Abstract

Addressing the issue of inadequate temperature tolerance in traditional polymers, in this study, we successfully executed a one-step synthesis of intelligent-responsive polymers which have excellent adaptability in water-gas alternating displacement scenarios. Utilizing the fatty acid method, we produced OANND from oleic acid (OA) and N,N-dimethyl-1,3-propanediamine (NND). Upon testing the average particle size in the aqueous solution both prior and subsequent to CO2 passage, it became evident that OANND assumes the form of a small-molecule particle in the aqueous phase, minimizing damage during formation. Notably, upon CO2 exposure, it promptly organizes into stable micelles with an average size of 88 nm and a relatively uniform particle distribution. This unique characteristic endows it with a rapid CO2 response mechanism and the ability to form a highly resilient gel. In the exploration of viscoelastic fluids, we observed the remarkable behavior of the AONND aqueous solution when CO2/N2 was introduced. This system displayed repeatable transitions between aqueous and gel states, with the highest viscosity peaking at approximately 3895 mPa·s, highlighting its viscosity reversibility and reusability properties. The rheological property results that we obtained indicate that an elongated micellar structure is present in the solution system, with the optimal concentration ratio for its formation determined as 0.8, which is the molar ratio of the OANND-NaOA system. In the sealing performance tests, a 1.0 wt% concentration of the gel system exhibited excellent injectability properties. At 80 °C, this gel effectively reduced the permeability of a sand-filled model to 94.5% of its initial value, effectively sealing potential leakage paths or gas fluxes. This remarkable ability to block leakage paths and reduce seepage capacity highlights the material's superior blocking effect and erosion resistance properties. Furthermore, even at a temperature of 90 °C and an injection pore volume (PV) of 3, this plugging system could reduce the permeability of a high-permeability sand-filled model to over 90% of its initial value.

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