Quantifying Reservoir Quality Variations Using Grain-Size Volumetric Calculations from Image Logs
In sand-shale sequences, more sedimentological details could be measured and quantified with an image log, however, vertical resolution has historically been a major limitation in obtaining the data yielded from core analysis or cuttings. As defaults, sedimentological features like cross bedding, lateral accretion and erosion surfaces, and other elements could be identified to define depositional environments for various intervals along the image log. Porosity variations and permeability require additional data be acquired, such as nuclear magnetic resonance or triple-combo logs, but vertical resolution in these logs is limited.
Modeling with image petrophysics generates a texture map that examines grain-size details and their various volumes in each continuous log layer to calculate petrophysical parameters. This concept maps conductivity measured by the imaging tool around the borehole to enable each curve generated by button conductivity to be transformed into a porosity curve. The current injected by each button into the formation is modeled and the flow will perform like a fluid, seeking minimum resistance, looking for the space between grains (porosity).
This process converts each button conductivity curve into a porosity curve, initiating with the basic Archie equation or any other petrophysical model can be applied. To account for formation fluids, the Sw (Water Saturation) of the formation is integrated in the analysis in addition to lithology type. Once these petrophysical parameters are introduced, a porosity distribution for each interval (1.2 in.) and the upper and lower cutoffs are generated and adjusted if needed, to relate to grain sizes so that proportions can be calculated.
This paper will explain how modeling with image petrophysics can help determine the full sequence of grain size variations and how these curves can be used to guide seismic inversion products for enhanced reservoir characterization.
AAPG Search and Discovery Article #90142 © 2012 AAPG Annual Convention and Exhibition, April 22-25, 2012, Long Beach, California