Abstract

In recent years there has been a growing interest in accurately modelling the condensate banking phenomena in gas-condensate reservoirs to better predict production performances. The velocity-dependent relative permeability (VDRP) concept is one of the methodologies to replicate well production performance reflecting both condensate banking phenomena and velocity effect in gas-condensate reservoirs. In this paper, we present the result of a fine-scale compositional reservoir simulation study by introducing VDRP model validated against the actual field production data from a gas-condensate reservoir called S-Tuff Formation in Minami-Nagaoka Gas Field in Japan.

A comprehensive data acquisition program was implemented during the long-term production test of the S-Tuff formation to enable the detailed evaluation of production performance and near-wellbore fluid behavior in the reservoir. The program included the measurements of flowing and shut-in bottomhole pressures, surface flow data and fluid sampling. The ultimate objective was to accurately predict the field production performance by an established reservoir simulation model through history matching.

The fine-scale compositional reservoir simulation study showed that VDRP model was required to obtain reasonable match with production data, including BHPs and GOR, whilst it was not achieved by the model with conventional gas-oil relative permeability curves because the simulated FBHP fell far below the observed data when the FBHP was below dewpoint. Hence, the study suggested that improvement of gas-oil relative permeability by velocity effect occurred during production. It was also shown that the well productivity impairment due to condensate banking in VDRP model was not as severe as in the case where the conventional fixed gas-oil relative permeability was used.

In this study, the VDRP concept was adopted to evaluate the impact of condensate banking and velocity effect, and its methodology was validated using the actual field production data and its history matching. This study will contribute further improvement of performance prediction for similar gas-condensate reservoirs.

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