In the last two decades, nanotechnology has flourished due to its vast number of applications in many fields such as drug delivery, oil and gas, and thermal applications, like cooling and air-conditioning. This study focuses on the applications of nanoparticles/nanofluids in the Enhanced Oil Recovery (EOR) process to increase oil recovery efficiency. To understand the nanoparticle-assisted EOR process, the first step is to understand the flow characteristics of nanoparticles in porous media, including entrapment and release in the pores and the behavior of nanoparticles under high temperatures, pressures, and salinity levels and in the presence of external electric and magnetic fields. Also, the process looks at the roles of various pore distributions during their application as EOR agents. The experimental approaches are not only time consuming, but they are also cumbersome and expensive. Hence, the mathematical models could help to facilitate the understanding of the transport and interaction of nanofluids in a reservoir and how such processes can be optimized to get maximum oil recovery and, in turn, reduce the production cost. This paper reviews and critically analyzes the latest developments in mathematical modeling and simulation techniques that have been reported for nanofluid-assisted EOR. One section is dedicated to discussing the challenges ahead, as well as the research gaps in the modeling approach to help the readers to also contribute to further enlightening the modeling nanofluid-assisted EOR process.

This study deals with the application of new rational bi-cubic Ball function with six parameters in image interpolation, especially for the grayscale image. These six free parameters can be modified to get better and quality image resolution, and refine the shape of the interpolating surface. This bivariate rational Ball function has been extended from univariate cases by using a tensor product approach. The proposed scheme is tested for image upscaling with factors of two and four through an efficient algorithm. The effectiveness of the proposed scheme is measured by using an image quality assessment (IQA), such as peak-signal-to-noise-ratio (PSNR), root mean square error (RMSE) or feature similarity (FSIM) index. Numerical and graphical results with comparisons against some existing scheme are presented by using MATLAB. The proposed scheme resulted in higher PSNR and FSIM, and smaller RMSE. Thus, the new rational bi-cubic Ball with six parameters is better than the existing scheme via an efficient algorithm.

The coupling of electromagnetic (EM) wave to nanoflooding experiments, termed EM-assisted nanoflooding has gained enormous attention in recent years. This brings about the consideration of transmitter efficiency and the propagation pattern of the ensuing EM wave, both of which depend on reservoir electromagnetic properties. However, this has not been considered in previous works, despite its potential to improve the efficiency of the process through energy maximization. Hence, this study considers the effects of reservoir EM properties on the operation of a transmitter. The EM properties of saturated reservoir rock samples were measured. Afterward, a half-wave dipole antenna was modeled in a cylindrical reservoir based on the measured EM properties. The EM propagation pattern of the antenna was simulated in a frequency range of 100 MHz—2.0 GHz using the finite element method. The antenna was found to display dual resonance (at 800 MHz and 1.3 GHz) for sandstone saturated with oil, brine and nanofluid. Application of the EM wave at resonance frequency can help increase the efficiency of EM-assisted nanoflooding.