2013/02/03 by Abhra Giri, Giri, Abhra, Sujata Tarafdar +5
Engineering · Physics and Astronomy · #Disordered Systems and Neural Networks (cond-mat.dis-nn) #Enhanced Oil Recovery Techniques #FOS: Physical sciences #Hydrocarbon exploration and reservoir analysis #NMR spectroscopy and applications #Statistical Mechanics (cond-mat.stat-mech)
paper · pdf · doi:10.48550/arxiv.1302.0483
openalex publication_date 2013/02/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
It is well known that sedimentary rocks having same porosity can have very\ndifferent pore size distribution. The pore distribution determines many\ncharacteristics of the rock among which, its transport property is often the\nmost useful. Multifractal analysis is a powerful tool that is increasingly used\nto characterize the pore space. In this study we have done multifractal\nanalysis of pore distribution on sedimentary rocks simulated using the Relaxed\nBidisperse Ballistic Model (RBBDM). The RBBDM can generate a 3-D structure of\nsedimentary rocks of variable porosity by tuning the fraction p of particles\nof two different sizes. We have also done multifractal analysis on two samples\nof real sedimentary rock to compare with the simulation studies. One sample, an\noolitic limestone is of high porosity (40%)while the other is a reefal\ncarbonate of low porosity around 7%. 2-D sections of X-ray micro-tomographs\nof the real rocks were stacked sequentially to reconstruct the real rock\nspecimens. Both samples show a multifractal character, but we show that RBBDM\ngives a very realistic representation of a typical high porosity sedimentary\nrock.\n