Integration of expert and data-driven workflows to manage reservoir and well life cycle in Arctic conditions using innovative SICLO methodology

Research output: Contribution to conference › Paper › peer-review

Standard

Integration of expert and data-driven workflows to manage reservoir and well life cycle in Arctic conditions using innovative SICLO methodology. / Antonic, Miroslav; Solesa, Miso; Zolotukhin, Anatoly et al.
2019. Paper presented at Second Conference of Computational Methods in Offshore Technology and First Conference of Oil and Gas Technology in Cold Climate, Stavanger, Norway.

Research output: Contribution to conference › Paper › peer-review

Harvard

Antonic, M, Solesa, M, Zolotukhin, A, Rakic, D & Aleksic, M 2019, 'Integration of expert and data-driven workflows to manage reservoir and well life cycle in Arctic conditions using innovative SICLO methodology', Paper presented at Second Conference of Computational Methods in Offshore Technology and First Conference of Oil and Gas Technology in Cold Climate, Stavanger, Norway, 27/11/19 - 29/11/19. https://doi.org/10.1088/1757-899X/700/1/012056

APA

Antonic, M., Solesa, M., Zolotukhin, A., Rakic, D., & Aleksic, M. (2019). Integration of expert and data-driven workflows to manage reservoir and well life cycle in Arctic conditions using innovative SICLO methodology. Paper presented at Second Conference of Computational Methods in Offshore Technology and First Conference of Oil and Gas Technology in Cold Climate, Stavanger, Norway. https://doi.org/10.1088/1757-899X/700/1/012056

Vancouver

Antonic M, Solesa M, Zolotukhin A, Rakic D, Aleksic M. Integration of expert and data-driven workflows to manage reservoir and well life cycle in Arctic conditions using innovative SICLO methodology. 2019. Paper presented at Second Conference of Computational Methods in Offshore Technology and First Conference of Oil and Gas Technology in Cold Climate, Stavanger, Norway. doi: 10.1088/1757-899X/700/1/012056

Author

Antonic, Miroslav ; Solesa, Miso ; Zolotukhin, Anatoly et al. / Integration of expert and data-driven workflows to manage reservoir and well life cycle in Arctic conditions using innovative SICLO methodology. Paper presented at Second Conference of Computational Methods in Offshore Technology and First Conference of Oil and Gas Technology in Cold Climate, Stavanger, Norway.13 p.

Bibtex - Download

@conference{d759b9759e204adfa83f2192b925d710,
title = "Integration of expert and data-driven workflows to manage reservoir and well life cycle in Arctic conditions using innovative SICLO methodology",
abstract = "SICLO (Source of data and information; Input data; Calculation/Analytic; Logic Analysis; Output/Value Delivery) methodology is an innovative concept for smart diagnostic, reservoir/well performance optimization and estimation of remaining reserves based on the integration of Petroleum Data Management System (PDMS) and expert rules. Implementation of SICLO methodology provides the best strategy on how to produce remaining reserves most profitably. PDMS is the foundation of SICLO methodology and provides structured and verified information that follows the Well Life Cycle. Within PDMS, data are organized and structuredaccording to clearly defined principles and rules and filtered by different levels of quality control. Structured data allows integration of production and reservoir information with real-time data to achieve the maximum level of diagnosis of system operation performance according to reservoir and well potentials and system constraints. The built-in workflows and architecture of the whole process are automated and make the task accomplishment faster. SICLO methodology integrates expert-driven knowledge and pattern recognition tools improved by data-driven, artificial intelligence, neural network, and fuzzy logic technologies to deliver adaptive solutions for identifying locations of remaining reserves, optimizing oil and gas production, and minimizing associated operational costs.",
author = "Miroslav Antonic and Miso Solesa and Anatoly Zolotukhin and Dejan Rakic and Milos Aleksic",
year = "2019",
month = nov,
day = "26",
doi = "10.1088/1757-899X/700/1/012056",
language = "English",
note = "Second Conference of Computational Methods in Offshore Technology and First Conference of Oil and Gas Technology in Cold Climate ; Conference date: 27-11-2019 Through 29-11-2019",
url = "http://www.ux.uis.no/COTech/CFP.htm",

}

RIS (suitable for import to EndNote) - Download

TY - CONF

T1 - Integration of expert and data-driven workflows to manage reservoir and well life cycle in Arctic conditions using innovative SICLO methodology

AU - Antonic, Miroslav

AU - Solesa, Miso

AU - Zolotukhin, Anatoly

AU - Rakic, Dejan

AU - Aleksic, Milos

PY - 2019/11/26

Y1 - 2019/11/26

N2 - SICLO (Source of data and information; Input data; Calculation/Analytic; Logic Analysis; Output/Value Delivery) methodology is an innovative concept for smart diagnostic, reservoir/well performance optimization and estimation of remaining reserves based on the integration of Petroleum Data Management System (PDMS) and expert rules. Implementation of SICLO methodology provides the best strategy on how to produce remaining reserves most profitably. PDMS is the foundation of SICLO methodology and provides structured and verified information that follows the Well Life Cycle. Within PDMS, data are organized and structuredaccording to clearly defined principles and rules and filtered by different levels of quality control. Structured data allows integration of production and reservoir information with real-time data to achieve the maximum level of diagnosis of system operation performance according to reservoir and well potentials and system constraints. The built-in workflows and architecture of the whole process are automated and make the task accomplishment faster. SICLO methodology integrates expert-driven knowledge and pattern recognition tools improved by data-driven, artificial intelligence, neural network, and fuzzy logic technologies to deliver adaptive solutions for identifying locations of remaining reserves, optimizing oil and gas production, and minimizing associated operational costs.

AB - SICLO (Source of data and information; Input data; Calculation/Analytic; Logic Analysis; Output/Value Delivery) methodology is an innovative concept for smart diagnostic, reservoir/well performance optimization and estimation of remaining reserves based on the integration of Petroleum Data Management System (PDMS) and expert rules. Implementation of SICLO methodology provides the best strategy on how to produce remaining reserves most profitably. PDMS is the foundation of SICLO methodology and provides structured and verified information that follows the Well Life Cycle. Within PDMS, data are organized and structuredaccording to clearly defined principles and rules and filtered by different levels of quality control. Structured data allows integration of production and reservoir information with real-time data to achieve the maximum level of diagnosis of system operation performance according to reservoir and well potentials and system constraints. The built-in workflows and architecture of the whole process are automated and make the task accomplishment faster. SICLO methodology integrates expert-driven knowledge and pattern recognition tools improved by data-driven, artificial intelligence, neural network, and fuzzy logic technologies to deliver adaptive solutions for identifying locations of remaining reserves, optimizing oil and gas production, and minimizing associated operational costs.

U2 - 10.1088/1757-899X/700/1/012056

DO - 10.1088/1757-899X/700/1/012056

M3 - Paper

T2 - Second Conference of Computational Methods in Offshore Technology and First Conference of Oil and Gas Technology in Cold Climate

Y2 - 27 November 2019 through 29 November 2019

ER -

View graph of relations

Documents

SFX

Publication SFX