Abstract

Verifiable and accurate prediction of reservoir pore sizes from well logs in a well with no previous exposure of core data is the desirable outcome for any technique intended to estimate pore size. Many methods are based on core and crushed rock samples such as thin section analysis, scanning electron microscope (SEM) and mercury intrusion capillary pressure (MICP) to characterize pore features but these methods are not commonly used because of their high cost. This study introduces a cost-effective approach to establish a relationship between hydraulic flow unit and pore size distribution using routine core analysis data and geophysical well logs. Multi-parameter cluster analysis is used to classify the reservoir rock volume into hydraulic flow unit with similar rock characteristics using reservoir quality index (RQI) and flow zone indicators. Well log and core analysis data were used to identify the hydraulic flow unit in the reservoir interval. The discriminant approach was then applied to the predicted hydraulic flow unit to access the range of pore sizes. The predicted hydraulic flow unit with high porosity and permeability and high RQI revealed a range of pore sizes (macro and mega pores). Comparing the obtained results with high-resolution rock thin section study and available empirical approaches indicated verifiable and satisfactory results. The study can extrapolate the pore size information vertically as well as in the neighboring wells in a quite simple and economical way.

Full Text
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