| Keterangan |
: A method used in evaluating reservoir production prediction is chosen by considering the availability of
time and resources, the percentage of reliability and last but not least is the ease of application of
prediction. Capacitance-Resistance Model (CRM) came as a tremendous predictive model to study
reservoir performance, especially in evaluating the reservoir production prediction. The used of CRM in
this study is as a predictive model which will help to evaluate the right model of oil fractional-flow
models based on its water cut.
Injection and production rate are considered as input and output signals in CRM. The parameters such as
inter-well connectivity and time also play its role toward the CRM performance. In an effort to obtain the
CRM parameter of inter-wells connectivity and time, solving the history of production/injection has to be
done in the very first place. In order to obtain the parameters, (GRG) nonlinear solver is used to find the
best representative parameters with production and injection data as an input. Thereafter, the CRM
calibrated model obtained is used to study the empirical oil fractional-flow model when calculating the oil
production rate.
In this study, the application of CRM is demonstrated in one synthetic field obtained by CMG reservoir
simulator and one oilfield case study. When calculating the oil production rate, 5 different types of oil
fractional-flow models are used in the study. After solving the parameters of each model, the models
would then be combined according to its water cut to obtain the model which would give the minimum
error in predicting the reservoir performance. The result showed that the combination model obtained is
able to predict oil produced with minimum error compare to other 5 empirical models. |
