An evaluation method and system of a corrosion master control factor, an electronic device and a medium

Abstract

This invention relates to the field of oil and gas exploration technology, and discloses a method, system, electronic equipment, and medium for evaluating the main corrosion control factors. The method includes: acquiring at least three corrosion factors and constructing different main corrosion control factors based on these factors; constructing multiple sets of experimental parameters for each corrosion factor using a multi-factor, multi-level orthogonal combination method, and conducting corrosion immersion experiments to determine the corrosion rate; performing multivariate nonlinear fitting to determine the coefficient of each main corrosion control factor; and determining the degree of influence of each main corrosion control factor on the corrosion rate of the injection-production tubing based on Pareto analysis. This application considers more than three corrosion factors simultaneously to construct the main corrosion control factors, and combines multivariate nonlinear fitting and Pareto analysis to establish the degree of influence of each main corrosion control factor on the corrosion rate of the injection-production tubing, aiming to fully predict the relationship between the corrosion rate of the injection-production tubing and the control factors.

Description

Technical Field

[0001] This invention relates to the field of oil and gas exploration technology, and in particular to an evaluation method, system, electronic device and medium for the main controlling factors of corrosion. Background Technology

[0002] With the rapid development of the national economy, the contradiction between oil and gas supply and demand has become increasingly prominent. Meanwhile, my country's easily exploitable onshore oil and gas resources are gradually being depleted. To ensure national energy security, it is imperative to adopt carbon dioxide enhanced oil recovery (CEM) technology to increase oil and gas production. Current research shows that CEM can improve oil recovery efficiency by 8% to 15%. However, with the injection of carbon dioxide, impurity gases are introduced into the existing corrosive environment, leading to more severe corrosion of the casing and tubing. Furthermore, changes in temperature can also alter the corrosion rate. Therefore, it is necessary to identify the main corrosion-controlling factors affecting the corrosion rate of the injection and production tubing.

[0003] Currently, domestic and international evaluation and analysis methods for the main controlling factors of pipeline corrosion mainly include artificial neural networks. For example, by acquiring historical pipeline failure data, processing the historical pipeline failure data to form an intermediate database, and using the Python language to call the logistic regression model through the scikit-learn data package to perform supervised machine learning based on the intermediate database, a corrosion rate range prediction model is established to predict corrosion inside the pipe; based on the prediction results of corrosion inside the pipe, the main controlling factors of corrosion inside the pipe and the remaining service life are determined.

[0004] The existing technologies mentioned above focus on evaluating the main controlling factors of pipeline corrosion using single-factor or two-factor coupling methods. However, for multi-factor environmental corrosion, especially for the evaluation of corrosion controlling factors obtained by the combination of three or more factors, it is difficult to achieve the expected results. Summary of the Invention

[0005] To overcome the problem that it is difficult to achieve the expected results when evaluating the main corrosion control factors obtained by combining three or more factors, this invention provides an evaluation method, system, electronic device, and medium for the main corrosion control factors.

[0006] Firstly, in order to solve the above-mentioned technical problems, the present invention provides a method for evaluating the main controlling factors of corrosion, comprising:

[0007] At least three corrosion factors affecting the corrosion rate of the injection and production tubing were identified, and different main corrosion control factors were constructed based on these factors; wherein the main corrosion control factor is a single corrosion factor or a coupling of multiple corrosion factors.

[0008] Multiple sets of experimental parameters for corrosion immersion experiments of injection and production tubing were constructed by using a multi-factor, multi-level orthogonal combination method for various corrosion factors.

[0009] Corrosion immersion experiments were conducted on injection and production tubing based on multiple sets of experimental parameters to determine the corrosion rate corresponding to each set of experimental parameters.

[0010] Using each set of experimental parameters and the corresponding corrosion rate, a quantitative relationship between corrosion rate and each major corrosion controlling factor is constructed, and multivariate nonlinear fitting is performed to determine the coefficient of each major corrosion controlling factor.

[0011] Pareto analysis was used to analyze the coefficients of each major corrosion control factor in order to determine the degree of influence of each major corrosion control factor on the corrosion rate of the injection-production tubing.

[0012] Secondly, the present invention provides an evaluation system for the main controlling factors of corrosion, comprising:

[0013] The corrosion factor acquisition module is used to acquire at least three corrosion factors that affect the corrosion rate of the injection and production tubing, and to construct different main corrosion control factors based on the corrosion factors; wherein the main corrosion control factor is a single corrosion factor or a coupling of multiple corrosion factors;

[0014] The experimental parameter construction module is used to construct multiple sets of experimental parameters for the corrosion immersion experiment of the injection and production tubing by using a multi-factor, multi-level orthogonal combination of various corrosion factors.

[0015] The corrosion rate determination module is used to conduct corrosion immersion experiments on the injection and production tubing based on multiple sets of experimental parameters, and to determine the corrosion rate corresponding to each set of experimental parameters.

[0016] The fitting module is used to construct a quantitative relationship between the corrosion rate and each main corrosion control factor using each set of experimental parameters and the corresponding corrosion rate, and to perform multivariate nonlinear fitting to determine the coefficient of each main corrosion control factor.

[0017] The corrosion control factor evaluation module is used to analyze the coefficients of each corrosion control factor based on Pareto analysis to determine the degree of influence of each corrosion control factor on the corrosion rate of the injection-production tubing.

[0018] Thirdly, the present invention provides a computing device, including a memory, a processor, and a program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps of the evaluation method for the main control factor of corrosion as described above.

[0019] Fourthly, the present invention provides a computer-readable storage medium storing instructions that, when executed on a terminal device, cause the terminal device to perform the steps of the evaluation method for a corrosion control factor as described above.

[0020] The beneficial effects of this invention are as follows: At least three corrosion factors affecting the corrosion rate of the injection-production tubing are identified, and different main corrosion control factors are constructed. Then, multiple sets of experimental parameters are constructed using a multi-factor, multi-level orthogonal combination method for corrosion immersion experiments. The corrosion rate corresponding to each set of experimental parameters is determined. Finally, using the experimental parameters and corrosion rate, a quantitative relationship between the corrosion rate and each main corrosion control factor is constructed, and multivariate nonlinear fitting is performed to obtain the coefficient of each main corrosion control factor. Pareto analysis is then used to analyze and evaluate each main corrosion control factor. This application simultaneously considers more than three corrosion factors to construct main corrosion control factors, and combines multivariate nonlinear fitting and Pareto analysis to establish the degree of influence of each main corrosion control factor on the corrosion rate of the injection-production tubing, aiming to fully predict the relationship between the corrosion rate of the injection-production tubing and the control factors. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0022] Figure 1 This is a flowchart illustrating an evaluation method for the main corrosion-controlling factors according to an embodiment of the present invention.

[0023] Figure 2 A schematic diagram showing the weights of each major corrosion-controlling factor;

[0024] Figure 3 This is a schematic diagram of the structure of an evaluation system for the main corrosion control factors according to an embodiment of the present invention. Detailed Implementation

[0025] The following embodiments are further explanations and supplements to the present invention and do not constitute any limitation on the present invention.

[0026] The following describes, with reference to the accompanying drawings, an evaluation method, system, electronic device, and medium for the main corrosion control factors according to an embodiment of the present invention.

[0027] like Figure 1 As shown, this embodiment of the invention provides a method for evaluating the main controlling factors of corrosion, including:

[0028] S1. Obtain at least three corrosion factors that affect the corrosion rate of the injection and production tubing, and construct different main corrosion control factors based on the corrosion factors; wherein, the main corrosion control factor is a single corrosion factor or a coupling of multiple corrosion factors.

[0029] In this embodiment, considering that liquid carbon dioxide is mainly used in the carbon dioxide injection and production tubing process, the corresponding corrosion rate is relatively small. Therefore, the focus is on the factors that affect the corrosion rate during the water-gas alternation process of carbon dioxide injection. Preferably, the corrosion factors in this embodiment can be temperature (ambient temperature), carbon dioxide partial pressure, hydrogen sulfide partial pressure, and oxygen partial pressure.

[0030] In this embodiment, each corrosion factor can be constructed as a corrosion controlling factor in a single-factor or multi-factor coupling manner. Since some of the constructed corrosion controlling factors have low significance in the subsequent multivariate nonlinear fitting process, they are automatically deleted. Preferably, in this embodiment, the corrosion controlling factors can be ① temperature, ② temperature and carbon dioxide dual corrosion factor coupling, ③ oxygen, ④ hydrogen sulfide, ⑤ carbon dioxide, ⑥ temperature, hydrogen sulfide and oxygen triple corrosion factor coupling.

[0031] S2. Multiple sets of experimental parameters for corrosion immersion experiments of injection and production tubing are constructed by using a multi-factor, multi-level orthogonal combination method for various corrosion factors.

[0032] In this embodiment, multi-factor multi-level orthogonal combination is a core concept in orthogonal experimental design (also known as orthogonal experimental method). It aims to systematically study the influence of multiple different factors on experimental results through fewer experiments and find the optimal combination of factors. Therefore, constructing experimental parameters by using multi-factor multi-level orthogonal combination can also reduce workload and improve evaluation efficiency.

[0033] For example, the experimental parameters for the corrosion immersion test of the constructed injection-production tubing are shown in Table 1 below:

[0034] Table 1

[0035]

[0036] Table 1 uses number 1 as an example. The experimental parameters obtained indicate that when conducting the corrosion immersion experiment, the temperature is 30℃, the partial pressure of carbon dioxide is 1MPa, the partial pressure of hydrogen sulfide is 0.1MPa, and the partial pressure of oxygen is 0.1MPa.

[0037] S3. Corrosion immersion experiments were conducted on the injection and production tubing based on multiple sets of experimental parameters to determine the corrosion rate corresponding to each set of experimental parameters.

[0038] In this embodiment, a high-temperature and high-pressure corrosion immersion experiment was conducted. The experiment was designed according to the experimental parameters obtained from the 4 factors and 3 levels in Table 1 above. The experimental solution was collected from water samples collected from the oilfield. The immersion time was 96 hours. After the sample was fixed in the reactor, the field solution was poured into the reactor and deoxygenated for 4 hours. When the temperature reached the target temperature, it was pressurized to the target temperature through a gas cylinder. The pressurization sequence was oxygen, hydrogen sulfide, and carbon dioxide. After the experiment, the samples were removed from the reaction vessel, rinsed with anhydrous ethanol and deionized water, and dried. Following the national standard GB / T 16545-2015 "Removal of Corrosion Products from Corrosion Specimens of Metals and Alloys", the samples underwent a film removal treatment. The film removal solution was prepared by adding 100ml of hydrochloric acid (analytical grade), 5-10g of hexamethylenetetramine (analytical grade), and distilled or deionized water to make 1000ml of solution. The samples were then immersed in the prepared solution and ultrasonically cleaned for 3-5 minutes to remove the corrosion product film on the surface. After rinsing with anhydrous ethanol and deionized water, the samples were dried with cold air. Finally, the samples were weighed using a precision balance (accuracy 0.0001g) and the weight after corrosion was recorded. The corrosion rate was calculated using the weight loss method, as follows:

[0039]

[0040] In the formula, V c denoted as corrosion rate, W0-W1 as the mass difference of the sample before and after corrosion, t as the corrosion period, ρ as the density of the sample, and A as the surface area of ​​the sample.

[0041] S4. Using the experimental parameters and corresponding corrosion rates of each group, construct a quantitative relationship between corrosion rate and each major corrosion control factor, and perform multivariate nonlinear fitting to determine the coefficient of each major corrosion control factor.

[0042] S5. Analyze the coefficients of each major corrosion control factor based on Pareto analysis to determine the degree of influence of each major corrosion control factor on the corrosion rate of the injection and production tubing.

[0043] In this embodiment, at least three corrosion factors affecting the corrosion rate of the injection-production tubing are identified, and different main corrosion control factors are constructed. Then, a multi-factor, multi-level orthogonal combination method is used to construct multiple sets of experimental parameters for corrosion immersion experiments. The corrosion rate corresponding to each set of experimental parameters is determined. Finally, using the experimental parameters and corrosion rate, a quantitative relationship between the corrosion rate and each main corrosion control factor is constructed, and multivariate nonlinear fitting is performed to obtain the coefficient of each main corrosion control factor. Finally, Pareto analysis is used to analyze and evaluate each main corrosion control factor. This application considers more than three corrosion factors simultaneously to construct main corrosion control factors, and combines multivariate nonlinear fitting and Pareto analysis to establish the degree of influence of each main corrosion control factor on the corrosion rate of the injection-production tubing, aiming to fully predict the relationship between the corrosion rate of the injection-production tubing and the control factors.

[0044] Optionally, multiple sets of experimental parameters for corrosion immersion experiments of injection-production tubing are constructed by using a multi-factor, multi-level orthogonal combination of various corrosion factors, including:

[0045] Obtain the range value for each corrosion factor;

[0046] Multiple preset values ​​within the range of each corrosion factor are used as the actual values ​​of the corresponding corrosion factor.

[0047] Each real value is encoded to obtain the encoded value corresponding to each real value;

[0048] Based on each corrosion factor and each coding value, a multi-factor, multi-level orthogonal combination was performed to determine multiple sets of experimental parameters.

[0049] In this embodiment, the preset values ​​can be the endpoint values ​​and the center point values ​​in the range values.

[0050] For example, the temperature range is 30 to 90°C, the partial pressure range of carbon dioxide is 1 MPa to 5 MPa, the partial pressure range of hydrogen sulfide is 0.1 MPa to 1 MPa, and the partial pressure range of oxygen is 0.1 MPa to 0.5 MPa.

[0051] The actual values ​​obtained are shown in Table 2 below:

[0052] Table 2

[0053]

[0054] Optionally, each real value is encoded to obtain the encoded value corresponding to each real value, as shown in the following formula:

[0055]

[0056] Where, x i X represents the encoded value corresponding to the i-th real value. i，maxX i，min ΔX represents the maximum and minimum values ​​within the range corresponding to the corrosion factor, respectively. i This represents the range of values ​​corresponding to the corrosion factors. X represents the true value at the center point within the range corresponding to the corrosion factor. i This represents the i-th true value.

[0057] In this embodiment, the true value is converted into the coded value, which can reduce the difference in magnitude between various corrosion factors. After encoding, the true value of each corrosion factor can be converted into three level values: low level value is -1; middle value is 0; and high level value is 1.

[0058] For example, as shown in Table 3 below:

[0059] Table 3

[0060]

[0061] Taking temperature as an example, when the temperature (30℃), the partial pressure of carbon dioxide (0.1MPa), the partial pressure of hydrogen sulfide (1MPa), and the partial pressure of oxygen (0.1MPa) are taken at the corresponding values ​​of the endpoints, the coded value can be -1, thereby reducing the difference in magnitude between various corrosion factors and making the subsequent multivariate nonlinear fitting results more accurate.

[0062] Optionally, using the experimental parameters and corresponding corrosion rates for each set, a quantitative relationship between the corrosion rate and each major corrosion-controlling factor is constructed, and a multivariate nonlinear fitting is performed to determine the coefficient of each major corrosion-controlling factor, as shown in the following formula:

[0063]

[0064] Where Y represents the corrosion rate, b0 represents the constant term, and b ii Let x′ represent the coefficient of the quadratic term. i 、x′ j 、x′ n These represent different corrosion factors, x′ i 、x′ i x′ j 、x′ i x′ j x′ n These represent the main corrosion-controlling factors constructed from different corrosion factors, b i b ij b ijn They represent x′ respectively i 、x′ i x′ j 、x′ i x′ j x′n The corresponding coefficient.

[0065] In this embodiment, a quantitative relationship between corrosion rate and various main corrosion control factors can be constructed through multivariate nonlinear fitting, thereby obtaining the coefficient of each main corrosion control factor. This coefficient can be used for subsequent weight calculation to determine the degree of influence of each main corrosion control factor on the corrosion rate of the injection and production tubing.

[0066] In this embodiment, x′ i This indicates a single corrosion factor, or x′ i Corrosion controlling factors constructed from single corrosion factors, x′ i x′ j Indicated by x′ i and x′ j Corrosion controlling factor constructed from two corrosion factors, x′ i x′ j x′ n Indicated by x′ i 、x′ j 、x′ n The corrosion-controlling factors constructed from the three corrosion factors are illustrated with an example from Table 2. After converting the true values ​​into coded values, a multivariate nonlinear fitting is performed to obtain the fitting results:

[0067]

[0068] Where x′1 represents temperature, x′2 represents hydrogen sulfide, x′3 represents carbon dioxide, and x′4 represents oxygen. x′1x′3 represents the main corrosion controlling factor constructed by the dual corrosion factors of temperature and carbon dioxide, and x′1x′2x′4 represents the main corrosion controlling factor constructed by the three corrosion factors of temperature, hydrogen sulfide, and oxygen.

[0069] Optionally, the coefficients of each major corrosion controlling factor are analyzed using Pareto analysis to determine the degree of influence of each major corrosion controlling factor on the corrosion rate of the injection-production tubing, including:

[0070] The coefficients of each major corrosion controlling factor were analyzed using Pareto analysis to determine the weight of each factor.

[0071] Based on the magnitude of each weight, the degree of influence of each major corrosion control factor on the corrosion rate of the injection and production tubing is determined.

[0072] In this embodiment, Pareto analysis is used to obtain the corresponding weight of each major corrosion control factor based on its coefficient, thereby enabling the identification of the importance of the major corrosion control factors.

[0073] Optionally, the coefficients of each major corrosion controlling factor are analyzed using Pareto analysis to determine the weight of each factor, as shown in the following formula:

[0074]

[0075] Where, when b′ i For b i At that time, P i For b i The corresponding weights of the main corrosion control factors, when b′ i For b ij At that time, P i For b ij The corresponding weights of the main corrosion control factors, when b′ i For b ijn At that time, P i For b ijn The corresponding weights of the main corrosion control factors.

[0076] For example, taking Table 2 above as an example, after converting each true value into an encoded value, a multivariate nonlinear fitting is performed, and the fitting result is as follows:

[0077]

[0078] It can be seen that the coefficients of the coupling of temperature x′1, temperature and carbon dioxide as dual corrosion factors x′1x′3, oxygen x′4, hydrogen sulfide x′2, carbon dioxide x′3, and temperature, hydrogen sulfide and oxygen as triple corrosion factors x′1x′2x′4 are -0.776, -1.078, 0.321, 0.607, 0.478 and -0.405, respectively.

[0079] Then, based on the coupling coefficients of the two corrosion factors (temperature, oxygen, and carbon dioxide) and the three corrosion factors (oxygen, hydrogen sulfide, carbon dioxide, temperature, and oxygen), the weights are calculated to obtain the following: Figure 2 The results show that the influence of each major corrosion control factor on the corrosion rate of the injection and production tubing is as follows: temperature (44.57%) > temperature and carbon dioxide (20.91%) > oxygen (20.32%) > hydrogen sulfide (6.63%) > carbon dioxide (4.62%) > temperature, hydrogen sulfide and oxygen (2.95%).

[0080] Alternatively, corrosive factors include temperature, hydrogen sulfide, carbon dioxide, and oxygen.

[0081] In this embodiment, to verify the accuracy of the obtained corrosion factors, the K value, k value, and R value of each corrosion factor in constructing a multi-factor, multi-level orthogonal combination were calculated, where:

[0082] The K-value (sum value) reflects the cumulative effect of all experimental results at all levels of a factor. By calculating the K-value, we can gain a preliminary understanding of the trend of the influence of different levels on the experimental results.

[0083] The k-value (average) is obtained by dividing the k-value by the number of times that level occurs. It eliminates the influence of unequal occurrences of different levels, making the comparison between different factors more fair and accurate.

[0084] The R-value (range) is the difference between the maximum and minimum k-values ​​for a given factor, reflecting the magnitude or importance of that factor's influence on the experimental results.

[0085] Table 2 below shows the corrosion rate corresponding to each set of experimental parameters, as well as the K, k, and R values ​​corresponding to each corrosion factor.

[0086] Table 2

[0087]

[0088]

[0089] The R values ​​in Table 4 show that the influence of corrosion factors on the corrosion rate is ranked as follows: temperature > oxygen. ＞ Hydrogen sulfide > carbon dioxide, and the R value of each corrosion factor is greater than 1 (carbon dioxide is close to 1), indicating that the influence or importance of this corrosion factor on the corrosion rate is relatively high.

[0090] like Figure 3 As shown, the present invention provides an evaluation system for the main controlling factors of corrosion, comprising:

[0091] The corrosion factor acquisition module is used to acquire at least three corrosion factors that affect the corrosion rate of the injection and production tubing, and to construct different main corrosion control factors based on the corrosion factors; wherein the main corrosion control factor is a single corrosion factor or a coupling of multiple corrosion factors;

[0092] The experimental parameter construction module is used to construct multiple sets of experimental parameters for the corrosion immersion experiment of the injection and production tubing by using a multi-factor, multi-level orthogonal combination of various corrosion factors.

[0093] The corrosion rate determination module is used to conduct corrosion immersion experiments on the injection and production tubing based on multiple sets of experimental parameters, and to determine the corrosion rate corresponding to each set of experimental parameters.

[0094] The fitting module is used to construct a quantitative relationship between the corrosion rate and each main corrosion control factor using each set of experimental parameters and the corresponding corrosion rate, and to perform multivariate nonlinear fitting to determine the coefficient of each main corrosion control factor.

[0095] The corrosion control factor evaluation module is used to analyze the coefficients of each corrosion control factor based on Pareto analysis to determine the degree of influence of each corrosion control factor on the corrosion rate of the injection-production tubing.

[0096] Optionally, the corrosion rate determination module is specifically used for:

[0097] Obtain the range value for each corrosion factor;

[0098] Multiple preset values ​​within the range of each corrosion factor are used as the actual values ​​of the corresponding corrosion factor.

[0099] Each real value is encoded to obtain the encoded value corresponding to each real value;

[0100] Based on each corrosion factor and each coding value, a multi-factor, multi-level orthogonal combination was performed to determine multiple sets of experimental parameters.

[0101] Optionally, the corrosion rate determination module is specifically used for:

[0102] Each real value is encoded to obtain the corresponding encoded value, as shown in the following formula:

[0103]

[0104] Where, x i X represents the encoded value corresponding to the i-th real value. i，max X i，min ΔX represents the maximum and minimum values ​​within the range corresponding to the corrosion factor, respectively. i This represents the range of values ​​corresponding to the corrosion factors. X represents the true value at the center point within the range corresponding to the corrosion factor. i This represents the i-th true value.

[0105] Optionally, the fitting module is specifically used for:

[0106] Using the experimental parameters and corresponding corrosion rates for each group, a quantitative relationship between corrosion rate and each major corrosion-controlling factor is constructed, and a multivariate nonlinear fitting is performed to determine the coefficient of each major corrosion-controlling factor, as shown in the following formula:

[0107]

[0108] Where Y represents the corrosion rate, b0 represents the constant term, and b ii Let x′ represent the coefficient of the quadratic term. i 、x′ j 、x′ n These represent different corrosion factors, x′ i 、x′ i x′j 、x′ i x′ j x′ n These represent the main corrosion-controlling factors constructed from different corrosion factors, b i b ij b ijn They represent x′ respectively i 、x′ i x′ j 、x′ i x′ j x′ n The corresponding coefficient.

[0109] Optionally, the corrosion control factor evaluation module is specifically used for:

[0110] The coefficients of each major corrosion controlling factor were analyzed using Pareto analysis to determine the weight of each factor.

[0111] Based on the magnitude of each weight, the degree of influence of each major corrosion control factor on the corrosion rate of the injection and production tubing is determined.

[0112] Optionally, the corrosion control factor evaluation module is specifically used for:

[0113] The coefficients of each major corrosion controlling factor were analyzed using Pareto analysis to determine the weight of each factor, as shown in the following formula:

[0114]

[0115] Where, when b′ i For b i At that time, P i For b i The corresponding weights of the main corrosion control factors, when b′ i For b ij At that time, P i For b ij The corresponding weights of the main corrosion control factors, when b′ i For b ijn At that time, P i For b ijn The corresponding weights of the main corrosion control factors.

[0116] The present invention also provides a computing device, including a memory, a manager, and a program stored in the memory and running on the manager, wherein the manager executes the program to implement some or all of the steps of the above-described method for evaluating the main control factors of corrosion.

[0117] The computing device can be a computer, and the corresponding program is computer software. The parameters and steps in the computing device of the present invention can be referred to the parameters and steps in the embodiment of the evaluation method of the main control factor of corrosion mentioned above, and will not be repeated here.

[0118] Those skilled in the art will recognize that this invention can be implemented as a system, method, or computer program product. Therefore, this disclosure can be embodied in the following forms: it can be entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, the invention can also be implemented as a computer program product contained in one or more computer-readable media, which contains computer-readable program code. Computer-readable storage media can be, for example, but not limited to—electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof.

[0119] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0120] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for evaluating the main controlling factors of corrosion, characterized in that, include: At least three corrosion factors affecting the corrosion rate of the injection and production tubing are identified, and different main corrosion control factors are constructed based on these corrosion factors; wherein, the main corrosion control factors are single corrosion factors or coupling of multiple corrosion factors. The corrosion factors were constructed using a multi-factor, multi-level orthogonal combination method to create multiple sets of experimental parameters for the corrosion immersion test of the injection and production tubing. Corrosion immersion experiments were conducted on the injection and production tubing based on multiple sets of experimental parameters to determine the corrosion rate corresponding to each set of experimental parameters. Using the experimental parameters and corresponding corrosion rates of each group, a quantitative relationship between corrosion rate and each major corrosion controlling factor is constructed, and a multivariate nonlinear fitting is performed to determine the coefficient of each major corrosion controlling factor. The coefficients of each of the aforementioned major corrosion control factors were analyzed using Pareto analysis to determine the degree of influence of each of the aforementioned major corrosion control factors on the corrosion rate of the injection-production tubing.

2. The method according to claim 1, characterized in that, The various corrosion factors were constructed using a multi-factor, multi-level orthogonal combination method to create multiple sets of experimental parameters for the corrosion immersion experiment of the injection-production tubing, including: Obtain the range value for each of the corrosion factors; Multiple preset values ​​within the range of each corrosion factor are used as the actual values ​​of the corresponding corrosion factor. Each of the real values ​​is encoded to obtain the encoded value corresponding to each real value; Based on each of the corrosion factors and each of the coding values, a multi-factor, multi-level orthogonal combination is performed to determine multiple sets of experimental parameters.

3. The method according to claim 2, characterized in that, The process of encoding each real value to obtain the encoded value corresponding to each real value is as follows: Where, x i X represents the encoded value corresponding to the i-th real value. i，max X i，min ΔX represents the maximum and minimum values ​​within the range corresponding to the corrosion factor, respectively. i This represents the range of values ​​corresponding to the corrosion factors. X represents the true value at the center point within the range corresponding to the corrosion factor. i This represents the i-th true value.

4. The method according to claim 1, characterized in that, Using the experimental parameters and corresponding corrosion rates for each group, a quantitative relationship between corrosion rate and each major corrosion-controlling factor is constructed, and a multivariate nonlinear fitting is performed to determine the coefficient of each major corrosion-controlling factor, as shown in the following formula: Where Y represents the corrosion rate, b0 represents the constant term, and b ii x represents the coefficient of the quadratic term. i x j 、x′ n These represent different corrosion factors, x′ i 、x′ i x′ j 、x′ i x′ j x′ n These represent the main corrosion-controlling factors constructed from different corrosion factors, b i b ij b ijn They represent x′ respectively i 、x′ i x′ j 、x′ i x′ j x′ n The corresponding coefficient.

5. The method according to claim 4, characterized in that, The coefficients of each of the aforementioned major corrosion control factors were analyzed using Pareto analysis to determine the degree of influence of each factor on the corrosion rate of the injection-production tubing, including: The coefficients of each of the main corrosion-controlling factors are analyzed using Pareto analysis to determine the weight of each of the main corrosion-controlling factors. Based on the magnitude of each of the aforementioned weights, the degree of influence of each of the aforementioned main corrosion control factors on the corrosion rate of the injection-production tubing is determined.

6. The method according to claim 5, characterized in that, The coefficients of each of the main corrosion-controlling factors are analyzed using Pareto analysis to determine the weight of each factor, as shown in the following formula: Where, when b′ i For b i At that time, P i For b i The corresponding weights of the main corrosion control factors, when b′ i For b ij At that time, P i For b ij The corresponding weights of the main corrosion control factors, when b′ i For b ijn At that time, P i For b ijn The corresponding weights of the main corrosion control factors.

7. The method according to any one of claims 1-6, characterized in that, The corrosive factors include temperature, hydrogen sulfide partial pressure, carbon dioxide partial pressure, and oxygen partial pressure.

8. An evaluation system for the main controlling factors of corrosion, characterized in that, The system for implementing the method according to any one of claims 1 to 7 comprises: The corrosion factor acquisition module is used to acquire at least three corrosion factors that affect the corrosion rate of the injection and production tubing, and to construct different main corrosion control factors based on the corrosion factors; wherein the main corrosion control factor is a single corrosion factor or a coupling of multiple corrosion factors; The experimental parameter construction module is used to construct multiple sets of experimental parameters for the corrosion immersion experiment of the injection and production tubing by using a multi-factor, multi-level orthogonal combination of various corrosion factors. The corrosion rate determination module is used to conduct corrosion immersion experiments on the injection and production tubing based on multiple sets of experimental parameters, and to determine the corrosion rate corresponding to each set of experimental parameters. The fitting module is used to construct a quantitative relationship between the corrosion rate and each main corrosion control factor using each set of experimental parameters and the corresponding corrosion rate, and to perform multivariate nonlinear fitting to determine the coefficient of each main corrosion control factor. The corrosion control factor evaluation module is used to analyze the coefficients of each corrosion control factor based on Pareto analysis to determine the degree of influence of each corrosion control factor on the corrosion rate of the injection-production tubing.

9. A computing device, comprising a memory, a processor, and a program stored in the memory and running on the processor, characterized in that, The processor executes the program to implement the steps of the evaluation method for the main control factors of corrosion as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a terminal device, cause the terminal device to perform the steps of the evaluation method for the main corrosion control factors as described in any one of claims 1-7.

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