Risk Assessment of Pipeline Engineering Geological Disaster Based on GIS and WOE-GA-BP Models

Oil and gas pipelines are part of long-distance transportation projects which pass through areas with complex geological conditions and which are prone to geological disasters. Geological disasters significantly affect the safety of pipeline operations. Therefore, it is essential to conduct geologic...

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Autores principales:	Bohu He, Mingzhou Bai, Hai Shi, Xin Li, Yanli Qi, Yanjun Li
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	oil and gas pipelines hazard zone GIS GA BP WOE Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/3361c75527dc45b992867a232bf59671
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spelling	oai:doaj.org-article:3361c75527dc45b992867a232bf596712021-11-11T15:00:56ZRisk Assessment of Pipeline Engineering Geological Disaster Based on GIS and WOE-GA-BP Models10.3390/app112199192076-3417https://doaj.org/article/3361c75527dc45b992867a232bf596712021-10-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/9919https://doaj.org/toc/2076-3417Oil and gas pipelines are part of long-distance transportation projects which pass through areas with complex geological conditions and which are prone to geological disasters. Geological disasters significantly affect the safety of pipeline operations. Therefore, it is essential to conduct geological disaster risk assessments in areas along pipelines to ensure efficient pipeline operation, and to provide theoretical support for early warning and forecasting of geological disasters. In this study, the pipeline routes of the Sichuan-Chongqing and Western Hubei management offices of the Sichuan-East Gas Transmission Project were studied. Seven topographic factors—surface elevation, topographic slope, topographic aspect, plane curvature, stratum lithology, rainfall, and vegetation coverage index—were superimposed using the laying method with a total of eight evaluation indicators. The quantitative relationships between the factors and geological disasters were obtained using the geographic information system (GIS) and weight of evidence (WOE). The backpropagation neural network (BP) was optimised using a genetic algorithm (GA) to obtain the weight of each evaluation index. The quantified index was then utilized to identify the geological hazard risk zone along the pipeline. The results showed that the laying method, stratum lithology, and normalised difference vegetation index were the factors influencing hazards.Bohu HeMingzhou BaiHai ShiXin LiYanli QiYanjun LiMDPI AGarticleoil and gas pipelineshazard zoneGISGABPWOETechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 9919, p 9919 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	oil and gas pipelines hazard zone GIS GA BP WOE Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	oil and gas pipelines hazard zone GIS GA BP WOE Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Bohu He Mingzhou Bai Hai Shi Xin Li Yanli Qi Yanjun Li Risk Assessment of Pipeline Engineering Geological Disaster Based on GIS and WOE-GA-BP Models
description	Oil and gas pipelines are part of long-distance transportation projects which pass through areas with complex geological conditions and which are prone to geological disasters. Geological disasters significantly affect the safety of pipeline operations. Therefore, it is essential to conduct geological disaster risk assessments in areas along pipelines to ensure efficient pipeline operation, and to provide theoretical support for early warning and forecasting of geological disasters. In this study, the pipeline routes of the Sichuan-Chongqing and Western Hubei management offices of the Sichuan-East Gas Transmission Project were studied. Seven topographic factors—surface elevation, topographic slope, topographic aspect, plane curvature, stratum lithology, rainfall, and vegetation coverage index—were superimposed using the laying method with a total of eight evaluation indicators. The quantitative relationships between the factors and geological disasters were obtained using the geographic information system (GIS) and weight of evidence (WOE). The backpropagation neural network (BP) was optimised using a genetic algorithm (GA) to obtain the weight of each evaluation index. The quantified index was then utilized to identify the geological hazard risk zone along the pipeline. The results showed that the laying method, stratum lithology, and normalised difference vegetation index were the factors influencing hazards.
format	article
author	Bohu He Mingzhou Bai Hai Shi Xin Li Yanli Qi Yanjun Li
author_facet	Bohu He Mingzhou Bai Hai Shi Xin Li Yanli Qi Yanjun Li
author_sort	Bohu He
title	Risk Assessment of Pipeline Engineering Geological Disaster Based on GIS and WOE-GA-BP Models
title_short	Risk Assessment of Pipeline Engineering Geological Disaster Based on GIS and WOE-GA-BP Models
title_full	Risk Assessment of Pipeline Engineering Geological Disaster Based on GIS and WOE-GA-BP Models
title_fullStr	Risk Assessment of Pipeline Engineering Geological Disaster Based on GIS and WOE-GA-BP Models
title_full_unstemmed	Risk Assessment of Pipeline Engineering Geological Disaster Based on GIS and WOE-GA-BP Models
title_sort	risk assessment of pipeline engineering geological disaster based on gis and woe-ga-bp models
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/3361c75527dc45b992867a232bf59671
work_keys_str_mv	AT bohuhe riskassessmentofpipelineengineeringgeologicaldisasterbasedongisandwoegabpmodels AT mingzhoubai riskassessmentofpipelineengineeringgeologicaldisasterbasedongisandwoegabpmodels AT haishi riskassessmentofpipelineengineeringgeologicaldisasterbasedongisandwoegabpmodels AT xinli riskassessmentofpipelineengineeringgeologicaldisasterbasedongisandwoegabpmodels AT yanliqi riskassessmentofpipelineengineeringgeologicaldisasterbasedongisandwoegabpmodels AT yanjunli riskassessmentofpipelineengineeringgeologicaldisasterbasedongisandwoegabpmodels
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Risk Assessment of Pipeline Engineering Geological Disaster Based on GIS and WOE-GA-BP Models

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