MVR evaporation crystallization equipment for oil and gas field water treatment

Abstract

The application belongs to the technical field of oil and gas field water treatment, and particularly relates to an MVR evaporation crystallization equipment for oil and gas field water treatment, which comprises an MVR evaporation crystallization equipment body and a separation tank body integrally arranged on the MVR evaporation crystallization equipment body; an air flotation and coalescence separation unit is arranged in the separation tank body; a sensing detection system and a dosing system are arranged on the separation tank body; the sensing detection system and the dosing system are both in communication connection with a controller; the controller performs operation by extracting multi-dimensional physical parameters of the sensing detection system, effectively solves the defect that a traditional dosing system only performs extensive linear regulation according to water inflow, thereby providing deep process state insight, enabling the dosing of medicaments to be self-adaptively matched with the real deterioration state of the equipment bearing capacity and the microcosmic characteristics of fluid, avoiding medicament overdose or insufficient dosing, and preventing bubbling, scaling or forced shutdown of the rear-end core evaporation component from the source.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas field water treatment technology, specifically an MVR evaporation and crystallization device for oil and gas field water treatment. Background Technology

[0002] Before entering the MVR evaporator crystallizer, oil and gas field wastewater usually needs to pass through a pre-separation tank for oil removal and suspended solids pretreatment to prevent scaling or blockage of the core evaporation components. Traditional separation equipment often uses a combination of air flotation and coalescence separation processes, and adds demulsifiers to the tank through a dosing system to accelerate oil-water separation. In existing technologies, the dosage is usually roughly linearly adjusted according to the proportion of influent flow rate in order to achieve the expected phase separation effect.

[0003] However, existing dosing systems cannot detect in real time the nonlinear changes of multidimensional deterioration factors such as the stubbornness of the emulsion layer, the stabilizing effect of hydrogen sulfide, and the pressure difference of the coalescing filter element, making it difficult to dynamically assess the true health status of the equipment and the fluid synergy. On the other hand, traditional dosing control strategies lack a time series phase compensation mechanism, which cannot strictly align the macroscopically delayed flotation efficiency with the microscopically instantaneous interfacial tension and oil droplet size. As a result, when the system faces fluctuations in operating conditions, it is very easy to cause demulsification failure due to excessive dosing of reagents, which increases costs, or insufficient dosing, which leads to foaming, scaling on the pipe walls, or even forced shutdown of the downstream MVR evaporation and crystallization equipment, thereby affecting the effect of subsequent wastewater treatment.

[0004] Therefore, the present invention provides an MVR evaporation crystallization device for oil and gas field water treatment. Summary of the Invention

[0005] In order to overcome the shortcomings of the prior art, at least one technical problem raised in the background art is solved.

[0006] The technical solution adopted by the present invention to solve its technical problem is: the MVR evaporation crystallization equipment for oil and gas field water treatment of the present invention includes an MVR evaporation crystallization equipment body and a separation tank integrated on the MVR evaporation crystallization equipment body; The separation tank is equipped with an air flotation and coalescence separation unit. The separation tank is equipped with a sensing and detection system and a dosing system. Both the sensing and detection system and the dosing system are connected to a controller. The controller extracts the multi-dimensional physical parameters of the sensing and detection system for calculation and uses this to dynamically adjust the amount of demulsifier injected into the dosing system in order to control the state of the emulsion layer in the separation tank. The sensing and detection system includes: an online array profiler, an online gas detector transmitter, a differential pressure transmitter, a suspended solids concentration meter, a high-precision gas flow meter, a liquid flow meter, an online microwave density meter, an online laser particle size analyzer, and an online dynamic interfacial tension meter. The controller performs the following operations: S1: Based on the real-time emulsion layer thickness and height position obtained by the online array profiler and the gas phase hydrogen sulfide mass concentration obtained by the online gas detection transmitter, an emulsion layer stability model is constructed and the emulsion layer stability coefficient is calculated. S2: Based on the actual gas-water volume ratio of dissolved air and water obtained by the high-precision gas flow meter and liquid flow meter, the water content of scum in the flotation tank obtained by the online microwave density meter, the pressure difference of the coalescing filter element obtained by the differential pressure transmitter, and the total amount of suspended solids in the influent obtained by the suspended solids concentration meter, a coalescing health model is constructed to calculate the coalescing health coefficient. S3: Based on the median value of the influent oil droplet size obtained by the online laser particle size analyzer and the dynamic interfacial tension of the effluent obtained by the online dynamic interfacial tension meter, the demulsification phase separation synergy model is constructed by combining the emulsion layer stability coefficient and the coalescer health coefficient to calculate the demulsification phase separation synergy. S4: Based on the demulsification phase separation synergy and the extracted air flotation operation efficiency coefficient, construct an online concentration and flow rate optimization model, and output the target demulsifier injection flow rate and online mass concentration to control the dosing system.

[0007] The beneficial effects of this invention are as follows: 1. The MVR evaporation crystallization equipment for oil and gas field water treatment described in this invention effectively solves the shortcomings of traditional dosing systems that rely solely on coarse linear adjustments based on influent flow rate by setting up a sensing and detection system and combining it with a multi-dimensional evaluation model built within the controller. It can not only capture the degradation trend of the equipment's physical performance in real time, but also accurately identify the actual needs of the current separation conditions, thereby providing in-depth insights into the process status. This allows the dosing of chemicals to adaptively match the actual deterioration state of the equipment's carrying capacity and the microscopic characteristics of the fluid, avoiding excessive or insufficient dosing of chemicals and preventing foaming, scaling, or forced shutdown of the core evaporation components at the source.

[0008] 2. The MVR evaporation crystallization device for oil and gas field water treatment described in this invention breaks through the technical bottleneck of the inability to align macroscopic lag with microscopic instantaneous state in traditional control strategies by setting an online concentration and flow optimization model with time delay compensation characteristics and discrete update mechanism. It can adjust the injection flow of demulsifier in advance or delay according to the actual lag characteristics of the physical process, ensuring that the control command and the actual response are strictly synchronized on the time axis. At the same time, the introduced exponential decay regulation and synergy dead zone benchmark value filter out small fluctuations in operating conditions, realize smooth and dynamic closed-loop regulation of the dosing concentration, and eliminate the impact of sudden dosing on the water treatment system.

[0009] 3. The MVR evaporation crystallization equipment for oil and gas field water treatment described in this invention, through the setting of a three-dimensional sensor hardware layout structure and a variable frequency dosing and mixing execution system, ensures the efficient implementation of the entire intelligent control process. In addition, the bypass detection pipe connected in parallel on the outlet pipe of the separation tank ensures the continuity of fluid state monitoring. With the series operation of the variable frequency dosing pump and the pipeline static mixer, it can not only seamlessly receive the frequency adjustment command of the controller to achieve precise metering, but also use the fluid kinetic energy to promote the rapid and uniform mixing of demulsifier and oily wastewater, thereby maximizing the utilization rate and separation efficiency of the reagent. Attached Figure Description

[0010] The invention will now be further described with reference to the accompanying drawings.

[0011] Figure 1 This is a perspective view of the present invention; Figure 2 This is a schematic diagram of the separation tank in this invention; Figure 3 This is a schematic diagram of the installation of the online array profiler in this invention; Figure 4 This is a flowchart of the calculation process for the emulsion layer stability model in this invention; Figure 5 This is a flowchart of the coalescer health model calculation in this invention; Figure 6 This is a flowchart of the demulsification phase synergy model calculation in this invention; Figure 7 This is a flowchart of the online concentration and flow optimization model calculation in this invention.

[0012] In the diagram: 1. MVR evaporation crystallization equipment body; 2. Separation tank; 3. Water outlet pipeline; 4. Booster pump; 5. Gas phase balance pipeline; 6. Online gas detection transmitter; 7. Online array profiler; 8. Bypass detection pipe. Detailed Implementation

[0013] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0014] The present invention discloses an MVR evaporation crystallization device for oil and gas field water treatment, comprising an MVR evaporation crystallization device body 1 and a separation tank 2 integrated on the MVR evaporation crystallization device body 1; the MVR evaporation crystallization device body 1 is used for deep treatment of oil and gas field wastewater, realizing the concentration and crystallization of wastewater, thereby recovering water resources or solid salts, while the separation tank 2, as a pretreatment unit of the MVR evaporation crystallization device body 1, mainly functions to remove oily substances from the wastewater.

[0015] The separation tank 2 is equipped with an air flotation and coalescence separation unit. The separation tank 2 is equipped with a sensing and detection system and a dosing system. Both the sensing and detection system and the dosing system are connected to the controller. The controller extracts the multi-dimensional physical parameters of the sensing and detection system for calculation and uses this to dynamically adjust the amount of demulsifier injected into the dosing system in order to control the state of the emulsion layer in the separation tank 2. The air flotation separation unit separates oil and water by injecting microbubbles into the wastewater, causing oil droplets and suspended solids to adhere to the bubbles and float to the surface to form scum. For example, dissolved air flotation technology can be used, where dissolved air water is released through a release device to generate a large number of microbubbles. The coalescence separation unit utilizes the surface properties of coalescing materials to promote the coalescence of dispersed micro oil droplets into larger oil droplets, accelerating their floating and separation. For example, fiber bundles, corrugated plates, or porous media can be used as coalescing materials. When wastewater flows through these materials, oil droplets coalesce on the surface.

[0016] The sensing and detection system is configured to monitor multiple process parameters inside the separation tank 2 and the inlet and outlet water in real time. For example, it can be configured with independent sensors to transmit data to the controller via wired or wireless means. The dosing system is configured to accurately add demulsifiers and other chemical agents to the separation tank 2 to assist the oil-water separation process. For example, the dosing system can consist of a metering pump, a chemical storage tank, and a dosing pipeline. The controller sends commands to control the start, stop, and flow of the metering pump. As the core control unit of the entire system, the controller receives data from the sensing and detection system, executes complex calculation models, and sends control commands to the dosing system.

[0017] The sensing and detection system includes: an online array profiler 7, an online gas detector transmitter 6, a differential pressure transmitter, a suspended solids concentration meter, a high-precision gas flow meter, a liquid flow meter, an online microwave density meter, an online laser particle size analyzer, and an online dynamic interfacial tension meter; The online array profiler 7 is used to measure the thickness and height of the emulsion layer inside the separation tank 2 in real time. For example, the instrument can use ultrasonic or capacitive principles to measure at different heights using multiple probes.

[0018] The online gas detection transmitter 6 is used to monitor the mass concentration of harmful gases such as hydrogen sulfide in the gas phase space of the separation tank 2 in real time. For example, an electrochemical sensor or a semiconductor sensor can be used and installed in the top space of the tank.

[0019] Differential pressure transmitters are used to measure the pressure difference across a coalescing filter element to assess the degree of clogging. For example, differential pressure data can be obtained in real time by connecting pressure taps to the inlet and outlet of the filter element.

[0020] Suspended solids concentration meters are used to measure the total amount of suspended solids in incoming water. For example, they can be installed on the inlet pipe using optical scattering or transmission principles.

[0021] High-precision gas flow meters and liquid flow meters are used to measure the actual flow rates of gas and liquid in dissolved air water, respectively, to calculate the gas-to-water volume ratio. For example, vortex flow meters or Coriolis mass flow meters can be used.

[0022] Online microwave densitometers are used to measure the moisture content of scum in dissolved air flotation (DAF) tanks. For example, by using microwaves to penetrate the scum layer, the density is calculated based on the degree of attenuation, and then the moisture content is estimated.

[0023] Online laser particle size analyzers are used to measure the particle size distribution of oil droplets in incoming water, especially the median value. For example, the principle of laser diffraction can be used to analyze the flowing liquid in real time.

[0024] Online dynamic interfacial tensiometers are used to measure the interfacial tension between oil and water in effluent, reflecting the effectiveness of oil-water separation. For example, the pendant drop method or the oscillating jet method can be used for online monitoring of the effluent.

[0025] The controller (which receives data from the sensor detection system, executes complex calculation models, and sends control commands to the dosing system to achieve closed-loop intelligent control) performs the following operations: S1: Based on the real-time emulsion layer thickness and height position obtained by the online array profiler 7 and the gaseous hydrogen sulfide mass concentration obtained by the online gas detection transmitter 6, an emulsion layer stability model is constructed to calculate the emulsion layer stability coefficient; (The emulsion layer stability model is used to quantitatively evaluate the stability or stubbornness of the emulsion layer. For example, the controller can receive emulsion layer thickness and height position data from the online array profiler 7 and gaseous hydrogen sulfide mass concentration data from the online gas detection transmitter 6. These data are input into a preset mathematical model, which comprehensively considers the influence of these factors on the stability of the emulsion layer through weighted averaging or fuzzy logic, and finally outputs a dimensionless emulsion layer stability coefficient. The value of this coefficient can reflect the ease or difficulty of emulsion layer separation. The higher the value, the more stable the emulsion layer is and the more difficult it is to separate).

[0026] S2: Based on the dissolved air-water volume ratio obtained from high-precision gas flow meters and liquid flow meters, the scum moisture content of the flotation tank obtained from the online microwave densitometer, the coalescing filter element pressure difference obtained from the differential pressure transmitter, and the total suspended solids in the influent obtained from the suspended solids concentration meter, a coalescing health model is constructed to calculate the coalescing health coefficient; (The coalescing health model is used to evaluate the operating status and efficiency of the flotation and coalescing separation unit. For example, the controller receives the dissolved air-water volume ratio provided by the high-precision gas flow meters and liquid flow meters, the scum moisture content of the flotation tank provided by the online microwave densitometer, the coalescing filter element pressure difference provided by the differential pressure transmitter, and the total suspended solids in the influent provided by the suspended solids concentration meter. These parameters are input into another mathematical model, which can use multivariate regression analysis or neural network methods to comprehensively analyze the impact of these parameters on the performance of the coalescing unit and calculate a coalescing health coefficient. This coefficient reflects the working efficiency of the coalescing unit, and the higher the value, the better the operating status of the coalescing unit).

[0027] S3: Based on the median influent oil droplet size obtained from the online laser particle size analyzer and the effluent dynamic interfacial tension obtained from the online dynamic interfacial tension meter, a demulsification phase separation synergy model is constructed by combining the emulsion layer stability coefficient and the coalescer health coefficient to calculate the demulsification phase separation synergy. (The demulsification phase separation synergy model is used to comprehensively evaluate the overall synergy between the demulsifier dosing effect and oil-water separation. For example, the controller receives the median influent oil droplet size provided by the online laser particle size analyzer and the effluent dynamic interfacial tension provided by the online dynamic interfacial tension meter. At the same time, the emulsion layer stability coefficient calculated by S1 and the coalescer health coefficient calculated by S2 are used as inputs to the model. This model can use nonlinear fitting or expert system methods to correlate these micro and macro parameters and calculate a demulsification phase separation synergy. This synergy reflects the degree of matching between the demulsifier action and the physical separation process under the current operating conditions. The higher the value, the better the synergy effect and the higher the separation efficiency.)

[0028] S4: Based on the demulsification and phase separation synergy and the extracted air flotation operation efficiency coefficient, an online concentration and flow rate optimization model is constructed, outputting the target demulsifier injection flow rate and online mass concentration control dosing system (the online concentration and flow rate optimization model is used to dynamically optimize the demulsifier dosing strategy. For example, the controller receives the demulsification and phase separation synergy calculated by S3 and combines it with the air flotation operation efficiency coefficient extracted from historical data or real-time monitoring, such as the oil removal rate calculated by the oil content of the influent and effluent. These parameters are input into an optimization algorithm, which can use methods such as PID control, fuzzy adaptive control, or model predictive control. Based on the current separation state and target effect, the optimal target demulsifier injection flow rate and online mass concentration are calculated in real time. The controller then sends these optimized parameters to the dosing system to guide it to accurately dosing the agent. For example, the dosing system can adjust the pump speed according to the received flow command and adjust the agent dilution ratio according to the concentration command).

[0029] By integrating multiple sensors such as an online array profiler 7, an online gas detection transmitter 6, a differential pressure transmitter, a suspended solids concentration meter, a high-precision gas flow meter, a liquid flow meter, an online microwave density meter, an online laser particle size analyzer, and an online dynamic interfacial tension meter, real-time, multi-dimensional quantitative sensing of key parameters such as emulsion layer state, gas phase composition, coalescer health, oil droplet size, and interfacial tension is achieved. This overcomes the limitations of existing systems in sensing complex deterioration factors and provides a comprehensive data foundation for precise control.

[0030] Furthermore, by constructing an emulsion layer stability model, a coalescer health model, and a demulsification and phase separation synergy model, these multi-dimensional sensing data are deeply integrated and analyzed, enabling a refined assessment of the oil-water separation process. When the emulsion layer stability coefficient is high and the coalescer health coefficient is low, the demulsification and phase separation synergy model can accurately identify the current poor separation effect, which far exceeds the judgment capability of existing technologies based solely on flow regulation, providing a deeper level of insight into the process status.

[0031] Furthermore, based on the demulsification phase separation synergy and the extracted air flotation operation efficiency coefficient, an online concentration and flow optimization model is constructed. This model can dynamically calculate and output the target demulsifier injection flow rate and online mass concentration, thereby achieving precise control of the dosing system. This allows the dosing amount to respond to changes in operating conditions in real time, avoiding over- or under-dosing, significantly improving demulsification efficiency, reducing operating costs, and effectively protecting the stable operation of the downstream MVR evaporation crystallization equipment 1. Compared with traditional dosing control strategies that lack a time series phase compensation mechanism, this application can strictly align the macroscopically delayed air flotation efficiency with the microscopically instantaneous interfacial tension and oil droplet size state, ensuring the accuracy and effectiveness of dosing when the system faces fluctuations in operating conditions.

[0032] The specific calculation logic of the emulsion layer stabilization model built within the controller is as follows: The normalized ratio of the real-time emulsion layer thickness to the preset maximum allowable thickness limit, the normalized ratio of the gas phase hydrogen sulfide mass concentration to the stabilization critical concentration threshold, and the normalized ratio of the absolute deviation of the real-time emulsion layer height from the optimal interface to the maximum effective working height are obtained. After assigning the three normalized ratios to the corresponding emulsion stabilization factor weight coefficients, a weighted sum is performed, and the summation result is processed by an S-type nonlinear mapping function to output a dimensionless value between 0 and 1 as the emulsion layer stability coefficient. The stability coefficient of the emulsion layer is positively correlated with the real-time emulsion layer thickness, the mass concentration of hydrogen sulfide in the gas phase, and the degree of high interface deviation.

[0033] The emulsion layer stabilization model built within the controller is as follows: ; In the formula, Let be the emulsion layer stability coefficient, which is dimensionless and ; The real-time emulsion layer thickness has the dimension of . ; The maximum allowable emulsion layer thickness limit for the process, with dimensions of ; The mass concentration of hydrogen sulfide in the gaseous phase, with dimensions of ; The critical mass concentration threshold for hydrogen sulfide stabilization, with dimensions of ; The real-time height position of the emulsion layer, with dimensions of ; The optimal interface elevation has the following dimensions: ; The maximum effective working height of separation tank 2, with dimensions of ; , , The weighting coefficient for the emulsification stabilization factor is dimensionless.

[0034] This emulsion layer stability model aims to quantify the complex and dynamic stability state of the emulsion layer during oil and gas field water treatment, transforming it into a calculable and comparable numerical index. The concept is to establish a mathematical relationship by comprehensively considering multiple key parameters affecting the stability of the emulsion layer, thereby providing an objective assessment of the stubbornness of the emulsion layer. Possible implementation methods include, but are not limited to: empirical models derived from physicochemical principles, or predictive models obtained by training historical operating data through machine learning algorithms (such as support vector machines, neural networks, etc.).

[0035] Emulsion layer stability coefficient This is a quantitative indicator output by the model, used to characterize the stability or stubbornness of the current emulsion layer. Its value range is... The closer the value is to 1, the more stable and stubborn the emulsion layer is, and the more difficult it is to break down and separate; the closer the value is to 0, the more unstable the emulsion layer is, and the easier it is to separate. The dimensionless nature of this coefficient allows it to be independent of specific physical units, making it easy to compare and apply it between different working conditions and equipment.

[0036] Real-time emulsion layer thickness This refers to the actual thickness of the emulsion layer in the vertical direction as monitored in real time in the separation tank 2. The acquisition method may include: continuous measurement by an online array profiler 7, which can use ultrasonic, radar, capacitance or optical principles to detect the position of different medium interfaces and thus calculate the thickness of the emulsion layer; or by setting multiple liquid level sensors at different heights in the tank, combining the sensor readings to determine the position of the upper and lower interfaces of the emulsion layer, and then calculating its thickness.

[0037] Maximum allowable emulsion layer thickness limit The maximum allowable thickness of the emulsion layer is set according to the design specifications, treatment process requirements, and historical operating experience of the separation tank 2, under the premise of ensuring separation efficiency and safe operation of the equipment. The determination method can be based on the operation manual provided by the equipment manufacturer, or determined through on-site tests and process optimization, so as to avoid the deterioration of the treated water quality or the impact on the operation of subsequent equipment due to excessive emulsion layer.

[0038] gaseous hydrogen sulfide mass concentration This refers to the mass concentration of hydrogen sulfide gas detected in real time in the gas phase space at the top of the separation tank 2. It can be obtained by means of continuous monitoring through an online gas detection transmitter 6, which can use technologies such as electrochemical sensors, semiconductor sensors or infrared absorption spectroscopy to detect the concentration of hydrogen sulfide; or by periodic sampling and laboratory analysis.

[0039] Hydrogen sulfide stabilization critical mass concentration threshold Based on the characteristics of oil and gas field wastewater and the performance of demulsifiers, this threshold is determined when the concentration of hydrogen sulfide in the gas phase reaches a critical concentration at which its impact on the stability of the emulsion layer becomes significant, and may even lead to the difficulty in demulsifying the emulsion layer. This threshold can be set through laboratory simulation experiments, field tests, or in combination with industry experience to guide the assessment of the stabilizing effect of hydrogen sulfide.

[0040] Real-time emulsion layer height position This refers to the vertical position of the emulsion layer inside the separation tank 2. It usually refers to the height of the center of the emulsion layer or a specific interface (such as the oil-water interface) relative to the bottom of the tank or a reference surface. The method of obtaining this information can include: direct measurement using an online array profiler 7, which can provide accurate vertical distribution information of the emulsion layer inside the tank; or measurement using a combination of multiple level sensors or differential pressure sensors, combined with the geometry of the tank to calculate the height of the emulsion layer.

[0041] Optimal Interface Elevation It is determined based on the design principles and optimal operating conditions of the separation tank 2. Under the premise of achieving efficient oil-water separation and minimizing the formation of the emulsion layer, the oil-water interface should maintain an ideal vertical position. This elevation is usually determined by the equipment designer or process engineer based on fluid mechanics, phase separation theory and actual operating experience to ensure that the oil phase, water phase and emulsion layer can be effectively separated.

[0042] Maximum effective working height of separation tank 2 This refers to the maximum vertical space from bottom to top of the separation tank 2 that can effectively perform oil-water separation and emulsion treatment. This height is usually determined by the physical dimensions and internal structure of the tank (such as inlet and outlet, internal baffles, etc.) and is the benchmark for assessing the degree of deviation of the emulsion height.

[0043] Emulsification Stabilization Factor Weighting Coefficient , , The relative contributions of three factors—emulsion layer thickness, gaseous hydrogen sulfide mass concentration, and emulsion layer height position—to the overall stability of the emulsion layer can be adjusted. By adjusting these weighting coefficients, the model can better adapt to the water quality characteristics of different oil and gas field wastewater, different separation tank structures, and different operating conditions. These coefficients can be determined through historical data regression analysis, expert experience setting, or on-site debugging and optimization.

[0044] hyperbolic tangent function It is an S-shaped function with an output range between -1 and 1. In this model, after appropriate adjustments, its output range is mapped to... The reason for choosing this function is that it has good nonlinear characteristics, which can smoothly map the linear combination of input parameters to a finite range, avoiding abrupt changes and making the calculation results of the emulsion layer stability coefficient more stable and continuous. In addition, its saturation characteristics also make the output value tend to stabilize when the input parameters reach a certain level, which is consistent with the physical behavior of emulsion layer stability under extreme conditions.

[0045] By constructing an emulsion layer stability model within the controller, the real-time emulsion layer thickness is first... With respect to the maximum allowable emulsion layer thickness limit of the process Normalization was performed to assess the extent to which the emulsion layer occupies the separation space, and the mass concentration of gaseous hydrogen sulfide was also normalized. With the critical mass concentration threshold for hydrogen sulfide stabilization A comparison was made to quantify the chemical stabilizing effect of hydrogen sulfide on the stability of the emulsion layer.

[0046] In addition, the model also calculates the real-time height position of the emulsion layer. With optimal interface elevation The deviation between them, and the maximum effective working height of the separation tank 2 Normalization is performed to reflect the degree to which the oil-water interface deviates from ideal operating conditions. These three normalized parameters are then multiplied by their corresponding emulsification stabilization factor weighting coefficients. , , Then, a weighted summation is performed, and finally, the hyperbolic tangent function is applied. A nonlinear mapping is performed to output an emulsion layer stability coefficient between 0 and 1. This design enables the model to comprehensively and dynamically capture various deterioration factors of the emulsion layer, such as physical accumulation, chemical stabilization, and interface deviation, transforming the originally qualitative emulsion state into quantitative values. This provides a precise quantitative basis for subsequent demulsifier dosing. By integrating this emulsion layer stability model into the sensing and detection system and dosing system configured in the separation tank 2 on the MVR evaporation crystallization equipment body 1, the controller can obtain the emulsion layer stability coefficient in real time and make intelligent decisions based on it. This is in stark contrast to the traditional extensive dosing method based solely on the influent flow rate, greatly improving the accuracy and response speed of dosing. The model works closely with the online array profiler 7 and online gas detector transmitter 6 on the separation tank 2 to achieve real-time perception and in-depth analysis of the emulsion layer state. This effectively addresses the challenges of complex oil and gas field wastewater composition and variable operating conditions, avoiding the problem of inaccurate demulsifier dosing caused by the difficulty in quantifying the stubbornness of the emulsion layer, and providing a solid guarantee for the stable operation of the MVR evaporation crystallization equipment body 1.

[0047] The emulsion layer stability model comprehensively considers multiple key influencing factors such as emulsion layer thickness, gaseous hydrogen sulfide mass concentration, and emulsion layer height position, and uses a hyperbolic tangent function for nonlinear mapping to ensure the output emulsion layer stability coefficient. It can accurately reflect the true stubbornness of the emulsion layer, which provides a scientific quantitative basis for the precise addition of demulsifier in the subsequent dosing system. It avoids the problem of over- or under-dosing of reagents due to inaccurate assessment of the emulsion layer state, significantly improves oil-water separation efficiency, reduces reagent consumption, and effectively prevents the risk of foaming, scaling, or shutdown of downstream MVR evaporation and crystallization equipment caused by improper emulsion layer treatment, thereby ensuring the stable operation and treatment effect of the entire wastewater treatment system.

[0048] The specific calculation logic of the coalescer health model built within the controller is as follows: The coalescer health coefficient is calculated by coupling the physical blockage attenuation term, the gas-water ratio deviation correction term, and the slag discharge efficiency penalty term. Among them, the physical blockage attenuation term is an exponential attenuation function constructed by weighting the normalized values ​​of the real-time pressure difference of the coalescing filter element and the total amount of suspended solids in the influent; the air-water ratio deviation correction term is constructed based on the degree of deviation of the actual dissolved air-water ratio from the optimal air-water ratio, and is non-linearly negatively correlated with the actual air-water deviation; the slag discharge efficiency penalty term is constructed based on the deviation margin of the slag moisture content in the flotation tank from the maximum moisture content limit, and is negatively correlated with the moisture content; the three are combined to output the coalescing health coefficient.

[0049] The specific health model of the coalescer built within the controller is as follows: ; In the formula, The coalescing health coefficient is dimensionless and... ; The real-time pressure difference of the coalescing filter element, in units of ; The critical pressure differential for filter cartridge disposal, with dimensions of ; The total suspended solids in the influent, with dimensions of ; Design limit value for suspended solids in influent, dimensionless ; The actual gas-water volume ratio of dissolved air and water is dimensionless. The optimal air-to-water ratio for the system design is dimensionless. The moisture content of the scum in the flotation tank is dimensionless. The maximum moisture content limit of scum is dimensionless. , , , The sensitivity coefficient for health decline is dimensionless.

[0050] Among them, the coalescer health coefficient It is a key indicator used to quantitatively evaluate the operating status of coalescer, and its value range is: It can intuitively reflect the degree to which the coalescer degrades from its optimal state to its performance decline, and the real-time differential pressure of the coalescer filter element. It is an important parameter for measuring the degree of filter element clogging. An increase in its value usually means that more suspended solids or oil droplets are trapped inside the filter element, resulting in increased resistance to fluid flow. This pressure difference can be obtained by installing pressure sensors at the inlet and outlet of the coalescing filter element and calculating the difference between the two.

[0051] Critical pressure difference for filter cartridge disposal This is a preset threshold that indicates when the filter cartridge pressure differential reaches a certain value, at which cleaning or replacement is required. It can be determined based on the filter cartridge manufacturer's recommendations, historical operating data analysis, or process design requirements, and includes the total suspended solids in the influent. This reflects the content of solid impurities in the water entering the coalescer. These impurities are one of the main causes of filter cartridge clogging and performance degradation. Real-time monitoring can be performed using an online suspended solids concentration meter.

[0052] Inlet suspended solids design limit This is the maximum allowable concentration of suspended solids in the influent during system design. Exceeding this value may lead to a decrease in system treatment capacity or equipment damage. It is typically set based on process design specifications or environmental emission standards. The actual air-to-water volume ratio is also considered. It is the ratio of the volumetric flow rate of the gas phase to that of the liquid phase during the air flotation process. It has a significant impact on the air flotation effect and the subsequent coalescence separation efficiency. This ratio can be calculated by measuring the flow rates of the gas phase and the liquid phase using a high-precision gas flow meter and a liquid flow meter, respectively.

[0053] Optimal air-water ratio of the system This is the air-to-water ratio determined based on process optimization experiments or design experience to achieve the best air flotation separation effect. Deviating from this value will lead to a decrease in air flotation efficiency and a decrease in the water content of the scum in the air flotation tank. It is an indicator for measuring the sludge removal effect of the flotation tank. Too high a water content may mean that too much water is carried in the sludge, which reduces the separation efficiency. This parameter can be monitored in real time by an online microwave density meter.

[0054] Maximum moisture content limit of scum This is the upper limit of permissible scum moisture content. Exceeding this value may indicate abnormal operation of the flotation tank or inefficiency of the scum removal system. Its setting can be based on operational experience or process requirements, and the health degradation sensitivity coefficient. , , , These are weighting factors in the model, used to adjust the influence of various parameters on the coalescer health coefficient. The sensitivity of the impact can be determined by fitting historical operating data, setting expert experience, or optimizing through machine learning algorithms.

[0055] The coalescer health model, constructed by comprehensively considering the filter cartridge pressure difference and the total amount of suspended solids in the influent through an exponential decay term, can effectively reflect the decline in physical performance caused by impurities clogging the filter cartridge. By introducing the normalized ratio of pressure difference and suspended solids concentration, the model can capture the risk trend of the filter cartridge approaching the end of its service life in real time. The actual air-water volume ratio deviation term introduced in the model, using a quadratic function, characterizes the negative impact of the actual air-water ratio deviating from the optimal design value on the separation efficiency, ensuring the stability of the flotation operation environment. In addition, by introducing a power function term for the scum moisture content, the model can dynamically evaluate the impact of the flotation tank's scum discharge efficiency on the overall separation environment, thus transforming the scum moisture content, an indicator of the flotation effect, into a correction factor for the health coefficient. Through the coupled calculation of the above multi-dimensional parameters, the model can transform the complex physical operating state into a single health coefficient, enabling the controller to identify whether the equipment is in a sub-healthy state based on this coefficient. This allows for the reservation of compensation space for equipment performance degradation in the dosing control, effectively avoiding poor demulsification effect caused by equipment performance degradation.

[0056] Through the above technical solution, this application can evaluate the operational health status of the coalescer in real time and quantitatively, overcoming the limitation of traditional dosing control strategies that cannot perceive the evolution of the physical state of the core components inside the equipment. This enables the dosing strategy to adaptively adjust to the degradation of equipment performance, avoiding excessive or insufficient dosing of demulsifier due to the sub-healthy state of the equipment. This effectively prevents problems such as foaming, scaling on the pipe walls, or even forced shutdown of the downstream MVR evaporation crystallization equipment, and significantly improves the stability and efficiency of oil and gas field wastewater treatment.

[0057] The specific calculation logic of the demulsification phase synergy model built within the controller is as follows: The obtained coalescer health coefficient, emulsion layer stability coefficient, normalized ratio of median influent oil droplet size to benchmark critical size, and normalized ratio of online dynamic interfacial tension of effluent to benchmark value of standard interfacial tension are respectively assigned corresponding synergy response incentive weights. The demulsification and phase separation synergy was evaluated using a nonlinear function with logistic characteristics. The system-wide excitation independent variable of this function consists of the positive excitation weighted value of the coalescer health coefficient and the influent oil droplet size, minus the negative inhibition weighted value of the emulsion layer stability coefficient and interfacial tension, combined with the function offset constant. The resulting demulsification and phase separation synergy is positively correlated with physical separation capability and oil droplet size, and negatively correlated with the emulsion layer stubbornness and effluent interfacial tension.

[0058] The demulsification phase synergy model built within the controller is as follows: ; In the formula, The degree of synergy in demulsification is dimensionless, and ; To obtain the coalescer health coefficient; To obtain the stability coefficient of the emulsion layer; The median size of the oil droplets in the influent is given by the dimensionless standard. ; The reference critical particle size for easy separation has the following dimensions: ; The dynamic interfacial tension of the effluent, with dimensions of ; The standard interfacial tension reference value for two phases, with dimensions of ; , , , The coefficient for synergistic response is dimensionless. is the function offset constant, which is dimensionless.

[0059] This demulsification and phase separation synergy model aims to quantify the degree of synergy between demulsification and phase separation in oil-water mixtures. Its core is a logistic function, which can nonlinearly map multiple input variables to an output value between 0 and 1, thereby effectively evaluating the synergistic effect in complex systems. By comprehensively considering various influencing factors, the model provides a unified and quantifiable index to reflect the ease or difficulty of the oil-water separation process and the response requirements of demulsifier addition.

[0060] in, As the demulsification phase synergy, it is a dimensionless index, and its value range is: The higher the index, the easier it is for the oil-water mixture to demulsify and separate into phases, and the better the response of the demulsifier; conversely, the lower the index, the more difficult it is to demulsify and separate into phases, requiring a stronger demulsifier or more optimized operating conditions.

[0061] The coalescer health coefficient is an indicator that reflects the current operating status and performance of the coalescer. Its value is calculated by the controller according to the preset coalescer health model. This coefficient takes into account factors such as the pressure difference of the coalescer filter element, the total amount of suspended solids in the influent, the actual air-water volume ratio of dissolved air and water, and the water content of the scum in the flotation tank, in order to evaluate the efficiency and carrying capacity of the coalescer in physical separation.

[0062] The emulsion stability coefficient is an indicator that measures the stability of the oil-water interface emulsion. Its value is calculated by the controller based on the preset emulsion stability model. This coefficient takes into account factors such as the real-time emulsion thickness and height position, as well as the mass concentration of hydrogen sulfide in the gas phase, to assess the difficulty of emulsion demulsification.

[0063] The median value of the oil droplet size in the influent refers to the middle value of the oil droplet size distribution in the influent, i.e., 50. The oil droplet size is smaller than this value. This parameter is obtained in real time by an online laser particle size analyzer and reflects the physical dispersion state of the oil droplets in the influent. The size of the oil droplet directly affects the contact area and demulsification efficiency of the demulsifier and is a key physical indicator for assessing the ease of demulsification.

[0064] The critical particle size for easy separation is a reference value that represents the minimum particle size at which oil droplets can be relatively easily separated from water under specific process conditions. This value is usually determined based on historical operating data, experimental results, or process design specifications. For example, it can be set as the oil droplet particle size threshold that can achieve the expected separation effect without the addition of demulsifier or with a small amount of demulsifier.

[0065] The online dynamic interfacial tension of the effluent refers to the tension of the oil-water interface in the treated effluent. This parameter is measured in real time by an online dynamic interfacial tension meter and is a direct chemical and physical indicator for evaluating the effect of demulsifiers and the degree of oil-water separation. The lower the interfacial tension, the more unstable the oil-water interface is, which is more conducive to oil-water separation.

[0066] This is a reference value for the standard interfacial tension between the two phases. It represents the interfacial tension between the oil and water phases under ideal or target separation conditions. This value is usually determined based on the interfacial tension between pure water and pure oil, or experimental data under optimal demulsification conditions. For example, it can be set as the interfacial tension value corresponding to when the oil content in the effluent meets the discharge standard. , , , These are the synergy response incentive coefficients, which are dimensionless weighting factors used to adjust the degree of influence of each input variable on the synergy of demulsification. These coefficients can be determined in various ways, such as by regression analysis based on historical operating data or by optimization training using machine learning algorithms.

[0067] The function offset constant is a dimensionless constant used to adjust the position of the logistic function curve to better fit the actual process data. This constant is usually determined during model calibration through optimization algorithms or trial and error methods to ensure that the model can accurately reflect the degree of synergy between demulsification and phase separation under different operating conditions.

[0068] This model considers the macroscopic equipment conditions (via the coalescer health coefficient) that affect demulsification and phase separation efficiency during oil-water separation. (reflected) and microfluidic properties (through the emulsion layer stability coefficient) Oil droplet size interfacial tension (Reflecting) the organic combination of the coalescer health coefficient It reflects the physical separation capability of the equipment itself. When the performance of the coalescer deteriorates, even if the fluid characteristics are good, the overall separation effect will be affected. Therefore, this coefficient has a positive incentive effect on the degree of synergy.

[0069] Emulsion layer stability coefficient This directly quantifies the stubbornness of the emulsion; a higher value indicates a more stable emulsion and greater difficulty in demulsification. Therefore, this coefficient has a negative inhibitory effect on synergy. The median droplet size of the influent is... With the critical particle size of easy separation reference The ratio reflects the physical dispersion state of oil droplets. Larger droplet sizes are easier to separate and have a positive impact on the degree of synergy.

[0070] Online dynamic interface tension of water output Reference value of interfacial tension between two phases The ratio directly reflects the degree of improvement in the oil-water interface properties after the demulsifier's action. The lower the interfacial tension, the stronger the effect of the surfactant, which is more conducive to oil-water separation. Therefore, in the algebraic sum term of the exponential function, this factor is given a negative sign. ), so that when When the sum of terms decreases, the overall algebraic sum increases, which in turn increases the coherence of the final output. The coefficient of friction increases positively, and the mathematical model rigorously maps the actual difficulty of physical separation. This model can overcome the one-sidedness of single-index evaluation and transform the complex oil-water separation process into a quantifiable synergy index. For example, when the coalescer health is high, the emulsion layer stability coefficient is low, the influent oil droplet size is large, and the effluent interfacial tension is low, the model will calculate a high demulsification phase separation synergy, indicating that the oil-water separation effect is good or easy to achieve. Conversely, the synergy is low. This comprehensive evaluation capability enables the controller to more accurately determine the actual demand for demulsifier under the current operating conditions, providing a solid data foundation and decision-making basis for the subsequent refined and intelligent adjustment of the dosing system.

[0071] In the online concentration and flow rate optimization model, the calculation logic for the target demulsifier injection flow rate includes time-delay compensation features for hydraulic residence time, specifically: The target demulsifier injection flow rate is obtained by multiplying the current demulsifier injection flow rate by the flow dynamic correction factor. The direction of adjustment of the flow dynamic correction factor is jointly constrained by the current demulsification phase synergy and the historical time-delay flotation operation efficiency coefficient: its increase is positively correlated with the current urgent demand for demulsifier (derived in reverse from the current demulsification phase synergy); its decrease is positively correlated with the actual oil removal rate calculated in advance based on the hydraulic retention time of the flotation tank (i.e., the current actual efficiency of the historical added agent); Meanwhile, the single adjustment step size of the target demulsifier injection flow rate is limited by a smooth scaling of the ratio of the sampling calculation cycle of the control system to the response time constant of the process object.

[0072] In the online concentration and flow rate optimization model, the formula for calculating the target demulsifier injection flow rate has a time-delay compensation feature that includes the hydraulic residence time, specifically: ; In the formula, The injection flow rate of the target demulsifier, with dimensions of ; The current demulsifier injection flow rate, in units of... ; The degree of synergy of demulsification obtained at the current moment; The efficiency coefficient of air flotation operation after time delay compensation is extracted by the controller at the current time. The oil content in the effluent is calculated by subtracting the hydraulic retention time of the flotation tank from the current time. The oil removal rate is obtained by cross-comparing the historical oil content of the influent at any given time, and is dimensionless. The hydraulic retention time in the flotation tank, with dimensions of ; The sampling and calculation period of the control system, with dimensions of ; Let be the response time constant of the process object, with dimensions . ; , The feedback proportionality constant is dimensionless.

[0073] Among them, hydraulic residence time The hydraulic retention time refers to the average time a liquid spends in an air flotation tank from entry to exit. This concept reflects the relationship between the treatment capacity of the air flotation tank and its volume and flow rate. It is a key parameter affecting the response speed of the air flotation separation effect. The hydraulic retention time can be estimated by the ratio of the effective volume of the air flotation tank to the influent flow rate, or it can be accurately measured by tracer experiments. For example, the average retention time can be determined by injecting a tracer at the inlet and monitoring its concentration change curve at the outlet; or, during the design phase, it can be theoretically calculated based on the geometric dimensions and design flow rate of the air flotation tank.

[0074] Time delay compensation is a strategy employed in control systems to offset or reduce signal transmission or response delays caused by physical processes (such as hydraulic residence time). This feature ensures that control commands (such as demulsifier injection volume) are synchronized with or predictively adjusted in time with the controlled object (such as the air flotation separation effect). Time delay compensation can be achieved in various ways, such as by using predictive control algorithms to predict future states based on historical data and system models, and performing control actions in advance; or by introducing delay elements to align feedback signals with control actions in time.

[0075] Air flotation operation efficiency coefficient This is an indicator for measuring the actual oil removal effect of the air flotation separation unit after hydraulic residence time compensation. To accurately establish a causal mapping between reagent dosage and final separation effect, and to avoid control blind spots caused by fluid penetration delay, the oil removal rate calculation must adopt the cross-time point alignment method. The specific calculation method is as follows: [historical moments] Oil content in influent Current moment Oil content in effluent Historical moment The oil content of the influent and the oil content of the effluent can be monitored in real time by an online oil content analyzer and stored in the controller's historical database. This time-aligned calculation method truly reflects the separation results produced at present after the previously added reagents have stayed in the tank.

[0076] Sampling and processing cycle The sampling and calculation cycle refers to the time interval between the controller acquiring data on the system state and executing control algorithm calculations. This cycle is a fundamental parameter in digital control systems, determining the real-time performance and response speed of the control system. The sampling and calculation cycle can be set according to process requirements and controller hardware performance. For example, it can be set to several seconds to tens of seconds to balance control accuracy and computational resource consumption; or, based on the dynamic characteristics of the system, a sufficiently short cycle can be selected to capture key changes.

[0077] Process object response time constant The response time constant refers to the time scale required for a controlled process object (such as an air flotation separation process) to respond to a control input (such as the amount of demulsifier injected). This constant characterizes the magnitude of the inertia of the process and is an important basis for designing controller parameters. The response time constant of the process object can be determined by conducting a step response experiment on the process. For example, while keeping other conditions constant, suddenly change the amount of demulsifier injected and record the change curves of parameters such as water and oil content, and extract the response time constant from the curves; or, it can be determined by establishing a mathematical model of the process and conducting simulation analysis.

[0078] The online concentration and flow optimization model will determine the degree of demulsification synergy at the current moment. Compared with the hydraulic retention time in the flotation tank Compensated air flotation operation efficiency coefficient Coupled calculations are performed to overcome the control blind spot caused by the response lag of the physical system. The controller first calculates the demulsification phase separation coordination degree at the current moment based on the real-time data obtained by the sensing system, combined with the emulsion layer stability model, the coalescer health model, and the demulsification phase separation coordination degree model. This synergy reflects the current ease or difficulty of oil-water separation and the demand for demulsifiers. Simultaneously, the controller will backtrack to the current moment and subtract the hydraulic retention time of the flotation tank. Historical oil content data of influent and effluent at various times were used to calculate the efficiency coefficient of the air flotation operation after time-delay compensation. This coefficient truly reflects the situation in The actual degreasing effect produced by the previously added chemicals at the current moment.

[0079] The controller then adjusts the current demulsifier injection flow rate. Multiplied by a based and The correction factor is used to calculate the target demulsifier injection flow rate. Among them, the numerator of the correction factor This reflects the intensity of the current demulsification demand. When the synergy is low (i.e., the demulsification effect is poor), this term will increase, prompting an increase in injection flow rate; denominator term This reflects the actual effect of historical chemical dosing. When the efficiency coefficient of the flotation operation is high (i.e., the oil removal effect is good), this term will increase, causing the injection flow rate to decrease. This ensures that the feedback signal and the current dosing action are strictly aligned on the time axis, thereby achieving closed-loop regulation of the dosing amount. In addition, the calculation formula also introduces an exponential term. Through sampling and operation cycles With the response time constant of the process object The ratio of the values ​​is used to smooth the adjustment range, which effectively avoids drastic fluctuations in the dosage caused by sudden changes in operating conditions. This allows the dosing system to adjust the dosage in advance or in advance based on the actual hysteresis characteristics of the system, ensuring the stability of the demulsification process. In this way, this solution can strictly align the macroscopic hysteresis flotation efficiency with the microscopic instantaneous interfacial tension and oil droplet size, thereby achieving precise dosing of the demulsifier.

[0080] By introducing a time-delay compensation feature that includes hydraulic residence time, this scheme achieves precise dynamic optimization of the demulsifier injection flow rate. This allows the dosing system to adjust the injection amount in advance or after the actual lag characteristics of the system, ensuring strict alignment of the feedback signal and the current dosing action on the time axis. This avoids the risk of increased costs due to excessive dosing or demulsification failure due to insufficient dosing. Ultimately, it effectively prevents foaming, scaling on the pipe walls, or even forced shutdown of the downstream MVR evaporation and crystallization equipment, significantly improving the treatment effect of oil and gas field wastewater and the operational stability of the system.

[0081] The calculation logic for the online mass concentration of the target demulsifier conforms to the discrete update characteristic, specifically as follows: The target online mass concentration of the demulsifier is obtained by multiplying the current online mass concentration of the demulsifier by a concentration dynamic correction term based on the principle of exponential decay. The exponential variable of the concentration dynamic correction term is calculated based on the deviation between the current comprehensive performance index of the system (i.e., the comprehensive evaluation of the current demulsification phase synergy and the efficiency coefficient of the air flotation operation after time delay compensation) and the preset synergy trigger dead zone benchmark value. Only when the deviation of the overall system performance index exceeds the dead zone benchmark value will the smoothing index correction of the dosing mass concentration be triggered according to the preset attenuation ratio constant, in order to filter out the interference caused by minor operating condition fluctuations.

[0082] The formula for calculating the online mass concentration of the target demulsifier conforms to the discrete update characteristic, specifically: ; In the formula, The target demulsifier online mass concentration, with dimensions of ; The current online mass concentration of the demulsifier, with dimensions of _____. ; The constant for the dead zone reference value of the degree of synergy trigger is dimensionless; The feedback attenuation ratio constant is dimensionless.

[0083] The calculation formula for the online mass concentration of the target demulsifier conforms to the discrete update characteristic, meaning that the calculation formula is updated in the controller at a preset sampling period. Instead of continuous real-time adjustments, this discrete update mechanism, which performs periodic calculations and updates, effectively manages the computational load of the control system and matches the response characteristics of the reagent dosing equipment in actual industrial processes. The calculation formula itself, by introducing an exponential function, achieves nonlinear and smooth adjustment of the online mass concentration of the demulsifier. This exponential adjustment method can avoid the drastic fluctuations in reagent concentration that may be caused by traditional linear adjustment, ensuring the stability and continuity of the system response.

[0084] Synergy trigger dead zone baseline constant Its function is to set a threshold, when the demulsification phase synergy... Compared with the efficiency coefficient of air flotation operation after time delay compensation When the product of the two values ​​deviates from the baseline value within a certain range, the system does not make or makes only minor concentration adjustments, thereby filtering out minor fluctuations in operating conditions and reducing unnecessary reagent additions.

[0085] Feedback attenuation proportional constant This is used to adjust the sensitivity or response speed of concentration adjustment; its value determines the online mass concentration of the target demulsifier when the system deviates from the ideal state. The speed at which the target value converges can be optimized based on the dynamic characteristics of the actual process object to achieve the best control effect.

[0086] By introducing an exponential decay model with discrete update characteristics, dynamic and smooth adjustment of the online mass concentration of demulsifier is achieved. The core of this scheme lies in the controller utilizing the real-time acquired demulsification phase separation synergy. (This synergy comprehensively reflects multiple key parameters such as the emulsion layer stability coefficient, coalescer health, median influent oil droplet size, and effluent dynamic interfacial tension) as well as the air flotation operation efficiency coefficient after time-delay compensation. The product of the two is used as an indicator of the current overall system performance. Subsequently, this overall performance indicator is compared with a preset synergy trigger dead zone baseline constant. Compare them.

[0087] When the comprehensive performance index deviates At that time, the controller will adjust the feedback attenuation ratio constant based on the degree of deviation. Sampling and calculation cycle of the control system and the response time constant of the process object An adjustment factor is calculated using an exponential function, and this adjustment factor acts multiplicatively on the current online demulsifier concentration. This generates a new target demulsifier online mass concentration. This index update mechanism ensures the continuity and stability of the concentration adjustment process, effectively suppresses drastic fluctuations in the control process, and avoids system shocks caused by abrupt dosing. Simultaneously, the synergy triggers the dead zone baseline value. The introduction of this feature effectively filters out minor fluctuations in operating conditions, triggering effective concentration correction only when the synergy deviates from the preset benchmark, thereby reducing reagent waste. Feedback attenuation ratio constant. With sampling period Process response time constant The combination of these technologies enables the concentration adjustment to adaptively match the actual response characteristics of the system, ensuring that the dosage concentration can accurately respond to the comprehensive changes in the demulsification phase separation synergy and air flotation efficiency, and realizing refined closed-loop management of the dosing process.

[0088] By introducing an exponential decay model with discrete update characteristics, dynamic and smooth adjustment of the online mass concentration of demulsifier is achieved, avoiding over- or under-dosing. Utilizing the synergy-triggered dead zone baseline effectively filters out minor fluctuations in operating conditions, reducing reagent waste. Simultaneously, combining the feedback decay ratio constant, sampling period, and process response time constant allows concentration adjustment to adaptively match system characteristics, ensuring precise response of the dosing concentration to the combined changes in demulsification phase separation synergy and flotation efficiency. This refined closed-loop management significantly improves the pretreatment effect of MVR evaporation crystallization equipment in oil and gas field water treatment, reduces operating costs, and effectively avoids problems such as foaming, pipe scaling, and even forced shutdowns caused by improper pretreatment in downstream MVR evaporation crystallization equipment, thereby ensuring the stable and efficient operation of the entire water treatment system.

[0089] The hardware layout of the sensing and detection system on the separation tank 2 is as follows: The probe of the online array profiler 7 penetrates vertically through the top plate of the separation tank 2 and extends to the oil-water interface in the middle of the tank; The online gas detection transmitter 6 is flange-connected to the gas phase balance pipeline 5 at the top of the separation tank 2; The high-pressure and low-pressure ports of the differential pressure transmitter are rigidly connected to the side walls of the inlet and outlet manifolds of the coalescing separation unit, respectively. The online microwave density meter is installed in series in the slag discharge overflow pipe on the side wall of the air flotation unit of the separation tank 2.

[0090] The probe of the online array profiler 7 is a sensor component used to monitor the position of liquid layering interfaces in real time. It is used to directly contact and sense the differences in physical properties of different liquid phases (such as oil phase, water phase, and emulsion layer), thereby accurately obtaining the thickness and height position information of the emulsion layer. The probe can be implemented based on a variety of principles. By using multiple capacitive sensors distributed along the length of the probe, the interface is identified by measuring the change in dielectric constant at different heights.

[0091] The online gas detection transmitter 6 is a device used to monitor the mass concentration of a specific gas (such as hydrogen sulfide) in the gas phase in real time. It can convert the detected gas concentration into a standard electrical signal output for the controller to process. The transmitter can use the principle of electrochemical sensor to measure the concentration by the change in current generated by the reaction of the target gas with the electrode.

[0092] A differential pressure transmitter is an instrument used to measure the pressure difference between two pressure points. Its high-pressure tap and low-pressure tap are connected to different locations of the fluid being measured to obtain the pressure difference between the two points. This transmitter can use the diaphragm principle and output a signal by measuring the displacement caused by the pressure difference on both sides of the diaphragm.

[0093] The aforementioned online microwave densitometer is a device that uses microwave technology to measure fluid density in real time. It determines fluid density by analyzing the attenuation or phase shift changes of microwave signals after they penetrate the fluid medium. This densitometer can adopt the principle of microwave resonant cavity and measure the characteristics of resonant frequency changing with the density of the medium.

[0094] By precisely defining the hardware layout of the sensing and detection system, efficient and accurate acquisition of key physical quantities inside the separation tank 2 is achieved, providing reliable input data for subsequent automated control models. The probe of the online array profiler 7 vertically penetrates the top plate of the separation tank 2 and extends to the oil-water interface in the middle of the tank, avoiding distortion in the calculation of the emulsion layer stability coefficient due to measurement position offset. The online gas detection transmitter 6 is flanged and connected to the gas phase balance pipeline 5 at the top of the separation tank 2. Using the gas phase balance pipeline 5 as a gas sampling point, the true concentration of hydrogen sulfide in the gas phase at the top of the separation tank 2 can be effectively captured, thus providing accurate concentration parameters for the evaluation of the hydrogen sulfide stabilization effect in the emulsion layer stability model. The high-pressure and low-pressure taps of the differential pressure transmitter are rigidly connected to the side walls of the inlet and outlet manifolds of the coalescing separation unit, respectively. This differential pressure measurement layout can directly reflect the fluid flow through the coalescing filter element. The pressure loss during operation accurately characterizes the degree of filter clogging and the health of the coalescer, ensuring the real-time and effective calculation of the health coefficient. An online microwave densitometer is installed in series in the slag overflow pipe on the side wall of the flotation unit in separation tank 2. By monitoring the density of the slag discharged from the flotation tank online, the moisture content of the slag can be directly obtained. This arrangement places the sensor on the critical path of material flow, ensuring dynamic perception of the flotation operation efficiency and slag status, providing crucial material attribute data for the coalescer health model. Through the specific placement of the sensors, a three-dimensional perception of the fluid state inside separation tank 2 is achieved, solving the problem of data acquisition lag or distortion caused by improper sensor installation. This ensures that the subsequent demulsification and phase separation synergy model and dosing optimization model can be calculated based on real and accurate operating data, thereby improving the operational stability of the entire water treatment system.

[0095] Separation tank 2 and MVR evaporation crystallization equipment body 1 are integrated in series via a piping system: The treated water outlet at the bottom of the separation tank 2 is connected to the raw material liquid preheater inlet of the MVR evaporation crystallization equipment body 1 through the water outlet pipe 3 and the booster pump 4. A bypass detection pipe 8 is connected in parallel on the water outlet pipe of the separation tank 2. An online laser particle size analyzer and an online dynamic interfacial tension meter are installed in a flow-through manner on the bypass detection pipe 8.

[0096] The separation tank 2 and the MVR evaporation crystallization equipment body 1 are integrated in series through a pipeline system. This means that the pretreatment unit (separation tank 2) and the core treatment unit (MVR evaporation crystallization equipment body 1) are connected by physical pipelines to form a continuous process flow. This pipeline system can use rigid pipelines, such as welded steel pipes or flanged connecting pipes, to ensure stable fluid transmission between the two devices. Alternatively, flexible pipelines, such as pressure-resistant hoses or corrugated pipes, can be used to accommodate equipment installation errors or vibrations while maintaining the continuity of fluid transmission. This integration method aims to ensure that oil and gas field wastewater, after preliminary separation treatment, can directly and orderly enter the MVR evaporation crystallization equipment for deep treatment, forming an integrated water treatment system.

[0097] The treated water outlet at the bottom of the separation tank 2 refers to the discharge port of the aqueous phase fluid in the separation tank 2 after pretreatment such as oil-water separation and suspended solids removal. It is located at the bottom of the tank to discharge the denser aqueous phase. This outlet serves as the output end of the pretreatment effect of the separation tank 2 and is a key interface for connecting to the subsequent MVR evaporation crystallization equipment. The intermediate booster pump 4 is a mechanical device used to increase the fluid pressure and / or flow rate. It is installed between the treated water outlet of the separation tank 2 and the liquid inlet of the MVR evaporation crystallization equipment body 1. The booster pump 4 can be a centrifugal pump, suitable for high flow rate and medium-low head liquid transportation; or it can be a positive displacement pump, such as a screw pump or gear pump, suitable for high viscosity liquids or liquids that require precise metering and transportation. Its function is to overcome pipeline resistance and ensure that the treated water can enter stably at the pressure and flow rate required by the MVR evaporation crystallization equipment body 1.

[0098] The raw material liquid preheater inlet of the MVR evaporation crystallization equipment body 1 is the inlet of the component in the MVR evaporation crystallization equipment body 1 used to receive the raw material liquid to be treated and perform preliminary heating. It is the starting point for the MVR evaporation crystallization equipment body 1 to receive the front-end treated water and start the evaporation process. The bypass detection pipe 8 is connected in parallel on the water outlet pipe of the separation tank 2. This means that a part of the water flow is diverted from the main water outlet pipe of the separation tank 2 into an independent pipe, usually with a smaller diameter, for online detection. The bypass detection pipe 8 can be led out by welding a T-joint on the main pipe or by installing a bypass valve group on the main pipe to achieve precise control of the bypass flow.

[0099] An online laser particle size analyzer is an instrument that uses the principle of laser scattering to measure the particle size distribution of particles (such as oil droplets and suspended solids) in a fluid in real time. This analyzer can be based on... The laser diffraction principle of scattering theory is applicable to a wide range of particle sizes; it can also be based on the dynamic light scattering (DLS) principle and is applicable to the measurement of nanoscale particles. Its role is to monitor the particle size distribution of oil droplets in treated water in real time and provide key input parameters for the demulsification and phase separation synergy model.

[0100] An online dynamic interfacial tension meter is an instrument that measures the interfacial tension between a liquid and a gas, or between two immiscible liquids, in real time. It is typically used to assess the surface activity or emulsion stability of liquids. This interfacial tension meter can be based on bubble pressure methods (such as the maximum bubble pressure method), oscillating jet methods, or drop volume methods. Its function is to monitor the dynamic interfacial tension of treated water in real time, providing key input parameters for demulsification and phase separation synergy models, and reflecting the demulsification effect.

[0101] The online laser particle size analyzer and online dynamic interfacial tensiometer are flow-through mounted on the bypass detection tube 8. This means that the instruments are directly installed in the bypass detection tube 8, allowing the fluid to be measured to continuously flow through the instrument's measuring chamber, achieving real-time and continuous online measurement. This installation method can be achieved by directly inserting the instrument's sensor into the bypass pipe via a flange or threaded connection. Alternatively, the bypass pipe can be designed as a structure with a measuring pool, in which the instrument probe is immersed. Its purpose is to ensure that the instruments can continuously contact representative water samples, acquire real-time data, and support online control.

[0102] By integrating the separation tank 2 with the MVR evaporation crystallization equipment body 1 through a pipeline system and optimizing the physical layout of fluid transportation and online detection, this solution effectively solves the problems of poor fluid connection and insufficient representativeness of detection data between the separation tank 2 and the subsequent evaporation crystallization equipment body in the traditional solution. It significantly improves the operational stability, treatment efficiency and automation level of the entire oil and gas field wastewater treatment system, and effectively reduces the operating costs and equipment failure risks caused by improper reagent dosing.

[0103] The dosing system includes a variable frequency dosing pump and a pipeline static mixer: The pipeline static mixer is installed in series on the main water inlet line of the separation tank 2. The outlet of the variable frequency dosing pump is connected to the inlet of the pipeline static mixer through the dosing check valve. The variable frequency dosing pump is electrically connected to the controller to receive the target demulsifier injection flow rate and online mass concentration command and adjust the output frequency and reagent ratio.

[0104] A variable frequency dosing pump is a metering pump that can adjust its output flow rate and pressure according to external control signals (such as instructions output by a controller). Its working principle is usually to control the motor speed through a frequency converter, thereby precisely controlling the pump's stroke frequency or the displacement speed of the piston / diaphragm to achieve accurate dosing of the agent. A variable frequency diaphragm metering pump can be used, which drives the diaphragm to reciprocate through a variable frequency motor to achieve the intake and discharge of the agent; or a variable frequency plunger metering pump can be used, which drives the plunger to reciprocate through a variable frequency motor to achieve accurate metering of the agent.

[0105] A pipeline static mixer is a mixing device without moving parts. It uses specially structured mixing elements inside the pipeline to generate complex movements such as diversion, merging, shearing, and vortexing when the fluid passes through the mixer, thereby achieving rapid and uniform mixing of two or more fluids. A spiral static mixer can be used, in which the internal mixing elements are arranged in a spiral shape, forcing the fluid to divert and merge radially.

[0106] A chemical dosing check valve is a one-way valve designed to prevent backflow of fluid. In a chemical dosing system, it ensures that the chemical can only flow from the dosing pump to the main pipeline, preventing backflow when the pressure in the main pipeline is higher than the outlet pressure of the dosing pump. This protects the safety of the dosing pump and the dosing pipeline. A spring-loaded check valve can be used, where the valve disc closes when there is no pressure difference and opens when there is a positive pressure difference; or a lift-type check valve can be used, where the valve disc moves up and down along the valve body axis due to fluid pressure, achieving unidirectional flow.

[0107] The electrical connection between the controller and the variable frequency dosing pump refers to the communication and control between the two through electrical signal transmission. This connection enables the controller to send the calculated target demulsifier injection flow rate and online mass concentration command to the variable frequency dosing pump in real time, and to receive feedback on the pump's operating status.

[0108] The variable frequency dosing pump changes the pump's output flow rate by adjusting the operating frequency of its motor according to the instructions received from the controller, thereby achieving precise control of the target demulsifier injection flow rate. At the same time, if the agent needs to be diluted or mixed, the variable frequency dosing pump can also adjust the ratio of agent to diluent according to instructions through internal or external proportioning units to achieve the target online mass concentration.

[0109] The introduction of a variable frequency dosing pump allows for precise adjustment of the demulsifier injection flow rate and online mass concentration based on the optimal instructions calculated in real time by the controller. This avoids waste or insufficient dosing of the agent. The static mixer in the pipeline ensures that the demulsifier can be efficiently and uniformly mixed with the oily wastewater before entering the separation tank 2, greatly improving the utilization rate and demulsification efficiency of the agent, thereby enhancing the overall demulsification and phase separation synergy. The dosing check valve ensures the operational safety and stability of the dosing system. This combination of precise dosing and efficient mixing enables the separation tank 2 to perform oil removal and suspended solids pretreatment more stably and efficiently, significantly reducing the risk of foaming, scaling on the pipe walls, or forced shutdown of the downstream MVR evaporation and crystallization equipment, thus ensuring the continuity and economy of oil and gas field wastewater treatment.

[0110] In this solution, in order to solve the problem that traditional systems cannot perceive multidimensional deterioration factors in real time and that sensor data acquisition is prone to lag and distortion, a sensing and detection system covering equipment such as array profilers and multi-parameter transmitters is set up. A specific three-dimensional arrangement of the separation tank 2 and the bypass detection tube 8 structure are adopted. By directly collecting multidimensional physical parameters on the key material path, the system achieves the effect of providing a comprehensive and real data foundation for subsequent intelligent closed-loop control. To address the difficulty in objectively assessing the stubbornness of the emulsion layer, an emulsion layer stability model was constructed within the controller. This model utilizes the obtained emulsion layer thickness, optimal interface deviation, and gaseous hydrogen sulfide concentration to perform nonlinear mathematical calculations, thereby transforming the complex emulsion accumulation and chemically stabilized state into a single quantitative evaluation index. To address the limitations of traditional strategies in detecting the degradation of coalescing device physical performance, a coalescing device health model was constructed. By comprehensively calculating parameters such as filter cartridge pressure difference, total suspended solids in influent, and air-water ratio deviation through an exponential degradation term, the model achieves a dynamic quantitative assessment of the actual load-bearing capacity and sub-health status of the separation equipment. To overcome the one-sidedness of evaluating the separation state with a single parameter, the system combines the coefficients obtained from the first two models and introduces the median value of the influent oil droplet size and the dynamic interfacial tension of the effluent to construct a demulsification and phase separation synergy model. This process deeply integrates the macroscopic equipment operating health and microscopic fluid characteristics, achieving the effect of accurately understanding the actual difficulty of oil-water separation and the current real demand for demulsifiers. To address the issues of blind spots and over- or under-dosing caused by the lack of time-series phase compensation in traditional dosing control, an online concentration and flow optimization model was constructed. The controller aligns historical oil removal rates by extracting time-delay compensation features including the hydraulic retention time of the flotation tank, and calculates the target concentration and flow rate using an exponential decay formula that conforms to discrete update characteristics. This achieves the effects of overcoming system response lag, automatically filtering out minor operating condition fluctuations, and realizing smooth dynamic adjustment. To address the issues of poor fluid connection between the front and back ends and low reagent mixing efficiency, this solution integrates the separation tank 2 and the MVR evaporation crystallization equipment body 1 in series via a booster pump 4 pipeline. An execution system including a variable frequency dosing pump and a pipeline static mixer is also included. The variable frequency dosing pump receives concentration and flow commands from the optimization model and performs precise frequency adjustment. The static mixer then utilizes fluid kinetic energy to achieve efficient shear mixing, thereby significantly improving demulsification efficiency, reducing reagent costs, and effectively preventing foaming, scaling, or shutdown of the core components of the subsequent MVR evaporation crystallization process.

[0111] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. An MVR evaporation crystallization device for oil and gas field water treatment, comprising an MVR evaporation crystallization device body (1) and a separation tank (2) integrated on the MVR evaporation crystallization device body (1); Its features are: The separation tank (2) is equipped with an air flotation and coalescence separation unit. The separation tank (2) is equipped with a sensing detection system and a dosing system. The sensing detection system and the dosing system are both connected to a controller. The controller extracts the multi-dimensional physical parameters of the sensing detection system for calculation and dynamically adjusts the amount of demulsifier injected in the dosing system to control the state of the emulsion layer in the separation tank (2). The sensing and detection system includes: an online array profiler (7), an online gas detection transmitter (6), a differential pressure transmitter, a suspended solids concentration meter, a high-precision gas flow meter, a liquid flow meter, an online microwave density meter, an online laser particle size analyzer, and an online dynamic interfacial tension meter. The controller performs the following operations: S1: Based on the real-time emulsion layer thickness and height position obtained by the online array profiler (7) and the gas phase hydrogen sulfide mass concentration obtained by the online gas detection transmitter (6), an emulsion layer stability model is constructed and the emulsion layer stability coefficient is calculated. S2: Based on the actual gas-water volume ratio of dissolved air and water obtained by the high-precision gas flow meter and liquid flow meter, the water content of scum in the flotation tank obtained by the online microwave density meter, the pressure difference of the coalescing filter element obtained by the differential pressure transmitter, and the total amount of suspended solids in the influent obtained by the suspended solids concentration meter, a coalescing health model is constructed to calculate the coalescing health coefficient. S3: Based on the median value of the influent oil droplet size obtained by the online laser particle size analyzer and the dynamic interfacial tension of the effluent obtained by the online dynamic interfacial tension meter, the demulsification phase separation synergy model is constructed by combining the emulsion layer stability coefficient and the coalescer health coefficient to calculate the demulsification phase separation synergy. S4: Based on the demulsification phase separation synergy and the extracted air flotation operation efficiency coefficient, construct an online concentration and flow rate optimization model, and output the target demulsifier injection flow rate and online mass concentration to control the dosing system.

2. The MVR evaporation and crystallization equipment for oil and gas field water treatment according to claim 1, characterized in that: The specific calculation logic of the emulsion layer stabilization model constructed within the controller is as follows: The normalized ratio of the real-time emulsion layer thickness to the preset maximum allowable thickness limit, the normalized ratio of the gas phase hydrogen sulfide mass concentration to the stabilization critical concentration threshold, and the normalized ratio of the absolute deviation of the real-time emulsion layer height from the optimal interface to the maximum effective working height are obtained. After assigning the three normalized ratios to the corresponding emulsification stabilization factor weight coefficients, a weighted sum is performed, and the summation result is processed by an S-type nonlinear mapping function to output a dimensionless value between 0 and 1 as the emulsification layer stability coefficient. The stability coefficient of the emulsion layer is positively correlated with the real-time emulsion layer thickness, the mass concentration of hydrogen sulfide in the gas phase, and the degree of high interface deviation.

3. The MVR evaporation crystallization equipment for oil and gas field water treatment according to claim 2, characterized in that: The specific calculation logic of the coalescer health model built within the controller is as follows: The coalescing unit health coefficient is calculated by coupling a physical blockage attenuation term, a gas-water ratio deviation correction term, and a slag discharge efficiency penalty term. The physical blockage attenuation term is an exponential decay function constructed by weighting the normalized values ​​of the real-time pressure difference of the coalescing filter element and the total amount of suspended solids in the influent; the air-water ratio deviation correction term is constructed based on the degree of deviation of the actual dissolved air-water ratio from the optimal air-water ratio, and is non-linearly negatively correlated with the actual air-water deviation; the sludge discharge efficiency penalty term is constructed based on the deviation margin of the sludge moisture content in the flotation tank from the maximum moisture content limit, and is negatively correlated with the moisture content; the three terms are combined to output the coalescing filter health coefficient.

4. The MVR evaporation and crystallization equipment for oil and gas field water treatment according to claim 3, characterized in that: The specific calculation logic of the demulsification phase synergy model constructed within the controller is as follows: The obtained coalescer health coefficient, emulsion layer stability coefficient, normalized ratio of median influent oil droplet size to benchmark critical size, and normalized ratio of online dynamic interfacial tension of effluent to benchmark standard interfacial tension are respectively assigned corresponding synergistic response incentive weights. The demulsification and phase separation synergy is evaluated using a nonlinear function with logistic characteristics. The system-wide excitation independent variable of this function is composed of the positive excitation weighted value of the coalescing coefficient and the influent oil droplet size, minus the negative inhibition weighted value of the emulsion layer stability coefficient and interfacial tension, and combined with the function offset constant. The resulting demulsification and phase separation synergy is positively correlated with physical separation capability and oil droplet size, and negatively correlated with the emulsion layer stubbornness and effluent interfacial tension.

5. The MVR evaporation crystallization equipment for oil and gas field water treatment according to claim 4, characterized in that: In the online concentration and flow rate optimization model, the calculation logic for the target demulsifier injection flow rate includes a time-delay compensation feature for the hydraulic residence time, specifically: The target demulsifier injection flow rate is obtained by multiplying the current demulsifier injection flow rate by a flow dynamic correction factor. The adjustment direction of the flow dynamic correction factor is jointly constrained by the current demulsification phase synergy and the historical time-delay flotation operation efficiency coefficient: its increase is positively correlated with the current urgent need for demulsifier; its decrease is positively correlated with the actual oil removal rate calculated in advance based on the hydraulic retention time of the flotation tank. Meanwhile, the single adjustment step size of the target demulsifier injection flow rate is limited by a smooth scaling of the ratio of the sampling calculation cycle of the control system to the response time constant of the process object.

6. The MVR evaporation crystallization equipment for oil and gas field water treatment according to claim 5, characterized in that: The calculation logic for the online mass concentration of the target demulsifier conforms to the discrete update characteristic, specifically: The target online mass concentration of the demulsifier is obtained by multiplying the current online mass concentration of the demulsifier by a concentration dynamic correction term based on the principle of exponential decay. The exponential variable of the concentration dynamic correction term is calculated based on the deviation between the current comprehensive performance index of the system and the preset synergy trigger dead zone benchmark value. When the deviation of the overall performance index of the system exceeds the dead zone reference value, the smoothing index correction of the dosing mass concentration is triggered according to the preset attenuation ratio constant to filter out the interference caused by minor operating condition fluctuations.

7. The MVR evaporation crystallization equipment for oil and gas field water treatment according to claim 6, characterized in that: The hardware layout of the sensing and detection system on the separation tank (2) is as follows: The probe of the online array profiler (7) penetrates vertically through the top plate of the separation tank (2) and extends to the oil-water interface in the middle of the tank. The online gas detection transmitter (6) is flange-connected to the gas phase balance pipeline (5) at the top of the separation tank (2); The high-pressure and low-pressure ports of the differential pressure transmitter are rigidly connected to the side walls of the inlet and outlet manifolds of the coalescing separation unit, respectively. The online microwave density meter is installed in series in the slag discharge overflow pipe on the side wall of the air flotation unit of the separation tank (2).

8. The MVR evaporation crystallization equipment for oil and gas field water treatment according to claim 7, characterized in that: The separation tank (2) and the MVR evaporation crystallization equipment body (1) are integrated in series via a pipeline system: The treatment water outlet at the bottom of the separation tank (2) is connected to the raw material liquid preheater inlet of the MVR evaporation crystallization equipment body (1) through the water outlet pipe (3) and the booster pump (4). A bypass detection pipe (8) is connected in parallel on the water outlet pipe (3) of the separation tank (2). The online laser particle size analyzer and the online dynamic interfacial tension meter are installed in a flow-through manner on the bypass detection pipe (8).

9. The MVR evaporation crystallization equipment for oil and gas field water treatment according to claim 8, characterized in that: The dosing system includes a variable frequency dosing pump and a pipeline static mixer. The pipeline static mixer is installed in series on the main water inlet line of the separation tank (2). The outlet of the variable frequency dosing pump is connected to the inlet of the pipeline static mixer through the dosing check valve. The variable frequency dosing pump is electrically connected to the controller and is used to receive the target demulsifier injection flow rate and online mass concentration command and adjust the output frequency and reagent ratio.

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