Cloud Service Model for Safety Monitoring and Assessment of Oil and Gas Pipelines Si-jian Lin 1, Xiao-lie Liao2, Wei Long 1, Jun-bi Liao 1 1 School of Manufacturing Science and Engineering, Sichuan University, Chengdu, China 2 School of Materials Science and Engineering, Xihua University, Chengdu, China (Corresponding Author: [email protected] ) Abstract - The traditional assessment model that is used to assess the safety and predict the remaining life of oil and gas pipelines consumes substantial resources, such as manpower and materials. In a sense, it hampers the development of assessment technology. So, we set up a new assessment model, Cloud Service Model, which is based on Cloud Computing, Field Signature Method (FSM) and Dynamic Assessment Technology. With the characteristics of timeliness, high efficiency, resource sharing and low cost, it may have a great application prospect. Keywords - Cloud Computing, dynamic assessment, Field Signature Method, pipelines, safety monitoring I. INTRODUCTION Pipelines play an irreplaceable role in the transport of oil and gas. A small oil spill of pipelines can become a big catastrophe, as it did in the 2006 spill in the Prudhoe Bay oil field of Alaska. So, it’s absolutely necessary to ensure that pipelines work in a safe condition. In most situations, we don’t need to inspect the whole pipelines because of the predictability of most defects’ positions. According to the working condition, structure of pipelines and experience of inspectors, we can obtain the sections which have a greater possibility of failure. Then, we can use some useful techniques, such as straight beam ultrasonic thickness examination (UT), Radiographic examination (RT), Magnetic Particle (MT), Dye Penetrant (PT) to get the size of defects . When having gotten the size of defects and material data of pipelines and other data that are necessary to assessment, we can assess the security or fitness-forservice and estimate the remaining life of the equipment according to standards or codes available, such as API 510, API 570, API 653, API 579 and ANSI/NB-23. Then we can make the plan of checking or take some remediation methods to prevent or minimize the rate of further damage . However, it’s not enough! It’s very difficult to check out the whole pipelines, because it may be used in the open-air, underground or subsea condition and often it’s not too short. Stem from competitive consideration, oil and gas companies possessing a large number of pipelines won’t share the inspection and assessment equipment with each other, which may occupy large amount of resources. For the so-called data security consideration, they also may not provide the inspection data of defects to research institutes, although they may develop significant theories to prevent the defects in return. So, there must be a more effective service model to manage the data. II. KEY TECHNOLOGIES A. Cloud Computing Cloud Computing has been regarded as a new largescale distributed computing paradigm, where computational power is provided similar to utilities like water, electricity, gas and telephony . It involves Grid computing, Distributed computing, parallel computing, utility computing, network storage technology, virtualization and load balance techniques . It delivers infrastructure, platform, software, storage as services, which are made available as subscription-based services in a pay-as-you-go model to consumers . These services in industry are respectively referred to as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), and Storage as a Service (StaaS) . Users access services based on their requirements without regard to where the services are hosted . Since the CEO of Google, Eric Schmidt, put forward the concept of cloud computing for the first time in 2006, Cloud Computing develops rapidly and is widely used in Internet Technology applications, for example, BT for IaaS, Amazon EC2 for PaaS, Google apps for SaaS, Amazon S3 for StaaS . With the characteristics of service-oriented, loose coupling, scalability, strong fault tolerant, ease use, virtualization and high security, it will make a lot sense to introduce Cloud Computing into the service of oil pipeline’s safety monitoring and assessment. B. Field Signature Method As has been noted, pipelines may be in a severe working condition where manpower can’t reach easily. So, we need a practical and effective inspection method to detect and monitor the defects of pipelines on line. Because corrosion is the main defect that results in the failure of pipelines , the Field Signature Method (FSM) is the best option. FSM is a nondestructive, on-line, reliable inspection method, which was put forward and developed by the CorrOcean ASA in Norway . In case of having metal Cloud computing … … (Service providers) Internet BTS Satellite Inspection communication equipment Pipelines … … CSP SaaS, PaaS StaaS, IaaS Internet BTS Satellite Inspection communication equipment Pipelines Institutes Pipe manufacturers Oil and gas companies … Fig. 1. Structure of Cloud Service Mode loss and cracks on the steel object and current flowing through it, the electrical resistance of these regions will rise . According to Ohm’s law, the potential difference will rise in proportion to the increase of electrical resistance. FSM detects corrosion and cracks by detecting the changes of voltage measurements of the sensing pins (electrodes) which are distributed in an array over the monitored area. With the advantages of nonintrusion, accuracy and adaptability in extreme conditions , FSM has been used in oil and gas industry, in petrochemical plants, in refineries, in power plants and in nuclear reactors. With the improvement of FSM technology , using FSM technology has become an unavoidable trend. cracks as an example, we often utilize Failure Assessment Diagram(FAD) to judge the security of pipelines by determining whether the assessment point is in the acceptable region or not. For dynamic assessment method, the failure routine and failure rate can be simulated through a system based on dynamic assessment technology. The residual life is found by dividing the failure routine by the failure rate after considering all sensitive factors, such as loads, material properties and temperature. Undoubtedly, this method is intelligent, the results of which are more intuitive and practical. Because of the powerful data processing ability, it will take less time to obtain the assessment results. C. Dynamic Assessment Technology III. ANALYSIS OF CLOUD SERVICE MODEL There are many methods to assess the security or fitness-for-service and estimate the remaining life of the equipment, such as finite element method, linear-elastic fracture mechanics, fracture mechanics, most of which are based on the residual strength of pipelines. With the application of these methods, enormous economic benefits have been gained. However, most of these methods are either too conservative or too restrictive, such as the ANSI/ASME B31G-1991 based on fracture mechanics. And they belong to static assessment methods, that is, they can only gain the security of current working condition and predict the residual life of the condition that is the same as the current conditon. It is known to us that the working conditions having a huge influence on the security and residual life may change, so the results we obtained by paying a heavy price sometimes may be inaccurate and impractical. Thus, dynamic assessment method is developed. Dynamic assessment technology, which was firstly put forward by School of Manufacturing Science and Engineering of SICHUAN UNIVERSITY, is based on computer technology. Taking the safety assessment of A. Structure of Cloud Service Model Given that the traditional service model has many disadvantages and can’t meet the need of society, we put forward a new service model, Cloud Service Model, which is mainly based on Cloud Computing, Field Signature Method (FSM) and Dynamic Assessment Technology. In fig. 1, the structure of the new model is displayed. B. Characteristics of Cloud Service Model 1) Timeliness: The inspection communication equipment can conduct real-time data acquisition and the Cloud Service Center will deliver the safety information of pipelines to the oil and gas companies in time in a way that is accessible to them. The oil and gas companies can also use Mobile Terminals (MT), such as cell phone, tablet PC and laptop computer, to get the safety information at any place and any time through the Cloud Service Provider (CSP). Pipelin es Inspection equipment Data processing Oil or gas companies Fig.2. Structure of traditional assessment model 2) High efficiency: Because the amount of inspection data is very large, it may take the processing center of oil and gas companies a lot of time to process it, which is the last thing they want. Cloud Computing can solve this problem very easily and quickly, because of the enormous data processing capacity and system scalability. 3) Resource sharing: The confidentiality of the inspection data of pipelines which is completely unnecessary impedes the progress of assessment technology. Through the Cloud Service Center (CSC) can we overcome this barrier, and the institutes, Oil and Gas companies and pipe manufacturers take what they need. Because what the institutes are concerned with are the laws behind the inspection data, the oil companies is the safety of pipelines, the pipe manufacturers are the problems resulting from the use of pipelines, through the CSC can the rational allocation of resources be achieved. 4) Low Cost: Compared with the traditional assessment model, see Fig. 2, it will take the oil and gas companies less money to get what they want, because the institutes and pipe manufacturers pay the rest. IV. CONCLUSION Based on Cloud Computing technology, Field Signature Method and Dynamic Assessment technology, a new service model, Cloud Service Model, is set up. Compared with the traditional assessment model, we conclude that the Cloud Service Model has many advantages. We can define it as a resource conserving model with a great deal of promise. ACKNOWLEDGMENT The present study was supported in part by the National Natural Science Foundation of China entitled “Defects failure routine and failure rate simulation and research of dynamic safety margin of pressure vessel” under Grant NO.51075286, Project duration 1st January 2011 to 31st December 2013 (3 years). REFERENCES  American Petroleum Institute. Fitness-for-service. API RP579-1/ASME FFS-1, 2007.  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