Towards dynamic data-driven management of the ruby gulch waste repository

Manish Parashar; Vincent Matossian; Hector Klie; Sunil G. Thomas; Mary F. Wheeler; Tahsin Kurc; Joel Saltz; Roelof Versteeg

doi:10.1007/11758532_52

Towards dynamic data-driven management of the ruby gulch waste repository

Manish Parashar
, Vincent Matossian
, Hector Klie
, Sunil G. Thomas
, Mary F. Wheeler
, Tahsin Kurc
, Joel Saltz
, Roelof Versteeg

Biomedical Informatics

Rutgers - The State University of New Jersey, New Brunswick
University of Texas at Austin
Idaho National Laboratory

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Scopus citations

Abstract

Previous work in the Instrumented Oil-Field DDDAS project has enabled a new generation of data-driven, interactive and dynamically adaptive strategies for subsurface characterization and oil reservoir management. This work has led to the implementation of advanced multiphysics, multi-scale, and multi-block numerical models and an autonomic software stack for DDDAS applications. The stack implements a Grid-based adaptive execution engine, distributed data management services for real-time data access, exploration, and coupling, and self-managing middleware services for seamless discovery and composition of components, services, and data on the Grid. This paper investigates how these solutions can be leveraged and applied to address another DDDAS application of strategic importance - the data-driven management of Ruby Gulch Waste Repository.

Original language	English
Title of host publication	Computational Science - ICCS 2006
Subtitle of host publication	6th International Conference, Proceedings
Publisher	Springer Verlag
Pages	384-392
Number of pages	9
ISBN (Print)	3540343830, 9783540343837
DOIs	https://doi.org/10.1007/11758532_52
State	Published - 2006
Event	ICCS 2006: 6th International Conference on Computational Science - Reading, United Kingdom Duration: May 28 2006 → May 31 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3993 LNCS - III
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	ICCS 2006: 6th International Conference on Computational Science
Country/Territory	United Kingdom
City	Reading
Period	05/28/06 → 05/31/06

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10.1007/11758532_52

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Parashar, M., Matossian, V., Klie, H., Thomas, S. G., Wheeler, M. F., Kurc, T., Saltz, J., & Versteeg, R. (2006). Towards dynamic data-driven management of the ruby gulch waste repository. In Computational Science - ICCS 2006: 6th International Conference, Proceedings (pp. 384-392). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3993 LNCS - III). Springer Verlag. https://doi.org/10.1007/11758532_52

Parashar, Manish ; Matossian, Vincent ; Klie, Hector et al. / Towards dynamic data-driven management of the ruby gulch waste repository. Computational Science - ICCS 2006: 6th International Conference, Proceedings. Springer Verlag, 2006. pp. 384-392 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{434ad794cdc04f4e88b32350d495a4a7,

title = "Towards dynamic data-driven management of the ruby gulch waste repository",

abstract = "Previous work in the Instrumented Oil-Field DDDAS project has enabled a new generation of data-driven, interactive and dynamically adaptive strategies for subsurface characterization and oil reservoir management. This work has led to the implementation of advanced multiphysics, multi-scale, and multi-block numerical models and an autonomic software stack for DDDAS applications. The stack implements a Grid-based adaptive execution engine, distributed data management services for real-time data access, exploration, and coupling, and self-managing middleware services for seamless discovery and composition of components, services, and data on the Grid. This paper investigates how these solutions can be leveraged and applied to address another DDDAS application of strategic importance - the data-driven management of Ruby Gulch Waste Repository.",

author = "Manish Parashar and Vincent Matossian and Hector Klie and Thomas, \{Sunil G.\} and Wheeler, \{Mary F.\} and Tahsin Kurc and Joel Saltz and Roelof Versteeg",

year = "2006",

doi = "10.1007/11758532\_52",

language = "English",

isbn = "3540343830",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "384--392",

booktitle = "Computational Science - ICCS 2006",

note = "ICCS 2006: 6th International Conference on Computational Science ; Conference date: 28-05-2006 Through 31-05-2006",

}

Parashar, M, Matossian, V, Klie, H, Thomas, SG, Wheeler, MF, Kurc, T , Saltz, J & Versteeg, R 2006, Towards dynamic data-driven management of the ruby gulch waste repository. in Computational Science - ICCS 2006: 6th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3993 LNCS - III, Springer Verlag, pp. 384-392, ICCS 2006: 6th International Conference on Computational Science, Reading, United Kingdom, 05/28/06. https://doi.org/10.1007/11758532_52

Towards dynamic data-driven management of the ruby gulch waste repository. / Parashar, Manish; Matossian, Vincent; Klie, Hector et al.
Computational Science - ICCS 2006: 6th International Conference, Proceedings. Springer Verlag, 2006. p. 384-392 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3993 LNCS - III).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Towards dynamic data-driven management of the ruby gulch waste repository

AU - Parashar, Manish

AU - Matossian, Vincent

AU - Klie, Hector

AU - Thomas, Sunil G.

AU - Wheeler, Mary F.

AU - Kurc, Tahsin

AU - Saltz, Joel

AU - Versteeg, Roelof

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AB - Previous work in the Instrumented Oil-Field DDDAS project has enabled a new generation of data-driven, interactive and dynamically adaptive strategies for subsurface characterization and oil reservoir management. This work has led to the implementation of advanced multiphysics, multi-scale, and multi-block numerical models and an autonomic software stack for DDDAS applications. The stack implements a Grid-based adaptive execution engine, distributed data management services for real-time data access, exploration, and coupling, and self-managing middleware services for seamless discovery and composition of components, services, and data on the Grid. This paper investigates how these solutions can be leveraged and applied to address another DDDAS application of strategic importance - the data-driven management of Ruby Gulch Waste Repository.

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DO - 10.1007/11758532_52

M3 - Conference contribution

AN - SCOPUS:33746775360

SN - 3540343830

SN - 9783540343837

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Parashar M, Matossian V, Klie H, Thomas SG, Wheeler MF, Kurc T et al. Towards dynamic data-driven management of the ruby gulch waste repository. In Computational Science - ICCS 2006: 6th International Conference, Proceedings. Springer Verlag. 2006. p. 384-392. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11758532_52

Towards dynamic data-driven management of the ruby gulch waste repository

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