A method for testing and optimizing the corrosion resistance of a metal coating of a geothermal well

Abstract

The application discloses a kind of geothermal well metal coating corrosion resistance test optimization methods, comprising the following steps: geothermal well downhole environmental factor acquisition and coupling parameter determination, coating corrosion pretest and key test node preliminary screening, multi-factor coupling dynamic test environment building and parameter calibration, stage dynamic corrosion performance test and full-dimensional data acquisition, corrosion rate attenuation model construction and dynamic corrosion rate calculation, corrosion resistance comprehensive evaluation index calculation and performance classification, test parameter and process optimization iteration, optimization method verification and engineering adaptability evaluation, standardized test report output and coating formula optimization guidance;The application constructs geothermal well five-factor synchronous coupling dynamic simulation test system, restores the real downhole environment of high temperature, high pressure, high salinity, corrosive gas, fluid scouring, downhole vibration completely, the deviation of test result and downhole actual corrosion resistance is significantly reduced, and the core problem of traditional single-factor test environment distortion is solved completely.

Description

Technical Field

[0001] This invention relates to the field of geothermal well corrosion testing technology, specifically to an optimization method for testing the corrosion resistance of metal coatings in geothermal wells. Background Technology

[0002] As a core component of a clean and low-carbon energy system, medium-deep geothermal resources rely on geothermal wells for extraction, heat exchange, and heating. The well's downhole heat exchange tubing and sealing components are primarily made of carbon steel and stainless steel, coated with a high thermal conductivity metal coating to simultaneously enhance downhole heat exchange and provide long-term corrosion protection. The downhole environment of medium-deep geothermal wells is characterized by high temperatures (100-250℃), high pressure (10-30MPa), highly salinized formation water (10-50g / L), and highly corrosive ions (Cl). - SO4 2- HCO3 - The complex and extreme environment of geothermal wells, characterized by the coupling of multiple factors such as acidic corrosive gases (H2S, CO2), fluid dynamic scouring, and downhole micro-vibration, makes metal coatings prone to pitting corrosion, crevice corrosion, interface delamination, thermal conductivity degradation, and corrosion failure. This directly leads to a decrease in the heat exchange efficiency of geothermal wells, tubing leakage, and a shortened service life, which seriously restricts the efficient development and utilization of medium and deep geothermal resources.

[0003] The corrosion resistance of metal coatings is a core indicator determining their reliability in the extreme environments of geothermal wells. Optimization methods for corrosion resistance testing are crucial for accurately characterizing the true corrosion resistance of coatings, guiding coating formulation optimization, and verifying engineering suitability. Current methods for testing the corrosion resistance of metal coatings in geothermal wells largely follow the common standards of conventional oil and gas well corrosion testing and atmospheric pressure / room temperature metal corrosion testing. These methods fail to consider the actual downhole conditions of medium-deep geothermal wells and the functional characteristics of high thermal conductivity coatings, resulting in numerous insurmountable technical problems. Traditional tests only use single-factor static simulation of temperature and corrosive medium, which does not reproduce the dynamic working conditions of multi-factor coupling in geothermal wells. The test results deviate from the actual anti-corrosion performance downhole by more than 30%, and cannot truly reflect the corrosion behavior of the coating in extreme environments. The test did not divide the test into stages according to the corrosion evolution law of the geothermal well coating, and only used a single-cycle immersion test. It ignored the accelerating effect of fluid dynamic scouring and downhole vibration on coating corrosion, and could not capture the performance changes of the coating throughout the entire corrosion cycle from initial to development and stabilization. The test cycle, sampling nodes, and environmental factor loading order are all set based on experience, resulting in large dispersion and poor repeatability of test data, making it impossible to achieve precise control of the test process. Using corrosion rate as the sole evaluation index, without considering performance indicators that are strongly related to the heat exchange and sealing requirements of geothermal wells, such as coating adhesion, thermal conductivity, and porosity, it is impossible to comprehensively characterize the overall adaptability of the coating. At the same time, it lacks a scientific corrosion kinetic model and comprehensive evaluation formula, and the data processing is crude, making it impossible to achieve quantitative optimization of the testing method. Without optimizing the core technologies required for enhanced heat exchange and sealing corrosion prevention in medium-deep geothermal wells, the test results could not guide the precise optimization of the metal coating composition, thickness, and preparation process, leading to frequent failures in coating engineering applications. Summary of the Invention

[0004] The purpose of this invention is to provide an optimized method for testing the corrosion resistance of metal coatings in geothermal wells, so as to solve at least one problem existing in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for optimizing the corrosion resistance test of metal coatings for geothermal wells, comprising the following steps: Step 1: Collection of downhole environmental factors and determination of coupling parameters for geothermal wells. Collect downhole measured data of the target deep geothermal wells, screen core corrosion environmental factors through factor analysis, determine the coupling parameter range of each factor, eliminate non-critical interference factors, and construct a multi-factor coupled corrosion environment benchmark parameter set for geothermal wells. Step 2: Pre-testing of coating corrosion and initial screening of key test nodes. The high thermal conductivity metal coating to be tested is pre-immersed using a benchmark parameter set. The corrosion morphology, corrosion product composition, adhesion changes and thermal conductivity decay of the coating surface are monitored throughout the process. The time boundary points of the initial, development and stable stages of coating corrosion are recorded. Key sampling and detection nodes in the initial screening test process are also recorded. Step 3: Construction and parameter calibration of multi-factor coupled dynamic test environment. Based on the reference parameter set of multi-factor coupled corrosion environment of geothermal well, a dynamic simulation test environment is built. Temperature, pressure, corrosive medium, fluid flow rate and vibration factor are loaded simultaneously. The output parameters of each environmental factor are calibrated by gradient calibration method to ensure the consistency between the simulated environment and the real downhole environment. Step 4: Phased dynamic corrosion performance testing and full-dimensional data collection. According to the corrosion stage determined by the pre-test, phased dynamic corrosion testing of the coating is carried out. At key test nodes, data such as corrosion rate, surface porosity, interfacial adhesion, thermal conductivity, corrosion product film thickness, and number of surface defects of the coating are collected. Real-time parameters of various environmental factors are recorded simultaneously to establish a test database. Step 5: Construction of corrosion rate decay model and calculation of dynamic corrosion rate. Based on the corrosion rate and time series data in the test database, a coating corrosion rate decay model is constructed. The test data of each stage are substituted into the model for fitting calculation to obtain the real-time corrosion rate and cumulative corrosion amount of the coating under dynamic coupling environment, and to correct the corrosion rate deviation of the static test. Step Six: Calculation of Comprehensive Evaluation Index and Performance Grading of Corrosion Resistance. Combining the core indicators of coating corrosion rate, porosity, adhesion and thermal conductivity, construct a comprehensive evaluation index model for corrosion resistance. Substitute the test data to calculate the comprehensive evaluation index of the coating to be tested, and complete the standardized grading of the coating's corrosion resistance performance based on the index range. Step 7: Iterative optimization of test parameters and processes. Taking the comprehensive evaluation index of corrosion resistance as the optimization target, the control variable method is used to adjust the weight of test environment factors, test cycle, sampling node interval, and dynamic loading parameters one by one. The stability and data dispersion of the evaluation index under different parameter combinations are compared to select the optimal test parameters and process scheme. Step 8: Optimization method verification and engineering adaptability assessment. The standard metal coating is retested using the optimal test parameters and procedures. The reliability of the optimized method is verified from the dimensions of repeatability, accuracy and stability. Combined with the requirements of enhanced heat exchange and sealing corrosion protection of geothermal wells, the engineering adaptability of the optimized test method is assessed, and the final test optimization scheme is formed. Step Nine: Standardized Test Report Output and Coating Formulation Optimization Guidance. Organize the optimized test data, evaluation results, and verification conclusions, output a standardized test report, and propose optimization directions for the metal coating composition, thickness, preparation process, and post-treatment process based on the test results.

[0006] Furthermore, in step one, the core corrosion environment factors include formation temperature, wellbore pressure, formation water salinity, chloride ion concentration, hydrogen sulfide partial pressure, carbon dioxide partial pressure, fluid velocity, and downhole vibration acceleration; the coupling parameter ranges are: temperature 100-250℃, pressure 10-30MPa, salinity 10-50g / L, chloride ion concentration 1-10g / L, hydrogen sulfide partial pressure 0.1-50ppm, carbon dioxide partial pressure 0.1%-10%, fluid velocity 0.5-5m / s, and vibration acceleration 0.1-5g.

[0007] Furthermore, in step two, the testing cycle of the pre-test is 240-480 hours; the initial screening of key test nodes is based on the abrupt change point of coating corrosion rate, the inflection point of adhesion decrease, the thermal conductivity decay point, and the surface defect initiation point; the number of key test nodes after initial screening is 6-10, and the node interval is dynamically adjusted according to the corrosion stage.

[0008] Furthermore, in step five, the expression for the coating corrosion rate attenuation model is:

[0009] In the formula: The real-time corrosion rate of the coating under dynamic coupling environment; The initial corrosion rate of the coating; For corrosion testing time; The corrosion decay time constant represents the rate at which the coating corrosion rate decays. To stabilize the corrosion rate of the coating.

[0010] Furthermore, in step six, the expression for the comprehensive evaluation index model of corrosion resistance performance is:

[0011] In the formula: This is a comprehensive evaluation index for corrosion resistance, with a value range of 0-1; , , , Let be the weighting coefficients for corrosion rate, porosity, adhesion, and thermal conductivity, respectively. ; The real-time corrosion rate of the coating; The maximum allowable corrosion rate for the coating; Porosity of the coating surface; The maximum allowable porosity for the coating; The interfacial adhesion between the coating and the substrate; For optimal coating adhesion; The thermal conductivity of the coating; The optimal thermal conductivity is that of the coating.

[0012] Furthermore, the weighting coefficients are determined using the analytic hierarchy process (AHP) combined with the corrosion prevention requirements of geothermal wells, wherein... =0.4, =0.2, =0.25, =0.15; The corrosion resistance performance grading standard is: ≥0.8 is considered excellent, 0.6≤ <0.8 is considered good, 0.4≤ <0.6 is considered intermediate. <0.4 is considered a poor grade.

[0013] Furthermore, in step seven, the adjustment variables of the control variable method include the loading order of environmental factors, the total test cycle, the sampling interval, the dynamic fluid scouring intensity, and the vibration loading frequency; the screening criteria for the optimal test parameters are: evaluation index dispersion coefficient ≤ 5%, data repeatability error ≤ 3%, and test efficiency improvement ≥ 30%.

[0014] Furthermore, in step eight, the indicators for verifying the optimization method include test data repeatability, corrosion rate calculation accuracy, and consistency of the comprehensive evaluation index; the dimensions of engineering adaptability assessment include coating heat exchange adaptability, wellbore sealing adaptability, and downhole long-term corrosion protection adaptability.

[0015] Furthermore, in step nine, the optimization of the metal coating composition includes adding rare earth modifying elements, adjusting the chromium-aluminum alloy ratio, and optimizing the ceramic phase doping ratio; the coating thickness optimization range is 50-200μm; the optimization of the preparation process includes plasma spraying power, vacuum cladding temperature, and coating sealing post-treatment process.

[0016] Compared with the prior art, the beneficial effects of the present invention are: This invention constructs a five-factor synchronously coupled dynamic simulation testing system for geothermal wells, fully reproducing the real downhole environment of high temperature, high pressure, high mineralization, corrosive gases, fluid erosion, and downhole vibration. The deviation between the test results and actual downhole corrosion resistance is significantly reduced, completely solving the core problem of environmental distortion in traditional single-factor testing. A phased dynamic testing method is adopted, using a three-stage corrosion division and key node initial screening to accurately capture the entire lifecycle evolution of coating corrosion, avoiding invalid tests and data gaps, thus improving testing efficiency. A corrosion rate decay model is introduced to achieve accurate quantitative calculation of dynamic corrosion rate, correcting static test deviations and providing scientific data support for coating corrosion mechanism research. A comprehensive corrosion resistance performance evaluation index is constructed, integrating four core adaptive indicators to achieve quantitative classification of coating performance. The evaluation results fully meet the dual needs of heat exchange and corrosion resistance in geothermal wells. With the comprehensive evaluation index as the target, test parameters are iteratively optimized using the controlled variable method. Under the optimal parameter combination, the data dispersion coefficient is ≤5%, and the repeatability error is ≤3%, significantly improving the stability and reliability of the testing method and forming a standardized testing process. The optimization method closely integrates with the core needs of enhanced heat exchange and sealing corrosion prevention in medium-deep geothermal wells, directly outputting the optimization direction of coating composition, thickness and process, which can extend the service life of geothermal well heat exchange tubing and adapt to medium-deep geothermal wells in different regions and at different depths. Attached Figure Description

[0017] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0018] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see Figure 1This invention provides a method for optimizing the testing of the corrosion resistance of metal coatings for geothermal wells, comprising the following steps: Step 1: Collection of downhole environmental factors and determination of coupling parameters for geothermal wells. Collect downhole measured data of the target deep geothermal wells, screen core corrosion environmental factors through factor analysis, determine the coupling parameter range of each factor, eliminate non-critical interference factors, and construct a multi-factor coupled corrosion environment benchmark parameter set for geothermal wells. Step 2: Pre-testing of coating corrosion and initial screening of key test nodes. The high thermal conductivity metal coating to be tested is pre-immersed using a benchmark parameter set. The corrosion morphology, corrosion product composition, adhesion changes and thermal conductivity decay of the coating surface are monitored throughout the process. The time boundary points of the initial, development and stable stages of coating corrosion are recorded. Key sampling and detection nodes in the initial screening test process are also recorded. Step 3: Construction and parameter calibration of multi-factor coupled dynamic test environment. Based on the reference parameter set of multi-factor coupled corrosion environment of geothermal well, a dynamic simulation test environment is built. Temperature, pressure, corrosive medium, fluid flow rate and vibration factor are loaded simultaneously. The output parameters of each environmental factor are calibrated by gradient calibration method to ensure the consistency between the simulated environment and the real downhole environment. Step 4: Phased dynamic corrosion performance testing and full-dimensional data collection. According to the corrosion stage determined by the pre-test, phased dynamic corrosion testing of the coating is carried out. At key test nodes, data such as corrosion rate, surface porosity, interfacial adhesion, thermal conductivity, corrosion product film thickness, and number of surface defects of the coating are collected. Real-time parameters of various environmental factors are recorded simultaneously to establish a test database. Step 5: Construction of corrosion rate decay model and calculation of dynamic corrosion rate. Based on the corrosion rate and time series data in the test database, a coating corrosion rate decay model is constructed. The test data of each stage are substituted into the model for fitting calculation to obtain the real-time corrosion rate and cumulative corrosion amount of the coating under dynamic coupling environment, and to correct the corrosion rate deviation of the static test. Step Six: Calculation of Comprehensive Evaluation Index and Performance Grading of Corrosion Resistance. Combining the core indicators of coating corrosion rate, porosity, adhesion and thermal conductivity, construct a comprehensive evaluation index model for corrosion resistance. Substitute the test data to calculate the comprehensive evaluation index of the coating to be tested, and complete the standardized grading of the coating's corrosion resistance performance based on the index range. Step 7: Iterative optimization of test parameters and processes. Taking the comprehensive evaluation index of corrosion resistance as the optimization target, the control variable method is used to adjust the weight of test environment factors, test cycle, sampling node interval, and dynamic loading parameters one by one. The stability and data dispersion of the evaluation index under different parameter combinations are compared to select the optimal test parameters and process scheme. Step 8: Optimization method verification and engineering adaptability assessment. The standard metal coating is retested using the optimal test parameters and procedures. The reliability of the optimized method is verified from the dimensions of repeatability, accuracy and stability. Combined with the requirements of enhanced heat exchange and sealing corrosion protection of geothermal wells, the engineering adaptability of the optimized test method is assessed, and the final test optimization scheme is formed. Step Nine: Standardized Test Report Output and Coating Formulation Optimization Guidance. Organize the optimized test data, evaluation results, and verification conclusions, output a standardized test report, and propose optimization directions for the metal coating composition, thickness, preparation process, and post-treatment process based on the test results.

[0020] In step one, the core corrosion environment factors include formation temperature, wellbore pressure, formation water salinity, chloride ion concentration, hydrogen sulfide partial pressure, carbon dioxide partial pressure, fluid velocity, and downhole vibration acceleration; the coupling parameter range is: temperature 100-250℃, pressure 10-30MPa, salinity 10-50g / L, chloride ion concentration 1-10g / L, hydrogen sulfide partial pressure 0.1-50ppm, carbon dioxide partial pressure 0.1%-10%, fluid velocity 0.5-5m / s, and vibration acceleration 0.1-5g.

[0021] In step two, the testing cycle for the preliminary test is 240-480 hours; the initial screening of key test nodes is based on the abrupt change point of coating corrosion rate, the inflection point of adhesion decrease, the thermal conductivity decay point, and the initiation point of surface defects; the number of key test nodes after the initial screening is 6-10, and the node interval is dynamically adjusted according to the corrosion stage.

[0022] In step five, the expression for the coating corrosion rate attenuation model is:

[0023] In the formula: The real-time corrosion rate of the coating under dynamic coupling environment; The initial corrosion rate of the coating; For corrosion testing time; The corrosion decay time constant represents the rate at which the coating corrosion rate decays. To stabilize the corrosion rate of the coating.

[0024] Furthermore, in step six, the expression for the comprehensive evaluation index model of corrosion resistance performance is:

[0025] In the formula: This is a comprehensive evaluation index for corrosion resistance, with a value range of 0-1; , , , Let be the weighting coefficients for corrosion rate, porosity, adhesion, and thermal conductivity, respectively. ; The real-time corrosion rate of the coating; The maximum allowable corrosion rate for the coating; Porosity of the coating surface; The maximum allowable porosity for the coating; The interfacial adhesion between the coating and the substrate; For optimal coating adhesion; The thermal conductivity of the coating; The optimal thermal conductivity is that of the coating.

[0026] The weighting coefficients were determined using the analytic hierarchy process (AHP) combined with the corrosion prevention requirements of geothermal wells. =0.4, =0.2, =0.25, =0.15; The corrosion resistance performance grading standard is: ≥0.8 is considered excellent, 0.6≤ <0.8 is considered good, 0.4≤ <0.6 is considered intermediate. <0.4 is considered a poor grade.

[0027] In step seven, the adjustment variables of the controlled variable method include the loading order of environmental factors, total test cycle, sampling interval duration, dynamic fluid scouring intensity, and vibration loading frequency; the screening criteria for the optimal test parameters are: evaluation index dispersion coefficient ≤ 5%, data repeatability error ≤ 3%, and test efficiency improvement ≥ 30%.

[0028] In step eight, the indicators for optimizing the method include test data repeatability, corrosion rate calculation accuracy, and consistency of the comprehensive evaluation index; the dimensions of engineering adaptability assessment include coating heat exchange adaptability, wellbore sealing adaptability, and downhole long-term corrosion protection adaptability.

[0029] In step nine, the optimization directions for the metal coating composition include adding rare earth modifying elements, adjusting the chromium-aluminum alloy ratio, and optimizing the ceramic phase doping ratio; the coating thickness optimization range is 50-200μm; the optimization directions for the preparation process include plasma spraying power, vacuum cladding temperature, and coating sealing post-treatment process.

[0030] Example: Step 1: Geothermal well downhole environmental factor acquisition and coupling parameter determination Data Acquisition: Retrieve long-term downhole monitoring data of the target geothermal well from 2023 to 2025, including formation temperature, wellbore pressure, formation water quality report, corrosive gas detection data, fluid flow rate monitoring data, and downhole vibration sensor data, with a total of 1200 sets of valid data collected; Factor screening: Factor analysis was used to reduce the dimensionality of the collected data and remove non-critical interference factors such as daily temperature fluctuations and instantaneous pressure pulsations. Eight core corrosion environment factors were identified: formation temperature, wellbore pressure, formation water salinity, chloride ion concentration, hydrogen sulfide partial pressure, carbon dioxide partial pressure, fluid velocity, and downhole vibration acceleration. Parameter determination: Based on the long-term operating conditions of the geothermal well, the coupling parameter range of the core factors was determined as follows: temperature 180℃, pressure 25MPa, salinity 30g / L, chloride ion concentration 6g / L, hydrogen sulfide partial pressure 20ppm, carbon dioxide partial pressure 8%, fluid velocity 2m / s, and vibration acceleration 1g. Construction of the benchmark parameter set: Integrating the above parameters, a multi-factor coupled corrosion environment benchmark parameter set for 3500m medium-deep geothermal wells in North China was formed, which serves as the core basis for subsequent tests.

[0031] Step 2: Preliminary testing of coating corrosion and initial screening of key test points Pre-test implementation: Using the benchmark parameter set from step one, the Ni-Cr-Al-Y coating to be tested was pre-immersed for testing. The test cycle was set to 360 hours, and the changes in coating performance were monitored throughout the test. Performance monitoring: Continuously monitor the corrosion morphology of the coating surface, the phase composition of corrosion products, the adhesion between the coating and the substrate, and the thermal conductivity of the coating, and record the performance change patterns; Corrosion stage division: The three-stage boundary points of coating corrosion are determined by monitoring data: initial stage 0-72h, development stage 72-240h, and stable stage 240-360h; Initial screening of key nodes: Based on the abrupt change point of corrosion rate, the inflection point of adhesion decrease, and the node of thermal conductivity decay, eight key test nodes are initially screened: 0h, 24h, 72h, 120h, 168h, 240h, 300h, and 360h. Invalid nodes are excluded to ensure coverage of the entire corrosion cycle.

[0032] Step 3: Setting up and calibrating the multi-factor coupled dynamic test environment Dynamic environment setup: Based on the benchmark parameter set, a dynamic simulation test environment with simultaneous loading of five factors - temperature, pressure, corrosive medium, fluid flow rate and vibration is set up. The logic of geothermal well downhole operation is strictly followed. Temperature and pressure are loaded first, then corrosive medium is introduced, and finally fluid scouring and vibration loading are started. Gradient calibration: The gradient calibration method is used to calibrate each factor parameter point by point: temperature calibration accuracy ±1℃, pressure calibration accuracy ±0.5MPa, mineralization calibration accuracy ±0.5g / L, fluid flow rate calibration accuracy ±0.1m / s, vibration acceleration calibration accuracy ±0.05g; Error elimination: After calibration, the system continuously monitors parameter drift for 24 hours to eliminate systematic errors caused by single-factor loading lag and parameter fluctuations, ensuring that the parameters of the simulated environment are more than 99% consistent with the actual downhole environment.

[0033] Step 4: Phased Dynamic Corrosion Performance Testing and Comprehensive Data Acquisition Phased testing implementation: Dynamic corrosion testing is carried out in three phases according to the pre-test division, strictly following the sampling and testing of 8 key test nodes, maintaining synchronous loading of five factors throughout the process, and not interrupting the test process; Data Acquisition: Collect the following core data at each key node: Corrosion rate: The corrosion rate was measured using a combination of weight loss and electrochemical methods, and the average value was taken as the valid data. Surface porosity: The open porosity of the coating surface was tested using metallographic microscopy. Interfacial adhesion: The bonding strength between the coating and the substrate was tested using the pull-off method; Thermal conductivity: The thermal conductivity of the coating was tested using the transient hot wire method; Corrosion product film thickness: The thickness of the product film was measured using the cross-sectional method of scanning electron microscopy; Surface defect count: Count the number of pitting, cracking, and delamination defects on the coating surface; Database establishment: All test data were categorized and stored according to time nodes and corrosion stages to establish a structured test database, ensuring data traceability and reusability. A total of 64 sets of valid data were collected.

[0034] Step 5: Construction of Corrosion Rate Attenuation Model and Calculation of Dynamic Corrosion Rate Model Construction: Based on corrosion rate-time series data in the test database and combined with the corrosion kinetics characteristics of geothermal well coatings, a coating corrosion rate decay model was constructed.

[0035] in: The real-time corrosion rate of the coating under dynamic coupling environment (mm / a); The initial corrosion rate of the coating was measured to be 0.085 mm / a after 0 hours of testing. The corrosion test time (h) is used. The corrosion decay time constant is calculated to be 48.2 h. To ensure the stability of the coating corrosion rate, a 360-hour test was conducted, which yielded a rate of 0.012 mm / a. Data fitting: The test data of each stage are substituted into the model for fitting to obtain the real-time corrosion rate of the coating throughout the entire cycle, and the deviation of the traditional static test is corrected (the deviation of the static test is 0.023 mm / a, and the deviation is reduced to 0.003 mm / a after optimization). Cumulative corrosion calculation: Based on the real-time corrosion rate, the cumulative corrosion of the coating over 360 hours is calculated to be 0.032 mm, accurately characterizing the degree of coating corrosion.

[0036] Step Six: Calculation of Comprehensive Evaluation Index and Performance Grading for Corrosion Resistance Evaluation Model Construction: Combining the four core adaptation indicators of the coating, a comprehensive evaluation index model for corrosion resistance performance is constructed.

[0037] in: Weighting coefficients: determined using the analytic hierarchy process (AHP). =0.4、 =0.2、 =0.25、 =0.15; Threshold parameter: =0.1mm / a =5% =40MPa =35W / (m K); Measured parameters: =0.012mm / a =1.2%, =32MPa =28W / (m K); Exponent calculation: Substitute the parameters into the model to calculate... =0.82; Performance grading: According to the grading standards, =0.82≥0.8, the anti-corrosion performance of the coating is judged to be excellent, which meets the long-term anti-corrosion requirements of geothermal wells.

[0038] Step 7: Iterative Optimization of Test Parameters and Processes Optimization goal: The core optimization objectives are index stability, data dispersion, and testing efficiency. Control variable adjustment: Adjust the following parameters one by one: Environmental factor weights: Adjust the weight ratios of corrosion rate, porosity, etc. Test cycle: Comparison of three cycles: 240h, 360h, and 480h; Sampling nodes: Adjust the node interval to 24h, 48h, and 72h; Dynamic loading parameters: Adjust fluid velocity and vibration acceleration; Optimal parameter selection: By comparing the test results of different combinations, the optimal combination of test parameters is selected. Total testing period: 360 hours; Key test nodes: 8, namely 0h, 24h, 72h, 120h, 168h, 240h, 300h, and 360h; Factor loading sequence: temperature → pressure → corrosive medium → fluid flow rate → vibration; Screening criteria: The coefficient of variation is 3.2% ≤ 5%, the data repeatability error is 2.1% ≤ 3%, and the testing efficiency is improved by 35%. Process standardization: Based on optimal parameters, a standardized testing process is formed, and testing steps and operating procedures are solidified.

[0039] Step 8: Optimization Method Validation and Engineering Suitability Assessment Method validation: Using optimal test parameters and procedures, the standard Ni-Cr-Al-Y coating (known) was tested. =0.80) was retested, and the test was repeated 3 times. The results are as follows: first: =0.81; Second time: =0.82; Third time: =0.80; Verification results: The repeatability error of the test data was 1.2%, the accuracy of corrosion rate calculation was 98.5%, the consistency of the comprehensive evaluation index was 99%, and the reliability of the optimization method met the standards. Engineering compatibility assessment: Based on the requirements for enhanced heat exchange and sealing / corrosion protection of geothermal wells, an assessment is conducted from three dimensions: Heat transfer compatibility: Coating thermal conductivity 28 W / (m K), to meet the needs of enhanced heat exchange in downhole wells; Sealing compatibility: The coating has a porosity of 1.2% and no penetrating defects, meeting the wellbore sealing requirements; Long-lasting corrosion resistance: stable corrosion rate of 0.012 mm / a, with an estimated service life of over 15 years; Final Solution: Integrate the verification results and evaluation conclusions to form the final optimization solution for testing the corrosion resistance of metal coatings in medium-deep geothermal wells in North China.

[0040] Step Nine: Standardized Test Report Output and Coating Formulation Optimization Guidance Report Output: Compile raw test data, model calculation results, performance evaluation conclusions, and method validation reports to compile the "Optimization Report on Corrosion Resistance Test of Ni-Cr-Al-Y Coating for 3500m Geothermal Wells in North China". The report includes comprehensive content on test methods, procedures, parameters, models, results, and recommendations, and meets the standardization requirements of the geothermal industry. Coating optimization guidance: Based on the test results, targeted optimization directions are proposed: Composition optimization: Adding 0.5% rare earth yttrium element improves the high-temperature stability of the coating; Thickness optimization: The coating thickness was adjusted from 100μm to 120μm to improve long-term corrosion resistance; Process optimization: The plasma spraying power was adjusted from 40kW to 45kW to improve coating density; Post-treatment: Vacuum sealing is used to reduce the coating porosity to below 0.8%; Application guidance: Submit the optimized plan to the geothermal engineering unit to guide the coating preparation and downhole application, ensuring that the coating is suitable for the extreme environment of the geothermal well.

[0041] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for optimizing the testing of corrosion resistance of metal coatings for geothermal wells, characterized in that: Includes the following steps: Step 1: Collection of downhole environmental factors and determination of coupling parameters for geothermal wells. Collect downhole measured data of the target deep geothermal wells, screen core corrosion environmental factors through factor analysis, determine the coupling parameter range of each factor, eliminate non-critical interference factors, and construct a multi-factor coupled corrosion environment benchmark parameter set for geothermal wells. Step 2: Pre-testing of coating corrosion and initial screening of key test nodes. The high thermal conductivity metal coating to be tested is pre-immersed using a benchmark parameter set. The corrosion morphology, corrosion product composition, adhesion changes and thermal conductivity decay of the coating surface are monitored throughout the process. The time boundary points of the initial, development and stable stages of coating corrosion are recorded. Key sampling and detection nodes in the initial screening test process are also recorded. Step 3: Construction and parameter calibration of multi-factor coupled dynamic test environment. Based on the reference parameter set of multi-factor coupled corrosion environment of geothermal well, a dynamic simulation test environment is built. Temperature, pressure, corrosive medium, fluid flow rate and vibration factor are loaded simultaneously. The output parameters of each environmental factor are calibrated by gradient calibration method to ensure the consistency between the simulated environment and the real downhole environment. Step 4: Phased dynamic corrosion performance testing and full-dimensional data collection. According to the corrosion stage determined by the pre-test, phased dynamic corrosion testing of the coating is carried out. At key test nodes, data such as corrosion rate, surface porosity, interfacial adhesion, thermal conductivity, corrosion product film thickness, and number of surface defects of the coating are collected. Real-time parameters of various environmental factors are recorded simultaneously to establish a test database. Step 5: Construction of corrosion rate decay model and calculation of dynamic corrosion rate. Based on the corrosion rate and time series data in the test database, a coating corrosion rate decay model is constructed. The test data of each stage are substituted into the model for fitting calculation to obtain the real-time corrosion rate and cumulative corrosion amount of the coating under dynamic coupling environment, and to correct the corrosion rate deviation of the static test. Step Six: Calculation of Comprehensive Evaluation Index and Performance Grading of Corrosion Resistance. Combining the core indicators of coating corrosion rate, porosity, adhesion and thermal conductivity, construct a comprehensive evaluation index model for corrosion resistance. Substitute the test data to calculate the comprehensive evaluation index of the coating to be tested, and complete the standardized grading of the coating's corrosion resistance performance based on the index range. Step 7: Iterative optimization of test parameters and processes. Taking the comprehensive evaluation index of corrosion resistance as the optimization target, the control variable method is used to adjust the weight of test environment factors, test cycle, sampling node interval, and dynamic loading parameters one by one. The stability and data dispersion of the evaluation index under different parameter combinations are compared to select the optimal test parameters and process scheme. Step 8: Optimization method verification and engineering adaptability assessment. The standard metal coating is retested using the optimal test parameters and procedures. The reliability of the optimized method is verified from the dimensions of repeatability, accuracy and stability. Combined with the requirements of enhanced heat exchange and sealing corrosion protection of geothermal wells, the engineering adaptability of the optimized test method is assessed, and the final test optimization scheme is formed. Step Nine: Standardized Test Report Output and Coating Formulation Optimization Guidance. Organize the optimized test data, evaluation results, and verification conclusions, output a standardized test report, and propose optimization directions for the metal coating composition, thickness, preparation process, and post-treatment process based on the test results.

2. The method for testing and optimizing the corrosion resistance of metal coatings for geothermal wells according to claim 1, characterized in that: In step one, the core corrosion environment factors include formation temperature, wellbore pressure, formation water salinity, chloride ion concentration, hydrogen sulfide partial pressure, carbon dioxide partial pressure, fluid velocity, and downhole vibration acceleration; the coupling parameter ranges are: temperature 100-250℃, pressure 10-30MPa, salinity 10-50g / L, chloride ion concentration 1-10g / L, hydrogen sulfide partial pressure 0.1-50ppm, carbon dioxide partial pressure 0.1%-10%, fluid velocity 0.5-5m / s, and vibration acceleration 0.1-5g.

3. The method for testing and optimizing the corrosion resistance of metal coatings for geothermal wells according to claim 1, characterized in that: In step two, the testing cycle of the pre-test is 240-480 hours; the initial screening of key test nodes is based on the abrupt change point of coating corrosion rate, the inflection point of adhesion decrease, the thermal conductivity decay point, and the surface defect initiation point; the number of key test nodes after initial screening is 6-10, and the node interval is dynamically adjusted according to the corrosion stage.

4. The method for optimizing the corrosion resistance test of metal coatings for geothermal wells according to claim 1, characterized in that: In step five, the expression for the coating corrosion rate attenuation model is: In the formula: The real-time corrosion rate of the coating under dynamic coupling environment; The initial corrosion rate of the coating; For corrosion testing time; The corrosion decay time constant represents the rate at which the coating corrosion rate decays. To stabilize the corrosion rate of the coating.

5. The method for testing and optimizing the corrosion resistance of metal coatings for geothermal wells according to claim 1, characterized in that: In step six, the expression for the comprehensive evaluation index model of corrosion resistance performance is: In the formula: This is a comprehensive evaluation index for corrosion resistance, with a value range of 0-1; , , , Let be the weighting coefficients for corrosion rate, porosity, adhesion, and thermal conductivity, respectively. ; The real-time corrosion rate of the coating; The maximum allowable corrosion rate for the coating; Porosity of the coating surface; The maximum allowable porosity for the coating; The interfacial adhesion between the coating and the substrate; For optimal coating adhesion; The thermal conductivity of the coating; The optimal thermal conductivity is that of the coating.

6. The method for optimizing the corrosion resistance test of metal coatings for geothermal wells according to claim 5, characterized in that: The weighting coefficients were determined using the analytic hierarchy process (AHP) combined with the corrosion prevention requirements of geothermal wells. =0.4, =0.2, =0.25, =0.15; The corrosion resistance performance grading standard is: ≥0.8 is considered excellent, 0.6≤ <0.8 is considered good, 0.4≤ <0.6 is considered intermediate. <0.4 is considered a poor grade.

7. The method for optimizing the corrosion resistance test of metal coatings for geothermal wells according to claim 1, characterized in that: In step seven, the adjustment variables of the control variable method include the loading order of environmental factors, total test cycle, sampling interval duration, dynamic fluid scouring intensity, and vibration loading frequency; the screening criteria for the optimal test parameters are: evaluation index dispersion coefficient ≤ 5%, data repeatability error ≤ 3%, and test efficiency improvement ≥ 30%.

8. The method for optimizing the corrosion resistance test of metal coatings for geothermal wells according to claim 1, characterized in that: In step eight, the indicators for verifying the optimization method include test data repeatability, corrosion rate calculation accuracy, and consistency of comprehensive evaluation index; the dimensions of engineering adaptability assessment include coating heat exchange adaptability, wellbore sealing adaptability, and downhole long-term corrosion protection adaptability.

9. The method for optimizing the corrosion resistance test of metal coatings for geothermal wells according to claim 1, characterized in that: In step nine, the optimization of the metal coating composition includes adding rare earth modifying elements, adjusting the chromium-aluminum alloy ratio, and optimizing the ceramic phase doping ratio; the coating thickness optimization range is 50-200 μm. Optimization of the preparation process includes plasma spraying power, vacuum cladding temperature, and post-treatment process for coating sealing.

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