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Data Supporting E&P Decisions

20 – 22 May 2013

Dubai, UAE | Amwaj Rotana Hotel

Technical Agenda


Keynote Speaker

Khaled O. Al Subai, Manager, Reservoir Description and Simulation Dept., Saudi Aramco

Session 1: Data Quality Management

Data quality is the key to making the right decisions. Reliable data for effective decisions will be the main theme of this session. Presenters will draw the relationship between data quality management and business decision making. The importance of data quality programme, quality expectations, and techniques will be further evaluated under the scope of the E&P business.

Topics to be covered:

  • Data quality management overview
    1. Data quality management benefits
    2. Data quality management challenges
  • Practical implementation within E&P (Case studies)
  • Data quality management techniques:
    • Data profiling
    • Data analysis
    • Data validation
    • Data correlation
    • Data synchronisation
    • Data cleansing
  • Market solutions

Discussion Leaders:

  • Majed AbdulHamid, Schlumberger
  • Zainab Al-Awaini, Petroleum Development Oman
  • Lwanga Yonke, Aera Energy
  • Ahmed Shukaili, Petroleum Development Oman
  • Philip Lesslar, Petronas

Session 2: Data Integration I

Strategic decision-making for integrated oil and gas companies, optimal depletion of reservoirs, enhancing ultimate recovery, and adding to reserves require a seamless look across data. Data integration tools play a major role in gathering scattered information across various domains, and present the findings cohesively for decision makers to arrive at the right conclusions. These technologies deal with seismic subsurface images, drilling information, production volumes, and planning reservoir depletion.

Topics to be covered:

  • Introduction to data integration
  • Data integration applications within E&P
  • Data integration complexity
  • Virtual data integration
  • Physical data integration
  • Data presentation

Discussion Leaders:

  • Yigit Karabag, Informatica
  • Ahmed Abou Syed, Advantek International
  • Paul van den Hoek, Shell


Session 3: Data Integration II

Discussion Leaders:

  • Gossen Bakker, Petroleum Development Oman
  • Henry Martinez, Schlumberger
  • Tareq Ghamdi, Saudi Aramco

Session 4: From Data Integration to Business Decision in Petroleum Reservoirs

Many business decisions (field development planning, infill drilling, etc.) are based on production forecasts generated by a reservoir model for different operational scenarios and under different uncertainties. Significant effort is devoted to make these reservoir models as realistic as possible via a combination of proper description of the geology, proper understanding of the reservoir, and overall integration of the measurement data. This process has three, mutually related, problems with it:

(1) Results based on data integration will generally be good in describing past performance, but will be (partly) inadequate for predictions, especially when in the future streamlines will be changed via infill drilling, producer-injector conversion, or when the recovery scheme will be changed (e.g. moving from IOR to EOR),

(2) Each decision type needs its own specific level of modelling and corresponding level of data integration (e.g. business planning versus finding infill locations versus reservoir management), and

(3) There exists no general consensus about how the impact of uncertainties (e.g. using representative model ensembles) should be "optimally" incorporated into the final business decision.

This session will address the issues around "translating" the results from data integration towards business decisions.

Discussion Leaders:

  • Texas A&M University
  • Sippe Douma, Shell
  • Rida Abdel Ghani, Saudi Aramco
  • Ali Didanloo, Schlumberger


Session 5: Data Mining

This session will help delegates understand data mining concepts, and its role in facilitating business decisions by introducing knowledge discovery practices within E&P. Data mining offers the potential to extract useful information from the immense size of data being gathered by energy companies.  Data mining based solutions can be used to reduce risks in finding hydrocarbons, and increase ultimate recovery from hydrocarbon reservoirs.  It can be applied analyze and predict trends in order to optimize operations, and address several issues and challenges faced during Oil and Gas production. During the session, successful case studies should be encouraged to be presented to demonstrate the power of data mining in supporting business decisions.

Discussion Leaders:

  • Carl Cook, Intellidynamics/BioComp Systems Inc.
  • Mohammed Casim Saloojee, Saudi Aramco
  • Nasier Fakier, Saudi Aramco