prospect and latest development of pipeline integrity …€¦ · and risk control, (2) to study...

Prospect and Latest Developmentof Pipeline Integrity Managementin China

Shaohua Dong, Yinuo Chen and Zongqi Liu

Abstract China’s pipeline industry has established a relatively complete technicalsystem of pipeline integrity to solve the major security problems of detections anddiagnosis of oil and gas pipeline, which effectively protect the intrinsic safety ofpipeline. However, in recent two years, with the development of new materials, bigdata, cloud computing and other technology, the pipeline whose steel grade isabove X80 has been developed successfully, and hydrogen-containing gas pipelinehas been put into use. However, there are new technical problems in pipelineindustry to be solved, and therefore it is necessary: (1) to gradually establish a bigdata management architecture model suitable for the pipeline system to study thefusion processing of big data, efficient algorithm and modeling technology, andprovide big data decision support for pipeline energy control, disaster managementand risk control, (2) to study the failure behavior of hydrogen-induced cracking ofpipeline whose steel grade is above X80, find out its failure mechanism, analyze thedifference of failure behavior between pipeline whose steel grade is above X80 andpipeline whose steel grade is lower, and finally form a set of integrity evaluationmethod of pipeline whose steel grade is above X80 in hydrogen-containing envi-ronment, (3) to study the reflection of the signal law of electromagnetic controlarray and piezoelectric ultrasound when they detect cracks and defects, in order todevelop defect reflection signal data processing system, and finally develop thecrack detection equipment of pipeline whose steel grade is above X80. In this paperthe prospect and latest development of pipeline integrity management in China isreviewed.

Keywords Integrity management � Big data � Hydrogen induced crackingCrack detection

S. Dong � Y. Chen (&) � Z. LiuPipeline Technology and Safety Research Center at China,University of Petroleum-Beijing, Beijing 102249, Chinae-mail: [email protected]

© Springer Nature Singapore Pte Ltd. 2018Y. Han (ed.), Advances in Materials Processing, Lecture Notes in MechanicalEngineering, https://doi.org/10.1007/978-981-13-0107-0_111

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Introduction

Pipeline integrity management and control technology originated in the 1970s,when a large number of long distance oil and gas pipeline built by Europe and theUnited States and other industrial developed countries after World War II hasentered the old age, frequent accidents resulted in huge economic losses andcasualties, greatly reduced the profitability of the pipeline company, and alsoseriously affected and restricted the normal production of upstream oil (gas) field.

The United States firstly began to draw lessons from the risk analysis techniquesin economics and other industrial sectors to evaluate the risk of oil and gaspipelines, in order to minimize the incidence of oil and gas pipelines, to extend theservice life of the major trunk pipelines as much as possible, and allocate limitedpipeline maintenance costs reasonably. After several decades of development andapplication, many countries have gradually established a pipeline safety assessmentand integrity management system and a variety of effective evaluation methods.

Development Overview of Pipeline Integrity Management

Foreign Research Progress

In 1968, the United States enacted the first legislation on pipeline safety named theNatural Gas Pipeline Safety Act, which issued The Pipeline Safety ImprovementAct (PSIA) in 2002, and in Chap. 14 of PSIA, it is expressly required that thepipeline operator to implement the pipeline integrity management plan in the HighConsequence Area (HCA). Based on the PSIA Act, the US Department ofTransportation has issued recommended rules for the safety management of gaspipelines and dangerous liquid pipelines in CFR49 Part 192 and CFR49 Part 195. In2006, the United States promulgated [1] “Pipeline Inspection, Protection,Enforcement and Safety Act”, which provided legal protection for pipeline integritymanagement and corrosion control. On February 3, 2011, the US Senate to theSenate Business Committee submitted the motion named “Pipeline SafetyImprovement Law of 2011”, and was approved. In 2012, Obama signed the“Pipeline Transport Safety Improvement Act.”

In Canada, [2] The National Bureau of Energy (NEB) has developed landlineregulations for Canadian provinces, which explicitly require “each company shoulddevelop a pipeline integrity management procedure”. The Canadian StandardsAssociation (CSA) has developed a pipeline standard CSZ662-2003, “Design,Construction, Operation and Maintenance of the Oil and Gas Pipeline System”,which clearly states that the operating company should develop and implement apipeline integrity management procedure.

At present, pipeline companies of The United States, Europe, Canada, Mexicoand other pipeline industry developed countries have implemented an integrated

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management strategy for oil and gas pipelines, which has achieved significanteconomic benefits and improved the intrinsic safety of pipeline system.

Domestic Research Progress

In China, Shanxi-Beijing natural gas pipeline developed a system document in2001, which put the Shanxi-Beijing pipeline integrity management proceduresdocuments and operating documents into the HSE system. In 2002–2003,Advantica company of the United Kingdom modified the oil pipeline detector fornatural gas pipeline of China Petroleum Pipeline Bureau, and completed the internaldetection of 1000 km high pressure and large diameter natural gas pipeline ofShanxi-Beijing line for the first time.

In March 2004, at the China Petroleum Pipeline Management and TechnologyExchange Conference, Yao Wei published technical exchange papers named“Promote the integrity of management, ensure the safety of the pipeline,” whichattracted the attention of many participants. The same year in July, the projectnamed “Shanxi-Beijing pipeline integrity management model and applicationresearch” won the first prize of State Administration of Work Safety ProductionScience and Technology Achievement Award. In 2005, “Shanxi and Beijingpipeline integrity technology and application” won the first prize in scientific andtechnological progress of PetroChina Gas Company; the same year, PII’shigh-definition detection technology was introduced, and the first application on thegas storage pipeline line GangQing line 711 mm was successful, the British waveof ultrasonic wave detection technology was also introduced and it was promoted inthe country. In the same year, China Petroleum Science and Technology Center alsobegan to carry out integrity management research. In September 2006, at theInternational Conference on IPC Pipeline in Canada, the theme report of “BestPractice of Shanxi-Beijing Pipeline Integrity Management” was published. In 2007,TNO-RISCURVE, ANSYS, ABQUS and other pipe mechanics analysis methodwere introduced. In 2009, a pipeline safety and material testing laboratories wasestablished, and obtained CNAS certificate of National Certification andAccreditation Board. In 2015, the pipeline company’s entire life cycle of assetintegrity (risk) control manual was formed. And the China Petroleum PipelineCompany led GB32167-2015 Oil and Gas Pipeline Integrity ManagementRegulations issued, marking the integrity of the pipeline management to becomethe technical regulations that managers must follow.

Prospect and Latest Development of Pipeline Integrity … 1169

Advances in Pipeline Integrity Management

At present, the integrity management system has been established. The system wasformed of four aspects: the pipeline line integrity technology, station facilities integritytechnology, oil and gas reservoir security technology, integrity system platform tech-nology, and strived to full coverage [3]. At the same time, oil and gas pipelines integritymanagement practices have also been established. The specification is intended topromote the intrinsic safety of the pipeline industry. It specifies the contents, methodsand requirements of oil and gas pipeline integrity management, including data collec-tion and integration, high consequence area identification, risk assessment, integrityevaluation, risk reduction andmaintenance, and efficiency evaluation.The specificationapplies toGB50251 orGB50253 designed to transport onshore steel pipe of oil and gasmedium, but not applicable to the station process pipeline [4].

Pipeline integrity management technology has the following landmark progress.

Pipeline Integrity Assessment Theory System

The system of pipeline integrity evaluation theory system has been established,pipeline hydrogen induced cracking, weld, plane defects, volume defects, pipelinedamage assessment of different theoretical methods have also been established. Therelevant personnel has studied a variety of online and offline pipeline assessmenttechnology, putting forward the hydrogen induced cracking fracture criteria,establishing the H2S pipeline safety evaluation model and failure assessment map,and solving the problem of detachment of pipeline integrity evaluation theory andproduction [5]. The pipeline failure assessment method based on stress and straindouble criterion was established for the first time, the fractal expansion mechanismof hydrogen—induced cracking and brittle hardening of tubes was found, thefailure model and the assessment chart were reconstructed, the failure probabilitymodel of pipeline under uncertainty was established based on stress-intensityinterference theory. New theories and new methods have improved the accuracy ofthe assessment by 10% (Table 1).

Table 1 Comparison of old and new technology (pipeline integrity assessment)

Contrast project The original technology The project technology

Failure judgment Stress determinationcriteria

Stress, strain double judgment criterion

Pipe fracture criterion Fatigue fracture model Fatigue + environment fracture fractalfracture model

Failure probabilitymodel

Deterministic probabilitydistribution

Fracture distribution based onuncertainty probability

The accuracy of thedecision (%)

80 90

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The software package of V3.0 (Oil & Gas Pipeline Integrity Super AssessmentSystem V3.0) is established, which is suitable for the evaluation of the applicabilityof oil and gas pipeline structure. It has good interface and good calculation pre-cision. The software package includes 6 modules, API 579 software module,BS7910 module, pipeline hydrogen induced cracking and life predictionmodule, weld evaluation module, ASME/Restreng/DNV corrosion evaluationmodule, internal detection data alignment and evaluation module.

Pipeline Three-Axis High-Definition Magnetic LeakageDetection Device

China Petroleum has developed a series devices of Pipeline three-axis high-definition magnetic leakage detection, the sensor used XYZ three-dimensionaldistribution instead of the traditional uniaxial distribution, the new integrated curingcoupling sensor and all-digital three-dimensional magnetic flux leakage signalacquisition system was developed, a series of detectors (POI) was formed. Thedetection threshold (POI) increased by 10–90%, and the detection of the depth of thedefect threshold increased from 20% of the wall thickness to 5% of the wallthickness (international test indicators) [6] (Table 2).

Table 2 Comparison of old and new technology (leakage detection device)

Performance Types

The original technology Three-axishigh-definitiondetection technology

Standard definitiondetectiontechnology

High-resolutiondetectiontechnology

Minimum axialsampling distance

Analog record � 2 mm 2 mm

Minimum returndetection pitch (mm)

40–150 8–17 4–12

Can detect theminimum defect depth(wt%)

20 10 5

Depth dimensionmeasurement accuracy(wt%)

±15 ±10 ±5 – 10

Credibility level (%) 80 80 85

Detection resultconfirmation degreePOI (%)

85 85 95


Multi-channel High-Precision Deformation Detection Deviceand Pipeline Strain Monitoring System

A multi-channel high-precision deformation detection device and pipeline strainmonitoring system was invented, high-precision angular displacement sensor,anti-shake probe swing device and topology algorithm instead of the originalstraight displacement sensor and simulation algorithm was adopted, positioningaccuracy was improved. Vibrating wire high precision anti-jamming sensor wasused to monitor f high-risk pipeline strain accurately. The accuracy of the acqui-sition is ±10 microstrain [7], which realizes the automatic control and remotemaintenance of the pipeline strain data acquisition strategy (Table 3).

The pipeline geology disaster monitoring system was developed, the accelera-tion sensing technology was developed, the time domain algorithm model wasestablished, the tube large displacement continuous monitoring was firstly realized,and the pipeline monitoring network based on the Internet of Things was formed(Fig. 1).

Risk Assessment and Control of Pipeline Level Upgrade

According to the stress-intensity interference theory, the probability distributionmodel of pipeline stress and intensity is proposed, and the regional level isupgraded. The probability distribution law of pipeline stress and intensity is putforward based on the stress-intensity interference theory, and the semi-quantitativerisk assessment model and software of pipeline failure probability were established,and the corresponding index system and control measures were put forward(Table 4).

Based on the statistical data of population distribution in urban areas of China,the acceptable risk probability of domestic gas pipeline regional grading was putforward. Based on the theory of stress-intensity interference, a quantitative analysismethod of failure probability of regional upgrading pipeline was proposed.

Table 3 Comparison of old and new technology (pipeline strain monitoring system)

Contrast project Foreign originaltechnology

The project is highly accurate monitoringtechnology

Monitoringparameters

Strain, earth pressure Strain, temperature, displacement, earthpressure

Sensor type Strain gauge, barometer Strain gauges, barometer, accelerometer

Displacement range Indirect measurement0–0.5 m

Accelerometer direct measurement 0–10 m

Monitoringaccuracy (le)

±20 ±10

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The influence of uncertainty on pipeline failure probability was quantified, thequantitative evaluation of regional upgrading of gas pipeline was put forward, andthe risk control measures were put forward and evaluation software was developed(Fig. 2; Table 5).

Station Security Technology

Based on the support vector machine (SVM) model, acoustic emission theory andmodern sensing and signal processing technology, the dual-channel natural gaspipeline ball valve leakage detection device and method are developed, and theminimum detectable inner leakage flow reaches 0.04 m3/h in.; Compressor groupcombined neural network adaptive fault diagnosis method and hybrid fault earlywarning model were proposed to improve the compressor group fault diagnosisdiscovery rate of more than 15% [8]. Compressor vibration monitoring and

monitoring center server

monitoringsoftware of thehost computer

mobile communication

wireless transceiver module

frontier signal acquisition instrument

sensor

connector and agreement

Fig. 1 Schematic diagram of the principle of acceleration sensing technology

Table 4 Comparison of old and new technology (risk assessment)

Contrast project Domestic and foreignoriginal technology

This project

Target failure probability Not presented byregion level

According to the regional level, putforward quantitative indicators

Risk assessment modelof regional level change

No research The semi-quantitative model ofregional level risk assessment isproposed

The establishment ofindex system

No research The study gives the regional gradingindex system


diagnostic management platform was formed, and it can be real-time monitoring ofcompressor unit operation (Table 6).

Natural gas station ultrasonic guided wave detection database was created.Pipeline single ring, double ring and double station test and other detection tech-nology methods are optimized, the situation of the buried pipeline and the sectionthrough the wall was studied, high water level, high clay, the test of asphalt coatingline and other problems were solved.

The sound signal acquisition and processing system, which is suitable for thecharacteristics of natural gas pipeline, was developed. The corresponding signalanalysis and processing software was developed. The natural gas pipeline ball valveleakage detection system integrated modern sensing technology, signal processinganalysis technology was developed, and ball valve leakage detection problem wassolved.

The minimum single-valve detection time is <10 Min; the minimum detectableinternal leakage flow rate is: 0.04 m3/hr in. (or 0.66 L/Min in.); the minimumdetection flow meets the petroleum industry API-6D standard. The equipment isshown in Fig. 3.

Table 5 Research results of regional grade and population density failure probability

Regionallevel

Failure probabilityvalue

The project is highly accurate monitoringtechnology

1 10−3 75

2 10−4 500

3 10−5 1000

4 10−6 2000

strengthen distribution

decay curvestrength variation

unsafestress distribution

actu

al sa

fety

cap

acity

initi

al sa

fety

deg

ree

Fig. 2 Pipeline stress intensity distribution curve

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An implicit feature extraction technique that suppresses boundary oscillation,eliminates frequency aliasing and signal denoising is invented, that is, the earlyweak fault detection and diagnosis technology of large dynamic group, whichrealizes the extraction of weak features and the diagnosis of early faults (Fig. 4).

As shown in Figs. 5 and 6, the traditional method is characterized by no rubbingeffect, and the characteristic of the project method can be used to extract the rubbingcharacteristics.

Table 6 Comparison of old and new technology (station security technology)

Contrast project Foreign originaltechnology

The project is highly accuratemonitoring technology

Ball valve leakagedetection accuracy

Can’t be quantifiedand positioned

Can be quantitatively positioned, ±10,0.04 m3/h in.

Ball valve internalleakage data extractionmode

Audio Audio, wavelet transform, supportvector machine SVM

Compressor faultdiagnosis

Acceleration signalthreshold warning

Neural network adaptive identification,coupled hybrid fault early warning

Compressor failuredetection rate (%)

70 85

Fig. 3 Valves to be tested and testing equipment


Pipeline Corrosion Control

The mechanism of black dust composition analysis was established to analyze thechemical composition of corrosion products. The mechanism of H2S, CO2 andmicrobial corrosion was studied. A physical model was established to characterizethe corrosion rate of pipe wall with the change of iron element concentration.A fungicide for inhibiting the corrosion of microbial sulfur bacteria, iron bacteriaand sulfate-reducing bacteria in natural gas pipeline, simulating the migrationcharacteristics of black dust in the tube, and developing a jet pigtilizer with goodapplication effect. So that the amount of dust reduced by 90% [9]. The Ion chro-matograph and X-ray single crystal surface detector is shown in Fig. 7.

Fig. 5 Traditional methodfeature extraction effect map

Volterraprediction model

singular value decomposition

ULSPdecomposition

original vibration signal

inhibit boundary oscillation

eliminate frequency aliasing

erase noiseextract implied characteristics

Fig. 4 Large dynamic group early weak fault detection and diagnosis technology schematicdiagram

Fig. 6 Traditional methodfeature extraction effect mapin a certain project

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Gas Storage Security Technology

In the aspect of gas storage safety and security technology, the technical system ofgas storage integrity management system was established (Fig. 8), and the technicalsystem of risk assessment of underground gas storage of salt hole type and dry oiland gas reservoir was systematically studied. The risk assessment of the gas storageand the safety assessment of the injection wells, casing and cement rings wereformed, and the gas storage risk assessment software was developed and the cor-responding risk control measures were put forward.

Integrity Management Information Platform Technology

PetroChina developed the PIS system, established a pipeline data dictionary andbuilt a digital pipeline emergency decision support GIS system to achieve theemergency situation in the pipeline data timely recall and to meet the emergencycommand information query analysis needs. Output of one-button emergencymanagement plan document can achieve the transformation and association ofpipeline basic information and completion information. Which complete the pipe-line geographic information based database, pipeline operation and maintenancedynamic database.

Fig. 7 Ion chromatograph and X-ray single crystal surface detector


Development of Big Data Technology Industry

Since 2014, China University of Petroleum (Beijing) Pipeline Technology ResearchCenter is committed to the development of the whole life cycle database andmanagement system, and work with PetroChina, Sinopec, CNOOC, and other unitsto study full life Cycle intelligent pipe network system, which achieved importantresults.

Quality Analysis of Pipeline Data Based on Big Data Analysis

The internal test data or the center line measurement data was integrated into thecenter line, and was one by one corresponded, according to the corresponding

integrity management of gas storage

system document

integrity detection of gas storage

christmas tree and cellar connection

casing/tubing examination

cementing evaluation

strength evaluation

life prediction

failure results

integrity data

performance evaluation

cementation quality of cement and casing

cementation quality of cement and rockw

ork

perf

orm

ance

devi

ce fl

aw

shel

l thi

ckne

ss

ND

T

hard

ness

det

ectio

n

direct inspection methodmagnetic powder inspection

ultrasonic thickness measurementultrasonic non-destructive detection

hardness measurementelectromagnetic defect detection

bats log

Fig. 8 Gas storage integrity management process

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logical relationship between the mileage, and the completion of the correspondingdata pipe correspondence, the difference between the completion of data andinternal testing data was found, the quality of the situation was determined.

Alignment technology of weld, valve, elbow characteristics, all the pipe data anda few obvious characteristics should be corresponded one to one to find the plotswhich clearly deviate from the center line and finally to determine the accuracy ofits characteristics.

Research on Third Party Damage Early Warning TechnologyBased on Large Position Data

Third-party damage is an important risk to the pipeline. According to statistics,from 2001 to 2015, the domestic pipeline accident due to third-party damageaccounted for 30% of the total *40% of the total; 1984–1992, the pipeline accidentin the European countries due to third-party damage accounted for % of the total;2010–2016, the United States occurred a total of 702 pipeline leakage incidents, ofwhich 177 is due to third-party damage (third-party excavation or external force)caused, accounting for 25.21% of the total.

Location data has become the current used to perceive the laws of humancommunity activities, analysis of geographical conditions and the construction ofintelligent city of the important strategic resources [10]. Through the analysis of thelocation of big data, from the simple positioning data we can derive the human’ssocial attributes and the relationship between environment, thus form a kind ofintelligent, socialized application.

The processing steps of the big data are: (1) Preprocessing. (2) Local locationdata feature extraction. (3) Dimension reduction analysis of big data. (4) Featureassociation and collaborative mining.

Technology of Geological Disaster Flood Forecast Basedon Big Data

The digital river basin model is established by summarizing the characteristics ofdifferent geomorphological sites, different sub—processes and different slope—ditch units. Digital river network can store simulation unit, characterize basintopology, auxiliary parallel computing. According to the meteorological forecast ormeasured rainfall data of Europe, North America, the United Kingdom and China,combined with the parallel computing function of the digital watershed model, theflow of the river is simulated and calculated. Then the surface factor based on the


catchment area and the linear factor based on the river are uniformly mapped to thelinear object of the gas pipe segment, so as to carry out the static risk assessment ofthe pipeline (Fig. 9).

Leakage, Early Warning Signal Time SeriesModel-Data Mining

As the time series data and static data has a great difference, so its clusteringanalysis has a lot of complexity. Time series data clustering methods are as fol-lowing: original data-based clustering; feature-based clustering; model-basedclustering.

Big Data Analysis Model in Pipeline Detection

The length of the national pipe network has reached 125,000 km, the detection datahas reached thousands of TB level, so the analysis of the detection data is signif-icant. Many researchers have analyzed the data management of the internaldetection, but only analyze the causality of the data, but not related to the issue ofrelated issues. Considering the comprehensive analysis of the non-causal factors inthe detection data, engineering quality and corrosion area is also important [11, 12].Therefore, the framework of internal data management based on big data envi-ronment is constructed, as shown in the following figure.

Through the detection of big data, we can analyze the following problems: thebasic quality of the national pipeline construction, the overall situation of thenational pipeline corrosion, the evolution and development of the national pipelineoperation risk, pipeline cathodic protection and corrosion of high incidence areas,pipeline welding quality and fill The quality of the situation, in order to achievemulti-round detection and evaluation of the correct comparison of data (Fig. 10).

gas pipeline channel water shed boundary

Fig. 9 Static evaluation of flood risk in Linxian pipeline

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Analysis of Big Data of Pipeline Weld

Weld is one of the important characteristics of the pipeline, its quality directlyaffects the safety of the pipeline. The poor quality of the welding caused a lot ofaccidents. The accidents which caused by the quality of welds are as following: thepipeline hit the mouth; weld radiographs failed with hidden defect; welded radio-graphs are not corresponding to welds [13]. big data analysis can find weld defectsor implied problems, thus to find the whole position of the film.

X-ray based weld images can be used for feature extraction and automaticidentification of defects. Firstly, two kinds of image enhancement algorithms arecompared with the method of mean filtering and median filtering. The histogramequalization method is used to image enhancement, and the iterative thresholdimage segmentation algorithm is used to segment the weld area and the featureextraction and feature selection of weld defects are carried out. Finally, the SVM

verification of pipeline basic information

data collection of pipeline inner detection

verification of pipeline inner detection

model modification data validation data report submission data acceptance

data loading basic line loading

multi-cycle inner detected data loadinganalysis of inner detected data loading

comparison ofinner detected data

increase analysis of inner detected corrosion

sensitivity analysis ofinner detected data

comprehensive analysis and treatment of the combination of inner detected data and operation data

inner detected data platform of national pipeline network

big data analysis model on inner detected data of national pipeline network

basic quality of

national pipeline

construction

overall corrosion

of national pipeline

risk evolvement

and development

pipeline cathodicprotection and corrosion high-

risk areas

pipeline welding and

repairing quality analysis

Fig. 10 Internal data management model for big data environment


classifier based on binary tree is used to classify and identify weld defects [14, 15],and filter the possible defect characteristics such as crack, non-penetration,non-fusion, Stomata, spherical slag and strip slag (Fig. 11).

In the figure above, A is not fused, B is not penetrated, C is the pore, and D is theinclusion. Through the description above, the most efficient SVM structure isobtained.

Pipe Corrosion Risk Data Model—Cluster Analysis Model

In terms of the performance of the K-means algorithm, it can not guarantee that theglobal optimal solution must be obtained. The accuracy of the final solutiondepends largely on the initialized grouping. As the algorithm is very fast, therefore,the commonly used method is to run the k average algorithm, select the optimalsolution. One of its drawbacks is that the number of groups k is an input parameter,and an inappropriate k may return poor results [16]. In addition, the algorithmassumes that the mean square error is the best parameter to calculate the group’sdivergence. The factors related to the corrosion area of the pipeline include thelow-lying area, the pipeline material and the manufacturing, the internal oil and gasmedium, the stray current region, the atmospheric acid rain area, the lightning area,the anticorrosive structure, the epoxy bonding force, the inner corrosion area. Thepressure fluctuation area, the downstream of the compressor station 32 km, thetemperature is higher than 38 °C, the pipe age is more than 10 years, the rock woolinsulation, dry and wet alternately, the beach area, Cl− and Na+ is rich, the internalH2S, the temperature is too low Non-related factors include pipe diameter, X80pipe, pressure, flow, inspection, geographical conditions, construction, construc-tion, and so on. [17] The non-related factors include pipe diameter, X80 pipe,pressure, flow, inspection, geographical conditions, engineering construction,

Fig. 11 Schematic diagramof the binary tree SVMalgorithm for weld defectclassification

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third-party damage, cross-construction, test piles, warning belt, elevation, thun-derstorms, floods, geological landslides, change lines, internal testing, atmosphericenvironment, fiber optic cable, external testing, human environment, constructionunits. However, when the corrosion direct and non-direct factors are intertwined, itmay produce different degrees of influence. Therefore, from the K-means algorithmto the “nuclear clustering and spectral clustering” analysis of pipeline corrosion(Fig. 12), and the correlation between the corrosion resistance of the pipeline andthe corrosion sensitivity is obtained by the clustering algorithm (Fig. 13). In thepipeline operation process, the dry and wet alternating, corrosive environment, straycurrent interference pipe section of the external corrosion should be strengthenedmanagement.

Fig. 12 Topological relationship between the relevant factors of pipeline corrosion zone andnon-direct factors

Fig. 13 Relationshipbetween corrosion factors andsensitivity


Pipeline Emergency Decision-Making and Support Basedon Big Data

The emergency data includes emergency planning database, detection plan data-base, defect disposal plan database, historical risk data, equipment data, historicalaccident data, aerial remote sensing data, pipeline equipment data, basic geographicdata, process flow chart data, station model Data and so on. According to thecorresponding emergency basic data, emergency decision support system can beestablished.

When the accident occurs, the system can be the city government informationcenter and from the public security. Fire, earthquake, weather, the scene and otherimportant information can be sent to the Civil Defense Information Center, thesystem can classify, decide and processed the image information and related datainformation that the department collected for the decision-making command staffquickly grasp the disaster, analysis and decision-making command [18]. And thesystem can automatically calculate the evacuation range, safety radius, automaticoutput contingency plans, emergency treatment programs, etc., through the repair ofmaterials and repair team routing optimization, to achieve one-button emergencyresponse program output. Output data include: pipeline basic information, Scope ofimpact, emergency facilities, population distribution, best routing, emergencyresponse programs [19, 20].

Summary

(1) The integrity management of oil and gas pipelines is bound to follow thedirection of the development of safety management in the whole life cycle. Thekey lies in the data integration and accuracy control. The key of the manage-ment platform is to analyze the history, present and future trend of equipmentand facilities.

(2) The integrity evaluation, risk prediction analysis and big data decision supportof pipeline network structure will be an important development direction of lifecycle management in oil and gas field (reservoir).

(3) To build a life cycle intelligent management platform of big data, the mostimportant part is functional applications, and the decision support is focused onhow to build data model.

(4) It is suggested that big data analysis should focus on the key issues such assolving the problems of material, structure and failure, and solving the keyissues such as safety, quality, energy consumption and operation which restrictthe development of oil and gas pipeline industry. The establishment of big datacenters for oil and gas pipelines will be the core element of the problems.

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(5) It is suggested that the integrity evaluation method of X80 pipeline in hydrogenenvironment with crack defects should be formed, the operation controlparameters of hydrogen concentration should be proposed, and the data pro-cessing system of the defect reflection signal should be developed to form thecrack and defect display method, and finally develop steel crack detectionequipment for pipeline whose steel grade is above X80.

Acknowledgements The authors gratefully acknowledge the financial support from the NationalKey R&D Program of China (No. 2017YFC0805800).

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