An Integrated Simulation Approach To Predict Permeability Impairment under Simultaneous Aggregation and Deposition of Asphaltene Particles

Formation damage mechanisms in general lower the quality of the near wellbore, often manifested in the form of permeability reduction, and thus reducing the productivity of production wells and injectivity of injection wells. Asphaltene deposition, as one of the important causes, can trigger serious formation damage issues and significantly restrict the production capacity of oil wells. Several mechanisms acting simultaneously contribute to the complexity associated with prediction of permeability impairment owing to asphaltene deposition; thus, integration of modeling efforts for asphaltene aggregation and deposition mechanisms seems inevitable for improved predictability. In this work, an integrated simulation approach is proposed to predict permeability impairment in porous medium. The proposed approach is novel because it integrates various mathematical models to study permeability impairment considering porosity reduction, particle aggregation, and pore connectivity loss caused by asphaltene deposition. To improve the accuracy of simulation results, porous media is considered as a bundle (different size) of capillary tubes with dynamic interconnectivity. The total volume change of interconnected tubes will directly represent permeability reduction realized in porous media. The prediction of asphaltene deposition in porous media is improved in this paper via integration of the particle aggregation model into calculation. The simulation results were verified by comparing with existing experimental data sets. After that, a sensitivity analysis was performed to study parameters that affect permeability impairment. The simulation results show that our permeability impairment model-considering asphaltene deposition, aggregation, and pore connectivity loss-can accurately reproduce the experimental results with fewer fitting or empirical parameters needed. The sensitivity analysis shows that longer aggregation time, higher flow velocity, and bigger precipitation concentration will lead to a faster permeability reduction. The findings of this study can help provide better understanding of the permeability impairment caused by asphaltene deposition and pore blockage, which provides useful insights for prediction of production performance of oil wells.

Automated summary

The study proposed an integrated simulation approach to predict permeability impairment in porous medium, considering porosity reduction, particle aggregation, and pore connectivity loss caused by asphaltene deposition. By integrating the particle aggregation model, the prediction of asphaltene deposition in porous media was improved. Sensitivity analysis revealed that longer aggregation time, higher flow velocity, and bigger precipitation concentration lead to faster permeability reduction, ultimately providing insights for predicting production performance of oil wells.