Experimental evaluation shows gelation efficiency improves seepage behavior in porous media, indicating potential in enhanced oil recovery.
An innovative hydrogel system (HBS) utilizing the principle of dynamic covalent bonds, was designed for deep conformance control. It has low-molecular-weight reactive precursors bearing diffusible ketone and acyl hydrazide groups. These precursors undergo in-situ crosslinking via dynamic hydrazone bonds within the pore spaces of the formation, effectively guiding the subsequent injected fluids toward unswept oil zones. The HBS system was investigated through experimental evaluation, numerical simulation, and artificial intelligence methods. A reaction index (RI) and its variation map were established to explore the dynamic chain growth behavior and resistance enhancement characteristics of the HBS system under various injection parameters. A dynamic chain growth experiment using a 9-meter-long core was conducted to evaluate the gelation efficiency of the HBS system. Results show that for HBS, as the chain growth reaction proceeds, the probability of interconnection between different molecular aggregates increases, leading to a corresponding enlargement of aggregate size, which rises its viscosity. Prolonged chain growth time enhances the retention and adsorption of the HBS system within porous media, resulting in higher resistance factors and residual resistance factors, thereby demonstrating distinct seepage characteristics. During migration through the long core, the HBS system exhibits excellent transport performance, effectively redirecting water flow and expanding the swept volume. Numerical simulations and machine learning analyses indicate that RI of the HBS system increases with higher concentration and injection rates. This dynamic chain growth not only enhances flow resistance but also enables deep profile control and further expansion of the swept volume. This research synergistically combines static experimental analyses, dynamic core flooding assessments, and artificial intelligence methodologies to comprehensively investigate the evolving chain growth dynamics and seepage behavior of the HBS system within porous formations. The integrated approach provides important theoretical support and methodological guidance for advancing enhanced oil recovery (EOR) technologies.
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Sun et al. (2025) studied this question.
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