The transport and elastic properties of a rock are functions of the pore size distribution, geometry and morphology. Due to limited availability of 3-D micro-structure images of rocks, several attempts to theoretically model the behavior of rocks have been made. However, all such methods have limitations. In addition, 3-D micro-structure images of rocks, even if available, represent only a small volume of the rock, and the predictions of macroscale properties based on them are uncertain. In this study, a new stochastic method to reconstruct a 3-D model for the rock using only a 2-D section of the imaged rock sample is proposed. The proposed method is a combination of a multiple point statistics simulation, gradual deformation of images, and calculation of transport and elastic properties. The first step is to generate multiple independent realizations by performing multiple-point statistics based stochastic simulations. These simulations represent independent 2-D scans through the rock volume. Next, a succession of images is generated spanning two adjacent independent sections. These images are generated so as to gradually morph features from one section to those in the next independent section. These 2-D images are then stacked together to reconstruct the 3-D image.
After reconstruction, transport and elastic properties of the reconstructed image are computed. For a test case for which the measured rock properties are available, the results obtained using the reconstructed image reveal that the calculated properties are close to the measured values. Finally, we generated multiple realizations with different porosity values, where the shape of pores and grains are preserved. We studied the sensitivity of the elastic properties to the porosity of the samples. The results provide insights on the effect of cementation or increased overburden pressure on flow and mechanical properties of rocks.