The Digitalization Journey of the Brage Digital Twin

Kronberger, Peter; Dabrowski, Peter; Chacón, Joel; Bangert, Patrick

doi:10.2118/200728-ms

Cited by 4 publications

(5 citation statements)

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“…Embora (TAO et al, 2019) destaque um componente explícito na arquitetura de um GD para lidar com a gestão dos dados, ele não detalha suas funcionalidades. Argumentamos que o componente gestão de dados pode ser aproximado da funcionalidade de dados e gerenciamento de conhecimento dos Data Lakes (KRONBERGER et al, 2020;CORREIA et al, 2022) e visam alcançar uma melhor compreensão das soluções do estado da arte em uma análise de granularidade fina.…”

Section: Discussionunclassified

“…Although (TAO et al, 2019) highlights an explicit component in the architecture of a DT to handle data management, it does not detail the support it must provide. We argue that the DM component can be approximated to the data and knowledge management functionality in Data Lakes (KRONBERGER et al, 2020;CORREIA et al, 2022), and aim to reach a better comprehension of the state-of-the-art solutions in a fine-grained analysis.…”

Section: List Of Figuresmentioning

confidence: 99%

“…Its role and functionalities are issues that need to be delimited, and we aim to understand more about these issues through this SLR. As a starting point, we understand that the functions of the DM component can be approximated to the data and knowledge management functionality in Data Lakes (KRONBERGER et al, 2020). In the light of Big Data value chain activities (CURRY, 2016), we detail in Section 2.5 the key DM issues to be handled by the DM component of a DT.…”

Section: Dt Definitionsmentioning

confidence: 99%

“…It should support the integration of any type of data; support for logical and physical organization of data; accessibility to various kinds of users; metadata catalog to enforce quality; and scalability in terms of storage and processing. The functions of the DM component can be approximated to the data and knowledge management functionality in Data Lakes (KRONBERGER et al, 2020;CORREIA et al, 2022).…”

Section: Data Management Issues In Digital Twinsmentioning

confidence: 99%

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Data management in digital twins: a systematic literature review

2023

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The Internet of Things (IoT), personal and wearable devices, and continuous advances in data-gathering techniques have significantly increased the amount of relevant data that can be leveraged for innovative real-time, data-driven applications. Digital Twins (DTs) are virtual representations of physical objects which are fully integrated and in which the automatic data exchange occurs in a bidirectional way. DTs and big data are mutually reinforcing technologies since huge volumes of data representing the physical/virtual worlds are collected, transformed, and generated through models to aggregate value to the business. Modern DTs follow a five-component architecture, which includes a Data Management (DM) component that bridges a physical system, a mirrored virtual one, and services components. However, there is no clarity on the functionality required for the DM component. This work presents a Systematic Literature Review on DM issues and proposed solutions in the DT context. We analyzed DM under the big data value chain activities, highlighting key issues to be addressed: data heterogeneity, interoperability, integration, data search/discovery, and quality. In addition to surveying existing solutions for handling these issues, we contextualized them in the domain and function for which the DT was proposed, the type of data dealt with, and the technical infrastructure. The compilation of these solutions sheds light on the functionality of the DM component in a DT, trends, and opportunities. Our main findings revealed that the maturity level assumed for the DM component is at an early stage. The most mature solutions were proposed for the industry domain, and many of them assume humans as the ultimate information consumers. Data integration is the prevalent DM issue addressed due to the bridging role of the DM component, and cloud computing is the key implementation technology. Among the research opportunities are reference data management architectures, adoption of industry standards and ontologies, interoperability among distinct DTs, the development of agnostic standard implementations, and data provenance mechanisms.

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Section: Discussionunclassified

Section: List Of Figuresmentioning

confidence: 99%

Section: Dt Definitionsmentioning

confidence: 99%

Section: Data Management Issues In Digital Twinsmentioning

confidence: 99%

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Data management in digital twins: a systematic literature review

2023

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“…The DFC acts as a bridge between all the other systems, collecting and consolidating data from separate and heterogeneous systems, to generate driving commands for the other components. In this role, the functions of the DFC can be approximated to the data and knowledge management functionality in Data Lakes [Kronberger et al 2020]. A Data Lake should provide support for [Sawadogo and Darmont 2021]: (1) storage of large volumes of data in their native format (structured, semi-structured and unstructured data); (2) data search and processing; (3) data life-cycle control; (4) metadata cataloging and management to ensure data quality; (5) implementation of policies and rules for data governance; (6) scalability of storage and processing and (7) an integrated architecture that facilitates data organization for better navigation and data manipulation.…”

Section: Related Workmentioning

confidence: 99%

Data Management in Digital Twins for the Oil and Gas Industry: beyond the OSDU Data Platform

Correia

Rodrigues

Santos

et al. 2022

jidm

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Competitiveness in the Oil and Gas (O&G) sector has required high technological investments for datacentric decisions. One of the trends is the adoption of Digital Twins (DTs), which use virtual spaces and advanced analytical services to monitor and improve physical spaces. Central to the interconnection of these systems is a Data Fusion Core (DFC) component, which provides data management capabilities. Although the literature has proposed data management functionality in the scope of specific O&G DT applications, different joint efforts towards standardization can be found to deal with data integration and interoperability in the industry. The Open Subsurface Data Universe (OSDU) data platform is an initiative by several partners members of The Open Group consortium created to eliminate data silos in the O&G ecosystem and leverage innovation through a data-driven approach. In this article, we look at the convergence of this effort in providing data management functionalities for digital twins, highlighting strengths, gaps, and opportunities. We investigated the extent to which the OSDU data platform meets the needs of a DFC implementation, with a focus on interoperability, integration, governance, and data lineage. We also propose additional resources for data management in this context, namely data enrichment, workflows, and data lineage. Our main contributions are: (i) analysis of possible data management capabilities for creating a working DFC for an O&G DT and (ii) initial ideas on the complementary role of OSDU data representation and ontologies and how this semantic enrichment can be leveraged in a DFC of a DT.

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Real-Time Reamer Vibration Predicting, Monitoring, and Decision-Making using Hybrid Modeling and a Process Digital Twin

Shi

Dourthe

et al. 2022

Day 2 Wed, March 09, 2022

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In hole enlargement while drilling (HEWD) operations, reamers are extensively used to enlarge the pilot hole. Reamer wipeout failure can cause additional bottom hole assembly (BHA) trips, which can cost operators millions of dollars. Excessive reamer shock and vibration is a leading cause of reamer wipeout; therefore, careful monitoring of reamer vibration is important in mitigating such a risk. Currently, downhole vibration sensors and drilling dynamics simulations are used to comprehend and reduce downhole vibration, but vibration sensors cannot be placed exactly at the reamer to monitor the vibrations in real time. Drilling dynamics simulations are difficult to calibrate and are computationally expensive for use in real time; therefore, the real-time reamer vibration status is typically unknown during drilling operations. A process digital twin using a hybrid modeling approach is proposed and tested to address the vibration issue. Large amounts of field data are used in advanced drilling dynamics simulations to calibrate the HEWD runs. For each HEWD section, calibrated drilling dynamics simulations are performed to comprehend the downhole vibration at the reamer and downhole vibration sensors. A surrogate regression model between reamer vibration and sensor vibration is built using machine learning. This surrogate model is implemented in a drilling monitoring software platform as a process digital twin. During drilling, the surrogate model uses downhole measurement while drilling (MWD) data as input to predict reamer vibration. Wipeout risk levels are calculated and sent to the operators for real-time decision making to reduce the possibility of reamer wipeout. Large volumes of reamer field data, including field recorded vibration and reamer dull conditions were used to validate the digital twin workflow. Then, the process digital twin was implemented and tested in two reamer runs in the Gulf of Mexico. A downhole high-frequency sensor was placed at the reamer in one field run and the recorded sensor vibration data and corresponding reamer dull conditions showed a very good match with the real-time digital twin predictions. The field tests demonstrated the feasibility and accuracy of the digital twin and established a method for aiding in future real-time decision making. State-of-the-art downhole sensors, drilling dynamics simulation packages, large amounts of field data, and a hybrid approach are the solutions to building, calibrating, and field testing the reamer digital twin to ensure its effectiveness and accuracy. Such a hybrid modeling approach can not only be applied to reamers, but also to other critical BHA components.

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The Digitalization Journey of the Brage Digital Twin

Cited by 4 publications

References 1 publication

Data management in digital twins: a systematic literature review

Data management in digital twins: a systematic literature review

Data Management in Digital Twins for the Oil and Gas Industry: beyond the OSDU Data Platform

Real-Time Reamer Vibration Predicting, Monitoring, and Decision-Making using Hybrid Modeling and a Process Digital Twin

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