Microbial corrosion rate prediction method for carbon steel submarine pipeline

Abstract

The invention discloses a method for predicting the microbial corrosion rate of a carbon steel submarine pipeline, and is suitable for the field of microbial corrosion prediction in offshore oil and gas fields and land pipelines. The invention aims to accurately evaluate the local corrosion rate in the pipeline induced by microorganisms. An Arrhenius formula and various influence factors including but not limited to temperature, pressure, pH, SO4 < 2->, flow velocity, inorganic sediment, organic sediment, bactericide, pigging, microbial growth stage and the like are fused in the model to form a comprehensive mathematical framework. Through experimental data calibration and verification, it is ensured that the model can accurately simulate the microbial corrosion rate in different environments. In addition, in consideration of an electrochemical corrosion phenomenon under a biological membrane, a compensation factor is introduced to improve accuracy. The method has an important auxiliary effect on design and maintenance of the submarine pipeline, can help to estimate the corrosion risk and residual life, guides to formulate a detection and protection strategy for corrosion control in the pipeline, and enhances the operation safety of the submarine oil and gas pipeline.

Description

Technical Field

[0001] The present invention relates to the technical field of predicting microbial corrosion in offshore oil and gas fields and inside onshore pipelines, and particularly relates to a method for predicting the microbial corrosion rate of carbon steel submarine pipelines. Background Art

[0002] The internal corrosion environment of submarine pipelines is extremely harsh. Due to being affected by multiple variables, the corrosion mechanism of microbial corrosion (MIC) is particularly complex and has become one of the key factors threatening the integrity of submarine pipelines. Therefore, deeply exploring various factors affecting microbial corrosion and establishing a model for predicting microbial corrosion are crucial for ensuring the long-term stable operation of submarine pipelines.

[0003] Currently, the research on microbial corrosion prediction models mainly focuses on empirical, mechanistic, and risk assessment-based models. For example, Zhang Zhe et al. established the DW91 correction model based on experience and studied the corrosion rates of 5 types of steel and their SRB corrosion resistance under different SRB contents at normal and high pressures. Al-Darbi et al. studied the numerical model of the anaerobic MIC mechanism in SRB environments (ocean, landfill, and fresh water) based on the cathodic depolarization theory proposed by Wolgozen Kuhr and van der Vlugt. As for the risk assessment model, it focuses on predicting the possibility or probability of corrosion occurrence. Although some factors affecting microbial corrosion are considered, the electrochemical reaction and mass transfer processes are not deeply explored. The research on these prediction models has significantly improved our understanding of the accuracy and reliability of microbial corrosion prediction.

[0004] However, the existing prediction models mostly calculate in a single dimension and fail to fully combine the interaction between the microbial corrosion mechanism and various influencing factors. Given the complexity of the microbial corrosion mechanism and influencing factors, there is an urgent need to develop a comprehensive prediction model to address the limitations in the existing technology and provide more reliable guidance for the safety maintenance of submarine pipelines. Summary of the Invention

[0005] The purpose of the present invention is to propose a method for predicting the microbial corrosion rate of carbon steel submarine pipelines, which can more comprehensively understand and predict microbial corrosion by combining the interaction between the microbial corrosion mechanism and various influencing factors, and ensure the safety and reliability of submarine pipelines.

[0006] To achieve the above purpose, the present application provides the following technical solutions:

[0007] A method for predicting the microbial corrosion rate of carbon steel submarine pipelines, comprising the following steps:

[0008] S1. Obtain the operating condition data of the submarine pipeline, including temperature, operating pressure, and flow rate;

[0009] S2. Obtain data related to the transport medium, including pH, CO2 content, H2S content, and SO4 2- concentration;

[0010] S3. Obtain bactericidal measures and bactericidal effects, including pigging conditions, bactericide usage, and microbial content;

[0011] S4. Use a prediction model to calculate the corrosion rate at different growth stages of microorganisms. The calculation formula of the prediction model is as follows:

[0012] CRmic = k × F + C

[0013]

[0014] F = [f1 × f2]m × [f3 × f4 × f5 × f6 × f7 × f8 × f9 × f10 × f11]n

[0015] Where, CRmic represents the microbial corrosion rate, mm / y; k represents the reaction rate constant, mm / y; F represents the influencing factor, dimensionless; C represents the electrochemical corrosion rate constant, mm / y; A represents the pre-exponential factor, mm / y; Ea represents the activation energy, kJ / mol; R represents the molar constant, kJ / (mol·K); T represents the temperature, K; f1 represents the temperature influencing factor; f2 represents the partial pressure influencing factor; f3 represents the pH influencing factor; f4 represents the sulfate radical influencing factor; f5 represents the flow rate influencing factor; f6 represents the inorganic deposit influencing factor; f7 represents the organic deposit influencing factor; f8 represents the bactericide influencing factor; f9 represents the pigging influencing factor; f10 represents the growth period influencing factor; f11 represents other influencing factors; m represents the total product index of key influencing factors; n represents the total product index of general influencing factors;

[0016] Calculate the average microbial corrosion rate during the growth period according to the corrosion rate at different growth stages of microorganisms. The calculation formula is as follows:

[0017]

[0018] Where, represents the average microbial corrosion rate during the growth period, mm / y; CRmic1 represents the microbial corrosion rate in the first growth stage, mm / y; CRmic2 represents the microbial corrosion rate in the second growth stage, mm / y; CRmic3 represents the microbial corrosion rate in the third growth stage, mm / y; t1 represents the time in the first growth stage, d; t2 represents the time in the second growth stage, d; t3 represents the time in the third growth stage, d.

[0019] Optionally, the first growth stage is the induction period of microbial corrosion, the second growth stage is the growth period of microbial corrosion, and the third growth stage is the death period of microbial corrosion.

[0020] Optionally, the pre-exponential factor A in the three growth stages follows the following rules:

[0021] Induction period, the value range is 0.2 - 0.8 mm / y;

[0022] Growth period, the value range is 1.5 - 4 mm / y;

[0023] Death period, the value range is 0.3 - 1.5 mm / y.

[0024] Optionally, the activation energy Ea has a value range of 35 - 100 kJ / mol.

[0025] Optionally, for subsea pipelines transporting wet natural gas, the value of Ea is 60 - 90 kJ / mol; for subsea pipelines transporting dry oil without free water, under the condition of not pigging, the value of Ea is 90 - 100 kJ / mol; for the condition of containing nutrients such as acetic acid, citric acid, and lactic acid, the value of Ea is 35 - 60 kJ / mol; for multiphase flow pipelines and subsea pipelines with a large amount of chemical agents added, the value of Ea is 40 - 70 kJ / mol. In this case, when the specific gravity of crude oil is greater than 0.9, the value of Ea is 50 - 70 kJ / mol, and when the specific gravity range of crude oil is 0.8 - 0.9, the value of Ea is 40 - 60 kJ / mol.

[0026] Optionally, the temperature influence factor f1 follows the following rules:

[0027] Temperature < -15°C, the value is 0;

[0028] -15°C ≤ Temperature < 15°C, the value range is 0.1 - 2;

[0029] 15°C ≤ Temperature < 50°C, the value range is 1 - 5;

[0030] 50°C ≤ Temperature < 80°C, the value range is 0.1 - 3;

[0031] 80°C ≤ Temperature < 100°C, the value range is 0.1 - 2;

[0032] Temperature ≥ 100°C, the value is 0;

[0033] And / or, the partial pressure influence factor f2 follows the following rules:

[0034] P CO2 ≥ 2 MPa, the value range is 0.01 - 4;

[0035] P CO2 / PH2S ≥20, with a value range of 0.1 - 3;

[0036] P CO2 / P H2S <20, with a value range of 0.1 - 3;

[0037] When there is no partial pressure of CO2 and H2S in the fluid, the value is 1; P CO2 represents the partial pressure of CO2, P H2S represents the partial pressure of H2S;

[0038] And / or, the pH influence factor f3 has the following value-taking rules:

[0039] pH < 2, the value is 0;

[0040] 2 ≤ pH < 5, with a value range of 0.1 - 2;

[0041] 5 ≤ pH < 9, with a value range of 0.5 - 5;

[0042] 9 ≤ pH < 14, with a value range of 0.1 - 2;

[0043] pH > 14, the value is 0;

[0044] And / or, the sulfate influence factor f4 has the following value-taking rules:

[0045] SO4 2- ≤ 20mg / L, with a value range of 0.01 - 1;

[0046] 20mg / L < SO4 2- ≤ 50mg / L, with a value range of 0.1 - 4;

[0047] 50mg / L < SO4 2- ≤ 150mg / L, with a value range of 0.1 - 5;

[0048] SO4 2- >150mg / L, with a value range of 0.1 - 6; SO4 2- represents the sulfate concentration;

[0049] And / or, the flow rate influence factor f5 has the following value-taking rules:

[0050] Flow rate ≤ 0.1m / s, with a value range of 0.1 - 8;

[0051] 0.1m / s < flow rate ≤ 1m / s, with a value range of 0.1 - 6;

[0052] 1m / s < flow rate ≤ 2m / s, with a value range of 0.1 - 5;

[0053] 2 m / s < flow velocity ≤ 3 m / s, value range 0.01 - 3;

[0054] flow velocity > 3 m / s, value range 0.01 - 3;

[0055] and / or, for the inorganic sediment influencing factor f6, the value rule is as follows:

[0056] There are obvious sediments in the pigging material, and SRB > 25 per mL in the sediments, value range 1 - 10;

[0057] There are obvious sediments in the pigging material, and SRB ≤ 25 per mL in the sediments, value range 0.1 - 9;

[0058] There are no obvious sediments in the pigging material, and SRB > 25 per mL in the water, value range 0.1 - 7;

[0059] There are no obvious sediments in the pigging material, and SRB ≤ 25 per mL in the water, value range 0.1 - 5; SRB refers to the content of sulfate-reducing bacteria;

[0060] Pigging cannot be carried out, and the sediment state cannot be determined, value range 1 - 10;

[0061] Pigging cannot be carried out, but it can be determined that there are no sediments, value range 0.1 - 5;

[0062] and / or, for the organic sediment influencing factor f7, the value rule is as follows:

[0063] There are organic sediments, value range 1 - 8;

[0064] There are no organic sediments, value range 0.1 - 5;

[0065] and / or, for the bactericide influencing factor f8, the value rule is as follows:

[0066] No bactericide is added, value range 1 - 5;

[0067] Bactericide is added, and occasionally SRB > 25 per mL, value range 0.5 - 4;

[0068] Bactericide is added, and SRB ≤ 25 per mL, value range 0.1 - 4;

[0069] Bactericide is added, and SRB ≤ 10 per mL, value range 0.1 - 3;

[0070] and / or, for the pigging influencing factor f9, the value rule is as follows:

[0071] The interference of the pigging ball can ensure the removal of the defect surface in the pipeline, and SRB ≤ 25 per mL, value range 0.1 - 2;

[0072] The pigging ball interference amount can ensure the removal of the defect surface in the pipeline, SRB > 25 per mL, with a value range of 0.1 - 4;

[0073] The pigging ball interference amount cannot ensure the removal of the defect surface in the pipeline, SRB ≤ 25 per mL before pigging, with a value range of 1 - 8;

[0074] The pigging ball interference amount cannot ensure the removal of the defect surface in the pipeline, SRB > 25 per mL before pigging, with a value range of 4 - 12;

[0075] No pigging, with a value range of 4 - 20;

[0076] And / or, the growth period influencing factor f10 has the following value-taking rules:

[0077] Induction period, with a value range of 0.1 - 5;

[0078] Growth period, with a value range of 0.5 - 6;

[0079] Death period, with a value range of 0.1 - 5;

[0080] When the growth period cannot be confirmed, the growth period value is taken in all cases;

[0081] And / or, the other influencing factor f11 includes, but is not limited to, the nutrient content, the number of other types of bacteria, and the bacterial reproduction time;

[0082] And / or, the total product index m of the key influencing factors has the following value-taking rules:

[0083] Induction period, with a value range of 0 - 1;

[0084] Growth period, with a value range of 0 - 2;

[0085] Death period, with a value range of 0 - 1;

[0086] And / or, the total product index n of the general influencing factors has the following value-taking rules:

[0087] Induction period, with a value range of 0.1 - 0.8;

[0088] Growth period, with a value range of 0.1 - 2;

[0089] Death period, with a value range of 0.1 - 0.8.

[0090] Optionally, the electrochemical corrosion rate constant C has the following value-taking rules:

[0091] Temperature ≤ 60°C, with a value range of 0.01 - 1 mm / y;

[0092] 60°C < temperature ≤ 85°C, with a value range of 0.01 - 0.09 mm / y;

[0093] temperature > 85°C, with a value range of 0.01 - 0.08 mm / y.

[0094] Optionally, the time t1 of the first growth stage has a value range of 3 - 7 d;

[0095] The time t2 of the second growth stage has a value range of 5 - 10 d;

[0096] The time t3 of the third growth stage has a value range of 3 - 7 d.

[0097] Optionally, the scope of use of the method is for microorganisms that can produce H2S, CO2, and / or slime to promote microbial corrosion.

[0098] In summary, the technical effects and advantages of the present invention are as follows:

[0099] By integrating the interaction between the microbial corrosion mechanism and various influencing factors, the present invention respectively predicts the corrosion rates of microorganisms in three different stages of induction, growth, and death. This innovation improves the accuracy of predicting the microbial corrosion rate;

[0100] In the present invention, ten key variables including temperature, pressure, pH, sulfate concentration, flow rate, inorganic deposits, organic deposits, biocide effect, pigging effect, and microbial growth stage are considered, and they are classified into key and general factors according to their importance, and different weight indices are assigned, thereby further improving the accuracy of the prediction model;

[0101] In the present invention, the electrochemical corrosion phenomenon occurring under the biofilm is particularly considered, and the model is corrected by adding a compensation factor. This innovation emphasizes the secondary hazards that may be caused during the microbial corrosion process and ensures the comprehensiveness and integrity of the prediction model;

[0102] The present invention has an important auxiliary effect on the design and maintenance of subsea pipelines, can help estimate the corrosion risk and remaining life, guide the formulation of detection and protection strategies for internal corrosion control of pipelines, and enhance the safety of subsea oil and gas pipeline operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0103] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those skilled in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0104] Figure 1It is a flowchart of the method according to an embodiment of the present invention. Detailed implementation manners

[0105] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0106] In addition, the technical features involved in different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0107] This application aims at microorganisms in pipelines containing free water at offshore and onshore oil and gas field sites that can metabolize to produce H2S, CO2, and / or slime, etc., which promote microbial corrosion.

[0108] This embodiment proposes a method for predicting the microbial corrosion rate of carbon steel submarine pipelines, as Figure 1 shown, including the following steps:

[0109] S1. Obtain the operating condition data of the submarine pipeline, including temperature, operating pressure, and flow rate;

[0110] S2. Obtain the data related to the transported medium, including pH, CO2 content, H2S content, and SO4 2- concentration;

[0111] S3. Obtain the bactericidal measures and bactericidal effects, including pigging conditions, bactericide usage, and microbial content;

[0112] S4. Use the prediction model to calculate the corrosion rate at different growth stages of microorganisms. The Arrhenius formula is introduced into the prediction model, and the formula is corrected by key influencing factors (temperature, pressure) and general influencing factors (pH, sulfate concentration, flow rate, inorganic deposits, organic deposits, bactericide effect, pigging effect, and microbial growth stage), and a compensation factor is introduced to compensate for the electrochemical corrosion under the biofilm. The Arrhenius formula is introduced into the prediction model to determine the reaction rate constant The reaction rate constant is affected by the microbial growth stage and temperature.

[0113] The calculation formula of the prediction model is as follows:

[0114] CRmic = k × F + C

[0115]

[0116] F = [f1 × f2]m × [f3 × f4 × f5 × f6 × f7 × f8 × f9 × f10 × f11]n

[0117] Wherein, CRmic represents the microbial corrosion rate, mm / y; k represents the reaction rate constant, mm / y; F represents the influence factor, dimensionless; C represents the electrochemical corrosion rate constant, mm / y; A represents the pre-exponential factor, mm / y; Ea represents the activation energy, kJ / mol; R represents the molar constant, kJ / (mol·K); T represents the temperature, K; f1 represents the temperature influence factor; f2 represents the partial pressure influence factor; f3 represents the pH influence factor; f4 represents the sulfate radical influence factor; f5 represents the flow rate influence factor; f6 represents the inorganic deposit influence factor; f7 represents the organic deposit influence factor; f8 represents the biocide influence factor; f9 represents the pigging influence factor; f10 represents the growth period influence factor; f11 represents other influence factors; m represents the total product index of key influence factors; n represents the total product index of general influence factors;

[0118] Calculate the average microbial corrosion rate during the growth period according to the corrosion rate at different growth stages of microorganisms. The calculation formula is as follows:

[0119]

[0120] Wherein, represents the average microbial corrosion rate during the growth period, mm / y; CRmic1 represents the microbial corrosion rate in the first growth stage, mm / y; CRmic2 represents the microbial corrosion rate in the second growth stage, mm / y; CRmic3 represents the microbial corrosion rate in the third growth stage, mm / y; t1 represents the time in the first growth stage, d; t2 represents the time in the second growth stage, d; t3 represents the time in the third growth stage, d 。

[0121] Optionally, the first growth stage is the induction period of microbial corrosion, the second growth stage is the growth period of microbial corrosion, and the third growth stage is the death period of microbial corrosion.

[0122] Optionally, the pre-exponential factor A is affected by different growth stages of microorganisms. In this embodiment, it is proposed that microbial corrosion should be divided into three stages, including: the induction period, the growth period, and the death period. According to the research data and on-site detection data, the value-taking rules of the pre-exponential factor A in the three growth stages are as follows:

[0123] Induction period, the value range is 0.2 - 0.8 mm / y;

[0124] Growth period, the value range is 1.5 - 4 mm / y;

[0125] Death period, with a value range of 0.3 - 1.5 mm / y;

[0126] Optionally, the activation energy Ea, obtained from experiments, has a value range of 35 - 100 kJ / mol.

[0127] Optionally, for subsea pipelines transporting wet natural gas, the Ea value is 60 - 90 kJ / mol; for subsea pipelines transporting dry oil without free water, under the condition of not pigging, the Ea value is 90 - 100 kJ / mol; for pipelines under conditions containing nutrients such as acetic acid, citric acid, and lactic acid, the Ea value is 35 - 60 kJ / mol; for multiphase flow pipelines and subsea pipelines with a large amount of chemical agents added, the Ea value is 40 - 70 kJ / mol. In this case, when the specific gravity of crude oil is greater than 0.9, the Ea value is 50 - 70 kJ / mol, and when the specific gravity range of crude oil is 0.8 - 0.9, the Ea value is 40 - 60 kJ / mol.

[0128] Optionally, in the prediction model, the formula is corrected by key influencing factors and general influencing factors to reflect the influence degree of different growth environments on microbial corrosion.

[0129] Optionally, the temperature influence factor f1, obtained from experiments, has the following value-taking rules:

[0130] Temperature < -15°C, the value is 0;

[0131] -15°C ≤ Temperature < 15°C, the value range is 0.1 - 2;

[0132] 15°C ≤ Temperature < 50°C, the value range is 1 - 5;

[0133] 50°C ≤ Temperature < 80°C, the value range is 0.1 - 3;

[0134] 80°C ≤ Temperature < 100°C, the value range is 0.1 - 2;

[0135] Temperature ≥ 100°C, the value is 0;

[0136] And / or, the partial pressure influence factor f2, obtained from experiments, has the following value-taking rules:

[0137] P CO2 ≥ 2 MPa, the value range is 0.01 - 4;

[0138] P CO2 / P H2S ≥ 20, the value range is 0.1 - 3;

[0139] P CO2 / P H2S <20, the value range is 0.1 - 3;

[0140] When there are no partial pressures of CO2 and H2S in the fluid, such as in water injection and produced water systems, the value is 1; P CO2 represents the partial pressure of CO2, and P H2S represents the partial pressure of H2S;

[0141] And / or, the pH influence factor f3, obtained from experiments, has the following value-taking rules:

[0142] When pH < 2, the value is 0;

[0143] When 2 ≤ pH < 5, the value range is 0.1 - 2;

[0144] When 5 ≤ pH < 9, the value range is 0.5 - 5;

[0145] When 9 ≤ pH < 14, the value range is 0.1 - 2;

[0146] When pH > 14, the value is 0;

[0147] And / or, the sulfate (SO4 2- ) influence factor f4, obtained from experiments, has the following value-taking rules:

[0148] When SO4 2- ≤ 20 mg / L, the value range is 0.01 - 1;

[0149] When 20 mg / L < SO4 2- ≤ 50 mg / L, the value range is 0.1 - 4;

[0150] When 50 mg / L < SO4 2- ≤ 150 mg / L, the value range is 0.1 - 5;

[0151] When SO4 2- > 150 mg / L, the value range is 0.1 - 6; SO4 2- represents the sulfate concentration;

[0152] And / or, the flow rate influence factor f5, obtained from experiments, has the following value-taking rules:

[0153] When the flow rate ≤ 0.1 m / s, the value range is 0.1 - 8;

[0154] When 0.1 m / s < flow rate ≤ 1 m / s, the value range is 0.1 - 6;

[0155] When 1 m / s < flow rate ≤ 2 m / s, the value range is 0.1 - 5;

[0156] When 2 m / s < flow rate ≤ 3 m / s, the value range is 0.01 - 3;

[0157] When the flow rate > 3 m / s, the value range is 0.01 - 3;

[0158] And / or, the inorganic sediment influencing factor f6, according to the test results, has the following value-taking rules:

[0159] There are obvious sediments in the pigging material, and the number of SRB in the sediment is > 25 / mL, and the value range is 1 - 10;

[0160] There are obvious sediments in the pigging material, and the number of SRB in the sediment is ≤ 25 / mL, and the value range is 0.1 - 9;

[0161] There are no obvious sediments in the pigging material, and the number of SRB in the water is > 25 / mL, and the value range is 0.1 - 7;

[0162] There are no obvious sediments in the pigging material, and the number of SRB in the water is ≤ 25 / mL, and the value range is 0.1 - 5; SRB refers to the content of sulfate-reducing bacteria;

[0163] Pigging cannot be carried out, and the sediment state cannot be determined, and the value range is 1 - 10;

[0164] Pigging cannot be carried out, but it can be determined that there is no sediment (such as a wet natural gas pipeline), and the value range is 0.1 - 5;

[0165] And / or, the organic sediment influencing factor f7, according to the test results, has the following value-taking rules:

[0166] There are organic sediments, and the value range is 1 - 8;

[0167] There are no organic sediments, and the value range is 0.1 - 5;

[0168] And / or, the bactericide influencing factor f8, according to the test results, has the following value-taking rules:

[0169] No bactericide is added, and the value range is 1 - 5;

[0170] Bactericide is added, and occasionally the number of SRB is > 25 / mL, and the value range is 0.5 - 4;

[0171] Bactericide is added, and the number of SRB is ≤ 25 / mL, and the value range is 0.1 - 4;

[0172] Bactericide is added, and the number of SRB is ≤ 10 / mL, and the value range is 0.1 - 3;

[0173] And / or, the pigging influencing factor f9, according to the test results, has the following value-taking rules:

[0174] The interference of the pigging ball can ensure the removal of the defective surface in the pipeline, and the number of SRB is ≤ 25 / mL, and the value range is 0.1 - 2;

[0175] The pigging ball interference can ensure the removal of the defect surface in the pipeline, SRB > 25 per mL, with a value range of 0.1 - 4;

[0176] The pigging ball interference cannot ensure the removal of the defect surface in the pipeline. Before pigging, SRB ≤ 25 per mL, with a value range of 1 - 8;

[0177] The pigging ball interference cannot ensure the removal of the defect surface in the pipeline. Before pigging, SRB > 25 per mL, with a value range of 4 - 12;

[0178] No pigging, with a value range of 4 - 20;

[0179] And / or, the growth period influencing factor f10, obtained from experiments, has the following value-taking rules:

[0180] Induction period, with a value range of 0.1 - 5;

[0181] Growth period, with a value range of 0.5 - 6;

[0182] Death period, with a value range of 0.1 - 5;

[0183] When the growth period cannot be confirmed, the growth period value is taken uniformly;

[0184] And / or, the other influencing factor f11, including but not limited to nutrient content, the number of other types of bacteria, and bacterial reproduction time, etc., is used for further correction and verification of the formula. The value-taking rules for different growth stages can be determined according to the detection and research conclusions;

[0185] And / or, the total product index m of the key influencing factors, obtained from experiments, has the following value-taking rules:

[0186] Induction period, with a value range of 0 - 1;

[0187] Growth period, with a value range of 0 - 2;

[0188] Death period, with a value range of 0 - 1;

[0189] And / or, the total product index n of the general influencing factors, obtained from experiments, has the following value-taking rules:

[0190] Induction period, with a value range of 0.1 - 0.8;

[0191] Growth period, with a value range of 0.1 - 2;

[0192] Death period, with a value range of 0.1 - 0.8.

[0193] Optionally, a compensation factor is introduced into the prediction model, which is mainly used to compensate for the electrochemical corrosion under the biofilm. The electrochemical corrosion rate constant C is mainly affected by temperature. The electrochemical corrosion rate constant C, obtained from experiments, has the following value-taking rules:

[0194] When the temperature ≤ 60°C, the value range is 0.01 - 1 mm / y;

[0195] When 60°C < temperature ≤ 85°C, the value range is 0.01 - 0.09 mm / y;

[0196] When the temperature > 85°C, the value range is 0.01 - 0.08 mm / y.

[0197] Optionally, the time t1 of the first growth stage, obtained from experiments, is the induction period, during which the hydrogen sulfide content increases significantly compared to normal, and the value range is 3 - 7 d;

[0198] The time t2 of the second growth stage, obtained from experiments, is the growth period, during which the hydrogen sulfide content is higher and more stable than during normal operation, and the value range is 5 - 10 d;

[0199] The time t3 of the third growth stage, obtained from experiments, is the death period, during which the hydrogen sulfide content decreases significantly, and the value range is 3 - 7 d.

[0200] Optionally, the application range of the method is for microorganisms that can produce H2S, CO2, and / or slime to promote microbial corrosion.

[0201] Specifically:

[0202] S1. This embodiment is a double-layer insulated subsea pipeline with an operating temperature of 67°C, an operating pressure of 2.1 MPa, and a flow rate of 1.5 m / s.

[0203] S2. This embodiment is an oil-gas-water multiphase transportation subsea pipeline with a pH value of 7.5, a CO2 content of 12%, an H2S content of 800 ppm, and an SO4 2- concentration of 650 mg / L.

[0204] S3. In this embodiment, foam balls are used for pigging, there are situations of CaCO3 and sediment deposition, and there are organic deposits; in addition, a bactericide is injected by impact, and the number of SRB in the water exceeds 70 per mL, and there are no TGB and FB.

[0205] S4. Use the prediction model in the present invention to calculate the microbial corrosion rate of this embodiment. The formula is as follows:

[0206] The microbial corrosion rate CRmic1 during the induction period = k1 × F1 + C1 = 2.0893 mm / y;

[0207] The microbial corrosion rate CRmic2 during the growth period = k2×F2 + C2 = 16.5608 mm / y;

[0208] The microbial corrosion rate CRmic3 during the death period = k3×F3 + C3 = 4.5297 mm / y;

[0209] The average microbial corrosion rate during the growth cycle

[0210]

[0211] In summary, by integrating the interaction between the microbial corrosion mechanism and various influencing factors, this application predicts the corrosion rates of microorganisms at three different stages: induction, growth, and death, respectively. This innovation improves the accuracy of predicting the microbial corrosion rate;

[0212] In this application, ten key variables including temperature, pressure, pH, sulfate concentration, flow rate, inorganic deposits, organic deposits, biocide effect, pigging effect, and microbial growth stage are considered, and they are classified into key and general factors according to their importance, and different weight indices are assigned, so as to further improve the accuracy of the prediction model;

[0213] In this application, the electrochemical corrosion phenomenon occurring under the biofilm is also particularly considered, and the model is corrected by adding a compensation factor. This innovation emphasizes the secondary hazards that may be caused during the microbial corrosion process and ensures the comprehensiveness and integrity of the prediction model;

[0214] This application plays an important auxiliary role in the design and maintenance of subsea pipelines, can help estimate the corrosion risk and remaining life, guide the formulation of detection and protection strategies for internal corrosion control of pipelines, and enhance the safety of subsea oil and gas pipeline operation.

[0215] Although the preferred embodiments of the present invention are described above in conjunction with the accompanying drawings, the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present invention, those of ordinary skill in the art can make many specific transformations in form without departing from the spirit of the invention and the scope protected by the claims. All of these fall within the protection scope of the present invention.

Claims

1. A method for predicting the microbial corrosion rate of carbon steel submarine pipelines, characterized in that, It includes the following steps: S1. Obtain the operating condition data of the subsea pipeline, including temperature, operating pressure, and flow rate; S2. Obtain the data related to the conveying medium, including pH, CO2 content, H2S content and SO4 2- concentration; S3. Obtain the bactericidal measures and bactericidal effects, including pigging conditions, bactericide usage, and microbial content; S4. Use the prediction model to calculate the corrosion rate at different growth stages of microorganisms. The calculation formula of the prediction model is as follows: CRmic = k × F + C F = [f1 × f2]m × [f3 × f4 × f5 × f6 × f7 × f8 × f9 × f10 × f11]n Where, CRmic represents the microbial corrosion rate, mm / y; k represents the reaction rate constant, mm / y; F represents the influence factor, dimensionless; C represents the electrochemical corrosion rate constant, mm / y; A represents the pre-exponential factor, mm / y; Ea represents the activation energy, kJ / mol; R represents the molar constant, kJ / (mol·K); T represents the temperature, K; f1 represents the temperature influence factor; f2 represents the partial pressure influence factor; f3 represents the pH influence factor; f4 represents the sulfate radical influence factor; f5 represents the flow rate influence factor; f6 represents the inorganic deposit influence factor; f7 represents the organic deposit influence factor; f8 represents the bactericide influence factor; f9 represents the pigging influence factor; f10 represents the growth period influence factor; f11 represents other influence factors; m represents the total product index of key influence factors; n represents the total product index of general influence factors; Calculate the average microbial corrosion rate during the growth period according to the corrosion rate at different growth stages of microorganisms. The calculation formula is as follows: Among them, represents the average microbial corrosion rate during the growth cycle, mm / y; CRmic1 represents the microbial corrosion rate in the first growth stage, mm / y; CRmic2 represents the microbial corrosion rate in the second growth stage, mm / y; CRmic3 represents the microbial corrosion rate in the third growth stage, mm / y; t1 represents the time in the first growth stage, d; t2 represents the time in the second growth stage, d; t3 represents the time in the third growth stage, d 。 2. The method for predicting the microbial corrosion rate of carbon steel submarine pipelines according to claim 1, characterized in that: The first growth stage is the induction period of microbial corrosion, the second growth stage is the growth period of microbial corrosion, and the third growth stage is the death period of microbial corrosion.

3. The method for predicting the microbial corrosion rate of a carbon steel subsea pipeline according to claim 2, wherein: The value-taking rules of the pre-exponential factor A in the three growth stages are as follows: Induction period, the value range is 0.2 - 0.8 mm / y; Growth period, the value range is 1.5 - 4 mm / y; Death period, the value range is 0.3 - 1.5 mm / y.

4. The method for predicting the microbial corrosion rate of carbon steel submarine pipelines according to claim 1, wherein: The value range of the activation energy Ea is 35 - 100 kJ / mol.

5. The method for predicting the microbial corrosion rate of carbon steel submarine pipelines according to claim 4, characterized in that: For wet natural gas subsea pipelines, the Ea value is taken as 60 - 90 kJ / mol; for dry oil subsea pipelines without free water, under non-pigging conditions, the Ea value is taken as 90 - 100 kJ / mol; for conditions containing nutrients such as acetic acid, citric acid, and lactic acid, the Ea value is taken as 35 - 60 kJ / mol; for multiphase flow pipelines and subsea pipelines with a large amount of chemical agents added, the Ea value is taken as 40 - 70 kJ / mol. In this case, when the specific gravity of crude oil is greater than 0.9, the Ea value is taken as 50 - 70 kJ / mol, and when the specific gravity range of crude oil is 0.8 - 0.9, the Ea value is taken as 40 - 60 kJ / mol.

6. The method for predicting the microbial corrosion rate of a carbon steel subsea pipeline according to claim 2, wherein: The value-taking rules of the temperature influence factor f1 are as follows: Temperature < -15°C, the value is 0; -15°C ≤ Temperature < 15°C, the value range is 0.1 - 2; 15°C ≤ temperature < 50°C, value range 1 - 5; 50°C ≤ temperature < 80°C, value range 0.1 - 3; 80°C ≤ temperature < 100°C, value range 0.1 - 2; temperature ≥ 100°C, value is 0; and / or, for the partial pressure influencing factor f2, the value rule is as follows: P CO2 ≥ 2 MPa, with a value range of 0.01 - 4; P CO2 / P H2S ≥20, with a value range of 0.1 - 3; P CO2 / P H2S <20, with a value range of 0.1 - 3; When there is no partial pressure of CO2 and H2S in the fluid, the value is 1; P CO2 represents the partial pressure of CO2, P H2S represents the partial pressure of H2S; and / or, for the pH influencing factor f3, the value rule is as follows: pH < 2, value is 0; 2 ≤ pH < 5, value range 0.1 - 2; 5 ≤ pH < 9, value range 0.5 - 5; 9 ≤ pH < 14, value range 0.1 - 2; pH > 14, value is 0; and / or, for the sulfate radical influencing factor f4, the value rule is as follows: SO4 2- ≤20 mg / L, with a value range of 0.01 - 1; 20 mg / L < SO4 2- ≤ 50 mg / L, with a value range of 0.1 - 4; 50mg / L < SO4 2- ≤ 150mg / L, with a value range of 0.1 - 5; SO4 2- > 150 mg / L, with a value range of 0.1 - 6; SO4 2- represents the sulfate ion concentration; and / or, for the flow rate influencing factor f5, the value rule is as follows: flow rate ≤ 0.1 m / s, value range 0.1 - 8; 0.1 m / s < flow rate ≤ 1 m / s, value range 0.1 - 6; 1 m / s < flow rate ≤ 2 m / s, value range 0.1 - 5; 2 m / s < flow rate ≤ 3 m / s, value range 0.01 - 3; flow rate > 3 m / s, value range 0.01 - 3; and / or, for the inorganic deposit influencing factor f6, the value rule is as follows: There are obvious deposits in the pigging material, and SRB > 25 cells / mL in the deposits, value range 1 - 10; There are obvious deposits in the pigging material, and SRB ≤ 25 cells / mL in the deposits, value range 0.1 - 9; There are no obvious deposits in the pigging material, and SRB > 25 cells / mL in the water, value range 0.1 - 7; There are no obvious deposits in the pigging material, and SRB ≤ 25 cells / mL in the water, value range 0.1 - 5; SRB refers to the content of sulfate-reducing bacteria; Pigging cannot be carried out, and the deposit state cannot be determined, value range 1 - 10; Pigging cannot be carried out, but it can be determined that there are no deposits, value range 0.1 - 5; and / or, for the organic deposit influencing factor f7, the value rule is as follows: There are organic deposits, value range 1 - 8; There are no organic deposits, value range 0.1 - 5; and / or, for the bactericide influencing factor f8, the value rule is as follows: No bactericide is added, value range 1 - 5; Bactericide is added, and occasionally SRB > 25 cells / mL, value range 0.5 - 4; Bactericide is added, and SRB ≤ 25 cells / mL, value range 0.1 - 4; Bactericide is added, and SRB ≤ 10 cells / mL, value range 0.1 - 3; and / or, for the pigging influencing factor f9, the value rule is as follows: The interference amount of the pigging ball can ensure the removal of the defective surface in the pipeline, and SRB ≤ 25 cells / mL, value range 0.1 - 2; The interference amount of the pigging ball can ensure the removal of the defective surface in the pipeline, and SRB > 25 cells / mL, value range 0.1 - 4; The interference amount of the pigging ball cannot ensure the removal of the defective surface in the pipeline, and SRB ≤ 25 cells / mL before pigging, value range 1 - 8; The interference amount of the pigging ball cannot ensure the removal of the defective surface in the pipeline, and SRB > 25 cells / mL before pigging, value range 4 - 12; No pigging is carried out, value range 4 - 20; and / or, for the growth period influencing factor f10, the value rule is as follows: Induction period, with a value range of 0.1 - 5; Growth period, with a value range of 0.5 - 6; Death period, with a value range of 0.1 - 5; When the growth period cannot be confirmed, the value of the growth period is used; And / or, the other influencing factor f11 includes, but is not limited to, the content of nutrients, the number of other types of bacteria, and the bacterial reproduction time; And / or, the total product index m of the key influencing factors has the following value-taking rules: Induction period, with a value range of 0 - 1; Growth period, with a value range of 0 - 2; Death period, with a value range of 0 - 1; And / or, the total product index n of the general influencing factors has the following value-taking rules: Induction period, with a value range of 0.1 - 0.8; Growth period, with a value range of 0.1 - 2; Death period, with a value range of 0.1 - 0.

8.

7. The method for predicting the microbial corrosion rate of carbon steel submarine pipelines according to claim 1, characterized in that, The electrochemical corrosion rate constant C has the following value-taking rules: When the temperature ≤ 60°C, the value range is 0.01 - 1 mm / y; When 60°C < temperature ≤ 85°C, the value range is 0.01 - 0.09 mm / y; When the temperature > 85°C, the value range is 0.01 - 0.08 mm / y.

8. The method for predicting the microbial corrosion rate of carbon steel submarine pipelines according to claim 1, characterized in that: The time t1 of the first growth stage, with a value range of 3 - 7 d; The time t2 of the second growth stage, with a value range of 5 - 10 d; The time t3 of the third growth stage, with a value range of 3 - 7 d.

9. The method for predicting the microbial corrosion rate of carbon steel submarine pipelines according to claim 1, characterized in that: The application range of the method is for microorganisms that can produce H2S, CO2, and / or slime to promote the occurrence of microbial corrosion.

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