Applications of Ensemble Kalman Filter for characterization and history matching of SAGD reservoirs

• Author / Creator

  Gul, Ali

• Steam-assisted gravity drainage (SAGD) is the most robust thermal recovery process that has unlocked western Canadian heavy oil and bitumen reserves into economical recovery. The prime challenges in SAGD heavy oil developments and well planning in the Northern Alberta formations are: characterizing the reservoir heterogeneity and identifying the potential steam barriers that may interfere with the recovery process. If characterized earlier, the field development plans could be efficient and effective. In SAGD projects, temperature sensors at several depths within observation wells are available for monitoring steam chamber growth. Characterization using data available from these real-time sensors and dynamic production data integrated in a closed-loop could be a probable solution.
  Ensemble Kalman filter (EnKF), a state and parameter estimation technique, has shown good promise for reservoir characterization using dynamic production data in conventional reservoirs. For the above discussed problem, constrained based adaptive EnKF approach was implemented.

• Subjects / Keywords

  • Reservoir Characterization
  • Ensemble Kalman Filter
  • Steam-assisted gravity drainage
  • Computer Assisted History Matching
  • Geostatistical Reservoir Modeling

• Graduation date

  Fall 2011

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R3CG84

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.