We consider second migration of hydrocarbons and analyse the effect of the uncertainty associated with three-phase relative permeability on reservoir simulation results. The two-dimensional vertical reservoir has a size of 5000 m × 5000 m and it is discretized by 50 × 50 uniform cells. Parameters of relative permeability models are evaluated via a Maximum Likelihood (ML) approach, relying on a set of coreflooding data available from the literature. Uncertainty in ML calibration of the relative permeability model parameters is propagated to the outputs of reservoir simulations within a Monte Carlo (MC) framework. Results are discussed in terms of time evolution of pressure, saturation (of all three phases) values as well as concentrations of the hydrocarbon components. Our results document a clear influence of the ML parameter estimation uncertainties on the reservoir simulations, especially considering local concentrations of hydrocarbon components. Moreover, even though the uncertain parameters follow a Gaussian distribution, outputs of the MC simulations are generally non-Gaussian and display long (positive and/or negative) tails.

Impact of Hysteresis on Relative Permeability in Hydrocarbon Migration

F. Olivari;E. Ranaee;M. Riva
2019

Abstract

We consider second migration of hydrocarbons and analyse the effect of the uncertainty associated with three-phase relative permeability on reservoir simulation results. The two-dimensional vertical reservoir has a size of 5000 m × 5000 m and it is discretized by 50 × 50 uniform cells. Parameters of relative permeability models are evaluated via a Maximum Likelihood (ML) approach, relying on a set of coreflooding data available from the literature. Uncertainty in ML calibration of the relative permeability model parameters is propagated to the outputs of reservoir simulations within a Monte Carlo (MC) framework. Results are discussed in terms of time evolution of pressure, saturation (of all three phases) values as well as concentrations of the hydrocarbon components. Our results document a clear influence of the ML parameter estimation uncertainties on the reservoir simulations, especially considering local concentrations of hydrocarbon components. Moreover, even though the uncertain parameters follow a Gaussian distribution, outputs of the MC simulations are generally non-Gaussian and display long (positive and/or negative) tails.
Offshore Mediterranean Conference and Exhibition 2019, OMC 2019
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1125999
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact