Sonic Velocity–Based Experimental and Modeling Approach to Determine Fluid Properties of Greenhouse Gas Mixtures of CO2 and CH4

Summary Climate-related concerns from rising carbon dioxide (CO2) emissions, along with geopolitical pressures, have prompted the chemical, manufacturing, and energy industries to urgently tackle the issue by developing/adopting emission-reduction technologies. To address this, various decarbonization pathways are being explored, including carbon capture and storage (CCS), enhanced geothermal, electrification, and hydrogen. In all these pathways, an accurate estimation of thermodynamic properties of fluids is essential for process design and scaleups. This study focuses primarily on greenhouse gases, especially CO2, methane (CH4), and their mixtures, for the applications of CCS and enhanced geothermal. In particular, a modeling framework is developed for these mixtures that couples an equation-of-state (EOS)-based model with sonic velocity–based experimental validation to estimate several fluid properties [such as heat capacities, enthalpy, entropy, sonic velocity, density, isothermal compressibility, and Joule-Thomson (JT) coefficient]. A pulse-echo technique was used to measure the sonic velocity of CO2-CH4 mixtures (containing 0–30 mol% CO2) in the pressure range of 1–200 bar and in the temperature range of 300–323 K. The corresponding density was measured using a magnetic suspension balance apparatus. The modeling is based on the Peng-Robinson (PR78) EOS with Peneloux shift, where the ideal part of the isobaric heat capacity (obtained from correlations available in literature) is used to determine the residual part of all fluid properties from the EOS model at extended pressure and temperature (PT) conditions. Coupled with prior work (Ratnakar 2024b) on pure CO2, this study captures the full composition range of CO2-CH4 mixtures. The experimentally measured sonic velocity and density data for CO2-CH4 mixture and CH4 are aligned with that available in literature. The modeling framework leads to a very good match with the in-house and available literature data, within the relative error of 1–3%, acceptable for most practical applications. The isothermal compressibility of the fluid is derived directly from the sonic velocity with better accuracies in contrast to the traditional (density derivative) approach that leads to significant noises near phase boundary and critical points. Most importantly, the framework presented in this study is general, able to use any other EOS model, can be extended to any fluid system as long as the EOS parameters and ideal part of isobaric heat capacity are known a priori, and determine the fluid properties more accurately.