May. 26 - May. 27, 2010


Description

Course Description

The course introduces engineers, geologists and geoscientists to both the fundamental theory and practice of reservoir description and modeling for reservoir management. This course covers the fundamental concepts of reservoir description and modeling using geostatistical techniques. It is an introductory course with emphasis on the principles and practice of integrated studies and uncertainty analysis. Upon completion of this course, you should be able to (l) make decisions on when and where to apply reservoir description and modeling to support reservoir management, (2) understand the methodology of integrated studies (3) select the appropriate reservoir description and geostatistical modeling tools (4) analyze and QC data for reservoir modeling, (5) understand variogram analysis, kriging and stochastic simulation, integrated studies, uncertainty analysis; and (6) recognize the limitations and opportunities for reservoir modeling.

Course Contents

Reservoir Modeling Fundamentals

  1. What is reservoir characterization and modeling?
  2. What is reservoir heterogeneity?
  3. Scales of heterogeneities
  4. What are the strengths and limitations of different reservoir modeling techniques

Overview of Statistics and Probability

  1. Basic definitions
  2. Histograms, frequency distribution and probability

Data analysis, QC and Preparation

  1. Data analysis and QC tools
  2. Applications

Variogram Modeling

  1. What is it? What is the information to be derived?
  2. How to calculate variograms

Kriging Techniques

  1. What is kriging?
  2. Different types of kriging
  3. Applications and limitations of kriging

Stochastic Simulation and Modeling Case Studies

  1. How to conduct a geostatistical reservoir modeling study
  2. Conditional simulation. Use of hard and soft data
  3. Sequential indicator simulation and Sequential Gaussian simulation
  4. Case Studies of geostatistical modeling

Overview of Uncertainty Analysis and Integrated Studies

  1. What is Uncertainty? Integrated Studies?
  2. How to account for uncertainty in Integrated reservoir studies
  3. Case Studies

Featured Speakers

Speaker David O. Ogbe, Ph.D., P.E.
Dr. David O. Ogbe, P.E. is President & Senior Reservoir Engineering Advisor with Greatland Solutions, LLC, in Denver, CO and Professor Emeritus, University of Alaska. Prior to this assignment he was a Lead Reservoir Engineer with Schlumberger, Denver, Colorado. He was a Professor of Petroleum Engineering and Coordinator of the …


Dr. David O. Ogbe, P.E. is President & Senior Reservoir Engineering Advisor with Greatland Solutions, LLC, in Denver, CO and Professor Emeritus, University of Alaska. Prior to this assignment he was a Lead Reservoir Engineer with Schlumberger, Denver, Colorado. He was a Professor of Petroleum Engineering and Coordinator of the Coalbed Methane for Rural Energy Research Program at the University of Alaska Fairbanks, USA. He is a registered professional engineer. He received B.S. and M.S. degrees from Louisiana State University and Ph.D. from Stanford University, all in petroleum engineering. Dr. Ogbe has more than 25 years of consulting, teaching and research experience. His areas of specialization are oil and gas reservoir engineering, well testing, reservoir simulation, reservoir characterization and formation evaluation, and large-scale reservoir simulation on high performance computers. He has published 100 technical papers on well testing, reservoir characterization, reservoir simulation, and computer applications. Dr. Ogbe has provided consulting services and training for clients from major and independent oil & gas companies, NOCs, and government agencies world-wide.


Full Description



Organizer

Kristen Lee


Date and Time

Wed, May. 26

-

Thu, May. 27, 2010

8 a.m. - 5 p.m.
(GMT-0600) US/Central


Location

SPE Houston Training Center

10777 Westheimer Suite 1075
Houston, TX 77042
USA