Application of Pore Network Modelling in Simulating Surfactant EOR Coreflooding Experiment: A Case Study in Clastic Rock Sample using CT-Scan Coreflood Equipment

Surfactant flooding is an enhanced oil recovery (EOR) technique that involves injecting surfactants into reservoirs to improve oil recovery. Pore network modelling (PNM) is a numerical method used to simulate fluid flow in porous media. While PNM has been successfully applied in various applications, its use in surfactant flooding has been limited to pore scale level up until micromodel scale networks only, which do not accurately represent the complex pore structure of real reservoir. This study aims to extend PNM to core-scale networks. The objective of this study is to evaluate the capability of the surfactant pore network modelling (PNM) simulator in analysing surfactant coreflood experiments. Besides that, by validating the PNM simulation against the CT-Scan coreflood experiment, it can also test the potential of the "medical" CTScan coreflood in digital core analysis (DCA) domain. In this study, a state-of-the-art attempt to compare our PNM simulation results against surfactant flooding CT-scan coreflood experiments was performed. These coreflood experiments also demonstrate the potential of utilizing the state-of-the-art CT-scan technology to complement the pore network modelling validation works. The CT-Scan has been conducted to monitor the displacement pattern throughout the 12-inch core samples during tertiary surfactant injection. Several 2D centimetre scale and upscaled 3D PNM simulations to simulate tertiary surfactant injection have been conducted. The results show that upscaling from 2D to 3D models improves the realism of simulation outcomes. The choice of surfactant injection protocol and initial water saturation significantly impact the displacement process. Secondary injection appears to provide favourable results. The comparison between simulation and coreflood experiments have showcased the capability of the surfactant PNM simulator to analyse coreflood experiments and give novel insights into the underlying recovery mechanisms. The study emphasizes the importance of accurately representing rock architecture and the need to consider 3D effects and initial water saturation for realistic PNM simulation results. The novelty of this work lies in the application of PNM to core-scale networks. A workflow for applying the PNM simulator for simulating coreflood experiment have been proposed. This study demonstrates the capability of the surfactant PNM simulator for analysing surfactant coreflood experiments. It highlights the importance of upscaling to 3D models, considering surfactant injection protocols, and understanding the impact of initial water saturation. This study has also tested the limitation of CT-Scan coreflood technology in DCA application. The findings provide valuable insights into the complex behaviour of surfactant flooding processes and emphasize the potential of PNM simulation for surfactant EOR evaluation. Future research should focus on improving the computational efficiency.