Datapipe: A Configurable Oil & Gas Automated Data Processor

Florent Bourgeois, Pierre Arlaud

2015

Abstract

Exploration and Production companies need to know where are the oil and gas reservoirs, how much they hold, and whether they can profitably produce oil and gas. Data collection, management and analysis are therefore central to the industry. As in most application areas, raw data are processed, implying several tools and experts interactions. Nevertheless, the oil an gas sector data processes imply unusual scale of, multimodal and long-lived, data alongside with complex analysis. DataPipe is a research project funded by the Eurostars Program of the European Commission which purpose is to develop a platform, toolkit and pipeline for the intelligent, rule-based selection, management, analysis, publishing and display of heterogeneous multimodal data in the oil and gas sector. This paper describes Actinote 4.0, a flexible web-based platform, which is developed to respond to the specified Datapipe context and is dedicated to the creation of specific domain-based process assistant applications that are certified by expert systems.

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Paper Citation


in Harvard Style

Arlaud P. and Bourgeois F. (2015). Datapipe: A Configurable Oil & Gas Automated Data Processor . In The Success of European Projects using New Information and Communication Technologies - EPS Colmar, ISBN 978-989-758-176-2, pages 75-96. DOI: 10.5220/0006163700750096


in Bibtex Style

@conference{eps colmar15,
author={Pierre Arlaud and Florent Bourgeois},
title={Datapipe: A Configurable Oil & Gas Automated Data Processor},
booktitle={The Success of European Projects using New Information and Communication Technologies - EPS Colmar,},
year={2015},
pages={75-96},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006163700750096},
isbn={978-989-758-176-2},
}


in EndNote Style

TY - CONF
JO - The Success of European Projects using New Information and Communication Technologies - EPS Colmar,
TI - Datapipe: A Configurable Oil & Gas Automated Data Processor
SN - 978-989-758-176-2
AU - Arlaud P.
AU - Bourgeois F.
PY - 2015
SP - 75
EP - 96
DO - 10.5220/0006163700750096