Complex medium-resistant multi-parameter cooperative control method and system for gel-nano composite foam scrubbing agent

Abstract

The invention discloses a complex-medium-resistant multi-parameter cooperative control method and system for a gel-nano composite foam scrubbing agent, and relates to the technical field of gas field foam drainage gas recovery, and the method comprises the steps: building a complex medium parameter correlation model, and analyzing a coupling rule and an interaction weight of four parameters of mineralization degree, temperature, gas condensate content and methanol content; constructing a multi-parameter response test matrix, setting a plurality of parameter combinations, and repeating the experiment; wellbore parameters are collected in real time, and whether cooperative regulation is triggered or not is judged through a control system; aiming at the mineralization degree and temperature synergetic overrun or condensate oil and methanol synergetic overrun, respectively starting corresponding adjusting modules to carry out synergetic regulation and control; the liquid carrying efficiency is tested through dynamic simulation, and the regulation and control effectiveness is judged according to the foam comprehensive index FCI lifting amplitude and the test deviation; the system comprises a parameter acquisition module, a data transmission module, a control module and a plurality of adjustment modules, and real-time monitoring and dynamic coordinated regulation of parameters are realized. The stability and liquid carrying efficiency of the foam scrubbing agent in a complex medium are effectively improved, the foam scrubbing agent adapts to the severe environment of a western gas field, and stable production of a gas well is guaranteed.

Description

Technical Field

[0001] The invention relates to the technical field of gas field foam drainage and gas production, and in particular to a multi-parameter coordinated control method and system for a gel-nano composite foam drainage agent resistant to complex media. Background Art

[0002] As an important natural gas producing area, the development of China's western gas fields faces severe challenges in complex media environments such as high temperature, high salinity, and condensate oil and methanol. During gas well production, bottomhole liquid accumulation can lead to a sharp drop in production capacity or even flooding and shutdown, and foam drainage and gas recovery technology is the core means to solve this problem. However, the performance of traditional foaming agents is greatly reduced under complex media conditions: high temperature accelerates the decomposition of surfactants, high-salinity ions destroy the double layer of the foam liquid film, condensate oil competes with surfactants for adsorption sites, and methanol reduces interfacial tension stability, resulting in a significant decrease in foaming ability and foam half-life. Therefore, there is an urgent need to develop a foaming agent control technology that can maintain high performance under the synergistic effect of multiple parameters to adapt to the harsh mining environment of western gas fields and ensure stable gas well production.

[0003] Traditional foam drainage technology primarily relies on a single surfactant or a simple compound system to achieve foaming and liquid carrying by reducing the surface tension of the liquid. For example, early use of anionic surfactants such as sodium dodecyl sulfate (SDS) produced good foaming effects at room temperature and low salinity, but they were easily hydrolyzed at high temperatures (>80°C), shortening their half-life by more than 50%. When faced with formation water with a salinity >100,000 mg / L, the ion shielding effect caused the foam film to rupture faster, reducing liquid carrying efficiency by 40%. Furthermore, traditional technologies lack the ability to regulate the coupling of multiple parameters. When condensate oil (>20%) and methanol (>15%) are present simultaneously, the surfactants tend to migrate to the oil phase, sharply deteriorating the foam stability and failing to meet the production needs of complex gas fields.

[0004] In recent years, researchers have tried to introduce nanoparticles and gels to improve the performance of foaming agents. For example, nano-SiO2 particles are compounded with surfactants, and the physical adsorption of particles at the gas-liquid interface is used to enhance the strength of the liquid film and improve salt tolerance; polymer gels are used to increase the viscosity of the liquid phase and delay the drainage of the liquid film. However, existing technologies still have limitations: first, a multi-parameter coordinated control mechanism has not been established, and only a single factor (such as temperature or salinity) is optimized. When multiple parameters exceed the standard at the same time, the performance improvement is limited; second, the synergistic effect of nanoparticles and gels has not been quantified, and the addition ratio is determined by experience, which can easily lead to increased costs or inhibition of foaming ability; third, there is a lack of real-time monitoring and dynamic control systems, and the formula cannot be adjusted in time according to changes in wellbore parameters, limiting its applicability. Summary of the Invention

[0005] Based on the above technical problems, the present application discloses a multi-parameter coordinated control method and system for a gel-nano composite foaming agent resistant to complex media, wherein the coordinated control method specifically includes:

[0006] S1. Establish a complex medium parameter correlation model, analyze the coupling effect between the four parameters of salinity, temperature, condensate content, and methanol content, and determine the interaction weights of the four parameters through orthogonal experimental design;

[0007] S2. Construct a multi-parameter response test matrix to obtain the distribution probability of typical operating conditions. Select benchmark points for salinity, temperature, condensate oil, and methanol. Set multiple parameter combinations based on salinity gradient, temperature gradient, condensate oil gradient, and methanol gradient. Repeat the experiment for a preset number of times for each parameter set.

[0008] S3. By collecting data on salinity, temperature, condensate oil, and methanol content in the wellbore in real time, the parameter values ​​are fed back to the control system using a data transmission module. The control system determines whether to trigger the coordinated control mechanism based on preset thresholds;

[0009] S4. When it is monitored that the salinity and temperature exceed the limit, the nanoparticle concentration adjustment module and the gel strength control module are used to increase the amount of solid foam stabilizer and adjust the gel cross-linking degree to form a synergistic enhancement effect. When the condensate oil and methanol exceed the limit, the surfactant supplementation module and the interfacial tension adjustment module are activated to balance the gas-liquid interface performance by compounding surfactants and adding additives.

[0010] S5. Use dynamic simulation to test the liquid carrying efficiency of the foam removal agent under the set parameter combination conditions. When the foam comprehensive index FCI is improved by more than the preset range compared with the single parameter control and the continuous test deviation is less than 5%, it is determined that the coordinated control is effective.

[0011] Preferably, when establishing the complex medium parameter association model in S1, the actual production data of salinity, temperature, condensate oil content, and methanol content of typical wells in the gas field are obtained, covering the parameter ranges of different well depths and mining stages, and the salinity C, temperature T, condensate oil O, and methanol content M are divided into preset range gradients. The dimension effect is eliminated by data normalization processing, and the foam comprehensive index FCI is used as the response value to construct a nonlinear mapping relationship model between the four parameters and FCI. The formula is: Among them, C0, T0, O0, and M0 are the benchmark values ​​of salinity, temperature, condensate oil content, and methanol content, respectively; k is the comprehensive correction coefficient; a, b, c, and d are the influence indices of salinity, temperature, condensate oil content, and methanol content, respectively. The model parameters are iteratively optimized to ensure that the error between the predicted value and the experimental value is controlled within 5%.

[0012] Preferably, when analyzing the coupling effect law between the four parameters in S1, an orthogonal experimental table is designed through the gradient range of the parameters of salinity, temperature, condensate oil content and methanol content. The salinity, temperature, condensate oil content and methanol content are used as four factors, and each factor takes a level value. The experimental combination is used to test the foaming power, half-life and FCI of the foam, and the range and variance of each factor are calculated. The influence of a single factor and interaction on FCI is analyzed. The greater the range, the more significant the influence of the factor or interaction on the performance of the foam removal agent. The weight of the interaction between salinity and temperature, and condensate oil and methanol is determined according to the range ratio. The credibility of the interaction effect is verified by combining the variance analysis significance test, and the influence weight of each interaction term between the four parameters is determined.

[0013] Preferably, a multi-parameter response test matrix is ​​constructed in S2, specifically as follows: by extracting characteristic values ​​of salinity, temperature, condensate content, and methanol content, the common fluctuation range of each parameter in the wellbore environment and the corresponding probability density distribution are determined, a reference point is selected as the center, and the gradients of each parameter are set at equal intervals. The parameter gradients are cross-combined to form a parameter combination, and the experiment is repeated for a preset number of times for each group of parameters. The degree of data dispersion is evaluated by calculating the standard deviation σ of the experimental data. The formula is: Where n is the number of experimental repetitions for each set of parameters, FCI i is the comprehensive foam index of the ith experiment, is the average value of the comprehensive foam index of the parameter experiment. When σ is less than the preset threshold, the experimental data is determined to be reliable.

[0014] Preferably, the data transmission module is used in S3 to feed back the parameter values ​​to the control system, specifically: by collecting the salinity, temperature, condensate oil and methanol content data in the wellbore in real time and transmitting them to the control system, the control system first calculates the comprehensive parameter deviation Where C, T, O, and M are the parameter values ​​collected in real time, C0, T0, O0, and M0 are the reference values ​​of the corresponding parameters, and the calculated comprehensive parameter deviation D is compared with the preset threshold D. th For comparison, when D≥D th , the coordinated control mechanism is triggered, otherwise the current control state remains unchanged.

[0015] Preferably, in S4, when it is monitored that the mineralization and temperature exceed the limit together, the nanoparticle concentration adjustment module calculates the required amount of nanoparticles to be supplemented according to the proportion of the mineralization exceeding the baseline value, and the synchronous gel strength control module adjusts the addition ratio of the cross-linking agent according to the extent by which the temperature exceeds the baseline value, wherein the nanoparticle concentration increases linearly with the proportion of the mineralization exceeding the limit, and the gel cross-linking degree increases stepwise with the extent of the temperature exceeding the limit. By increasing the amount of solid foam stabilizer added, the pore structure formed by the nanoparticles and the gel network is filled, the gel cross-linking degree is adjusted to optimize the network density to enhance the carrying capacity of the liquid membrane, so that the spatial steric effect of the nanoparticles and the three-dimensional network structure of the gel form a synergistic enhancement effect.

[0016] Preferably, in S4, when the condensate oil and methanol exceed the limit together, the surfactant replenishment module calculates the compound replenishment amount of anionic and nonionic surfactants according to the proportion of the condensate oil content exceeding the baseline value; the interfacial tension adjustment module determines the addition concentration of the auxiliary agent according to the extent to which the methanol content exceeds the baseline value, wherein the ratio of anions to nonionics in the compound surfactant is dynamically adjusted with the excess ratio of the condensate oil to enhance the oil phase compatibility, the addition concentration of the auxiliary agent increases linearly with the excess extent of methanol to offset its negative impact on the interfacial tension, the adsorption efficiency of the gas-liquid interface is improved and an elastic membrane structure is formed by compounding the surfactant, the addition of the auxiliary agent strengthens the directional arrangement stability of the surfactant at the interface, and balances the gas-liquid interface performance to resist the defoaming effect of the condensate oil and the dilution effect of methanol.

[0017] Preferably, in said S5, when dynamic simulation is used to test the liquid carrying efficiency of the foaming agent under the set parameter combination conditions, the foaming agent solution is prepared according to the set salinity, temperature, condensate oil content, and methanol content parameter combination, the foam generation and liquid carrying process are recorded, and the foam comprehensive index FCI at different times is calculated. At the same time, comparative experiments are carried out under the control of single salinity, single temperature, single condensate oil content, and single methanol content, and the corresponding FCI single value is calculated. The formula Calculate the promotion rate, where FCI x FCI is a comprehensive bubble index under coordinated regulation. d is the average FCI value under single parameter control, when η≥η th , η th is the foam comprehensive index threshold, and when the FCI value of continuous testing satisfies η<5%, the collaborative control is judged to be effective.

[0018] Gel-nano composite foaming agent resistant to complex media multi-parameter coordinated control system, including parameter acquisition module, data transmission module, control system, nanoparticle concentration adjustment module, gel strength control module, surfactant supplement module and interfacial tension adjustment module;

[0019] The output end of the parameter acquisition module is connected to the input end of the data transmission module, the output end of the data transmission module is connected to the input end of the control system, and the output end of the control system is respectively connected to the input ends of the nanoparticle concentration adjustment module, the gel strength control module, the surfactant supplementation module and the interfacial tension adjustment module. The parameter acquisition module is used to collect real-time data on salinity, temperature, condensate oil content and methanol content in the wellbore;

[0020] The data transmission module is used to transmit the collected parameter values ​​to the control system. The control system is used to receive the parameter values ​​and determine whether to trigger the collaborative control mechanism based on a preset threshold. When it is determined that the mineralization and temperature exceed the limit in a collaborative manner, the control system drives the nanoparticle concentration adjustment module and the gel strength adjustment module to start. When it is determined that the condensate oil and methanol exceed the limit in a collaborative manner, the control system drives the surfactant replenishment module and the interfacial tension adjustment module to start.

[0021] Preferably, the control system has a built-in parameter association model unit, a threshold judgment unit and a module driving unit. The parameter association model unit is used to store the nonlinear mapping relationship model between the four parameters and the foam comprehensive index. The threshold judgment unit is used to calculate the deviation of the comprehensive parameters and compare it with the preset threshold. The module driving unit is used to send a start signal to the corresponding adjustment module according to the judgment result.

[0022] Compared with the prior art, the technical solution of this application has the following technical effects:

[0023] The present invention effectively addresses the coupled effects of salinity, temperature, condensate oil content, and methanol content by establishing a four-parameter correlation model and a coordinated control mechanism, thereby solving the problem of sudden performance degradation of traditional foaming agents under the combined action of multiple factors. Through the synergistic enhancement effect of nanoparticles and gels, as well as the interfacial balance of compounded surfactants and additives, the anti-interference ability of the foaming agent in complex media is significantly improved, ensuring that the foam can still maintain good foaming power and stability under harsh conditions, providing reliable guarantee for the efficient removal of fluid accumulation in gas wells.

[0024] The present invention collects wellbore parameters in real time and feeds them back to the control system, combines preset threshold judgment to trigger the collaborative control mechanism, and starts the corresponding adjustment module for different parameter exceeding limit combinations, thereby realizing the transformation from static formulation to dynamic response. Compared with the traditional technology that relies on experience adjustment, the present method can optimize the composition and proportion of the foaming agent in real time according to the changes in the wellbore environment, avoiding the limitations of single parameter control, greatly improving the accuracy and timeliness of the control, and adapting to the actual needs of dynamic parameter fluctuations in gas well production.

[0025] The present invention ensures the consistency and repeatability of the coordinated control effect by constructing a multi-parameter response test matrix and dynamic simulation testing. When the comprehensive foam index is improved to a preset range compared with the single parameter control and the continuous test deviation is controlled within a limited range, the coordinated control is judged to be effective. This design strictly guarantees the stability of the liquid carrying efficiency of the foam removal agent. Compared with the existing technology, it reduces the impact of performance fluctuations on gas well production through scientific experimental design and judgment standards, and improves the reliability of the drainage and gas production process.

[0026] The present invention solves the applicability problems of traditional and existing technologies under high temperature, high mineralization, condensate oil and methanol conditions through multi-parameter coordinated control. It does not rely on single performance optimization, but fundamentally improves the foaming agent's resistance to complex media through the coordinated action of multiple modules, enabling the foaming agent to adapt to a wider range of wellbore environments, providing strong technical support for the efficient development of complex gas fields, and breaking through the limitations of existing technologies in application scenarios.

[0027] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application so that it can be implemented in accordance with the contents of the specification, and to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the following is a detailed description of the preferred embodiment of the present application in conjunction with the accompanying drawings.

[0028] Based on the detailed description of the specific embodiments of the present application in conjunction with the accompanying drawings below, those skilled in the art will become more aware of the above and other objects, advantages and features of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without inventive work. In all drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn according to the actual scale.

[0030] According to the description of the drawings in the document and the corresponding technical content, the titles of the drawings are as follows:

[0031] Figure 1 :Flowchart of the steps of multi-parameter coordinated control method for gel-nano composite foaming agent resistant to complex media;

[0032] Figure 2 : Module connection diagram of multi-parameter coordinated control system of gel-nano composite foaming agent resistant to complex media;

[0033] Figure 3: Composition and connection diagram of internal units of the control system;

[0034] Figure 4 : Comparison of foam half-life of three control methods under different salinities (temperature 60°C);

[0035] Figure 5 : Comparison of foam liquid carrying capacity of three control methods under different condensate oil contents (methanol content 25%);

[0036] Figure 6 : Comparison of the FCI improvement rate of the present invention method relative to the traditional method under different combinations of mineralization and temperature. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all of the embodiments. In the following description, specific details such as specific configurations and components are provided only to help fully understand the embodiments of the present application. Therefore, it should be clear to those skilled in the art that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. In addition, for clarity and brevity, the description of known functions and structures has been omitted in the embodiments.

[0038] It should be understood that references throughout this specification to "one embodiment" or "this embodiment" mean that a particular feature, structure, or characteristic associated with the embodiment is included in at least one embodiment of the present application. Therefore, the appearance of "one embodiment" or "this embodiment" throughout this specification does not necessarily refer to the same embodiment. Furthermore, these particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0039] In addition, the present application may repeat reference numerals and / or letters in different examples. This repetition is for the purpose of simplicity and clarity and does not in itself indicate the relationship between the various embodiments and / or settings discussed.

[0040] The term "and / or" in this article is only a description of the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, B exists alone, and A and B exist at the same time. The term " / and" in this article describes another type of association object relationship, indicating that two relationships can exist. For example, A / and B can mean: A exists alone, and A and B exist alone. In addition, the character " / " in this article generally indicates that the previous and subsequent associated objects are in an "or" relationship.

[0041] The term "at least one" in this article is merely a description of the association relationship between associated objects, indicating that three relationships may exist. For example, at least one of A and B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0042] It should also be noted that, in this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include," "comprises," or any other variations thereof are intended to cover non-exclusive inclusion.

[0043] Example 1

[0044] This embodiment mainly describes the multi-parameter coordinated control method of gel-nano composite foaming agent resistant to complex media, such as Figure 1 As shown, specifically including:

[0045] S1. Establish a complex medium parameter correlation model, analyze the coupling effect between the four parameters of salinity, temperature, condensate content, and methanol content, and determine the interaction weights of the four parameters through orthogonal experimental design;

[0046] S2. Construct a multi-parameter response test matrix to obtain the distribution probability of typical operating conditions. Select benchmark points for salinity, temperature, condensate oil, and methanol. Set multiple parameter combinations based on salinity gradient, temperature gradient, condensate oil gradient, and methanol gradient. Repeat the experiment for a preset number of times for each parameter set.

[0047] S3. By collecting data on salinity, temperature, condensate oil, and methanol content in the wellbore in real time, the parameter values ​​are fed back to the control system using a data transmission module. The control system determines whether to trigger the coordinated control mechanism based on preset thresholds;

[0048] S4. When it is monitored that the salinity and temperature exceed the limit, the nanoparticle concentration adjustment module and the gel strength control module are used to increase the amount of solid foam stabilizer and adjust the gel cross-linking degree to form a synergistic enhancement effect. When the condensate oil and methanol exceed the limit, the surfactant supplementation module and the interfacial tension adjustment module are activated to balance the gas-liquid interface performance by compounding surfactants and adding additives.

[0049] S5. Use dynamic simulation to test the liquid carrying efficiency of the foam removal agent under the set parameter combination conditions. When the foam comprehensive index FCI is improved by more than the preset range compared with the single parameter control and the continuous test deviation is less than 5%, it is determined that the coordinated control is effective.

[0050] Furthermore, when establishing the complex medium parameter association model in S1, actual production data of salinity, temperature, condensate oil content, and methanol content from typical wells in the western gas field were first selected, covering the parameter ranges of different well depths and production stages. The salinity C was divided into a gradient of 50,000-250,000 mg / L, the temperature T was divided into a gradient of 30-90°C, the condensate oil content O was divided into a gradient of 10%-50%, and the methanol content M was divided into a gradient of 5%-35%. The dimensional effect was eliminated through data normalization processing, and the foam comprehensive index FCI was used as the response value to construct a nonlinear mapping relationship model between the four parameters and FCI. The formula is: Among them, C0, T0, O0, and M0 are the benchmark values ​​of salinity, temperature, condensate oil content, and methanol content, respectively; k is the comprehensive correction coefficient; a, b, c, and d are the influence indices of salinity, temperature, condensate oil content, and methanol content, respectively. The model parameters are iteratively optimized to ensure that the error between the predicted value and the experimental value is controlled within 5%.

[0051] Furthermore, when analyzing the coupling effect between the four parameters in S1, an orthogonal experimental table was designed based on the gradient range of the parameters of salinity, temperature, condensate oil content, and methanol content. The salinity, temperature, condensate oil content, and methanol content were used as four factors. Each factor took a level value, and the experimental combination was carried out to test the foaming power, half-life, and FCI of the foam. The range and variance of each factor were calculated, and the influence of a single factor and interaction on FCI was analyzed. The larger the range, the more significant the influence of the factor or interaction on the performance of the foam removal agent. The weight of the interaction between salinity and temperature, and condensate oil and methanol was determined according to the range ratio. The credibility of the interaction effect was verified by combining the variance analysis significance test, and the influence weight of each interaction term between the four parameters was determined.

[0052] Furthermore, when calculating the range and variance of each factor, the range calculation formula is: where R j is the range of the jth factor, is the average value of the foam comprehensive index FCI at the i-th level of the j-th factor, m is the number of levels of the factor; the variance calculation formula is in is the variance of the jth factor, is the total average value of FCI at all levels of the jth factor. By calculating the range and variance of each factor, the influence of single factors and interactions on FCI is analyzed. The larger the range, the more significant the impact of the factor or interaction on the performance of the foaming agent. Then, the weight of the four-parameter interaction effect is determined according to the proportion of the range, and the credibility of the interaction effect is verified by combining the significance test of variance analysis.

[0053] Furthermore, a multi-parameter response test matrix is ​​constructed in S2. Specifically, by extracting the characteristic values ​​of salinity, temperature, condensate content, and methanol content, the common fluctuation range of each parameter in the wellbore environment and the corresponding probability density distribution are determined. The reference point is selected as the center, and the gradient of each parameter is set at equal intervals. The parameter gradients are cross-combined to form a parameter combination. The experiment is repeated a preset number of times for each group of parameters. The degree of data dispersion is evaluated by calculating the standard deviation σ of the experimental data. The formula is: Where n is the number of experimental repetitions for each set of parameters, FCI i is the comprehensive foam index of the ith experiment, is the average value of the comprehensive foam index of the parameter experiment. When σ is less than the preset threshold, the experimental data is determined to be reliable.

[0054] Furthermore, the data transmission module is used in S3 to feed back the parameter values ​​to the control system. Specifically, the data of mineralization, temperature, condensate oil and methanol content in the wellbore are collected in real time and transmitted to the control system. The control system first calculates the comprehensive parameter deviation. Where C, T, O, and M are the parameter values ​​collected in real time, C0, T0, O0, and M0 are the reference values ​​of the corresponding parameters, and the calculated comprehensive parameter deviation D is compared with the preset threshold D. th For comparison, when D≥D th , the coordinated control mechanism is triggered, otherwise the current control state remains unchanged.

[0055] Furthermore, in S4, when it is monitored that the mineralization and temperature exceed the limit together, the nanoparticle concentration adjustment module calculates the required amount of nanoparticles to be supplemented according to the proportion of the mineralization exceeding the baseline value, and the synchronous gel strength control module adjusts the addition ratio of the cross-linking agent according to the extent to which the temperature exceeds the baseline value, wherein the nanoparticle concentration increases linearly with the proportion of the mineralization exceeding the limit, and the gel cross-linking degree increases stepwise with the extent to which the temperature exceeds the limit. By increasing the amount of solid foam stabilizer added, the pore structure formed by the nanoparticles and the gel network is filled, and the gel cross-linking degree is adjusted to optimize the network density to enhance the liquid film carrying capacity, so that the spatial steric effect of the nanoparticles and the three-dimensional network structure of the gel form a synergistic enhancement effect.

[0056] Furthermore, in S4, when the condensate oil and methanol exceed the limit together, the surfactant replenishment module calculates the compound replenishment amount of anionic and non-ionic surfactants according to the proportion of the condensate oil content exceeding the baseline value; the interfacial tension adjustment module determines the addition concentration of the additive according to the extent to which the methanol content exceeds the baseline value, wherein the ratio of anions to non-ionics in the compound surfactant is dynamically adjusted with the condensate oil exceeding the limit ratio to enhance the oil phase compatibility, the additive addition concentration increases linearly with the methanol exceeding the limit extent to offset its negative impact on the interfacial tension, the adsorption efficiency of the gas-liquid interface is improved by compounding the surfactant and forming an elastic membrane structure, the addition of the additive strengthens the directional arrangement stability of the surfactant at the interface, and balances the gas-liquid interface performance to resist the defoaming effect of the condensate oil and the dilution effect of methanol.

[0057] Furthermore, in the S5, when the dynamic simulation is used to test the liquid carrying efficiency of the foaming agent under the set parameter combination conditions, the foaming agent solution is prepared according to the set salinity, temperature, condensate oil content, and methanol content parameter combination, the foam generation and liquid carrying process are recorded, and the foam comprehensive index FCI at different times is calculated. At the same time, comparative experiments are carried out under the control of single salinity, single temperature, single condensate oil content, and single methanol content, and the corresponding FCI single value is calculated. The formula Calculate the promotion rate, where FCI x FCI is a comprehensive bubble index under coordinated regulation. d is the average FCI value under single parameter control, when η≥η th , η th is the foam comprehensive index threshold, and when the FCI value of continuous testing satisfies η<5%, the collaborative control is judged to be effective.

[0058] This implementation describes in detail how to effectively address the coupled effects of complex medium parameters such as salinity and temperature by establishing a multi-parameter correlation model and a coordinated control mechanism, improve the foaming power and stability of the foaming agent under harsh conditions, accurately balance the gas-liquid interface performance, expand the applicability of the foaming agent in complex gas fields, and provide reliable technical support for the efficient production of gas wells.

[0059] Example 2

[0060] This embodiment describes in detail the multi-parameter coordinated control system of the gel-nano composite foaming agent resistant to complex media, such as Figure 2 As shown, it includes a parameter acquisition module, a data transmission module, a control system, a nanoparticle concentration adjustment module, a gel strength control module, a surfactant supplement module and an interfacial tension adjustment module;

[0061] The output end of the parameter acquisition module is connected to the input end of the data transmission module, the output end of the data transmission module is connected to the input end of the control system, and the output end of the control system is respectively connected to the input ends of the nanoparticle concentration adjustment module, the gel strength control module, the surfactant supplementation module and the interfacial tension adjustment module. The parameter acquisition module is used to collect real-time data on salinity, temperature, condensate oil content and methanol content in the wellbore;

[0062] The data transmission module is used to transmit the collected parameter values ​​to the control system. The control system is used to receive the parameter values ​​and determine whether to trigger the collaborative control mechanism based on the preset threshold. When it is determined that the mineralization and temperature exceed the limit in a collaborative manner, the control system drives the nanoparticle concentration adjustment module and the gel strength adjustment module to start. When it is determined that the condensate oil and methanol exceed the limit in a collaborative manner, the control system drives the surfactant replenishment module and the interfacial tension adjustment module to start.

[0063] The parameter acquisition module includes a salinity sensor, a temperature sensor, a condensate oil content detector and a methanol content detector, which are used to collect real-time data on salinity, temperature, condensate oil content and methanol content in the wellbore.

[0064] The data transmission module transmits the salinity, temperature, condensate oil content and methanol content data collected by the parameter acquisition module to the control system using wired or wireless communication.

[0065] like Figure 3 As shown, the control system has built-in parameter association model unit, threshold judgment unit and module driving unit. The parameter association model unit is used to store the nonlinear mapping relationship model between the four parameters and the foam comprehensive index. The threshold judgment unit is used to calculate the deviation of the comprehensive parameters and compare it with the preset threshold. The module driving unit is used to send a start signal to the corresponding adjustment module according to the judgment result.

[0066] The control system has a built-in parameter association model unit, which stores a nonlinear mapping relationship model between four parameters: salinity, temperature, condensate content, methanol content, and the foam comprehensive index FCI.

[0067] The built-in threshold judgment unit of the control system is used to calculate the comprehensive parameter deviation based on the parameter values ​​collected in real time, and compare it with the preset threshold to determine whether to trigger the collaborative control mechanism.

[0068] The module driving unit built into the control system is used to send a start signal to the nanoparticle concentration adjustment module, the gel strength control module, the surfactant replenishment module or the interfacial tension adjustment module according to the judgment result of the threshold judgment unit.

[0069] The nanoparticle concentration adjustment module includes a nanoparticle storage tank and a metering pump, which are used to adjust the amount of nanoparticles added according to the signal of the control system; the gel strength control module includes a crosslinker storage tank and a metering valve, which are used to adjust the addition ratio of the crosslinker according to the signal of the control system.

[0070] The surfactant replenishment module includes a compound surfactant storage tank and a delivery pump, which is used to replenish the compound surfactant according to the signal of the control system; the interfacial tension adjustment module includes an additive storage tank and a flow controller, which is used to adjust the additive addition concentration according to the signal of the control system.

[0071] This embodiment describes in detail a multi-parameter coordinated control system for a gel-nanocomposite foaming agent resistant to complex media. The parameter acquisition module collects relevant parameters in the wellbore in real time and sends them to the control system via the data transmission module. The control system determines whether to trigger regulation based on preset thresholds. When the mineralization and temperature exceed the limit, the nanoparticle concentration and gel strength adjustment module is driven. When the condensate oil and methanol exceed the limit, the surfactant supplement and interfacial tension adjustment module is driven.

[0072] Based on Example 1 or 2, this example describes in detail the technical process and technical effects of the multi-parameter coordinated control method for the resistance of gel-nano composite foaming agent to complex media, as follows:

[0073] Through a large number of experimental verifications, it has been shown that this method can effectively improve the performance of gel-nanocomposite foaming agents under different complex media conditions and ensure the stable production of gas wells. The method proposed in this application was applied to actual production scenarios of different gas fields to prove its applicability and effectiveness in complex media environments. Experimental scenarios were constructed using typical well data from western gas fields, covering different well depths and production stages, and setting a variety of combinations of salinity, temperature, condensate content, and methanol content to comprehensively evaluate the performance of this method.

[0074] To investigate the effects of different parameter combinations on the performance of the foaming agent, multiple comparative experiments were designed. The core variables were the values ​​and combinations of salinity, temperature, condensate content, and methanol content. Each parameter was set at multiple levels: salinity at 50,000 mg / L, 100,000 mg / L, 150,000 mg / L, 200,000 mg / L, and 250,000 mg / L; temperature at 30°C, 45°C, 60°C, 75°C, and 90°C; condensate content at 10%, 20%, 30%, 40%, and 50%; and methanol content at 5%, 15%, 25%, and 35%. Through experiments with different parameter combinations, the performance of this method was systematically evaluated under various complex media conditions.

[0075] During the experiment, a dynamic simulation device was used to simulate the actual wellbore environment. A foaming agent solution was prepared according to the set parameter combination and injected into the experimental device. Data such as the foam generation process, half-life, and liquid carrying capacity were recorded, and the Foam Composite Index (FCI) was calculated. Comparative experiments were also conducted using single-parameter control and coordinated multi-parameter control. Each experiment was repeated five times, and the average result was used to ensure the reliability of the experimental data.

[0076] To verify the effectiveness of the multi-parameter coordinated control method proposed in this application under different complex media conditions, comparative experiments were conducted in several typical wells in the Western Gas Field. The comparison methods included traditional single-parameter control methods and existing simple compound control methods. All comparative experiments were conducted under the same experimental environment and equipment to ensure the fairness and comparability of the experimental results. The experimental results under different salinity and temperature combinations are shown in Table 1:

[0077] Table 1 Comparison of FCI values ​​between this method and other methods at different salinity and temperature combinations

[0078]

[0079] As can be seen from Table 1, under different combinations of salinity and temperature, the foam comprehensive index FCI of the multi-parameter coordinated control method proposed in this application is higher than that of the traditional single-parameter control method and the existing simple compound control method. With the increase of salinity and the increase of temperature, the FCI values ​​of the three methods all show a downward trend, but the decline of the method of this application is relatively small, indicating that it has better performance stability under high salinity and high temperature conditions. Under the extreme conditions of salinity 250,000 mg / L and temperature 90°C, the FCI value of the method of this application is 10.7 higher than that of the traditional single-parameter control method and 7.3 higher than the existing simple compound control method, and the advantage is more obvious.

[0080] Furthermore, the experimental results under different combinations of condensate oil content and methanol content are shown in Table 2:

[0081] Table 2 Comparison of FCI values ​​of the proposed method and other methods at different condensate oil content and methanol content combinations

[0082]

[0083] As shown in Table 2, the FCI value of the present invention's method performs optimally under different combinations of condensate and methanol content. As the condensate content and methanol content increase, the FCI values ​​of the three methods gradually decrease, while the present invention's method consistently maintains a high value. Under the harsh conditions of 50% condensate and 35% methanol, the FCI value of the present invention's method is 11.1 higher than that of the traditional single-parameter control method and 6.7 higher than that of the existing simple compound control method, fully demonstrating its advantages in addressing the impact of condensate and methanol.

[0084] In order to fully verify the role of each key module in the method proposed in this application, an ablation experiment was designed to focus on analyzing the contribution of the parameter acquisition module, the coordinated regulation mechanism, the nanoparticle concentration regulation module, the gel strength regulation module, the surfactant supplementation module, and the interfacial tension regulation module to the performance of the foaming agent. The ablation experiment systematically evaluated the impact of each module on the FCI value by gradually removing the key modules in the method. The experimental results are shown in Table 3:

[0085] Table 3 Comparison of FCI values ​​of ablation experiments for key modules (mineralization 150,000 mg / L, temperature 60°C, condensate 30%, methanol 25%)

[0086]

[0087] As shown in Table 3, when the parameter acquisition module is removed, the FCI value drops significantly from 77.8 to 65.3. This indicates that the parameter acquisition module can acquire parameter information within the wellbore in real time, providing accurate data support for subsequent control and regulation, which is fundamental to ensuring method performance. After removing the collaborative control mechanism, the FCI value drops to 69.5, demonstrating that the collaborative control mechanism can promptly adjust the control strategy based on parameter changes, achieving coordinated optimization of multiple parameters and playing a significant role in improving the performance of the foaming agent. After removing the nanoparticle concentration control module, the gel strength control module, the surfactant replenishment module, and the interfacial tension control module, the FCI value reaches 72.1, indicating that these control modules can provide targeted control for different parameter out-of-limit situations, further improving the performance of the foaming agent.

[0088] Furthermore, in order to verify the application effect of this method in actual gas well production, three typical wells in the western gas field were selected for field experiments. The traditional single parameter control method, the existing simple compound control method, and the multi-parameter coordinated control method proposed in this application were used respectively. The daily gas production and liquid accumulation of the gas wells were recorded. The experimental results are shown in Table 4:

[0089] Table 4 Comparison of application effects of different methods in actual gas well production

[0090]

[0091] From the experimental results in Table 4, it can be seen that the daily gas production of the gas wells using the method of the present application is higher than that of the gas wells using the traditional method and the existing simple compound control method, and there is no liquid accumulation. After the method of the present application was used in well 1, the daily gas production was increased by 1200m 3 , which is 700m higher than the existing simple compound control method 3 The daily gas production of Well 2 is 1400m higher than that of the traditional method. 3 , which is 700m higher than the existing simple compound control method 3 The daily gas production of Well 3 is 1300m higher than that of the traditional method. 3 , which is 700m higher than the existing simple compound control method 3 This fully proves that the method of the present application can effectively improve the productivity of gas wells and solve the problem of liquid accumulation at the bottom of the well in actual production.

[0092] like Figure 4 The figure shows a comparison of foam half-lives using three methods at a salinity of 150,000 mg / L and a temperature of 60°C. The figure clearly shows that the proposed method achieves the longest foam half-life, significantly exceeding both traditional single-parameter control methods and existing simple compound control methods. This longer foam half-life indicates that the foam can maintain a stable state within the wellbore, effectively performing its liquid-carrying function, which aligns with the previously reported FCI experimental results.

[0093] Under the conditions of condensate oil content of 30% and methanol content of 25%, the comparison of foam liquid carrying capacity of the three methods is as follows: Figure 5 The figure intuitively shows that the foam liquid carrying capacity of the present invention's method is the highest, while the foam liquid carrying capacity of the traditional single-parameter control method is the lowest. The amount of foam liquid carrying capacity is directly related to the effectiveness of removing liquid accumulation in gas wells. The advantages of the present invention's method in this regard further demonstrate its effectiveness in complex media environments.

[0094] like Figure 6 The figure shows a comparison of the FCI value improvement rates of the present invention's method and traditional methods under different salinity and temperature conditions. As can be seen from the figure, the FCI value improvement rate of the present invention's method relative to traditional methods gradually increases with increasing salinity and temperature, reaching its maximum improvement rate at a salinity of 250,000 mg / L and a temperature of 90°C. This demonstrates that the present invention's advantages are even more pronounced under more severe and complex media conditions, and it can better address the adverse effects of high salinity and high temperature on the performance of the foaming agent.

[0095] Comprehensive experiments show that the multi-parameter coordinated control method for the gel-nanocomposite foaming agent's resistance to complex media proposed in this application has significant advantages. By establishing a complex medium parameter correlation model, this method can accurately analyze the coupling effect between various parameters; construct a multi-parameter response test matrix, providing a scientific basis for experimental design; real-time parameter acquisition and dynamic adjustment through a coordinated control mechanism achieve precise optimization of the foaming agent's performance; the synergistic effect of each regulation module effectively improves the foaming agent's stability and liquid carrying efficiency in complex media environments.

[0096] This example demonstrates how, in practical application, the method can significantly increase daily gas production in gas wells and resolve the problem of bottomhole liquid accumulation, providing strong technical support for efficient gas field development. Furthermore, ablation experiments have demonstrated the importance of each key module, providing guidance for further optimization and improvement of the method. Future work will expand the scope of the experiment to include validation in more diverse gas fields and complex media conditions, continuously improving the method's performance and broadening its applicability.

[0097] The above are only preferred embodiments of the present invention, which do not limit the scope of protection of the present invention. For those skilled in the art, the present invention can be modified and varied in various ways. Any changes, modifications, replacements, integrations and parameter changes to these embodiments through conventional substitutions or that can achieve the same functions without departing from the principles and spirit of the present invention fall within the scope of protection of the present invention.

Claims

1. A multi-parameter coordinated control method for gel-nano composite foaming agent resistant to complex media, characterized in that: include: S1. Establish a complex medium parameter correlation model, analyze the coupling effect between the four parameters of salinity, temperature, condensate content, and methanol content, and determine the interaction weights of the four parameters through orthogonal experimental design; S2. Construct a multi-parameter response test matrix to obtain the distribution probability of typical operating conditions. Select benchmark points for salinity, temperature, condensate oil, and methanol. Set multiple parameter combinations based on salinity gradient, temperature gradient, condensate oil gradient, and methanol gradient. Repeat the experiment for a preset number of times for each parameter set. S3. By collecting data on salinity, temperature, condensate oil, and methanol content in the wellbore in real time, the parameter values ​​are fed back to the control system using a data transmission module. The control system determines whether to trigger the coordinated control mechanism based on preset thresholds; S4. When it is monitored that the salinity and temperature exceed the limit, the nanoparticle concentration adjustment module and the gel strength control module are used to increase the amount of solid foam stabilizer and adjust the gel cross-linking degree to form a synergistic enhancement effect. When the condensate oil and methanol exceed the limit, the surfactant supplementation module and the interfacial tension adjustment module are activated to balance the gas-liquid interface performance by compounding surfactants and adding additives. S5. Use dynamic simulation to test the liquid carrying efficiency of the foam removal agent under the set parameter combination conditions. When the foam comprehensive index FCI is improved by more than the preset range compared with the single parameter control and the continuous test deviation is less than 5%, it is determined that the coordinated control is effective.

2. The multi-parameter coordinated control method for the complex medium resistance of the gel-nano composite foaming agent according to claim 1, characterized in that: When establishing the complex medium parameter association model in S1, the actual production data of salinity, temperature, condensate oil content, and methanol content of typical wells in the gas field are obtained, covering the parameter ranges of different well depths and production stages. The salinity C, temperature T, condensate oil O, and methanol content M are divided into preset range gradients, and the dimension effect is eliminated through data normalization. The foam comprehensive index FCI is used as the response value to construct a nonlinear mapping relationship model between the four parameters and FCI. The formula is: Among them, C0, T0, O0, and M0 are the benchmark values ​​of salinity, temperature, condensate oil content, and methanol content, respectively; k is the comprehensive correction coefficient; a, b, c, and d are the influence indices of salinity, temperature, condensate oil content, and methanol content, respectively. The model parameters are iteratively optimized to ensure that the error between the predicted value and the experimental value is controlled within 5%.

3. The multi-parameter coordinated control method for the complex medium resistance of the gel-nano composite foaming agent according to claim 1 or 2, characterized in that: When analyzing the coupling effect between the four parameters in S1, an orthogonal experimental table is designed through the gradient range of the parameters of salinity, temperature, condensate oil content, and methanol content. The salinity, temperature, condensate oil content, and methanol content are used as four factors. Each factor takes a level value, and an experimental combination is performed to test the foaming power, half-life, and FCI of the foam. The range and variance of each factor are calculated, and the influence of a single factor and interaction on the FCI is analyzed. The larger the range, the more significant the influence of the factor or interaction on the performance of the foam removal agent. The weight of the interaction between salinity and temperature, and condensate oil and methanol is determined according to the range ratio. The credibility of the interaction effect is verified by combining the variance analysis significance test, and the influence weight of each interaction term between the four parameters is determined.

4. The multi-parameter coordinated control method for the complex medium resistance of the gel-nano composite foaming agent according to claim 1, characterized in that: In S2, a multi-parameter response test matrix is ​​constructed. Specifically, the characteristic values ​​of salinity, temperature, condensate content, and methanol content are extracted to determine the common fluctuation range of each parameter in the wellbore environment and the corresponding probability density distribution. The reference point is selected as the center, and the gradients of each parameter are set at equal intervals. The parameter gradients are cross-combined to form a parameter combination. The experiment is repeated for a preset number of times for each group of parameters. The degree of data dispersion is evaluated by calculating the standard deviation σ of the experimental data. The formula is: Where n is the number of experimental repetitions for each set of parameters, FCI i is the comprehensive foam index of the ith experiment, is the average value of the comprehensive foam index of the parameter experiment. When σ is less than the preset threshold, the experimental data is determined to be reliable.

5. The multi-parameter coordinated control method for the complex medium resistance of the gel-nano composite foaming agent according to claim 1, characterized in that: In S3, the parameter values ​​are fed back to the control system by using the data transmission module. Specifically, the data of mineralization, temperature, condensate oil and methanol content in the wellbore are collected in real time and transmitted to the control system. The control system first calculates the comprehensive parameter deviation. Where C, T, O, and M are the parameter values ​​collected in real time, C0, T0, O0, and M0 are the reference values ​​of the corresponding parameters, and the calculated comprehensive parameter deviation D is compared with the preset threshold D. th For comparison, when D≥D th , the coordinated control mechanism is triggered, otherwise the current control state remains unchanged.

6. The multi-parameter coordinated control method for the complex medium resistance of the gel-nano composite foaming agent according to claim 1, characterized in that: In the S4, when it is monitored that the mineralization and temperature exceed the limit together, the nanoparticle concentration adjustment module calculates the required amount of nanoparticles to be supplemented according to the proportion of the mineralization exceeding the baseline value, and the synchronous gel strength control module adjusts the addition ratio of the cross-linking agent according to the extent to which the temperature exceeds the baseline value, wherein the nanoparticle concentration increases linearly with the proportion of the mineralization exceeding the limit, and the gel cross-linking degree increases stepwise with the extent to which the temperature exceeds the limit. By increasing the amount of solid foam stabilizer added, the pore structure formed by the nanoparticles and the gel network is filled, and the gel cross-linking degree is adjusted to optimize the network density to enhance the carrying capacity of the liquid membrane, so that the spatial steric effect of the nanoparticles and the three-dimensional network structure of the gel form a synergistic enhancement effect.

7. The multi-parameter coordinated control method for the complex medium resistance of the gel-nano composite foaming agent according to claim 1, characterized in that: In the S4, when the condensate oil and methanol exceed the limit together, the surfactant replenishment module calculates the compound replenishment amount of anionic and non-ionic surfactants according to the proportion of the condensate oil content exceeding the baseline value; the interfacial tension adjustment module determines the addition concentration of the auxiliary agent according to the extent to which the methanol content exceeds the baseline value, wherein the ratio of anionic and non-ionic in the compound surfactant is dynamically adjusted with the condensate oil exceeding the limit ratio to enhance the oil phase compatibility, the auxiliary agent addition concentration increases linearly with the extent to which methanol exceeds the limit to offset its negative impact on the interfacial tension, the adsorption efficiency of the gas-liquid interface is improved by compounding the surfactant and forming an elastic membrane structure, the addition of the auxiliary agent strengthens the directional arrangement stability of the surfactant at the interface, and balances the gas-liquid interface performance to resist the defoaming effect of the condensate oil and the dilution effect of methanol.

8. The multi-parameter coordinated control method for the complex medium resistance of the gel-nano composite foaming agent according to claim 1, characterized in that: In the S5, dynamic simulation is used to test the liquid carrying efficiency of the foaming agent under the conditions of set parameter combination. The foaming agent solution is prepared according to the set salinity, temperature, condensate oil content, and methanol content parameter combination, the foam generation and liquid carrying process are recorded, and the foam comprehensive index FCI at different times is calculated. At the same time, comparative experiments are carried out under the control of single salinity, single temperature, single condensate oil content, and single methanol content, and the corresponding FCI single value is calculated. The formula Calculate the promotion rate, where FCI x FCI is a comprehensive bubble index under coordinated regulation. d is the average FCI value under single parameter control, when η≥η th , η th is the foam comprehensive index threshold, and when the FCI value of continuous testing satisfies η<5%, the collaborative control is judged to be effective.

9. A multi-parameter coordinated control system for a gel-nano composite foaming agent resistant to complex media, applicable to any one of claims 1-8, characterized in that: It includes parameter acquisition module, data transmission module, control system, nanoparticle concentration adjustment module, gel strength control module, surfactant supplement module and interfacial tension adjustment module; The output end of the parameter acquisition module is connected to the input end of the data transmission module, the output end of the data transmission module is connected to the input end of the control system, and the output end of the control system is respectively connected to the input ends of the nanoparticle concentration adjustment module, the gel strength control module, the surfactant supplementation module and the interfacial tension adjustment module. The parameter acquisition module is used to collect real-time data on salinity, temperature, condensate oil content and methanol content in the wellbore; The data transmission module is used to transmit the collected parameter values ​​to the control system. The control system is used to receive the parameter values ​​and determine whether to trigger the collaborative control mechanism based on a preset threshold. When it is determined that the mineralization and temperature exceed the limit in a collaborative manner, the control system drives the nanoparticle concentration adjustment module and the gel strength adjustment module to start. When it is determined that the condensate oil and methanol exceed the limit in a collaborative manner, the control system drives the surfactant replenishment module and the interfacial tension adjustment module to start.

10. The multi-parameter coordinated control system for complex medium resistance of gel-nano composite foaming agent according to claim 9, characterized in that: The control system has built-in parameter association model units, threshold judgment units and module driving units. The parameter association model unit is used to store the nonlinear mapping relationship model of four parameters and the foam comprehensive index. The threshold judgment unit is used to calculate the deviation of the comprehensive parameters and compare it with the preset threshold. The module driving unit is used to send a start signal to the corresponding adjustment module according to the judgment result.

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