iLoPS – integrated Low Permeability Systems

This project is part of a collaborative research initiative together with the Energy & Mineral Resources Group (EMR) of the RWTH Aachen University and the Wintershall Holding GmbH. The main focus is on an improved description and prediction of fluid transport properties of tight sandstones (“tight gas” systems) and shales (“shale gas” systems). Knowledge of the transport properties is of utmost importance when considering reasonable productivity estimates and the development of flow rates during the entire production cycle. Here, petrophysical parameters of interest are intrinsic permeability k, effective permeability k eff , porosity-permeability relationships, critical capillary pressure Pc and the stress dependence of all the aforementioned parameters. While the EMR group approaches this problem from the experimental side, the Institute of Applied Geophysics and Geothermal Energy (GGE) follows two different but complementary numerical research lines.

High pressure and high temperature NMR-Flow-Cell for simultaneous NMR relaxation and permeability measurements under reservoir-like conditions Copyright: Thomas Hiller Fig. 1 High pressure and high temperature NMR-Flow-Cell for simultaneous NMR relaxation and permeability measurements under reservoir-like conditions

In a first part we use Nuclear Magnetic Resonance (NMR) relaxometry data at different stages of desaturation to jointly derive mineral parameters (surface relaxivity ρS) and pore size distribution. We replaced the standard cylindrical pore model with a pore model based on angular pores to consider the desaturation characteristics of more complex pore geometries. To conduct NMR measurements under reservoir-like conditions we developed a NMR-Flow-Cell where rock samples can be installed at confining pressures up to 300 bar and temperatures up to 80C (Fig. 1). These NMR measurements can then be compared against data directly acquired in a well or laboratory measurements under ambient conditions.

In a second part we will focus on modelling single- and two-phase flow transport properties of water and gas at the pore scale. Therefore, we will use high-resolution images (CT) of real rocks from which representative three-dimensional pore space models will be extracted and used for the numerical simulation of fluid flow (Fig. 2). Finally, both approaches shall be merged to derive a protocol that allows for a fast and cost-effective estimation of effective transport properties.

3D pore space model on the right and reconstructed from  smaller than 500 CT images on the left Copyright: Thomas Hiller Fig. 2 3D pore space model (right) reconstructed from >500 CT images (left)