The thin section rock physics: Modeling and measurement of seismic wave velocity on the slice of carbonates

Abstract

This paper discusses a new approach for investigating the seismic wave velocity of rock, specifically carbonates, as affected by their pore structures. While the conventional routine of seismic velocity measurement highly depends on the extensive laboratory experiment, the proposed approach utilizes the digital rock physics view which lies on the numerical experiment. Thus, instead of using core sample, we use the thin section image of carbonate rock to measure the effective seismic wave velocity when travelling on it. In the numerical experiment, thin section images act as the medium on which wave propagation will be simulated. For the modeling, an advanced technique based on artificial neural network was employed for building the velocity and density profile, replacing image's RGB pixel value with the seismic velocity and density of each rock constituent. Then, ultrasonic wave was simulated to propagate in the thin section image by using finite difference time domain method, based on assumption of an acoustic-isotropic medium. Effective velocities were drawn from the recorded signal and being compared to the velocity modeling from Wyllie time average model and Kuster-Toksoz rock physics model. To perform the modeling, image analysis routines were undertaken for quantifying the pore aspect ratio that is assumed to represent the rocks pore structure. In addition, porosity and mineral fraction required for velocity modeling were also quantified by using integrated neural network and image analysis technique. It was found that the Kuster-Toksoz gives the closer prediction to the measured velocity as compared to the Wyllie time average model. We also conclude that Wyllie time average that does not incorporate the pore structure parameter deviates significantly for samples having more than 40% porosity. Utilizing this approach we found a good agreement between numerical experiment and theoretically derived rock physics model for estimating the effective seismic wave velocity of rock.

Micromechanical modeling of ultrasonic velocity for pore-structure and porosity characterization considering anisotropy in carbonate samples

“…The thin sections are two-dimensional representations of the rock body in three dimensions (Assefa et al, 2003). Another method for velocity estimation from thin section images is based on numerical modeling using finite difference schemes for acoustic wave propagation; this involves neural networking to compute the pore aspect ratio (Wardaya et al, 2014). The Digital Image Analysis (DIA) technique has also been applied to quantify the pore geometry's effects on wave velocities (Weger et al, 2009).…”