Too much agreement kills a chat. --
Eldridge Cleaver
The Energy Conference Network (https://energyconferencenetwork.com/
) has announced the Digitalization in Oil and Gas conference
(https://www.digitalizationoilgas.com/23/2647079),
scheduled for September 14-15, 2023 in Houston, Texas.
REGISTRANTS include … Aramco, Dow, ExxonMobil, Sabic, Chevron … to name a few.
The conference is organized into FIVE TRACKS … IoT in Oil & Gas, Digital
Twins in Oil & Gas, Blockchain in Oil & Gas, Edge Computing
Technologies in Oil & Gas, and Connectivity in Oil & Gas.
TIP:
View a recent Desulfurization Blog
post: Reviews and
PDFs (http://desulf.blogspot.com/2023/06/reviews-and-pdfs.html)
for a list of free full text articles on the five conference tracks. Pick out
one or two in preparation for the conference.
For example:
///////
Industrial
Engineering with Large Language Models: A case study of ChatGPT's performance on Oil & Gas problems
Large Language Models (LLMs) have shown great potential in solving complex
problems in various fields, including oil and gas engineering and other
industrial engineering disciplines like factory automation, PLC programming
etc. However, automatic identification of strong and weak solutions to
fundamental physics equations governing several industrial processes remain a
challenging task. This paper identifies the limitation of current LLM
approaches, particularly ChatGPT in selected
practical problems native to oil and gas engineering but not exclusively. The
performance of ChatGPT in solving complex
problems in oil and gas engineering is discussed and the areas where LLMs are
most effective are presented.
Cite as: arXiv:2304.14354
source: https://doi.org/10.48550/arXiv.2304.14354
///////
And here’s another …
///////
Blockchain in Oil and Gas Supply Chain: A Literature Review from User
Security and Privacy Perspective (2023)
International Symposium on Human Aspects of Information Security and
Assurance
The oil and gas industry grapples with supply chain process challenges and is
known to have high risks, significant investments, and large asset volumes.
These include (i) tracking extracted resources, (ii) managing equipment and
assets, (iii) preventing company data leaks, (iv) managing data, and (v)
ensuring process security and integrity. Such issues can result in human
errors, misguided decisions due to inaccurate data, inflated operating costs,
transaction delays, and fraud. Blockchain technology could provide solutions to
some of these problems. For example, it facilitates reliable and secure data
storage, ensuring data integrity. Additionally, blockchain-based smart
contracts could deter oil trade fraud by automating contract execution when
agreement conditions are met. By incorporating blockchain technology,
businesses in the oil and gas sector can enhance their operations’ efficiency,
transparency, and security, leading to improved decision-making and cost
savings.
source: https://doi.org/10.48550/arXiv.2306.16576
///////
Google® Better!
Jean Steinhardt served as Librarian,
Aramco Americas (https://americas.aramco.com/
), Engineering Division, for 13 years. He now heads Jean Steinhardt Consulting
LLC, producing the same high quality research that he performed for Aramco.
Follow Jean’s blog at: http://desulf.blogspot.com/
for continuing tips on effective online research
Email Jean at jstoneheart@gmail.com with
questions on research, training, or anything else
Showing posts with label DIGITAL TWINS. Show all posts
Showing posts with label DIGITAL TWINS. Show all posts
Sunday, August 6, 2023
Conference Alert-Digitalization in Oil and Gas
Saturday, March 14, 2020
Congratulations! You've Got Twins!
There are two things in life for which we
are never truly prepared: twins. – Josh Billings
As an online researcher, I am always grateful to find a review article that explains a buzz phrase like Digital Twin. That’s why I like the article profiled below. It describes the digital twin concept as well any other source I have seen. BONUS … you can read the full text of the article at no charge.
TIP: Read on.
///////
CIRP Journal of Manufacturing Science and Technology
Available online 9 March 2020
In Press, Corrected Proof
Characterising the Digital Twin: A systematic literature review
David Jones, Chris Snider, Aydin Nassehi, Jason Yon, Ben Hicks
Department of Mechanical Engineering, University of Bristol, United Kingdom
Under a Creative Commons license
Abstract
While there has been a recent growth of interest in the Digital Twin, a variety of definitions employed across industry and academia remain. There is a need to consolidate research such to maintain a common understanding of the topic and ensure future research efforts are to be based on solid foundations. Through a systematic literature review and a thematic analysis of 92 Digital Twin publications from the last ten years, this paper provides a characterisation of the Digital Twin, identification of gaps in knowledge, and required areas of future research. In characterising the Digital Twin, the state of the concept, key terminology, and associated processes are identified, discussed, and consolidated to produce 13 characteristics (Physical Entity/Twin; Virtual Entity/Twin; Physical Environment; Virtual Environment; State; Realisation; Metrology; Twinning; Twinning Rate; Physical-to-Virtual Connection/Twinning; Virtual-to-Physical Connection/Twinning; Physical Processes; and Virtual Processes) and a complete framework of the Digital Twin and its process of operation. Following this characterisation, seven knowledge gaps and topics for future research focus are identified: Perceived Benefits; Digital Twin across the Product Life-Cycle; Use-Cases; Technical Implementations; Levels of Fidelity; Data Ownership; and Integration between Virtual Entities; each of which are required to realise the Digital Twin.
Keywords: Digital Twin, Virtual Twin
Introduction
Typically described as consisting of a physical entity, a virtual counterpart, and the data connections in between, the Digital Twin is increasingly being explored as a means of improving the performance of physical entities through leveraging computational techniques, themselves enabled through the virtual counterpart. Interest in the Digital Twin has greatly increased in the past five years across both academia and industry, accompanied by a growth in the number of related publications, processes, concepts, and envisaged benefits (see Fig. 1). Missing from literature, however, is a consolidated and consistent view on what the Digital Twin is, and how the concept is evolving to meet the needs of the many use-cases to which it is being tied. This lack of consistency has led to a breadth of characterisations and definitions for digital twins and the digital twinning process that, due to the breadth of frameworks applied across industry, leads to a risk of diluting the concept and missing the benefits that the Digital Twin was originally devised to deliver.
The origin of the Digital Twin
The origin of the Digital Twin is attributed to Michael Grieves and his work with John Vickers of NASA, with Grieves presenting the concept in a lecture on product life-cycle management in 2003 [33]. In a time when Grieves describes virtual product representations as “…relatively new and immature” and data collected about physical products as “…limited, manually collected, and mostly paper-based”, Grieves and Vickers saw a world where a virtual model of a product would provide the foundations for product life-cycle management.
The initial description defines a Digital Twin as a virtual representation of a physical product containing information about said product, with its origins in the field of product life-cycle management. In an early paper [33] Grieves expands on this definition by describing the Digital Twin as consisting of three components, a physical product, a virtual representation of that product, and the bi-directional data connections that feed data from the physical to the virtual representation, and information and processes from the virtual representation to the physical. Grieves depicted this flow as a cycle between the physical and virtual states (mirroring or twinning); of data from the physical to the virtual, and of information and processes from the virtual to the physical (see Fig. 2). The virtual spaces themselves consisting of any number of sub-spaces that enable specific virtual operations: modelling, testing, optimisation, etc.
Free full text source: https://www.cdbb.cam.ac.uk/Resources/ResoucePublications/BISBIMstrategyReport.pdf
///////
Google® Better!
Jean Steinhardt served as Librarian, Aramco Services, Engineering Division, for 13 years. He now heads Jean Steinhardt Consulting LLC, producing the same high quality research that he performed for Aramco.
Follow Jean’s blog at: http://desulf.blogspot.com/ for continuing tips on effective online research
Email Jean at research@jeansteinhardtconsulting.com with questions on research, training, or anything else
Visit Jean’s Web site at http://www.jeansteinhardtconsulting.com/ to see examples of the services we can provide
As an online researcher, I am always grateful to find a review article that explains a buzz phrase like Digital Twin. That’s why I like the article profiled below. It describes the digital twin concept as well any other source I have seen. BONUS … you can read the full text of the article at no charge.
TIP: Read on.
///////
CIRP Journal of Manufacturing Science and Technology
Available online 9 March 2020
In Press, Corrected Proof
Characterising the Digital Twin: A systematic literature review
David Jones, Chris Snider, Aydin Nassehi, Jason Yon, Ben Hicks
Department of Mechanical Engineering, University of Bristol, United Kingdom
Under a Creative Commons license
Abstract
While there has been a recent growth of interest in the Digital Twin, a variety of definitions employed across industry and academia remain. There is a need to consolidate research such to maintain a common understanding of the topic and ensure future research efforts are to be based on solid foundations. Through a systematic literature review and a thematic analysis of 92 Digital Twin publications from the last ten years, this paper provides a characterisation of the Digital Twin, identification of gaps in knowledge, and required areas of future research. In characterising the Digital Twin, the state of the concept, key terminology, and associated processes are identified, discussed, and consolidated to produce 13 characteristics (Physical Entity/Twin; Virtual Entity/Twin; Physical Environment; Virtual Environment; State; Realisation; Metrology; Twinning; Twinning Rate; Physical-to-Virtual Connection/Twinning; Virtual-to-Physical Connection/Twinning; Physical Processes; and Virtual Processes) and a complete framework of the Digital Twin and its process of operation. Following this characterisation, seven knowledge gaps and topics for future research focus are identified: Perceived Benefits; Digital Twin across the Product Life-Cycle; Use-Cases; Technical Implementations; Levels of Fidelity; Data Ownership; and Integration between Virtual Entities; each of which are required to realise the Digital Twin.
Keywords: Digital Twin, Virtual Twin
Introduction
Typically described as consisting of a physical entity, a virtual counterpart, and the data connections in between, the Digital Twin is increasingly being explored as a means of improving the performance of physical entities through leveraging computational techniques, themselves enabled through the virtual counterpart. Interest in the Digital Twin has greatly increased in the past five years across both academia and industry, accompanied by a growth in the number of related publications, processes, concepts, and envisaged benefits (see Fig. 1). Missing from literature, however, is a consolidated and consistent view on what the Digital Twin is, and how the concept is evolving to meet the needs of the many use-cases to which it is being tied. This lack of consistency has led to a breadth of characterisations and definitions for digital twins and the digital twinning process that, due to the breadth of frameworks applied across industry, leads to a risk of diluting the concept and missing the benefits that the Digital Twin was originally devised to deliver.
The origin of the Digital Twin
The origin of the Digital Twin is attributed to Michael Grieves and his work with John Vickers of NASA, with Grieves presenting the concept in a lecture on product life-cycle management in 2003 [33]. In a time when Grieves describes virtual product representations as “…relatively new and immature” and data collected about physical products as “…limited, manually collected, and mostly paper-based”, Grieves and Vickers saw a world where a virtual model of a product would provide the foundations for product life-cycle management.
The initial description defines a Digital Twin as a virtual representation of a physical product containing information about said product, with its origins in the field of product life-cycle management. In an early paper [33] Grieves expands on this definition by describing the Digital Twin as consisting of three components, a physical product, a virtual representation of that product, and the bi-directional data connections that feed data from the physical to the virtual representation, and information and processes from the virtual representation to the physical. Grieves depicted this flow as a cycle between the physical and virtual states (mirroring or twinning); of data from the physical to the virtual, and of information and processes from the virtual to the physical (see Fig. 2). The virtual spaces themselves consisting of any number of sub-spaces that enable specific virtual operations: modelling, testing, optimisation, etc.
Free full text source: https://www.cdbb.cam.ac.uk/Resources/ResoucePublications/BISBIMstrategyReport.pdf
///////
Google® Better!
Jean Steinhardt served as Librarian, Aramco Services, Engineering Division, for 13 years. He now heads Jean Steinhardt Consulting LLC, producing the same high quality research that he performed for Aramco.
Follow Jean’s blog at: http://desulf.blogspot.com/ for continuing tips on effective online research
Email Jean at research@jeansteinhardtconsulting.com with questions on research, training, or anything else
Visit Jean’s Web site at http://www.jeansteinhardtconsulting.com/ to see examples of the services we can provide
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