CN112069688A - Method for simulating and analyzing corrosion in natural gas long-distance pipeline - Google Patents
Method for simulating and analyzing corrosion in natural gas long-distance pipeline Download PDFInfo
- Publication number
- CN112069688A CN112069688A CN202010942642.9A CN202010942642A CN112069688A CN 112069688 A CN112069688 A CN 112069688A CN 202010942642 A CN202010942642 A CN 202010942642A CN 112069688 A CN112069688 A CN 112069688A
- Authority
- CN
- China
- Prior art keywords
- pipeline
- corrosion
- natural gas
- gas long
- distance
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 title claims abstract description 90
- 230000007797 corrosion Effects 0.000 title claims abstract description 74
- 238000005260 corrosion Methods 0.000 title claims abstract description 74
- 239000003345 natural gas Substances 0.000 title claims abstract description 45
- 238000000034 method Methods 0.000 title claims abstract description 19
- 238000004088 simulation Methods 0.000 claims abstract description 11
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 10
- 238000004458 analytical method Methods 0.000 claims abstract description 5
- 239000007788 liquid Substances 0.000 claims description 8
- 230000001133 acceleration Effects 0.000 claims description 6
- 239000007789 gas Substances 0.000 claims description 6
- 239000012533 medium component Substances 0.000 claims description 5
- 230000004913 activation Effects 0.000 claims description 4
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 4
- 238000013461 design Methods 0.000 claims description 4
- 230000007246 mechanism Effects 0.000 claims description 4
- 239000001301 oxygen Substances 0.000 claims description 4
- 229910052760 oxygen Inorganic materials 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 2
- 230000000694 effects Effects 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000001681 protective effect Effects 0.000 description 2
- 230000032683 aging Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000005536 corrosion prevention Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000004880 explosion Methods 0.000 description 1
- RAQDACVRFCEPDA-UHFFFAOYSA-L ferrous carbonate Chemical compound [Fe+2].[O-]C([O-])=O RAQDACVRFCEPDA-UHFFFAOYSA-L 0.000 description 1
- 239000012530 fluid Substances 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000003112 inhibitor Substances 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000002035 prolonged effect Effects 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 239000003381 stabilizer Substances 0.000 description 1
- 230000035882 stress Effects 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/28—Design optimisation, verification or simulation using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/10—Numerical modelling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/14—Pipes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Computer Hardware Design (AREA)
- General Engineering & Computer Science (AREA)
- Geometry (AREA)
- Evolutionary Computation (AREA)
- Fluid Mechanics (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Physics (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- Computing Systems (AREA)
- Algebra (AREA)
- Testing Resistance To Weather, Investigating Materials By Mechanical Methods (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to a method for simulating and analyzing the internal corrosion of a natural gas long-distance pipeline, which comprises the following steps: the method comprises the steps of intelligently collecting basic data of a pipeline, constructing a combined model BBM to calculate multiphase flow parameters of the pipeline along the way, developing a simulation experiment of corrosion environment in the pipeline, analyzing influence factors formed by corrosion in the pipeline, determining main control factors of pipeline corrosion by using an Apriori correlation algorithm, establishing a semi-theoretical semi-empirical corrosion prediction model formula of the natural gas long-distance pipeline, forming a simulation analysis method of corrosion in the natural gas long-distance pipeline, truly reflecting the flow state in the pipeline, predicting the corrosion condition of the pipeline and providing technical support for safe operation of the natural gas long-distance pipeline.
Description
Technical Field
The invention relates to the field of natural gas long-distance pipelines, in particular to a method for simulating and analyzing corrosion in a natural gas long-distance pipeline.
Background
With the rapid development of economy in China, natural gas is used as a novel clean energy source and has a good application market, the large-area popularization and use of the natural gas can gradually improve the environmental quality, and long-distance natural gas pipelines are listed as national key construction projects in China. The natural gas long-distance pipeline is buried underground or laid overhead all the year round, is greatly influenced by the environment and climate in the process along the line, and is easy to corrode. Internal corrosion is also one of the important factors of pipeline aging, the internal corrosion can cause the structural strength of the pipeline to be reduced, leakage is caused, accidents caused by the internal corrosion often have the burstiness and the concealment, and the consequences are generally serious. Corroded natural gas pipelines not only cause gas leakage loss and waste of manpower, material resources and financial resources due to pipeline repair and maintenance, but also may cause fire due to pipeline corrosion. Especially, the explosion of the natural gas pipeline caused by corrosion threatens the personal safety and pollutes the environment, and the consequence is extremely serious. Therefore, the related work of corrosion prevention of the natural gas long-distance pipeline is needed, the natural gas transportation pipeline is prevented from being corroded as much as possible, and the service life of the natural gas long-distance pipeline is prolonged.
In the related art, the medium is transported from the pipeline (CO)2And O2) The reason influencing the corrosion of the natural gas long-distance pipeline is analyzed, and protective measures suitable for the natural gas long-distance pipeline are provided from the direction of a corrosive medium. However, the effects on corrosion of long-distance pipelines for natural gas are not only due to corrosive media, but also flow effects, such as protective corrosion product films (iron carbonate), pH stabilizers and corrosion inhibitors, which may be unstable due to shear stresses caused by high flow rates of the fluid, are flushed away from the pipe walls. Meanwhile, the impact force of liquid drops and solid particles is also the main reason of flow-induced corrosion, and the corrosion of the pipeline is influenced by various reasonsThe result of the interaction of elements is necessary for data analysis under the interaction of various factors, but an effective technical method is lacked for determining the main factor of the various factors. In addition, the corrosion rate prediction model of the natural gas long-distance pipeline only considers from the aspect of medium components, so that the prediction accuracy is poor.
The method comprises the steps of intelligently collecting basic data of a pipeline aiming at accurately knowing the internal state of the natural gas long-distance pipeline, constructing a combined model BBM to calculate multiphase flow parameters of the pipeline, developing a simulation experiment of the corrosion environment in the pipeline, analyzing influence factors of corrosion formation in the pipeline, and determining main control factors of pipeline corrosion by using an Apriori correlation algorithm, thereby establishing a semi-theoretical semi-empirical corrosion prediction model formula of the natural gas long-distance pipeline.
Disclosure of Invention
The invention aims to solve the defects in the technology and designs a method for simulating and analyzing corrosion in a natural gas long-distance pipeline.
The invention provides a method for simulating and analyzing corrosion in a natural gas long-distance pipeline, which comprises the following steps: 1) collecting basic data aiming at a target natural gas long-distance pipeline; 2) dividing flow patterns, calculating liquid holdup, friction resistance pressure drop, elevation pressure drop, acceleration pressure drop and the like to form a corresponding combined model, and accurately calculating the multiphase flow parameters of the natural gas long-distance pipeline along the way; 3) carrying out a pipeline internal corrosion environment simulation experiment, and determining main control factors influencing internal corrosion by adopting an Apriori association algorithm; 4) and establishing a semi-theoretical semi-empirical model of the corrosion rate in the pipeline by combining the analysis result of the main control factor.
Specific embodiments are as follows:
taking design data of the natural gas long-distance pipeline, data collected by temperature and pressure sensors and data obtained by a flowmeter as basic data;
calculating friction resistance pressure drop, elevation pressure drop and acceleration pressure drop by adopting Beggs-Brill, dividing flow patterns by using Mukherjee-Brill to form a combined model BBM, and calculating multiphase flow parameters of the pipeline along the way.
Combining the results of the pipeline internal corrosion simulation experiment, establishing a correlation rule of the local corrosion rate, medium components and flow parameters by adopting an Apriori algorithm, wherein the rule meets the requirements that the minimum support degree of a formula (1) is 50% and the minimum confidence coefficient of a formula (2) is 50%, and determining the main control factors of the pipeline internal corrosion;
let I ═ I1, I2, I3, I4 be the set of all items in D, any subset X of I is called the set of items in D, X, Y are all sets of items,
then is implied by
And expressing an association rule, wherein X is an association precondition, and Y is a result of the association rule.
Determining a semi-theoretical semi-empirical corrosion prediction model formula (3) of the natural gas long-distance pipeline by combining a corrosion mechanism of a main control factor:
wherein r iscorrIs the corrosion rate, mm/a; r is a gas constant, T is an absolute temperature, K; eaJ/mol, which is the activation energy of the corrosion reaction; v is the liquid velocity, m/s;
wppm as oxygen concentration;
is CO2Partial pressure, MPa; a. b, c, d, e are all constants.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is a flow chart of a method for simulating and analyzing corrosion in a long-distance natural gas pipeline according to an embodiment of the present invention;
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the following embodiments and accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
The embodiment of the invention provides a method for simulating and analyzing corrosion in a natural gas long-distance pipeline, which comprises the following steps of:
102, calculating friction resistance pressure drop, elevation pressure drop and acceleration pressure drop by adopting Beggs-Brill, dividing flow patterns by using Mukherjee-Brill to form a combined model BBM, and calculating multiphase flow parameters of the pipeline along the way.
103, establishing a correlation rule of a local corrosion rate, a medium component and a flow parameter by using an Apriori algorithm in combination with a simulation experiment result of corrosion in the pipeline, wherein the rule meets the requirements that the minimum support degree of a formula (1) is 50% and the minimum confidence coefficient of the formula (2) is 50%, and determining a main control factor of the corrosion in the pipeline;
let I be the set of all items in D, { I1, I2, I3, I4}, any subset X of I being the set of items in D, X,Y is a set of terms that are both,
then is implied by
And expressing an association rule, wherein X is an association precondition, and Y is a result of the association rule.
104, determining a semi-theoretical semi-empirical corrosion prediction model formula (3) of the natural gas long-distance pipeline by combining a corrosion mechanism of a main control factor:
wherein r iscorrIs the corrosion rate, mm/a; r is a gas constant, T is an absolute temperature, K; eaJ/mol, which is the activation energy of the corrosion reaction; v is the liquid velocity, m/s;
wppm as oxygen concentration;
is CO2Partial pressure, MPa; a. b, c, d, e are all constants.
According to the method for simulating and analyzing the corrosion in the natural gas long-distance pipeline, provided by the embodiment of the invention, basic data of a target natural gas long-distance pipeline are collected; dividing flow patterns, calculating liquid holdup, friction resistance pressure drop, elevation pressure drop, acceleration pressure drop and the like to form a corresponding combined model, and accurately calculating the multiphase flow parameters of the natural gas long-distance pipeline along the way; carrying out a pipeline internal corrosion environment simulation experiment, and determining main control factors influencing internal corrosion by adopting an Apriori association algorithm; and establishing a semi-theoretical semi-empirical model of the corrosion rate in the pipeline by combining the analysis result of the main control factor. In the method, multiphase flow parameters are selected, an internal corrosion environment simulation experiment is combined, Apriori correlation algorithm sensitive factors are adopted to determine main control factors influencing internal corrosion, a semi-theoretical semi-empirical model of the internal corrosion rate of the pipeline is established, the flow state inside the pipeline can be truly reflected, the corrosion condition of the pipeline can be predicted, and a technical support is provided for safe operation of the natural gas long-distance pipeline.
The method for simulating and analyzing the corrosion in the natural gas long-distance pipeline provided by the embodiment of the invention is described in detail as follows:
the pipeline basic data involved in step 101 includes: routing data, gas composition Content (CO)2、O2Etc.), operational data (temperature, pressure, flow), inspection/monitoring data, etc.
102, calculating friction resistance pressure drop, elevation pressure drop and acceleration pressure drop by adopting Beggs-Brill, dividing flow patterns by using Mukherjee-Brill to form a combined model BBM, realizing the calculation of multiphase flow parameters of the natural gas long-distance pipeline along the way, and providing a data basis for a corrosion prediction model.
103, establishing a correlation rule of a local corrosion rate, a medium component and a flow parameter by using an Apriori algorithm in combination with a simulation experiment result of corrosion in the pipeline, wherein the rule meets the requirements that the minimum support degree of a formula (1) is 50% and the minimum confidence coefficient of the formula (2) is 50%, and determining a main control factor of the corrosion in the pipeline;
let I ═ I1, I2, I3, I4 be the set of all items in D, any subset X of I is called the set of items in D, X, Y are all sets of items,
then is implied by
And expressing an association rule, wherein X is an association precondition, and Y is a result of the association rule.
104, determining a semi-theoretical semi-empirical corrosion prediction model formula (3) of the natural gas long-distance pipeline by combining a corrosion mechanism of a main control factor:
wherein r iscorrIs the corrosion rate, mm/a; r is a gas constant, T is an absolute temperature, K; eaJ/mol, which is the activation energy of the corrosion reaction; v is the liquid velocity, m/s;
wppm as oxygen concentration;
is CO2Partial pressure, MPa; a. b, c, d, e are all constants.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes may be made to the embodiment of the present invention by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (5)
1. A corrosion simulation analysis method in a natural gas long-distance pipeline is characterized by comprising the following steps:
collecting basic data aiming at a target natural gas long-distance pipeline;
dividing flow patterns, calculating liquid holdup, friction resistance pressure drop, elevation pressure drop, acceleration pressure drop and the like to form a corresponding combined model, and accurately calculating the multiphase flow parameters of the natural gas long-distance pipeline along the way;
carrying out a pipeline internal corrosion environment simulation experiment, and determining main control factors influencing internal corrosion by adopting an Apriori association algorithm;
and establishing a semi-theoretical semi-empirical model of the corrosion rate in the pipeline by combining the analysis result of the main control factor.
2. The method of claim 1, wherein the data is based on design data of the long-distance natural gas pipeline, data collected by temperature and pressure sensors, and data obtained by a flow meter.
3. The method according to claim 1, wherein the friction pressure drop, the elevation pressure drop and the accelerated pressure drop are calculated by adopting Beggs-Brill, and a Mukherjee-Brill flow pattern is used for dividing the flow pattern to form a combined model BBM, so that the multiphase flow parameter calculation along the pipeline is carried out.
4. The method according to claim 1, characterized in that Apriori algorithm is adopted to establish a correlation rule of local corrosion rate, medium components and flow parameters, the rule meets the requirements that the minimum support degree of formula (1) is 50% and the minimum confidence degree of formula (2) is 50%, and main control factors of corrosion in the pipeline are determined;
let I ═ I1, I2, I3, I4 be the set of all items in D, any subset X of I is called the set of items in D, X, Y are all sets of items,
then is implied by
And expressing an association rule, wherein X is an association precondition, and Y is a result of the association rule.
5. The method of claim 1, wherein a semi-theoretical semi-empirical corrosion prediction model formula (3) of the natural gas long-distance pipeline is determined by combining the corrosion mechanism of the main control factor:
wherein r iscorrIs the corrosion rate, mm/a; r is a gas constant, T is an absolute temperature, K; eaJ/mol, which is the activation energy of the corrosion reaction; v is the liquid velocity, m/s;
wppm as oxygen concentration;
is CO2Partial pressure, MPa; a. b, c, d, e are all constants.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010942642.9A CN112069688A (en) | 2020-09-09 | 2020-09-09 | Method for simulating and analyzing corrosion in natural gas long-distance pipeline |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010942642.9A CN112069688A (en) | 2020-09-09 | 2020-09-09 | Method for simulating and analyzing corrosion in natural gas long-distance pipeline |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112069688A true CN112069688A (en) | 2020-12-11 |
Family
ID=73663260
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010942642.9A Pending CN112069688A (en) | 2020-09-09 | 2020-09-09 | Method for simulating and analyzing corrosion in natural gas long-distance pipeline |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112069688A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113063725A (en) * | 2021-03-25 | 2021-07-02 | 西南石油大学 | Method for quickly identifying corrosion main control factors in pipeline |
| CN113095008A (en) * | 2021-04-08 | 2021-07-09 | 中国石油天然气股份有限公司 | Corrosion position determination method, device and medium based on flow field analysis in total station |
| CN114492232A (en) * | 2022-01-08 | 2022-05-13 | 西南石油大学 | Method for analyzing corrosion sensitive factors in submarine pipeline |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101684727A (en) * | 2008-09-28 | 2010-03-31 | 中国石油化工股份有限公司 | Optimization method for determining proportion of mixing light oil into heavy oil of ultra-deep well and light hydrocarbon mixer thereof |
| US20130175030A1 (en) * | 2012-01-10 | 2013-07-11 | Adunola Ige | Submersible Pump Control |
| US20140081606A1 (en) * | 2012-09-17 | 2014-03-20 | Mohammed Omer | System and method for modeling corrosion-based multiphase flow friction in pipes |
| US20150199544A1 (en) * | 2014-01-16 | 2015-07-16 | King Fahd University Of Petroleum And Minerals | Modified beggs & brill multiphase flow correlation with fuzzy logic flow regime prediction |
| CN104895560A (en) * | 2015-06-16 | 2015-09-09 | 中国海洋石油总公司 | Method for predicting wellbore pressure and temperature field simulation as well as hydrate through deep-water test |
| CN107590516A (en) * | 2017-09-16 | 2018-01-16 | 电子科技大学 | Gas pipeline leak detection recognition methods based on Fibre Optical Sensor data mining |
| CN108119761A (en) * | 2017-12-14 | 2018-06-05 | 中国石油天然气股份有限公司 | A kind of gas-liquid two-phase flows down natural gas line extent of corrosion Forecasting Methodology |
| CN109162697A (en) * | 2018-10-13 | 2019-01-08 | 中石化石油工程技术服务有限公司 | A kind of natural gas well oil jacket annulus flowing Dynamic profiling method |
| CN110807540A (en) * | 2018-08-06 | 2020-02-18 | 中国石油天然气股份有限公司 | Method for predicting corrosion rate in natural gas pipeline |
| CN110866331A (en) * | 2019-10-28 | 2020-03-06 | 国网河北省电力有限公司电力科学研究院 | Evaluation method for quality defects of power transformer family |
| US20200182831A1 (en) * | 2018-12-05 | 2020-06-11 | Halliburton Energy Services, Inc. | Detecting and quantifying liquid pools in hydrocarbon fluid pipelines |
| US20200190950A1 (en) * | 2018-12-10 | 2020-06-18 | Schlumberger Technology Corporation | Methods and systems for reservoir and wellbore simulation |
| CN113343498A (en) * | 2021-07-05 | 2021-09-03 | 西南石油大学 | Containing H2S/CO2Method for calculating corrosion rate of environmental pipeline steel |
-
2020
- 2020-09-09 CN CN202010942642.9A patent/CN112069688A/en active Pending
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101684727A (en) * | 2008-09-28 | 2010-03-31 | 中国石油化工股份有限公司 | Optimization method for determining proportion of mixing light oil into heavy oil of ultra-deep well and light hydrocarbon mixer thereof |
| US20130175030A1 (en) * | 2012-01-10 | 2013-07-11 | Adunola Ige | Submersible Pump Control |
| US20140081606A1 (en) * | 2012-09-17 | 2014-03-20 | Mohammed Omer | System and method for modeling corrosion-based multiphase flow friction in pipes |
| US20150199544A1 (en) * | 2014-01-16 | 2015-07-16 | King Fahd University Of Petroleum And Minerals | Modified beggs & brill multiphase flow correlation with fuzzy logic flow regime prediction |
| CN104895560A (en) * | 2015-06-16 | 2015-09-09 | 中国海洋石油总公司 | Method for predicting wellbore pressure and temperature field simulation as well as hydrate through deep-water test |
| CN107590516A (en) * | 2017-09-16 | 2018-01-16 | 电子科技大学 | Gas pipeline leak detection recognition methods based on Fibre Optical Sensor data mining |
| CN108119761A (en) * | 2017-12-14 | 2018-06-05 | 中国石油天然气股份有限公司 | A kind of gas-liquid two-phase flows down natural gas line extent of corrosion Forecasting Methodology |
| CN110807540A (en) * | 2018-08-06 | 2020-02-18 | 中国石油天然气股份有限公司 | Method for predicting corrosion rate in natural gas pipeline |
| CN109162697A (en) * | 2018-10-13 | 2019-01-08 | 中石化石油工程技术服务有限公司 | A kind of natural gas well oil jacket annulus flowing Dynamic profiling method |
| US20200182831A1 (en) * | 2018-12-05 | 2020-06-11 | Halliburton Energy Services, Inc. | Detecting and quantifying liquid pools in hydrocarbon fluid pipelines |
| US20200190950A1 (en) * | 2018-12-10 | 2020-06-18 | Schlumberger Technology Corporation | Methods and systems for reservoir and wellbore simulation |
| CN110866331A (en) * | 2019-10-28 | 2020-03-06 | 国网河北省电力有限公司电力科学研究院 | Evaluation method for quality defects of power transformer family |
| CN113343498A (en) * | 2021-07-05 | 2021-09-03 | 西南石油大学 | Containing H2S/CO2Method for calculating corrosion rate of environmental pipeline steel |
Non-Patent Citations (5)
| Title |
|---|
| 张新建 等: "基于管道完整性数据的关联规则挖掘与应用", 油气储运, vol. 35, no. 05, pages 471 - 474 * |
| 张楠: "含CO2天然气管线内腐蚀直接评价方法的应用研究", 中国优秀硕士学位论文全文数据库, no. 2018, pages 019 - 1038 * |
| 阎红巧 等: "大数据下的油气管道腐蚀预警策略", 化工机械, vol. 47, no. 03, pages 295 - 298 * |
| 韩炜: "管道气液两相流动技术研究", 中国优秀博硕士学位论文全文数据库 (博士), no. 2006, pages 015 - 5 * |
| 马玉鹏: "混输海管内检测及评估技术研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅰ辑》, no. 2016, 15 July 2016 (2016-07-15), pages 019 - 509 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113063725A (en) * | 2021-03-25 | 2021-07-02 | 西南石油大学 | Method for quickly identifying corrosion main control factors in pipeline |
| CN113095008A (en) * | 2021-04-08 | 2021-07-09 | 中国石油天然气股份有限公司 | Corrosion position determination method, device and medium based on flow field analysis in total station |
| CN114492232A (en) * | 2022-01-08 | 2022-05-13 | 西南石油大学 | Method for analyzing corrosion sensitive factors in submarine pipeline |
| CN114492232B (en) * | 2022-01-08 | 2024-04-05 | 西南石油大学 | Submarine pipeline corrosion sensitive factor analysis method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112069688A (en) | Method for simulating and analyzing corrosion in natural gas long-distance pipeline | |
| Nyborg | CO2 corrosion models for oil and gas production systems | |
| Wang et al. | Development of erosion equation and numerical simulation methods with the consideration of applied stress | |
| CN110020399B (en) | Method for determining corrosion evaluation position in pipeline | |
| Zelmati et al. | A probabilistic approach to estimate the remaining life and reliability of corroded pipelines | |
| Gunaltun et al. | Progress In The Prediction Of Top Of The Line Corrosion And Challenges To Predict Orrosion Rates Measured In Gas Pipelines | |
| Witek et al. | Influence of gas transmission network failure on security of supply | |
| Barker et al. | Flow-induced corrosion and erosion-corrosion assessment of carbon steel pipework in oil and gas production | |
| Obaseki et al. | Diagnostic and prognostic development of a mechanistic model for multiphase flow in oil-gas pipelines | |
| Gartland et al. | A pipeline integrity management strategy based on multiphase fluid flow & corrosion modelling | |
| Obaseki | Diagnostic and prognostic analysis of oil and gas pipeline with allowable corrosion rate in Niger Delta Area, Nigeria | |
| Okoro et al. | Flow line corrosion failure as a function of operating temperature and CO2 partial pressure using real time field data | |
| Tiggor et al. | Risk Management of Carbon Steel Piping in Sweet Environment Multiphase Fluid Production | |
| Mnasri et al. | Data-driven modeling of carbon dioxide corrosion for integrity management application | |
| Guan et al. | Application of probabilistic model in pipeline direct assessment | |
| Chandra et al. | CFD-based flow-induced corrosion modeling | |
| Ghalib | Impact of presence of CO2 in natural gas streams | |
| Obaseki | Artificial neural network simulation model for predicting oil and gas pipeline corrosion rate in Nigerian Niger Delta | |
| Shirazi et al. | Integrity Management of offshore Process Piping and Equipment with Sand Production–Part I: The Pinhole Incident | |
| Gabetta et al. | Corrosion and flow models predictions compared using case histories | |
| Obaseki et al. | Application of Artificial Neural Network Model to Predict Corrosion Rates on Pipeline | |
| Jaragh et al. | Successful Application of MP-ICDA to Assess and Forecast Crude Oil Pipelines in Kuwait Using ILI | |
| Obaseki et al. | Corrosion Rate Prediction in Oil and Gas Pipelines Based on Multiphase Flow Modelling | |
| Edwards et al. | Reliability based design of CO2 corrosion control | |
| Wind et al. | North Sea Energy Technical assessment of Hydrogen transport, compression, processing offshore |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20230406 Address after: 100000 22 Chaoyangmen North Street, Chaoyang District, Beijing. Applicant after: CHINA PETROLEUM & CHEMICAL Corp. Applicant after: SHANDONG NATURAL GAS PIPELINE Co.,Ltd. Address before: No. 77 Tianchen Road, Lixia District, Jinan City, Shandong Province, 250000 Applicant before: SHANDONG NATURAL GAS PIPELINE Co.,Ltd. |