Large Pore Network simulations coupled with innovative wettability anchoring experiment to predict relative permeability of a mixed-wet rock

Abstract

Since the pioneering work of Oren et al. 1998several attempts have been made to predict relative permeability curves with Digital Rock Physics (DRP) technique. However, the problem has proved more complex than what researchers have expected, and these attempts failed. One of the main issues was the high number of uncertain parameters especially for the wettability input and this gets worst in mixed-wet scenario as the number of parameters is higher than in water-wet and oil-wet cases. In fact, Sorbie and Skauge 2012 stated that wettability assignment is the most complex and least validated stage in DRP simulation workflow. Similarly, Bondino et al. 2013concluded that “genuine prediction” of multi-phase flow properties will remain not credible until important progress is achieved in the area of wettability characterization at the pore scale. In this work, we propose a pragmatic approach to tackle these problems. First, we parallelize our pore network simulator in order to achieve large scale PNM simulations. Then, we develop an innovative and fast anchoring experiment imaged by micro-CT scanner, that helps to determine several wettability parameters needed for the DRP simulation (including the fraction of oil-wet/water-wet pores, any spatial or radius correlation of oil wet pores…). This experiment also provides an estimation of macroscopic parameters that help to anchor our pore scale simulations and further reduce the uncertainty. In addition to help reducing the uncertainty of the simulation, this experiment provides a fast estimation of the wettability of the system. Images representing large volumes with low resolution are, first, improved with Enhanced Super Resolution Generative Adversarial Networks (ESRGAN) to obtain a large image with high resolution. Then, a pore network is extracted, and TotalEnergies parallel pore network simulator is used for multiphase flow simulations considering the constraints from the anchoring experiment to reduce the uncertainty. Finally, we compare our simulations against high quality SCAL experiment performed in-house and we assess the predictive power of our DRP workflow.

Large-Pore Network Simulations Coupled with Innovative Wettability Anchoring Experiment to Predict Relative Permeability of a Mixed-Wet Rock

“…Therefore, we have designed a wettability anchoring experiment (described in the next section) to help us better estimate these wettability parameters. Subsequently, we have developed a statistical uncertainty work ow (Regaieg et al 2021) in which we vary the uncertain pore network simulation parameters within the ranges determined from the experiment. First, thousands of DynaPNM input les are generated in an experimental design phase using WSP method (Sergent 1989).…”

Fast wettability assessment on small rock samples using a 3D, high-resolution, image-based Amott-like test

“…In this paper, we explore the possibility of acquiring a qualitative wettability indicator, similar to that obtained using the conventional wettability characterization via Amott tests on centimeter-sized samples, using instead millimeter-sized samples imaged with a high-resolution micro-CT scanner. Following the idea presented in [6], also reported in [7] as a means of rapidly characterizing the wettability input required for Digital Rock Physics simulation, we used a similar experimental set-up to realize a full Amott-like cycle on small core samples (4mm diameter, 15mm long) with fluid saturations determined from micro-CT image analysis. It is also expected that pore scale imaging, at least in the part of pore network that can be fully resolved, will provide additional information on the wetting properties of the system.…”