Comparison of Traditional and Digital Rock Physics Techniques to Determine the Elastic Core Parameters in Cretaceous Formations, Abu Dhabi

Abstract Knowledge of the elastic properties of rock, such as Vp, Vs, and Poisson’s ratio, is required input to accurate and rigorous reservoir description. Traditionally, these values had been acquired from log data or direct measurement in a physical laboratory. Recent advances in imaging and image processing, together with improved availability of high performance computing, gave rise to digital techniques for investigating the properties of rock samples. These techniques are based on high-resolution imaging of the rock’s pore space, segmentation of the images into pores and various minerals and simulation of the physical processes controlled by the desired rock properties. These techniques form the novel discipline of digital rock physics (DRP). The goal of the current work is to validate the results of DRP measurements of elastic parameters by comparing them with the results obtained in traditional physical laboratories. This study includes eight core plugs from a Cretaceous formation, representing four reservoir rock types. Multiple sub-samples of each core plug were taken and analyzed using the digital rock physics technique. Our DRP computations are compared with the results of physical measurements of the elastic properties on samples from Cretaceous formations under various stress conditions. The latter measurements were conducted on regular core plugs, several cm in size, much larger than the digital rock samples used in this study. Although some of the physical data represent samples from wells different from where the digital samples used here were extracted, these physical samples cover the rock types included in the study. The elastic property values obtained in the digital rock physics laboratory closely match the results of physical measurements conducted at effective stress about 30 MPa. This validation of elastic measurements using DRP ensures quick and reliable data acquisition, at significantly lower costs.