Exploring the Gains of Artificial Intelligence for Addressing the Menance of Pipeline Vandalization in Nigeria: A Review

2021 ◽  
Author(s):  
Chinedu Ogwus
Keyword(s):  
Artificial Intelligence ◽  
Critical Factor ◽  
Petroleum Products ◽  
Economic Losses ◽  
Pipeline Network ◽  
Oil Pipeline ◽  
Oil Transport ◽  
Excavation Work ◽  
Edge Based ◽  
Pipeline Failures

Abstract Pipeline transport is a commonly utilised method for moving petroleum products from one location to another. It is considered as one of the safest, fastest, and most reliable options for transporting petroleum products. However, the use of pipelines for oil transport is associated with the risk of pipeline failure, a challenge caused by a range of factors including corrosion, ignition of natural gas, accidental damage during excavation work, lapses in maintenance as well as vandalization. Most prevalent in Nigeria is the menace of pipeline vandalization and oil thefts which is a critical factor responsible for most pipeline failures across the country. Varied efforts aimed at addressing the problem of vandalization and oil thefts in Nigeria have, over the years, yielded minimal benefits. Therefore, this review investigates the usefulness and suitability of artificial intelligence (AI) for securing Nigeria’s pipeline network. The review focuses on summarizing available evidence on the use of some relevant AI components such as Image Analytics, Convolutional Neural Network (CNN) as well as Edge-Based AI Solutions, for securing oil pipelines. Based on the findings of case studies and other primary research materials utilized in this review, this paper concludes that while there is need for further research on the subject, AI offers a promising and useful solution to Nigeria’s endemic challenge of pipeline vandalization and oil theft. This is as AI promotes early detection of illicit activities on pipelines and can relay signals to appropriate authorities on the need for urgent action. The use of AI in securing Nigeria’s vast pipeline network will not only minimize the economic losses caused by vandalization but will equally contribute towards mitigating the adverse environmental impact of oil pipeline vandalization in Nigeria.

Improvement of legislation in the field of development and approval of plans for the prevention and elimination of oil spillage and spills of petroleum products at the facilities of main pipelines

2020 ◽  
Vol 10 (6) ◽  
pp. 654-662
Author(s):  
Andrey V. Zakharchenko ◽  
◽  
Alexander E. Gonchar ◽  
Roman Y. Shestakov ◽  
Polina V. Pugacheva ◽  
...  
Keyword(s):  
Petroleum Products ◽  
Pipeline Transport ◽  
Federal Law ◽  
Oil Pipeline ◽  
Oil Spillage ◽  
Trunk Pipeline ◽  
Main Pipelines ◽  
The Us ◽  
Improvement Of Legislation ◽  
Main Oil Pipeline

The procedure for action in cases of a threat or an accident at oil pipeline transport facilities is defined in the relevant plans for emergency spillage prevention and response – ESPR. The purpose of the article is to analyze the requirements of the legislation in the field of development and approval of ESPR. The specifics of ESRP development at trunk pipeline facilities in Russia are noted, the US experience in combating oil and oil products spillage is presented. The problematic issues in the development and approval of ESRP, relevant for the domestic system of main oil pipeline transport, have been considered. It was established that the Federal Law No. 207-FL, adopted in July 2020, fundamentally changed the outdated and required revision approach to the coordination and approval of ESRP. At the same time, further work is needed to create a regulatory framework that establishes requirements for ESRP, as well as to improve ESRP, taking into account modern methods of predicting accidents, identifying emergencies, risk-oriented approaches to planning measures to localize and eliminate accidents, the specifics of operating organizations.

scholarly journals OBTAINING OF HYDRO-INSULATION MATERIALS, PENETRANTS AND OTHER DEFICIENT LOW- TONNAGE PRODUCTS FROM PETROLEUM

2020 ◽  
Author(s):  
Guram Khitiri ◽  
Raul Kokilashvili ◽  
Tinatin Gabunia ◽  
Madona Tsurtsumia
Keyword(s):  
Liquid Glass ◽  
Petroleum Products ◽  
The South ◽  
Oil Pipeline ◽  
Insulation Materials ◽  
The Cost

Hydro-insulation of building constructions, different purpose structures is one of the most important and urgent problems of the present day. Currently concrete, ferroconcrete, metal and wooden materials are used for this purpose. Materials of this kind are not produced in the South Caucasian region. Their import, transportation, clearance by the customs and other expenses significantly increase the cost of buildings and makes it unprofitable to use them. Excreted from petroleum products – paraffins and cerezines, petrolatum, luminophores and various purpose binders, can become profitable basis for obtaining of moderm hydroinsulation materials. Their inclusion in modern hydroinsulation compositions will help to increase quality of these materials and to decrease their cost. By mixing of the goudron obtained as a result of rectification of oil pipeline sediments with milled secondary tyre casting, liquid glass, quarz sand and several additives – new hydroinsulation material was obtained.

Dynamic Online Planning Operations System for Heavy Crude Oil Pipeline Network

2017 ◽  
Author(s):  
David A. Monroy ◽  
Claudia I. Valdez ◽  
Adelfo Torres ◽  
Claudia Collado
Keyword(s):  
Crude Oil ◽  
Heavy Crude Oil ◽  
Pipeline Network ◽  
Oil Pipeline ◽  
Online Planning ◽  
Heavy Crude

From the history of the problem of oil transportation and storage. Contribution of Shukhov V.G.

2021 ◽  
pp. 50-54
Author(s):  
L. R. Yurenkova ◽  
N. V. Bilash
Keyword(s):  
Oil Industry ◽  
Petroleum Products ◽  
Fuel Oil ◽  
Oil Pipeline ◽  
Oil Storage ◽  
Oil Transportation ◽  
Oil Pipelines ◽  
Steel Tanks ◽  
Cylindrical Steel Tanks ◽  
And Storage

A significant part of the oil consumed in the world is transported from production and processing sites to consumers via tankers and pipelines. According to experts' forecasts, the demand for oil and petroleum products in the coming years will be significantly higher than in 2020. In Russia, the oil transportation market is developing in several directions. The main directions are investing in pipeline transport and improving the design of tanks for storing oil and petroleum products. The article considers the contribution of the great Russian engineer V.G. Shukhov to the solution of the problem of oil transportation and storage and in general to the development of the oil industry. In the article "Oil Pipelines" (1884) and in the book "Pipelines and their application in the oil industry" (1894), V.G. Shukhov gave precise mathematical formulae for describing the processes of oil and fuel oil flowing through pipelines, creating a classical theory of oil pipelines. He is the author of the projects of the first Russian main pipelines: Baku-Batumi with a length of 883 km (1907) and Grozny-Tuapse with a length of 618 km (1928). Shukhov V.G. designed and then supervised the construction of oil pipelines of the companies "Branobel", "G.M. Lianozova and sons" and the world's first heated fuel oil pipeline. Working in the oil fields in Baku, Shukhov V.G. developed the basics of lifting and pumping oil products, proposed a method of lifting oil using compressed air — airlift, developed a calculation method and technology for the construction of cylindrical steel tanks for oil storage facilities.

scholarly journals Social Impacts of Land Acquisition for Oil and Gas Development in Uganda

Land ◽  
2019 ◽  
Vol 8 (7) ◽  
pp. 109 ◽  
Author(s):  
Tom Ogwang ◽  
Frank Vanclay
Keyword(s):  
Social Services ◽  
Oil And Gas ◽  
Social Issues ◽  
Oil Production ◽  
Petroleum Products ◽  
Social Impacts ◽  
Land Acquisition ◽  
Oil And Gas Development ◽  
Oil Pipeline ◽  
Products Pipeline

Uganda’s oil and gas sector has transitioned from the exploration phase to the development phase in preparation for oil production (the operations phase). The extraction, processing, and distribution of oil require a great deal of infrastructure, which demands considerable acquisition of land from communities surrounding project sites. Here, we examine the social impacts of project land acquisition associated with oil production in the Albertine Graben region of Uganda. We specifically consider five major oil related projects that have or will displace people, and we discuss the consequences of this actual or future displacement on the lives and livelihoods of local people. The projects are: Tilenga; Kingfisher; the East African Crude Oil Pipeline; the Kabaale Industrial Park; and the Hoima–Kampala Petroleum Products Pipeline. Our findings reveal both positive and negative outcomes for local communities. People with qualifications have benefited or will benefit from the job opportunities arising from the projects and from the much-needed infrastructure (i.e., roads, health centres, airport) that has been or will be built. However, many people have been displaced, causing food insecurity, the disintegration of social and cultural cohesion, and reduced access to social services. The influx of immigrants has increased tensions because of increasing competition for jobs. Crime and social issues such as prostitution have also increased and are expected to increase.

Causes and Consequences of the Black Sea Ecosystem Pollution with Petroleum Products

2020 ◽  
pp. 29-44
Author(s):  
Bogdan Cioruța ◽  
Diana Mădăras ◽  
Mirela Coman
Keyword(s):  
Protected Areas ◽  
Cultural Values ◽  
Black Sea ◽  
Marine Protected Areas ◽  
Oil Pollution ◽  
Marine Ecosystem ◽  
Marine Ecosystems ◽  
Petroleum Products ◽  
The Black Sea ◽  
Oil Pipeline

Until the beginning of the 21st century concerns related to the management of protected areas have been reduced to the voluntary initiatives of nature lovers, rarely materializing in specific conservation measures carried out by the authorities or administrators of those areas. As the concern for the management of protected areas is relatively new in Romania and the information related to this subject is relatively scarce, especially those regarding marine ecosystems, we considered necessary this study on the management of marine protected areas in relation to oil pollution. Marine protected areas, in particular, delimited as areas where the main purpose is the protection of nature and cultural values, are important for all segments of society. They have great potential to become models of harmonious society development, promoting more than other protected areas the sustainable resource management. At the same time, the management measures promoted, sometimes imposed, can affect the communities inside or in the immediate vicinity of the areas, and can significantly influence the development of the economy. Recently (as a reference 1970-2020), the pollution of the marine environment with petroleum products has gained dramatic accents. The maritime transport of oil, the exploration and exploitation of marine deposits, their processing in refineries located in the vicinity of the coastal area, to which are added other anthropogenic activities, have generated and still generate a number of risk factors, which involve numerous pollution incidents. Navigation accidents of large oil tanks or incidents at offshore drilling rigs caused, in the same period, major environmental disasters, with the most severe consequences. Marine ecosystems in polluted regions have thus suffered major losses and disturbances, which have been felt for a long time. Through this paper we aim to review some aspects of oil pipeline pollution of the Planetary Ocean, respectively the associated pollution in the Black Sea ecosystem. Following the analyzes carried out on the basis of the data from the consulted literature, as well as following other observations, we came to the conclusion that the protected areas associated with the Black Sea, as well as the marine ecosystem itself, are far from being affected by such accidents.

Neural Network Modeling for Monitoring Petroleum Pipelines

2016 ◽  
Vol 26 ◽  
pp. 122-131 ◽  
Author(s):  
Ighodaro Osarobo ◽  
Akaeze Chika
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Network Modeling ◽  
Petroleum Products ◽  
Input Pattern ◽  
Neural Network Modeling ◽  
Diagnostic Problem ◽  
Common Occurrence ◽  
Output Pattern ◽  
Pipeline Failures

It is common occurrence that the transportation of petroleum products via pipelines is susceptible to failure either naturally or intentionally. The paper is a diagnostic problem having continuous inputs of pattern recognition used in predicting pipeline failures. Our problem is to design a neural network that will recognize failure events in pipelines when fed with an input pattern denoting such a scenario. A neural network paradigm is selected, and encoding of input is done to obtain the input pattern. The selected model is simulated and trained to recognize the output pattern, which in our scenario after training, goes into operational mode.The neural network is fully implemented on a Pentium II MMX computer with a Borland C++ builder.

scholarly journals A Vision to Face Covid-19 pandemic and Future Risks Through Artificial Intelligence

2020 ◽  
Vol 6 (1) ◽  
pp. 15-20
Author(s):  
Malek Albzeirat ◽  
Nik Zulkepli ◽  
Haitham Qaralleh
Keyword(s):  
Artificial Intelligence ◽  
Health Economic ◽  
International Relations ◽  
Political Stability ◽  
Diagnosis And Treatment ◽  
Economic Losses ◽  
Social Stability ◽  
Short Period ◽  
The World

Coved-19 pandemic is spreading fear among the world in several aspects such as health, economic, international relations, political stability, and social stability. It emerged suddenly and attacked the world in a short period without warning. Details about the virus such as the source, symptoms, transmission, diagnosis and treatment are still incomplete.  Subsequently, more than one million people have died and huge economic losses. In order to avoid this issue in future, this paper aims to focus on artificial intelligence in predicting and tracking viral pandemic Disease and to control similar future risks using artificial intelligence, algorithms and cognitive fission theory.

scholarly journals The challenges and solution of implementing a leak detection system on a complex crude oil pipeline network in Romania

2021 ◽  
Vol 7 (1) ◽  
pp. 60-73
Author(s):  
Harry SMITH ◽  
Kirsty MCNEIL ◽  
Tom RECORD ◽  
Dan BUZATU ◽  
Georgian ILIESCU ◽  
...  
Keyword(s):  
Crude Oil ◽  
Detection System ◽  
Leak Detection ◽  
Pipeline Network ◽  
Oil Pipeline

scholarly journals Towards Landslides Early Warning System With Fog - Edge Computing And Artificial Intelligence**

2021 ◽  
Vol 15 (02) ◽  
pp. 11-17
Author(s):  
Olivier Debauche ◽  
Meryem Elmoulat ◽  
Saïd Mahmoudi ◽  
Sidi Ahmed Mahmoudi ◽  
Adriano Guttadauria ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Early Warning ◽  
Large Scale ◽  
Prediction Models ◽  
Warning System ◽  
Early Warning Systems ◽  
Economic Losses ◽  
Warning Systems ◽  
Large Scale Data ◽  
Set Up

Landslides are phenomena that cause significant human and economic losses. Researchers have investigated the prediction of high landslides susceptibility with various methodologies based upon statistical and mathematical models, in addition to artificial intelligence tools. These methodologies allow to determine the areas that could present a serious risk of landslides. Monitoring these risky areas is particularly important for developing an Early Warning Systems (EWS). As matter of fact, the variety of landslides’ types make their monitoring a sophisticated task to accomplish. Indeed, each landslide area has its own specificities and potential triggering factors; therefore, there is no single device that can monitor all types of landslides. Consequently, Wireless Sensor Networks (WSN) combined with Internet of Things (IoT) allow to set up large-scale data acquisition systems. In addition, recent advances in Artificial Intelligence (AI) and Federated Learning (FL) allow to develop performant algorithms to analyze this data and predict early landslides events at edge level (on gateways). These algorithms are trained in this case at fog level on specific hardware. The novelty of the work proposed in this paper is the integration of Federated Learning based on Fog-Edge approaches to continuously improve prediction models.

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