Experimental design and Response Surface Methodology (RSM), together with Monte Carlo simulation provide an efficient statistical framework to investigate the influence of multiple parameters and their interactions on a response of interest with limited number of simulations, and estimate the range of the response accurately. In the present study, the simulation model for a laboratory experiment of miscible CO2 injection into a matrix-fracture system is used to investigate the effect of different parameters on oil recovery. First, parameters with the most influence on oil recovery are determined by sensitivity analysis. Then in order to quantify the significance of each parameter, the model is employed to produce a response surface via Box-Behnken design, and the recovery factor is approximated as a second-order function of five reservoir and fluid parameters. Finally, the probable range of recovery factor is estimated by Monte Carlo simulation. The results show that the most effective parameters are matrix permeability, core diameter and diffusion coefficients with positive, and fracture permeability with negative contribution to oil recovery. In addition, the most-likely value (P50) calculated for oil recovery from matrix block is 71.6%. Recovery factor drops from 86.3% for the optimistic value (P10) to 55% for the pessimistic one (P90).


Article metrics loading...

Loading full text...

Full text loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error