Constraining 3D Petroleum Reservoir Models to Petrophysical Data, Local Temperature Observations, and Gridded Seismic Attributes with the Ensemble Kalman Filter (EnKF)

• Author / Creator

  Zagayevskiy, Yevgeniy

• A methodology based on the Ensemble Kalman Filter (EnKF) is proposed for petroleum reservoir characterization, using continuous integration of petrophysical core data, reservoir temperature observations, and gridded time-lapse acoustic impedances. The localization of updating and covariance matrices is performed to assimilate exhaustive seismic data. A shortcut based on propagation of the ensemble mean and co-simulation of the ensemble variations is implemented to reduce computational cost of the forecast step. The integration of additional data from multiple sources and time steps improves the estimates of porosity and permeability. This methodology is applied to a synthetic 2D steam assisted gravity drainage (SAGD) case study to examine the ability of the EnKF to constrain spatial distributions of porosity and permeability. A realistic 3D SAGD case study is used to demonstrate the applicability of this methodology to a real industrial problem. Obtained results show effective application of the EnKF to petroleum reservoir characterization.

• Subjects / Keywords

  • Petroleum Reservoir Characterization
  • Geostatistical Modeling
  • Continuous Data Integration
  • EnKF
  • Petroelastic Model
  • Temperature Data Assimilation
  • Ensemble Kalman Filter

• Graduation date

  Spring 2012

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R3DP5C

• 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.