A Dynamic Characterization Approach for a Complex Naturally Fractured Reservoir

Abstract

The Naturally Fractured Reservoirs (NFR) constitute a challenge for the oil industry due to its importance in hydrocarbon production and the technical complexity they represent, because well’s productivity in carbonated formations is influenced by fracture systems that govern the fluids motion within reservoirs. This approach is oriented to the analysis of a very complex NFR, where we show the results obtained through a dynamic characterization methodology focused on new opportunities in a High Pressure-High Temperature (HP-HT) coastal mature oilfield with high water cut production. The proposed methodology is based on a full analysis starting from the pressure-production historical data, fluids properties, dual-porosity material balance, a detailed static model update (petrophysics, core analysis, petrography, fracture analysis, sedimentology-diagenesis and structural geology), flow units discretization, Water-Oil Contact (WOC) advance monitoring in each block, Pressure Transient Analysis (PTA) (determination of preferential flow direction and interference), and Rate Transient Analysis (RTA). This methodology allowed to determine the real Original Oil in Place (OOIP) and the proper recovery factor according to the type of NFR and its characteristics, to detect different WOC’s for each block that were hydraulically connected to each other but with a different dynamic behavior among them, the detection of heterogeneities, facies changes and faults that originally were not mapped, sweet spots location, better distribution of the petrophysical properties, fracture analysis, static model reinterpretation based on the dynamic behavior, reservoir connectivity analysis (among blocks) and the generation of improved production forecasts based on an exploitation strategy especially designed for the current conditions and needs of the field; all of this contributed to have a better understanding of the reservoir and a good numerical simulation model.