Immersive Safety Handling and Training
Department of Petroleum Engineering and Applied Geophysics
The Norwegian University of Science and Technology
S.P. Andersens vei 15A, N-7491 Trondheim, Norway
e-mail: {sjovoll/egil.tjaland}@ntnu.no
Received:
Rec. 15 May 2006
DOI: 10.12921/cmst.2006.SI.01.55-60
OAI: oai:lib.psnc.pl:603
Abstract:
A central challenge for the oil industry is to make correct decisions in abnormal, complex and time-critical settings. This is to ensure safety, regularity and optimized operation and production. A new information platform has been developed to identify and localize unwanted events, and to train control room operators for optimal decision making. This platform has been implemented in an immersive CAVE environment to ensure a realistic setting and a better understanding of the problem. The system reports unwanted events in a 3D environment, and the user may obtain error handling procedures to rectify the given problem. These procedures are retrieved by semantic searches in an ontology. The ontology is stored in a central repository, and accessed through a client-server connection.
Key words:
immersive, Integrated Operations, safety, Semantic Web, training, Virtual Reality
References:
[1] M. T. Brannick, E. Salas and C. Prince (ed.), Team performance assessment and measurement: Theory, methods, and applications. Mahwah, JN: Lawrence Erlbaum 1997.
[2] R. H. Flint, Crew resource management for teams in the offshore oil industry, Journal of European Industrial Training, Vol 19, Issue 9, 23-27 (1995).
[3] D. Schaffer, Z. Zuo, S. Greenberg, L. Bartram, J. Dill, S. Dubs and M. Roseman, Navigating hierarchically clustered networks through fisheye and full-zoom methods. ACM Transactions on Computer-Human Interaction 3(2), 162-188 (1996).
[4] F. Chen, E. H. C Choi, N. Ruiz, Y. Shi and R. Taib, User Interface Design and Evaluation for Control Room, Proceedings of OZCHI 2005, Canberre, Australia, Nov. 23-25 (2005).
[5] E. Kalogerakis, S. Christodoulakis and N. Moumoutzis, Coupling Ontologies with Graphics Content for Knowledge Driven Visualization in: B. Frölich, D. Bowman and H. Iwata (ed.) Proceedings of IEEE Virtual Reality 2006, pp. 43-50 (2006).
[6] C. . Cera, W. C. Regli, I. Braude, Y. Shapirstein and C.V. Foster, In: A Collaborative 3D Environment for Authoring Design Semantics, IEEE Computer Graphics and Applications,
Special Issue on “Computer-Aided Design”, 22(3), 42-55 (2002).
[7] N. Sandsmark and S. Mehta, Integrated Information Platform for Reservoir and Subsea Production Systems, POSC Caesar Assosiation (2004).
[8] R. Fjellheim and D. Norheim, AKSIO – An application of Semantic Web technology for knowledge management in the petroleum industry, ISWC2005 Poster Submission (2005).
[9] J. Kleppe, M. Landrø, B. Ursin, S. Sangesland and A. Nystad, BRU-report, Internal publication at The Norwegian University of Science and Technology (2005).
[10] T. Berners-Lee, J. Hendler and O. Lassila, The Semantic Web, Scientific American, May (2001).
[11] J. Z. Pan and I. Horrocks. Metamodeling architecture of web ontology languages, Proceedings of the Semantic Web Working Symposium, Stanford, 131-149, July (2001).
[12] J. Broekstra, M. Klein, S. Decker, D. Fensel, F. van Harmelen and I. Horrocks, Enabling knowledge representation on the Web by Extending RDF Schema, Proceedings of the Tenth International World Wide Web Conference (2001).
[13] SGI. OpenGL Performer [online]. Available from: http://www.sgi.com/products/software/performer/
[14] VRCO. CAVELib [online]. Available from: http://www.vrco.com/CAVELib/OverviewCAVELib.html
[15] Jeff Donahoo, Practical C++ sockets [online]. Available from: http://cs.ecs.baylor.edu/~donahoo/ practical/CSockets/practical/
[16] TinyXml Projet. Tinyxml package [online]. Available from: http://www.grinninglizard.com/tinyxml/
[17] E. Tjåland, Visualization of Real-time Production Data from Subsea Installations, SGIUG 2005, Munich, Session C-7 VIZ (2005).
[18] M. N. Louka and C. Balducelli, Virtual Reality Tools for Emergency Operation Support and Training In Proceedings of TIEMS 2001 (The International Emergency Management Society), Oslo, June (2001).
A central challenge for the oil industry is to make correct decisions in abnormal, complex and time-critical settings. This is to ensure safety, regularity and optimized operation and production. A new information platform has been developed to identify and localize unwanted events, and to train control room operators for optimal decision making. This platform has been implemented in an immersive CAVE environment to ensure a realistic setting and a better understanding of the problem. The system reports unwanted events in a 3D environment, and the user may obtain error handling procedures to rectify the given problem. These procedures are retrieved by semantic searches in an ontology. The ontology is stored in a central repository, and accessed through a client-server connection.
Key words:
immersive, Integrated Operations, safety, Semantic Web, training, Virtual Reality
References:
[1] M. T. Brannick, E. Salas and C. Prince (ed.), Team performance assessment and measurement: Theory, methods, and applications. Mahwah, JN: Lawrence Erlbaum 1997.
[2] R. H. Flint, Crew resource management for teams in the offshore oil industry, Journal of European Industrial Training, Vol 19, Issue 9, 23-27 (1995).
[3] D. Schaffer, Z. Zuo, S. Greenberg, L. Bartram, J. Dill, S. Dubs and M. Roseman, Navigating hierarchically clustered networks through fisheye and full-zoom methods. ACM Transactions on Computer-Human Interaction 3(2), 162-188 (1996).
[4] F. Chen, E. H. C Choi, N. Ruiz, Y. Shi and R. Taib, User Interface Design and Evaluation for Control Room, Proceedings of OZCHI 2005, Canberre, Australia, Nov. 23-25 (2005).
[5] E. Kalogerakis, S. Christodoulakis and N. Moumoutzis, Coupling Ontologies with Graphics Content for Knowledge Driven Visualization in: B. Frölich, D. Bowman and H. Iwata (ed.) Proceedings of IEEE Virtual Reality 2006, pp. 43-50 (2006).
[6] C. . Cera, W. C. Regli, I. Braude, Y. Shapirstein and C.V. Foster, In: A Collaborative 3D Environment for Authoring Design Semantics, IEEE Computer Graphics and Applications,
Special Issue on “Computer-Aided Design”, 22(3), 42-55 (2002).
[7] N. Sandsmark and S. Mehta, Integrated Information Platform for Reservoir and Subsea Production Systems, POSC Caesar Assosiation (2004).
[8] R. Fjellheim and D. Norheim, AKSIO – An application of Semantic Web technology for knowledge management in the petroleum industry, ISWC2005 Poster Submission (2005).
[9] J. Kleppe, M. Landrø, B. Ursin, S. Sangesland and A. Nystad, BRU-report, Internal publication at The Norwegian University of Science and Technology (2005).
[10] T. Berners-Lee, J. Hendler and O. Lassila, The Semantic Web, Scientific American, May (2001).
[11] J. Z. Pan and I. Horrocks. Metamodeling architecture of web ontology languages, Proceedings of the Semantic Web Working Symposium, Stanford, 131-149, July (2001).
[12] J. Broekstra, M. Klein, S. Decker, D. Fensel, F. van Harmelen and I. Horrocks, Enabling knowledge representation on the Web by Extending RDF Schema, Proceedings of the Tenth International World Wide Web Conference (2001).
[13] SGI. OpenGL Performer [online]. Available from: http://www.sgi.com/products/software/performer/
[14] VRCO. CAVELib [online]. Available from: http://www.vrco.com/CAVELib/OverviewCAVELib.html
[15] Jeff Donahoo, Practical C++ sockets [online]. Available from: http://cs.ecs.baylor.edu/~donahoo/ practical/CSockets/practical/
[16] TinyXml Projet. Tinyxml package [online]. Available from: http://www.grinninglizard.com/tinyxml/
[17] E. Tjåland, Visualization of Real-time Production Data from Subsea Installations, SGIUG 2005, Munich, Session C-7 VIZ (2005).
[18] M. N. Louka and C. Balducelli, Virtual Reality Tools for Emergency Operation Support and Training In Proceedings of TIEMS 2001 (The International Emergency Management Society), Oslo, June (2001).
