oa Multi-scale Imaging Of Carbonate Rocks Using Confocal Laser Microscopy And Micro-ct Scanning And Predicting Two-phase Flow Using Lattice Boltzmann Simulation

More than 50% of the world's hydrocarbons reserves are contained in carbonate reservoirs. Carbonate rocks have a very complicated and heterogeneous porous structure in comparison with sandstone reservoir rock [1]. To understand the transport processes in any porous medium, we need to enhance our knowledge of the geometry and topology of the porous media [2]. Our understanding of porous carbonate rocks in this respect is still very limited in comparison with sandstones. In the last few years, pore scale studies have revolutionised the fundamental understanding of complex fluid flow processes in the field of groundwater remediation, oil industry and environmental issues related to carbon storage and capture. Therefore, in this work we present advances in several multi-scale imaging techniques to obtain 2D and 3D images at pore scale (voxel size 1- 10µm) using Confocal Laser Scanning Microscopy (CLSM)and Micro CT imaging as shown in Figure 1 . We will also discuss a novel technique of CLSM to obtain 2D images with a large field of view, including advantages and limitations for scanning porous carbonate rocks. We then describe approaches to extract statistical information about total, macro and micro-porosity from 2D large field of view CLSM and validate the results using Mercury Intrusion Porosimetry (MICP). In this work, using the image processing techniques for different phase segmentation, we study the effect of scanned resolution images on porosity and permeability using Lattice Boltzmann simulation and pore network modelling. Finally, we describe the recent development of lattice-Boltzmann (LB) simulations for the prediction of multi-phase flow properties in complex carbonate pore space images; as potential element of Special Core Analysis (SCAL); and for Enhanced Oil Recovery (EOR) operations. We introduce a GPU algorithm for large scale LB calculations, offering greatly enhanced computing performance in comparison with CPU calculations. References [1] Knackstedt, M., Arns, C., Ghous, A., Sakellariou, A., Senden, T., Sheppard, A., Sok, R., Averdunk, H., Val Pinczewski, W., Padhy, G.S., Ioannidis, M.A., 3D Imaging and flow characterization of the pore space of carbonate rock samples, International Symposium of the society of Core Analysts., SCA2006-23, Norway [2] Baldwin, C.A., Sederman, A.J., Mantle, M.D., Alexander, P., Gladden, L.F., Determination and characterization of the structure of a pore space from 3D volume images, Journal of Colloid and Interface Sciences., 181 (79-92), 1996.