Identification of high permeability zones from dynamic data using streamline simulation and inverse modeling of geology

Abstract

It is well-recognized that naturally fractured rocks can significantly influence the fluid flow patterns in a reservoir. Although it is very difficult to characterize fractures in deterministic detail, production data can be a vital source of information for identifying the spatial distribution and regional orientation of high permeability zones in a reservoir. This paper proposes to interpret the geological causes of preferential flow by integration of a prior geological model with dynamic data using streamline-based travel time inversion. The streamline-based generalized travel time inversion was performed constrained to a detailed stratigraphic model in a reservoir 3D grid with more than one million cells. No up-scaling was performed during the flow modeling. Dynamic data available on a significant number of wells were used to rapidly identify and reconcile discrepancies between the flow response from the prior geological model and measured dynamic data. The enhanced permeability was used to identify the spatial distribution of the dominant natural fracture zones and preferential flow paths in the reservoir. A statistical analysis of permeability modifications using correlations reveals the spatial distribution and possible extent of the high permeability zones that may be caused by macropores and fractures. In addition, results show the existence of localized high permeability fracture zones associated with specific rocks and high curvature regions. This integrative approach can potentially lead to significant savings in time and manpower as one is able to condition large prior geology models to dynamic data with fast streamline simulation and travel time inversion tools.