Mechanistic Models for Predicting Sand Production: A Case Study of Niger Delta Wells

Abstract Niger Delta Province is predominantly a friable, unconsolidated sandstone terrain which is susceptible to sand production while developing hydrocarbon reserves in such terrain. In this study, a simple and easy-to-use mechanistic model for predicting sand production rate (SPR) in Niger-Delta wells was developed by coupling the static sanding criteria and the dynamic requirement for fluidization of the produced sand. A generic mechanistic model that incorporates the concept of dimensionless quantities associated with sanding was developed; the quantities considered include the loading factor, Reynolds Number, water cut and gas-liquid ratio, GLR. The output from the proposed model is a dimensionless sand production rate (SPR) correlation index. Results indicated that every reservoir has a unique SPR correlation index which represents its propensity to produce sand or its sanding identity. The developed model was validated by comparing its predictions with field data and the results showed an acceptable maximum deviation of less than 6% in the wells of an onshore asset investigated in the Niger Delta. Compared to existing models, the proposed model predicts better results especially when GLR is significantly high. The applications of this study include reservoir management, completion design, perforation design, sand monitoring strategy, design of surface facilities and pipelines, and analysis of field development plans and economics.