08:00 ‒ 08:45 Registration & Coffee
08:45 ‒ 09:00 Welcome by Society of Petroleum Engineers (SPE) Oslo Section
Big Data Analytics Status in E&P and Drilling
Session chair: Morten Dalsmo, IBM
09:00 — 09:30 Harness Oil and Gas Big Data with Analytics: Optimize Exploration and Production with Data Driven Models, Kieth Holdaway, SAS Institute, USA
09:30 — 10:00 Big Data Status and Challenges in Statoil, Nina Reiersgaard, Statoil, Norway
10:00 – 10:20 Networking Break (Stand Presentations)
Data Management and Exploiting Data as a Strategic Asset
Session chair: Keith Holdaway, SAS Institute
10:20 — 10:50 Big Data in Oil & Gas for Improved Decision Making and Operational Efficiency, Ole Eyvind Evensen, IBM
Data is growing exponentially within core E&P domains. It has been described as "the new oil" - which first has to be refined to support users. IBM has introduced new "refining" technology to improve data capture, quality and analysis. Use cases cover real-time drilling operations, event prediction - like equipment failure, but also more qualitative decision support from unstructured data sources. Key drivers are continuous operational improvement and better qualified, challenged and auditable decisions.
10:50 — 11:20 Predictive Real-Time Analytics Drives Decision Support for Oil Well Drilling, Odd Erik Gundersen
During the drilling process of an oil well, drilling teams have to monitor several aspects of the operation to ensure the project is running smoothly. It’s common for unplanned events to arise that was not factored into the original well plan, causing unfavorable delays. When armed with more information, drilling teams can make better informed decisions due to increased situational awareness. Real-time analytics provides insight into drilling operations to proactively identify potential problematic situations to mitigate inefficiencies. This presentation will discuss how predictive real-time analytics can assist in decision support in real-world drilling situations through statistical models, heuristics and case-based reasoning. Case studies will also be presented.
11:20 — 12:00 Successful implementation of Big Data and Advanced analytics in O&G, Lars Jacob Boe, Bain & Company
entering a new era of unprecedented data availability, where digital trends are
disrupting traditional business models. These trends have enabled the emergence
of Big Data and Advanced analytics, which is rapidly becoming a big industry.
The Oil and Gas industry lags the leading industries when it comes to broad
based adoption. However, four key applications are emerging for Big Data in Oil
and Gas companies; Digital fields, Predictive plant and drilling analysis,
Remote operations and Reservoir modelling and seismic imaging. Companies can
get ahead in the game by taking the right approach - adopting key success
factors, and avoiding typical pitfalls. Our research suggests that, if done
right, significant value can be captured from Big Data and Advanced analytics.
12:00 – 13:00 Lunch (Stand Presentations)
Established and Emerging Big Data Technologies
Session chair: Duncan Irving, Teradata
13:00 ‒ 13:30 UiO: The Optique Project and Applications in Oil & Gas Industry, Professor Arild Waaler, University of Oslo
13:30 ‒ 14:00 Open/chain Data in a Big Data Context, Dumitru Roman, Sintef, Norway
14:00 ‒ 14:30 Big Data Technologies & Trends in Oil & Gas, Dr. M. Naci Akkøk, Oracle
A new technological trend is best understood by understanding the demands that have generated the technology, the demands that the technology aims to provide answers/solutions to. We start by looking at Big Data technologies from this point of view: by looking at the kinds of challenges/demands they are trying to address. We will then categorize these challenges into three typical "use cases" that demand Big Data solutions together with their architectural/technical implications, and look at how these apply to engineering operations in general, and Oil & Gas in particular. We will be focusing more on one of the three use cases, mainly due to the acute need in the Oil & Gas industry to automate and consolidate in order to reduce costs and increase efficiency.
14:30 ‒ 14:50 Networking Break (Stand Presentations)
Big Data for a Competitive Business Advantage
Session chair: Hector Manuel Escalona Gonzalez, Schlumberger SIS
14:50 ‒ 15:20 Connected, Predictive and Safer Oil Production with Microsoft's Big Data Solutions, Elena Terenzi, Microsoft
Oil and Gas industry trends such as increasing costs in upstream, aggressive competition, and safety and environment responsibility are driving companies in this sector to take big bets on technology in areas like connected oilfield, predictive maintenance and energy management in order to gain a competitive edge. During this talk, we will consider the impact of these trends and discuss some examples of Oil and Gas companies looking to Microsoft’s Big Data Platform to address the associated challenges.
15:20 ‒ 15:50 Big Value from Big Data, Dr Duncan Irving, Teradata
We live in exciting times where technology is changing so fast that it is often hard to keep up. Every week there is a new “next big thing” that management is interested in. Is Big Data just the next new fad or can it deliver on the promises that are being made? This session will dig into these questions and aim to show you how “Big Data” tools and techniques can give your company the ability to tap into your growing data volumes and put all of your data to work for you. By combining industry trends such as the Digital Oilfield and real life case studies we will investigate what Big Data really means for the oil & gas industry and the value of integrated data for oil & gas. We will explain how Oil and Gas companies can learn from other industries to exploit their data assets more fully in support of the ever-changing business requirements.
15:50 ‒ 16:20 O&M excellence through Big Data and Advanced Analytics, Tor Jakob Ramsøy, Director, McKinsey & Company
The complexity of oil and gas operations is ever increasing, assets and equipment are increasingly more instrumented, and information gets lost in a fragmented value and supply chain. In recent studies we have seen that less than 1% of all data collected in operations is used for operational decision making. Maintenance is one function suffering from this shortcoming of information. Whilst we know that probability of failure for any given equipment is a function of time, load and external conditions, the maintenance programs tend to be driven solely by time intervals. In some cases, we have even proven that regular maintenance interventions decreases the lifetime of equipment rather than prolonging it, due to issues with infant mortality or maintenance induced failures. Companies can radically enhance their operational performance through leveraging, existing data and known technology. Best practice examples within and outside the Oil and Gas industry will be discussed, alongside with practical tools to get started on the journey.
16:20 ‒ 18:00 Networking and Reception (Stand Presentations)
Dinner 19:00 ‒ 23:00 at Tjuvholmen Sjømagasin
For questions on the technical program and inquiries on poster/stand presentations, please send e-mail to: firstname.lastname@example.org
For questions on the sponsorship, please send e-mail to: email@example.com
For questions on the stand presentation and exhibition, please send e-mail to Vita Kalashnikova firstname.lastname@example.org
Please submit your stand or poster presentation before January 20 2015