تعيين پارامترهاي مدل سازي عددي شبكه درزه هاي مجزا با استفاده از داده هاي لاگ تصويري FMI

Determination of Parameters for Numerical Modeling of Discrete Fracture Network (DFN) Using FMI Imager Log Data

Mapping the geometrical parameters of natural fractures is very important in evaluation of hydrocarbon reservoirs. Since subsurface feature properties differ from fracture parameters detected from outcrops, the best way for modeling the fractured reservoir is using imager tools. Imager tools such as Formation Micro Imager (FMI), with appropriate resolution in detecting even small-scale discontinuity features, may help conceptualization of fractured reservoirs. The FMI presents virtual images from the walls of well based on the differences in electrical resistivity between the formation and the drill mud. One of the important applications of FMI log is detection of open and close natural fractures. In this study, using recorded data of open fractures in a well, firstly the best fitted density functions for the geometric parameters of fractures were recognized. Using the distribution function of geometric parameters of fractures and Monte Carlo process, a numbers of Discrete Fracture Network (DFN) models were generated. The most realistic DFN models fitting with the mapped fracture patterns in the well were identified using William-Watson (W-W) statistical test. The results of this research may be used for numerical modeling of fluid flow into DFN, studying of permeability tensor and modeling of production rate in deep hydrocarbon reservoirs.