Abstract
The North-African asset under evaluation is characterized by a tight matrix sandstone with poor petrophysical properties, although with natural fractures that sometimes improve the well performance. In this context, the simple description of the matrix system can result inadequate, therefore a dual media modelling (matrix & fractures) was performed, capable of capturing petrophysical heterogeneity and reproducing observed well deliverability.
Given the uncertainties related to fractured systems, a Petrel RE uncertainty workflow was properly designed to evaluate the impact of different parameters on DST matching, future production profiles and well behavior through a Monte Carlo risk analysis. The workflow incorporates different combination of natural fracture scenarios (extracted from seismic curvature), matrix block size and microfractures diffusion (observed at core/well scale) in the matrix system, together with petrophysical parameters. Since some historical well performance was improved by hydraulic fracturing, this action was also considered in the uncertainty workflow.
The outcomes show, on one hand, that the well start-up rates are dependent on the hydraulic fracture interaction with the natural fractures system in the near wellbore area, on the other hand the well performances (gas cumulative and plateau length) are influenced by the connectivity of the DFN and the diffusion of micro fractures in the matrix system. Among all the investigated parameters, the most impacting on well deliverability are: different seismic DFN scenarios, fracture permeability, matrix-fracture interaction and the microfractures diffusion. The automated parametrization of these variables allowed to generate multiple scenarios for infill wells placement and recovery maximization. This workflow works as an effective and powerful tool to properly evaluate the asset.
This novel approach has been successfully tested in a naturally fractured gas reservoir characterized by a generally tight matrix sandstone. All the recognized uncertainties were combined in a sophisticated, yet user-friendly workflow allowing a robust asset evaluation.
