Rank-based risk target data analysis using digital twin on oil pipeline network based on manifold learning

2022 ◽  
pp. 095440892110732
Author(s):  
E.B. Priyanka ◽  
S. Thangavel ◽  
Priyanka Prabhakaran
Keyword(s):  
Data Analysis ◽  
Manifold Learning ◽  
Clustering Algorithm ◽  
Oil And Gas ◽  
Pipeline System ◽  
Security Risk ◽  
Oil Pipeline ◽  
Cloud Server ◽  
Risk Rate ◽  
Risk Predictor

Oil and Gas Pipeline (OGP) projects face a wide scope of wellbeing and security Risk Factors (RFs) all around the world, especially in the oil and gas delivering nations having influencing climate and unsampled data. Lacking data about the reasons for pipeline risk predictor and unstructured data about the security of the OGP prevent endeavors of moderating such dangers. This paper, subsequently, means to foster a risk analyzing framework in view of a comprehensive methodology of recognizing, dissecting and positioning the related RFs, and assessing the conceivable pipeline characteristics. Hazard Mitigation Methods (HMMs), which are the initial steps of this approach. A new methodology has been created to direct disappointment investigation of pinhole erosion in pipelines utilizing the typical pipeline risk strategy and erosion climate reenactments during a full life pattern of the pipeline. Hence in the proposed work, manifold learning with rank based clustering algorithm is incorporated with the cloud server for improved data analysis. The probability risk rate is identified from the burst pressure by clustering the normal and leak category to improve the accuracy of the prediction system experimented on the lab-scale oil pipeline system. The numerical results like auto-correlation, periodogram, Laplace transformed P-P Plot are utilized to estimate the datasets restructured by the manifold learning approach. The obtained experimental results shows that the cloud server datasets are clustered with rank prioritization to make proactive decision in faster manner by distinguishing labelled and unlabeled pressure attributes.

scholarly journals Drag Reducer Selection for Oil Pipeline Based Laboratory Experiment

2017 ◽  
Vol 12 (1) ◽  
pp. 112 ◽  
Author(s):  
Leksono Mucharam ◽  
Silvya Rahmawati ◽  
Rizki Ramadhani
Keyword(s):  
Crude Oil ◽  
Large Scale ◽  
Oil And Gas ◽  
Energy Requirement ◽  
Pipeline System ◽  
Chemical Application ◽  
Oil Pipeline ◽  
Pipeline Flow ◽  
Oil Transportation ◽  
Pump Stations

Oil and gas industry is one of the most capital-intensive industry in the world. Each step of oil and gas processing starting from exploration, exploitation, up to abandonment of the field, consumes large amount of capital. Optimization in each step of process is essential to reduce expenditure. In this paper, optimization of fluid flow in pipeline during oil transportation will be observed and studied in order to increase pipeline flow performance.This paper concentrates on chemical application into pipeline therefore the chemical can increase overall pipeline throughput or decrease energy requirement for oil transportation. These chemicals are called drag reducing agent, which consist of various chemicals such as surfactants, polymers, nanofluids, fibers, etc. During the application of chemical into pipeline flow system, these chemicals are already proven to decrease pump work for constant flow rate or allow pipeline to transport more oil for same amount of pump work. The first application of drag reducer in large scale oil transportation was in Trans Alaskan Pipeline System which cancel the need to build several pump stations because of the successful application. Since then, more company worldwide started to apply drag reducer to their pipeline system.Several tedious testings on laboratory should be done to examine the effect of drag reducer to crude oil that will be the subject of application. In this paper, one of the testing method is studied and experimented to select the most effective DRA from several proposed additives. For given pipeline system and crude oil type, the most optimum DRA is DRA A for pipeline section S-R and for section R-P is DRA B. Different type of oil and pipeline geometry will require different chemical drag reducer. 

Failure Mode Recognition Clustering Algorithm Based on Manifold Learning

2012 ◽  
Vol 263-266 ◽  
pp. 2126-2130 ◽  
Author(s):  
Zhi Gang Lou ◽  
Hong Zhao Liu
Keyword(s):  
Manifold Learning ◽  
Clustering Algorithm ◽  
Learning Algorithm ◽  
Spectral Characteristics ◽  
Normal Operation ◽  
High Dimensional ◽  
Dimensional Manifold ◽  
Pattern Clustering ◽  
Oil Pipeline ◽  
Adjustable Valve

Manifold learning is a new unsupervised learning method. Its main purpose is to find the inherent law of generated data sets. Be used for high dimensional nonlinear fault samples for learning, in order to identify embedded in high dimensional data space in the low dimensional manifold, can be effective data found the essential characteristics of fault identification. In many types of fault, sometimes often failure and normal operation of the equipment of some operation similar to misjudgment, such as oil pipeline transportation process, pipeline regulating pump, adjustable valve, pump switch, normal operation and pipeline leakage fault condition similar spectral characteristics, thus easy for pipeline leakage cause mistakes. This paper uses the manifold learning algorithm for fault pattern clustering recognition, and through experiments on the algorithm is evaluated.

scholarly journals Imperatives for the Amendment of the Nigerian Oil Pipelines Act

2020 ◽  
pp. 1-9
Author(s):  
Obioma Helen Onyi-Ogelle
Keyword(s):  
Monitoring System ◽  
Oil And Gas ◽  
Effective Means ◽  
Research Work ◽  
Advanced Technology ◽  
Pipeline System ◽  
Gas Pipelines ◽  
Oil Pipeline ◽  
Oil Pipelines ◽  
Oil And Gas Pipelines

Pipelines have been recognized to be one of the most effective means of transportation in any oil producing state. It however has its technicalities, hence the provision of regulations and guidelines for their operation. Nigeria as an oil producing state has been operating with pipelines for many years now, but in all ramifications it has not had the best and efficient oil pipeline system. This research work was as a result of the failure of the Oil Pipelines Act and its subsidiary Regulation, Guidelines and Procedure for the Construction, Operation and Maintenance of Oil and Gas Pipelines and their Ancillary Facilities, to create for an effective pipeline operation. This research applied a doctrinal type of methodology and adopted an analytical, comparative and descriptive approach. It was found that the problem with the Nigerian Oil Pipelines Act, is that it is outdated. The Act has been in existence for more than 50 years; and because of this, it cannot meet the current needs and trends in the country. Some of the needs are: meeting up with Technological Advancements, Managerial and maintenance skills, Environmental Protection, Efficiency in transportation and Security issues. More importantly it cannot take care of the current exigenecies in the country with regard to transportation of oil. This research has offered some recommendations to improve the oil pipeline system. Some of which includes a proper creation for an effective monitoring system. This should be done by qualified personnel and also with the use of advanced technology obtainable in some countries like the US. This advanced technological monitoring system will not only report any vandalization, but will also indicate when there is need for maintenance especially pipeline corrosion. There should be more creation of oil and gas pipelines in all the cities to discourage transportation of petroleum products through tanker which over the years have been the cause of so many road accidents and fire outbreaks. There should be an improvement on the types of pipelines operated; this should include new age pipelines. These problems associated with the Oil Pipelines Act necessitated the call for its amendment.

Pipeline Integrity Assessment: Methodology

2015 ◽  
Author(s):  
Mohammed Riyazuddin Shaik
Keyword(s):  
Oil And Gas ◽  
Fatigue Cracks ◽  
Oil And Gas Industry ◽  
Transportation Safety ◽  
Pipeline System ◽  
Prolonged Release ◽  
Oil Pipeline ◽  
Integrity Assessment ◽  
Energy Demands ◽  
Primary Means

With ever increasing energy demands, approximately 90 million barrels of oil per day and 3314 billion cubic meters of gas per year are consumed around the world [1]. To meet such huge energy demands a complicated and vast network of offshore and onshore production and distribution pipelines is necessary. Pipelines connect areas that are relatively rich in resources with areas that are demand-hungry but poor in resources. They play a central role in providing to the energy needs of businesses and public, forming the veins and arteries of the Oil and Gas industry. These pipelines are susceptible to damage, both internal and external based on the type of product in the pipeline and the environment in the vicinity of the pipeline i.e. offshore or onshore. The damage to the pipeline needs to be identified and the significance of the damage clearly defined. The inline inspection (ILI) tools help to identify the damage and record the extent and type of damage. Inability to prioritize the damaged areas and carry out necessary intervention to at least curtail the damage may occasionally lead to calamitous consequences. One such example is of a 30-inch Liquid pipeline failure that occurred in Michigan on July 25, 2010. The National Transportation Safety Board (NTSB) reported that the corrosion fatigue cracks that grew and coalesced from corrosion defects resulted in the rupture and prolonged release from the 30-inch oil pipeline [2]. This failure resulted in a revenue loss of approximately $16 million and estimated costs of $767 million for regulatory and professional support in connection with the clean-up operations. Condition assessment of the pipelines as part of the pipeline integrity management system is the primary means through which such catastrophic pipeline system failures could be prevented. This paper presents the methodology that is adopted for “Integrity Assessment” of the pipelines.

Additional methods to improve the energy efficiency of oil pipeline transportation

2020 ◽  
Vol 10 (5) ◽  
pp. 558-565
Author(s):  
Marat R. Lukmanov ◽  
◽  
Sergey L. Semin ◽  
Pavel V. Fedorov ◽  
◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Saving ◽  
Pipeline System ◽  
Energy Costs ◽  
Improvement Program ◽  
Oil Pipeline ◽  
Energy Efficiency Improvement ◽  
Oil Transportation ◽  
Pumping Equipment ◽  
Preparatory Work

The challenges of increasing the energy efficiency of the economy as a whole and of certain production sectors in particular are a priority both in our country and abroad. As part of the energy policy of the Russian Federation to reduce the specific energy intensity of enterprises in the oil transportation system, Transneft PJSC developed and implements the energy saving and energy efficiency improvement Program. The application of energy-saving technologies allowed the company to significantly reduce operating costs and emissions of harmful substances. At the same time, further reduction of energy costs is complicated for objective reasons. The objective of this article is to present additional methods to improve the energy efficiency of oil transportation by the example of the organizational structure of Transneft. Possibilities to reduce energy costs in the organization of the operating services, planning and execution of work to eliminate defects and preparatory work for the scheduled shutdown of the pipeline, the use of pumping equipment, including pumps with variable speed drive, the use of various pipelines layouts, changing the volume of oil entering the pipeline system and increase its viscosity.

K-MEANS CLUSTERING ALGORITHM FOR SERVICE DATA ANALYSIS BASED ON CUSTOMERS COMBINATION

2018 ◽  
Vol 3 (1) ◽  
pp. 001
Author(s):  
Zulhendra Zulhendra ◽  
Gunadi Widi Nurcahyo ◽  
Julius Santony
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Clustering Algorithm ◽  
Customer Complaints ◽  
Using Data ◽  
Clustering Data ◽  
Service Data ◽  
Selection Of

In this study using Data Mining, namely K-Means Clustering. Data Mining can be used in searching for a large enough data analysis that aims to enable Indocomputer to know and classify service data based on customer complaints using Weka Software. In this study using the algorithm K-Means Clustering to predict or classify complaints about hardware damage on Payakumbuh Indocomputer. And can find out the data of Laptop brands most do service on Indocomputer Payakumbuh as one of the recommendations to consumers for the selection of Laptops.

scholarly journals Data Analysis and Discussion on the Reliability of the Control Principle of a Sealed Crude Oil Pipeline

2021 ◽  
Vol 1927 (1) ◽  
pp. 012021
Author(s):  
Junjiang Liu ◽  
Liang Feng ◽  
Dake Yang ◽  
Xianghui Li
Keyword(s):  
Data Analysis ◽  
Crude Oil ◽  
Oil Pipeline ◽  
Control Principle

Gas pipeline leakage detection in the presence of parameter uncertainty using robust extended Kalman filter

2021 ◽  
pp. 014233122198911
Author(s):  
Mohadese Jahanian ◽  
Amin Ramezani ◽  
Ali Moarefianpour ◽  
Mahdi Aliari Shouredeli
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Parameter Uncertainty ◽  
Oil And Gas ◽  
Estimation Error ◽  
Real Data ◽  
Gas Pipeline ◽  
Pipeline System ◽  
Parameter Uncertainties ◽  
Simulation Results

One of the most significant systems that can be expressed by partial differential equations (PDEs) is the transmission pipeline system. To avoid the accidents that originated from oil and gas pipeline leakage, the exact location and quantity of leakage are required to be recognized. The designed goal is a leakage diagnosis based on the system model and the use of real data provided by transmission line systems. Nonlinear equations of the system have been extracted employing continuity and momentum equations. In this paper, the extended Kalman filter (EKF) is used to detect and locate the leakage and to attenuate the negative effects of measurement and process noises. Besides, a robust extended Kalman filter (REKF) is applied to compensate for the effect of parameter uncertainty. The quantity and the location of the occurred leakage are estimated along the pipeline. Simulation results show that REKF has better estimations of the leak and its location as compared with that of EKF. This filter is robust against process noise, measurement noise, parameter uncertainties, and guarantees a higher limit for the covariance of state estimation error as well. It is remarkable that simulation results are evaluated by OLGA software.

Multiphase Transient Slugging Flow in Subsea Oil and Gas Production

2016 ◽  
Author(s):  
Zhenhua Zhang ◽  
Longbin Tao
Keyword(s):  
Data Analysis ◽  
Temperature Distribution ◽  
Numerical Model ◽  
Slug Flow ◽  
Field Data ◽  
Oil And Gas ◽  
Gas Production ◽  
Worst Case ◽  
Oil And Gas Production ◽  
Significant Difference

Slug flow in horizontal pipelines and riser systems in deep sea has been proved as one of the challenging flow assurance issues. Large and fluctuating gas/liquid rates can severely reduce production and, in the worst case, shut down, depressurization or damage topside equipment, such as separator, vessels and compressors. Previous studies are primarily based on experimental investigations of fluid properties with air/water as working media in considerably scaled down model pipes, and the results cannot be simply extrapolated to full scale due to the significant difference in Reynolds number and other fluid conditions. In this paper, the focus is on utilizing practical shape of pipe, working conditions and fluid data for simulation and data analysis. The study aims to investigate the transient multiphase slug flow in subsea oil and gas production based on the field data, using numerical model developed by simulator OLGA and data analysis. As the first step, cases with field data have been modelled using OLGA and validated by comparing with the results obtained using PIPESYS in steady state analysis. Then, a numerical model to predict slugging flow characteristics under transient state in pipeline and riser system was set up using multiphase flow simulator OLGA. One of the highlights of the present study is the new transient model developed by OLGA with an added capacity of newly developed thermal model programmed with MATLAB in order to represent the large variable temperature distribution of the riser in deep water condition. The slug characteristics in pipelines and temperature distribution of riser are analyzed under the different temperature gradients along the water depth. Finally, the depressurization during a shut-down and then restart procedure considering hydrate formation checking is simulated. Furthermore, slug length, pressure drop and liquid hold up in the riser are predicted under the realistic field development scenarios.

Applying the Quantitative Risk Assessment (QRA) to Improve Safety Management of Oil and Gas Pipeline Stations in China

2012 ◽  
Author(s):  
Wenxing Feng ◽  
Xiaoqiang Xiang ◽  
Guangming Jia ◽  
Lianshuang Dai ◽  
Yulei Gu ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Environmental Protection ◽  
Oil And Gas ◽  
Hazard Identification ◽  
Gas Pipeline ◽  
Industrial Safety ◽  
Quantitative Risk Assessment ◽  
Chinese Government ◽  
Land Resource ◽  
Oil Pipeline

The oil and gas pipeline companies in China are facing unprecedented opportunities and challenges because of China’s increasing demand for oil and gas energy that is attributed to rapid economic and social development. Limitation of land resource and the fast urbanization lead to a determinate result that many pipelines have to go through or be adjacent to highly populated areas such as cities or towns. The increasing Chinese government regulation, and public concerns about industrial safety and environmental protection push the pipeline companies to enhance the safety, health and environmental protection management. In recent years, PetroChina Pipeline Company (PPC) pays a lot of attention and effort to improve employees and public safety around the pipeline facilities. A comprehensive, integrated HSE management system is continuously improved and effectively implemented in PPC. PPC conducts hazard identification, risk assessment, risk control and mitigation, risk monitoring. For the oil and gas stations in highly populated area or with numerous employees, PPC carries out quantitative risk assessment (QRA) to evaluate and manage the population risk. To make the assessment, “Guidelines for quantitative risk assessments” (purple book) published by Committee for the Prevention of Disasters of Netherlands is used along with a software package. The basic principles, process, and methods of QRA technology are introduced in this article. The process is to identify the station hazards, determinate the failure scenarios of the facilities, estimate the possibilities of leakage failures, calculate the consequences of failures and damages to population, demonstrate the individual risk and social risk, and evaluate whether the risk is acceptable. The process may involve the mathematical modeling of fluid and gas spill, dispersion, fire and explosion. One QRA case in an oil pipeline station is described in this article to illustrate the application process and discuss several key issues in the assessment. Using QRA technique, about 20 stations have been evaluated in PPC. On the basis of the results, managers have taken prevention and mitigation plans to control the risk. QRAs in the pipeline station can provide a quantitative basis and valuable reference for the company’s decision-making and land use planning. Also, QRA can play a role to make a better relationship between the pipeline companies and the local regulator and public. Finally, this article delivers limitations of QRA in Chinese pipeline stations and discusses issues of the solutions.

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