Spatially Resolved CFD-DEM Modelling and Experimental Validation for Enhanced Sand Retention Understanding in Standalone Screen Completions

Abstract This paper aims to enhance the understanding of sand retention mechanism in oil and gas wells through a coupled CFD-DEM approach and innovative laboratory experiments. The motivation stems from the economic impact of sand production, where standalone screens serve as cost-effective alternatives to gravel-pack completions. However, existing selection criteria are limited under certain operating conditions. This study addresses these limitations by focusing on the often-overlooked role of the deposited bulk filter bed on the screen, a critical factor in sand retention. Utilising a spatially resolved CFD-DEM model, this study simulates the sand retention process, extending beyond basic parameters like the mass of sand particles produced. It incorporates a comprehensive analysis of filter bed growth, porosity, and permeability, which significantly impact the productivity index of the fluid rather than the screen itself. The permeability analysis includes both the numerical filter bed and the screen, inherently addressing screen plugging. A novel experimental methodology benchmarks the numerically derived single-phase permeability of the filter bed using micro-CT images of experimentally derived filter beds. The findings demonstrate strong matches between the CFD-DEM simulations and laboratory experiments, validating the numerical model and showing consistent porosity and single-phase permeability of the filter bed. These results highlight that the dominant filter medium is the filter bed rather than the screen itself. This contributes to a more nuanced understanding of sand retention systems, with implications for optimising standalone sand screen selection criteria in screen-only completions. The novelty of this research lies in its holistic approach to sand retention systems, considering the interplay between the filter bed and standalone screens. By addressing existing criteria limitations and incorporating a detailed analysis of filter bed properties, the presented CFD-DEM model provides a foundation for improving selection criteria. This model lays the groundwork for future analyses, exploring parameters to determine optimal conditions for maximising sand retention while maintaining hydrocarbon productivity in screen-only well completions.