Estimation of sub-core permeability statistical properties from coreflooding data

Research output: Contribution to journalArticlepeer-review

Abstract

Knowledge of sub-core permeability is necessary for accurate numerical modeling of coreflooding experiments and for investigation of sub-core flow phenomenon. A new method for estimating sub-core permeability geometric mean (kG) and log-permeability variance (σy 2) is presented. The method is based on matching coreflooding experiment measurements of wetting phase relative permeability with semi-analytical calculations of effective relative permeability. The semi-analytical solution is formulated assuming log-normal permeability (k), steady state and capillary-limit conditions. It is based on the geometric mean and log-phase-permeability variance for isotropic k and power law averaging for anisotropic correlations. The solution is validated on synthetic k realizations by comparison with numerical calculations. Then, the estimation method is tested on synthetic data assuming various types of core capillary pressure relationships, relative permeability functions and k anisotropies. Results demonstrate high accuracy in almost all of the cases except for small anisotropy ratios lh/lv between horizontal (lh) and vertical (lv) dimensionless correlation lengths, where flow is in the horizontal direction, and when σy 2 is large. The method is also validated using data from CO2-brine coreflooding experiments conducted on two different cores. It is found that the estimation method remains accurate in these realistic settings, however, accuracy of kG is reduced when the core permeability departs from a log-normal distribution.

Original languageEnglish
Pages (from-to)113-124
Number of pages12
JournalAdvances in Water Resources
Volume108
DOIs
StatePublished - Oct 2017

Keywords

  • CO-brine coreflooding
  • Capillary limit
  • Coreflooding experiments
  • Effective properties
  • Relative permeability
  • Sub-core permeability

All Science Journal Classification (ASJC) codes

  • Water Science and Technology

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