Microfluidic experiments and numerical modeling of pore-scale Asphaltene deposition: Insights and predictive capabilities

Abstract

Pore-scale asphaltene deposition not only affects reservoir permeability and hydrocarbon production efficiency but also impacts reservoirs performance used in other applications, such as geothermal and CO2 storage. The limited availability of comprehensive experimental data has impeded the development of precise predictive models for deposition behavior. This study employs real-time microfluidic experiments and a Lattice Boltzmann-Immersed Boundary numerical model to investigate pore-scale asphaltene deposition. Experimental results directly observe porosity reduction in diverse pore geometries, offering a detailed explanation of asphaltene deposition phenomena. The LB-IB model accurately replicates complex deposition behavior with over 93% agreement with experimental results across various geometries, using only two adjustable parameters. This enables precise predictions of asphaltene phase behavior in porous media. Sensitivity analyses explore the influence of reservoir geometry, flow rates, and asphaltene concentrations on deposition behavior, underscoring their significant impact on porosity reduction and emphasizing the importance of understanding asphaltene deposition. Additionally, the study compares the proposed model to the Wang-Civan model, showcasing its superior accuracy in capturing deposition mechanisms, and suggests modifications to include an upper limit for deposition when throats are entirely filled with asphaltene. This study improves our understanding of pore-scale asphaltene deposition, aiding in optimizing hydrocarbon extraction practices and industry efficiency.