The present study investigated the wax deposition tendencies of a light Malaysian crude oil (42.4° API), and the wax inhibiting potential of some surfactants and their blends with nanoparticles. With the knowledge that the majority of the wax inhibition research revolved around polymeric wax inhibitors, which cause environmental issues, we highlighted the potential of surfactants and their blend with SiO₂ nanoparticles as wax deposition inhibitors. Different surfactants including oil-based, silane-based, Gemini and bio-surfactants were considered as primary surfactants. The primary surfactants and their respective blends at a concentration of 400 ppm were screened as wax inhibitor candidates using cold finger apparatus. The screening results showed a significant influence on the paraffin inhibition efficiency on wax deposition by using 400 ppm of silane-based surfactant, which decreased the wax deposition up to 53.9% as compared to that of the untreated crude oil. The inhibition efficiency among the silane-based surfactant (highest) and bio-surfactant (lowest) revealed an appreciable difference up to 36.5%. Furthermore, the wax from the treated sample was found to deposit in a thin gel-like form, which adhered inadequately to the surface of the cold finger. A further investigation by blending the 400 ppm silane-based surfactant with a 400 ppm SiO₂ nanoparticle suspension in a load ratio of 3:1 found that the wax inhibition decreased up to 81% as compared to the scenario when they were not added. However, we have shown that the synergy between the silane-based surfactant and the nanoparticles is influenced by the concentration and load ratio of surfactant and nanoparticles, residence time, differential temperature and rotation rate.

Enhanced coal bed methane recovery using gas injection can provide increased methane extraction depending on the characteristics of the coal and the gas that is used. Accurate prediction of the extent of gas adsorption by coal are therefore important. Both experimental methods and modeling have been used to assess gas adsorption and its effects, including volumetric and gravimetric techniques, as well as the Ono–Kondo model and other numerical simulations. Thermodynamic parameters may be used to model adsorption on coal surfaces while adsorption isotherms can be used to predict adsorption on coal pores. In addition, density functional theory and grand canonical Monte Carlo methods may be employed. Complementary analytical techniques include Fourier transform infrared, Raman spectroscopy, XR diffraction, and ¹³C nuclear magnetic resonance spectroscopy. This review summarizes the cutting-edge research concerning the adsorption of CO₂, N_2, or mixture gas onto coal surfaces and into coal pores based on both experimental studies and simulations.