ABSTRACTThe authors present the application of the statistical model in CO hydrogenation to CH4, C2-C4 and C5+ over industrial iron-based catalyst (100 Fe/5 Cu/4.2 K/25 SiO2) in a 1-L stirred tank slurry reactor. The effect of different reaction conditions, including temperatures (T = 493, 513 and 533 K), pressures (P = 0.8, 1.5, 2.25, and 2.5 MPa), synthesis gas feed molar ratios (H2/CO = 0.67 and 2), and gas space velocity (GSV) from 0.52 to 23.5 Ndm3/g-Fe/h on selectivity investigated via a statistical models. The proposed selectivity model is very useful in the oil, gas, and petrochemical industries and can be used for interpretation of experimental data, comparison of performance of different reactor conditions, and reactor modeling and simulation studies. Furthermore, interaction between operating parameters such as pressure, temperature, H2/CO, and GSV was investigated in selectivity models. A CUBIC polynomial was successfully fitted to the experimental data. It was concluded that C5+ selectivity shifts to higher with increasing total pressure (H2/CO) ratio and decreasing temperature. Decreased H2/CO ratio and temperature and increasing in the reactor pressure cause CH4 formation decrease. Temperature and pressure fluctuations vary product distribution. As it is observed, the insignificant term in C2-C4 selectivity is pressure. With the models obtained from regression we can reach to the optimum condition for favorite products such as C2-C4 or C5+. So that optimization must be done to illustrate the optimum conditions. It was obtained that the maximum amount of C5+ and C2-C4 and minimum amount of methane achieved in T = 528.97 K, P = 1.23 bar, H2/CO = 2, and GSV = 23.49 Ndm3/g-Fe/h.