Digital Energy: Real-Time Data Management for E&P Operational Intelligence

Speaker Mike Brulé
Principal Technomation Dr. Mike Brulé, P.E. is principal of Technomation®, a consultancy providing research, advisory, and implementation services for E&P information management, software development, and real-time systems integration. A 25+ year member of SPE, he worked for E&P operators Shell and Kerr-McGee as a reservoir and production engineer in North ...

Principal
Technomation

Dr. Mike Brulé, P.E. is principal of Technomation®, a consultancy providing research, advisory, and implementation services for E&P information management, software development, and real-time systems integration. A 25+ year member of SPE, he worked for E&P operators Shell and Kerr-McGee as a reservoir and production engineer in North Sea gas-condensate field development, Gulf of Mexico enhanced-oil-recovery and deepwater-field development, and as a chemical-process engineer in alternative-fuels R&D projects. Mike currently focuses on integrated asset modeling, production optimization, workflow automation, SaaS and Cloud Computing, and MPP data mining and predictive analytics for real-time decision-making and E&P business improvement. He holds a PhD in chemical engineering and an MBA from the University of Oklahoma, and has coauthored over fifty publications including the SPE Monograph Phase Behavior.


Full Description

Many E&P operations- and business-improvement opportunities exist through real-time production surveillance and optimization, drilling and completions surveillance and optimization, and oilfield-equipment reliability and maintainability. In addition to smart-well technology, three data-management capabilities are crucial to modern E&P operations:

1)     Integrating and harmonizing data of different timescales,

2)     Integrating and harmonizing data across multiple disciplines and diverse subject areas, and

3)     Augmenting the industry’s traditional model-driven methods with data-driven methods, including AI statistical and stochastic approaches.

Drilling, reservoir, and production engineering would be further enabled by combining historical (accumulated over years), tactical (weeks to months), and high-frequency data from historians (sub-seconds to days) with data from shared-earth-modeling and discipline-oriented source systems (geology, petrophysics, reservoir, production, facilities, geographical, financial, ERP, supply chain, procurement, etc.).  The industry’s core deterministic, physics-based methods can be augmented on the fringe with AI empirical methods, by employing a “Modeling plus Mining” strategy.

Mike will explore how integrated asset modeling (IAM) can be combined with historians and massively-parallel-processing (MPP) data-warehousing and data-mining technology to create real-time architectures for E&P operations optimization and performance management. He will also review case studies outside the E&P industry to assess the feasibility and viability of such continuous “Modeling plus Mining” systems.

Organizer Martyn Harsley

When?

Tue, Oct. 27, 2009
11:30 a.m. - 1 p.m. US/Central

How Much?

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Where?

Courtyard on St James
1885 St James Place
Houston, TX 77056
USA

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