Hybrid Intelligent Modelling of the Viscoelastic Moduli of Coal Fly Ash Based Polymer Gel System for Water Shutoff Treatment in Oil and Gas Wells

Abstract

Qualitative polymer gels exhibiting considerable viscoelastic properties are of immense significance in the petroleum industry as they curtail excessive water production during the tertiary stage of crude oil production. The incorporation of suitable organic or inorganic solid substances into the polymer gel system strengthens its viscoelastic properties. This research work presents hybrid gravitational search algorithm (GSA) and support vector regression (SVR) as novel modelling tools for viscoelastic properties estimation of polymer gel synthesized from polyacrylamide (PAM)/polyethyleneimine (PEI). The coal fly ash (CFA) was incorporated in PAM/PEI gel in order to enhance its viscoelastic characteristics. The hybrid GSA‐SVR models were developed using real‐life experimental data. The results of the models validated using unseen data show a high degree of correlation coefficients (87.3 % for elastic modulus and 97.2 % for viscous modulus), with experimental data generating a small root mean square error (coefficients 669.5Pa for elastic modulus and 38.5Pa for viscous modulus). The developed hybrid models were further used to scrutinize the effect of the addition of various amounts of CFA on the PAM/PEI viscoelastic properties and observed behaviours were presented and discussed. The predictive capability of the developed hybrid model coupled with its strength in modelling the impact of CFA in the PAM/PEI gel are highly meritorious and the outcomes from this investigation would be relevant during the design and formulation of polymer gels employed for water shutoff treatment during hydrocarbon recovery.