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Probabilistic Digital Twins For Transmission Pipelines

Picture for Probabilistic Digital Twins For Transmission Pipelines
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Product Number: 51321-16780-SG
Author: Francois Ayello; Yonghe Yang; Long Li; Guanlan Liu; Yuchong Zhang; Shuhui Zhang
Publication Date: 2021
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Digitalization in the oil and gas industry has led to the formation of digital twins. Digital twins bring closer the physical and virtual world as data is transmitted seamlessly between real time sensors, databases and models. The strength of the digital twin concept is the interconnectivity of data and models. Any model can use any combination of inputs (e.g. operator owned data sets and sensors, third-party databases such as soil composition or weather data, results from other models such as flow assurance, threat modelling or risk modelling). Consequently, the result of one model may become the input of another. This strength is also a weakness, as uncertain (or missing data) will lead to a great source of uncertainty and may lead to wrong results. Worst case scenarios have been used to solve this issue without success. This paper presents a new concept: probabilistic digital twins for pipelines. Probabilistic digital twins do not lose uncertainty as results pass from one model to another, thus providing greater confidence in the final results. This publication reviews the probabilistic digital twin concept and demonstrates how it can be implemented using gas pipeline data from West Pipeline Company, CNPC.

Digitalization in the oil and gas industry has led to the formation of digital twins. Digital twins bring closer the physical and virtual world as data is transmitted seamlessly between real time sensors, databases and models. The strength of the digital twin concept is the interconnectivity of data and models. Any model can use any combination of inputs (e.g. operator owned data sets and sensors, third-party databases such as soil composition or weather data, results from other models such as flow assurance, threat modelling or risk modelling). Consequently, the result of one model may become the input of another. This strength is also a weakness, as uncertain (or missing data) will lead to a great source of uncertainty and may lead to wrong results. Worst case scenarios have been used to solve this issue without success. This paper presents a new concept: probabilistic digital twins for pipelines. Probabilistic digital twins do not lose uncertainty as results pass from one model to another, thus providing greater confidence in the final results. This publication reviews the probabilistic digital twin concept and demonstrates how it can be implemented using gas pipeline data from West Pipeline Company, CNPC.

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Corrosion Data Management Using 3D Visualisation and a Digital Twin

Product Number: 51320-14535-SG
Author: Robert Adey, Cristina Peratta, John Baynham
Publication Date: 2020
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There is a gap between the Integrity management systems used by companies to manage their assets and the needs of the CP engineer. Integrity management systems do not fully meet the needs of the engineer responsible for corrosion as they do not provide access and visualizations of all the data the engineer needs to make fast and informed decisions. There is also often no easy way to see the trends in the data, or easily access the relevant video and photographic data also recorded during the survey.

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The paper will describe the system developed and present applications of both the 3D corrosion data visualisation and the simulation based digital twin
Picture for The Promise of a Holistic Digital Strategy for Corrosion and Integrity Management
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51318-10831-The Promise of a Holistic Digital Strategy for Corrosion and Integrity Management

Product Number: 51318-10831-SG
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 An overview and possible methods to capture the full potential of digital technologies for corrosion and integrity management with a focus on upstream pipelines. Considering current industry offerings but also potential new technologies.
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A large power transmitter completed a multiyear corrosion study to verify the corrosion rate models for zinc and steel. As a result of that study, a long term field corrosion monitoring program, at 125 sites, was initiated.
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