Constraining a compositional flow model with flow-chemical data using an ensemble-based Kalman filter

Mohamad El Gharamti, Ahmad Salim Kadoura, J. Valstar, Shuyu Sun, Ibrahim Hoteit

Research output: Contribution to journalArticlepeer-review

21 Scopus citations


Isothermal compositional flow models require coupling transient compressible flows and advective transport systems of various chemical species in subsurface porous media. Building such numerical models is quite challenging and may be subject to many sources of uncertainties because of possible incomplete representation of some geological parameters that characterize the system's processes. Advanced data assimilation methods, such as the ensemble Kalman filter (EnKF), can be used to calibrate these models by incorporating available data. In this work, we consider the problem of estimating reservoir permeability using information about phase pressure as well as the chemical properties of fluid components. We carry out state-parameter estimation experiments using joint and dual updating schemes in the context of the EnKF with a two-dimensional single-phase compositional flow model (CFM). Quantitative and statistical analyses are performed to evaluate and compare the performance of the assimilation schemes. Our results indicate that including chemical composition data significantly enhances the accuracy of the permeability estimates. In addition, composition data provide more information to estimate system states and parameters than do standard pressure data. The dual state-parameter estimation scheme provides about 10% more accurate permeability estimates on average than the joint scheme when implemented with the same ensemble members, at the cost of twice more forward model integrations. At similar computational cost, the dual approach becomes only beneficial after using large enough ensembles.
Original languageEnglish (US)
Pages (from-to)2444-2467
Number of pages24
JournalWater Resources Research
Issue number3
StatePublished - Mar 19 2014

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01

ASJC Scopus subject areas

  • Water Science and Technology


Dive into the research topics of 'Constraining a compositional flow model with flow-chemical data using an ensemble-based Kalman filter'. Together they form a unique fingerprint.

Cite this