Improved Prediction of Reservoir Behavior Through Integration of Quantitative Geological and Petrophysical Data

Summary This paper presents a cost effective, quantitative methodology for reservoir characterization that results in improved prediction of permeability, production and injection behavior during primary and enhanced recovery operations. The method is based fundamentally on the identification of rock types (intervals of rock with unique pore geometry). This approach uses image analysis of core material to quantitatively identify various pore geometries. When combined with more traditional petrophysical measurements, such as porosity, permeability and capillary pressure, intervals of rock with various pore geometries (rock types) can be recognized from conventional wireline logs in noncored wells or intervals. This allows for calculation of rock type and improved estimation of permeability and saturation. Based on geological input, the reservoirs can then be divided into flow units (hydrodynamically continuous layers) and grid blocks for simulation. Results are presented of detailed studies in two, distinctly different, complex reservoirs: a low porosity carbonate reservoir and a high porosity sandstone reservoir. When combined with production data, the improved characterization and predictability of performance obtained using this unique technique have provided a means of targeting the highest quality development drilling locations, improving pattern design, rapidly recognizing conformance and formation damage problems, identifying bypassed pay intervals, and improving assessments of present and future value.