Natural gas (NG) is a low-carbon fossil fuel that carries impurities such as carbon dioxide (CO2) and nitrogen (N2). These two impurities reduce the heating value of NG. Also, CO2 causes corrosion in the pipeline and N2 produces nitrogen oxide (NOx) when combusted. These facts have forced NG transmission and distribution companies to limit the concentrations (mole percent) of CO2 (≤ 3%) and N2 (≤4%). Consequently, selective separation of CO2 and N2 from NG has gained considerable importance. There are many technologies that are in use for separation of these two constituents. Most of them are suitable for single component separation: either CO2 or N2. In the context of multicomponent separation common in industries, adsorption is an emerging technology that offers low-cost and energy-efficient separation for small- to medium-sized industries. The technology lacks commercial availability due to its dependency of design methodologies on experimentation, simulation or both. This work focuses on easy-to-use design methodology for the design of a double bed adsorber. This easy-to-use methodology is tailored for separation of CO2 and N2 from NG using zeolite13X and a carbon molecular sieve (CMS3K) or activated carbon (ACB). These adsorbents are commercially available, and they offer easy and energy efficient regeneration for repeated uses. The product will meet the specified concentration limit for NG transmission and distribution systems. To achieve this goal, two layered bed adsorbers, zeolite13X-CMS3K and zeolite13X-ACB, were simulated using Aspen Adsorption. Simulation requires a trustworthy mathematical framework i.e. model. Therefore, a model was developed in Aspen adsorption by selecting relevant equations and submodels. Inputs for the model were collected from literature, calculated using various equations, and obtained by fitting experimental data. A numerical solution method was specified and, finally, the model was validated against experimental measurements. A parametric study was performed for a wide range of operating conditions. Data generated through parametric study were correlated. The correlations, the first of this kind, can be used to predict required amounts of adsorbents for 100% CO2 separation and 50 to 90% N2 separation. Finally, a procedure was outlined to transform the amount of adsorbent into the physical dimensions of an adsorber.