Autonomous Reservoir Nano-Agents

Abstract This article demonstrates the ability of salinity gradients that naturally exist, or could otherwise be induced, in the reservoir to target-migrate nanoparticles in porous and fractured reservoirs. This nanoparticles’ autonomous migration marks a significant milestone towards the development of reservoir nano-agents that self-migrate in deep and hard-to-reach regions in the reservoir without the aid of advective flows. Direct microscopic visualization experiments were conducted in representative micromodel environments to quantify the displacement and velocity vectors of model nanoparticles in response to different concentration gradients of solutes in the absence of advective flow. One set of experiments used solutes with different divalent ions and another set used high-salinity water to create the concentration gradients. Nanoparticle migration distance and speed up or down the imposed gradients were precisely obtained from high resolution image sequences using particle image velocimetry (PIV) algorithms. The rate at which the particles migrate was calculated and used to validate and extend existing theories to high salinity conditions. Results showed that, in the absence of flow, nanoparticles readily migrate upon exposure to a given gradient, either up or down the gradient, depending on the solute composition (diffusiophoresis). The rate at which the particles migrate is on the order of μm/s and was found to be dependent on: 1) the gradient magnitude, 2) absolute value of the minimum and maximum concentration of the gradient, 3) ion diffusivities. The results presented here provide new insights into the transport mechanisms of nano and micro particles in oil reservoirs where naturally-occurring or induced solute and chemical gradients exist. These results provide a platform for the development of reservoir nano-agents that self-migrate in deep and hard-to-reach regions in the reservoir without the aid of advective flows.