Quantitative Textural Analysis – Input for Reservoir Quality and Rock Property Models

Lori A. Hathon, Thomas R. Taylor, and Fritz H. K. Rambow
Shell International E&P, Houston, TX

Observations and point count data collected using standard thin section petrography are an essential part of rock characterization. More detailed quantitative petrographic analysis of sandstone texture/microstructure can provide greater insights into fundamental factors that influence reservoir rock properties. Recognizing that the experience and knowledge of an expert petrologist is not fully duplicated by today's artificial intelligence systems, we constructed CAP (Computer Assisted Petrography), an image analysis system to assist the expert operator in the collection and storage of quantitative thin section data. CAP differs from many other petrographic image analysis systems in that it focuses on the interrelationships among solid phases as well as the pore space. For each identified solid particle the total perimeter and area, long and short axes lengths (particle size, sorting), shape, orientation, load-bearing contact length, number of grain contacts and the mineralogy of each contact partner are identified. These data can be used to test and establish predictive empirical relationships and theoretical models. For example, the nature of grain contacts directly influences acoustic and physical rock properties. Additionally, CAP supplies a statistically robust determination of sandstone modal composition. This is particularly important for quantifying volumetrically minor phases (< 2%, e.g. incipient quartz cement) where errors in standard point count data are high. Numerical forward models can under-predict porosity/over-predict quartz cement volumes at depth if calibrated using standard point count data alone. CAP data can also be used to estimate the evolution of surface area available for quartz cement precipitation as a function of mechanical compaction processes.