor, and the automatic sodium hydroxide solution replenishment unit is controlled in a closed-loop control manner based on the monitoring signal to dynamically control the pH value of the mixture within the range of 10.0 to 11.

0. At the same time, the reaction temperature in the first reaction vessel is dynamically controlled at 50°C to 60°C by a temperature control unit. Under these pH and temperature conditions, the mixture is stirred at a stirring speed of 200 rpm to 300 rpm for 20 min to 30 min to obtain a pretreated chelating agent mixture. S2. The pretreated chelating agent mixture and deionized water are pumped into the second reactor at a mass ratio of 1:5 to 1:

10. In the second reactor, the mixture is stirred at a stirring speed of 250 rpm to 350 rpm for 15 min to 25 min to form a homogeneous chelating agent solution. A penetrant is added, with a mass ratio of penetrant to chelating agent of 0.1:1 to 0.5:

1. The temperature in the second reactor is dynamically controlled at 35°C to 45°C using a temperature control unit, and the mixture is stirred at a stirring speed of 250 rpm to 350 rpm for 25 min to 35 min to obtain the first mixture. S3. Through the linkage between the loss-in-weight balance and the control system, the scale inhibitor and dispersant are gradually added to the first mixture in the second reactor at a rate of 5 g / min to 10 g / min. The total mass ratio of the scale inhibitor and dispersant to the chelating agent is 0.05:1 to 0.2:

1. During the feeding process, the stirring speed in the second reactor is dynamically maintained at 250 rpm to 350 rpm to obtain the second mixture. The pH value of the mixture in the second reactor is monitored in real time using a second pH sensor, and a 5% sodium hydroxide solution or hydrochloric acid solution is automatically added by a metering pump to dynamically adjust and stabilize the pH value of the mixture in the range of 8.0 to 9.0; then a solubilizer is added, and the volume ratio of the solubilizer to the total mixture is 1:100 to 5:

100. S4. The temperature of the mixture in the second reactor is raised to 45°C to 50°C within 10 minutes using a temperature control unit, and the mixture is reacted at a stirring speed of 150 rpm to 250 rpm within this temperature range for 40 minutes to 60 minutes. Subsequently, the temperature is raised to 55°C to 60°C within 10 minutes again using a temperature control unit, and the mixture is reacted at a stirring speed of 150 rpm to 250 rpm within this temperature range for 50 minutes to 70 minutes to obtain the composite unblocking agent.

2. The preparation method of the composite unblocking agent for oil and gas fields as described in claim 1, characterized in that, The chelating agent is composed of aminotriacetic acid and disodium ethylenediaminetetraacetate, and the mass ratio of the two is 1:1.5 to 1:2.5; the particle size distribution D90 of the aminotriacetic acid is not greater than 75 μm, and the free acid content of the disodium ethylenediaminetetraacetate is not greater than 0.5%.

3. The preparation method of the composite unblocking agent for oil and gas fields as described in claim 1, characterized in that, The penetrant is sodium dodecylbenzenesulfonate, the scale inhibitor and dispersant is sodium hexametaphosphate, and the solubilizer is isopropanol.

4. The preparation method of the composite unblocking agent for oil and gas fields as described in claim 1, characterized in that, In step S3, the process of dynamically adjusting and stabilizing the pH value of the mixture within the range of 8.0 to 9.0 through the control system specifically includes: monitoring the pH value of the mixture in real time through the second pH sensor, and automatically adding sodium hydroxide solution or hydrochloric acid solution with a mass concentration of 5% by the controller according to the monitoring signal, so as to quickly adjust the pH value to the range of 8.5±0.

3. Subsequently, the controller switches to fine-tuning mode and uses a PID algorithm to fine-tune the pH value to maintain it within the target range of 8.0 to 9.0 for at least 5 minutes, with fluctuations of less than ±0.

05.

5. The preparation method of the composite unblocking agent for oil and gas fields as described in claim 1, characterized in that, The automatic sodium hydroxide solution replenishment unit includes a controller, a metering pump, and a high-precision flow meter. The controller receives the signal from the first pH sensor, calculates the replenishment flow rate according to a preset PID control algorithm to drive the metering pump, and receives the feedback signal from the flow meter for closed-loop correction.

6. The preparation method of the composite unblocking agent for oil and gas fields as described in claim 5, characterized in that, The supplementary flow rate is calculated based on a preset PID control algorithm, specifically including the following steps: The current pH value of the mixture monitored by the first pH sensor is acquired in real time; The current pH value is compared with the preset pH target value of 10.5, and the deviation value e(t) is calculated, where e(t) = 10.5 - current pH value; Based on the deviation value e(t), the supplementary flow command u(t) is calculated using the PID control algorithm. The expression of the PID control algorithm is: u(t) = Kp × e(t) + Ki × ∫e(t)dt + Kd × de(t) / dt; where Kp is the proportional coefficient, with a value of 0.8 to 1.2; Ki is the integral coefficient, with a value of 0.02 to 0.05; and Kd is the derivative coefficient, with a value of 0.1 to 0.

3. The supplementary flow command u(t) is converted into an analog signal of 4 mA to 20 mA or a corresponding pulse frequency signal, which is used as a control signal to drive the metering pump to run at the corresponding speed. The flow rate of the metering pump is linearly related to the control signal. During the replenishment process, the temperature of the mixture inside the first reaction vessel is monitored in real time, and the current pH value measured by the first pH sensor is corrected by a temperature compensation unit. The correction formula is: pH c =pH m +α×(T-25), where pH c The corrected pH value, pH m The value measured by the sensor is T, which is the real-time temperature, and α is the temperature compensation coefficient, which is 0.003 pH / ℃. The corrected pH value is used as the current pH value for calculating the deviation value of the PID control algorithm.

7. The preparation method of the composite unblocking agent for oil and gas fields as described in claim 6, characterized in that, The PID control algorithm is a variable parameter algorithm with anti-integral saturation and parameter self-tuning functions: When the calculated value of the supplementary flow command u(t) exceeds the operating range of the metering pump, the integral term is locked; Furthermore, the proportional coefficient Kp, integral coefficient Ki, and derivative coefficient Kd are adjusted in segments according to the absolute value of the real-time deviation e(t): When |e(t)|>0.5, the first set of parameters is used, where Kp=1.2, Ki=0.02, and Kd=0.3; When 0.1 < |e(t)| ≤ 0.5, the second set of parameters is adopted, where Kp = 1.0, Ki = 0.035, and Kd = 0.2; When |e(t)| ≤ 0.1, the third set of parameters is adopted, where Kp = 0.8, Ki = 0.05, and Kd = 0.

1.

8. The preparation method of the composite unblocking agent for oil and gas fields as described in claim 7, characterized in that, The segmented adjustment adopts a method of adjusting the hysteresis width based on the deviation change rate; The first switching boundary B1 is set to 0.5, and the second switching boundary B2 is set to 0.1; the deviation change rate threshold R is set to 0.01 pH / min; The real-time hysteresis width is determined through the following steps: Calculate the change rate |Δe| of the absolute value |e(t)| of the real-time deviation; According to the comparison result between the change rate |Δe| and the threshold R, determine the first hysteresis width W1 and the second hysteresis width W2: if |Δe| ≥ R, then W1 = 0.1, W2 = 0.08; if |Δe| < R, then W1 = 0.05, W2 = 0.

04.

9. The preparation method of the composite unblocking agent for oil and gas fields as described in claim 8, characterized in that, The switching of parameter groups is performed through the following method: Upon system startup or reset, determine the initial parameter group according to the range where the absolute value of the initial deviation |e(t)| is located: If B2 + W2 ≤ |e(t)| ≤ B1 - W1, the second set of parameters is initially adopted; If |e(t)| > B1 - W1, the first set of parameters is initially adopted; If |e(t)| < B2 + W2, the third set of parameters is initially adopted; During operation, according to the absolute value of the current deviation |e(t)| and the current hysteresis width, update the adopted parameter group according to the following steps: If the first set of parameters is currently being adopted and |e(t)| ≤ B1 - W1, change to the second set of parameters; If the third set of parameters is currently being adopted and |e(t)| ≥ B2 + W2, change to the second set of parameters; If the second set of parameters is currently being adopted and |e(t)| > B1, change to the first set of parameters; If the second set of parameters is currently being adopted and |e(t)| < B2, change to the third set of parameters.

10. A composite unblocking agent for oil and gas fields, characterized in that, Made by the preparation method described in any one of claims 1 - 9.

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