Methodology to predict natural gas in loading and unloading of compressed natural gas (CNG) operations

摘要: Exploiting stranded gas reservoirs, associate from offshore production platforms, condensate reservoirs may not be feasible using traditional approaches (i.e. pipelines) due to volumes, composition, location and/or climate. Marine Compressed Natural Gas (CNG) technology is a possible alternative; however, the required quality for CNG remains challenge in commercial deployment. The optimal design conditions safely and efficiently load, store, unload vessels are highly dependent on of gas. objective this work was evaluate impact moderate/rich gases by performing dynamic simulations loading unloading operations. It demonstrated that existing Equations State (EOS) limited accurately predicting behaviour under load/unload conditions, particularly with large heavy hydrocarbons content. Experiments laboratory-synthesized samples were conducted PVT cell. accuracy EOSs dew points, liquid dropout percentages, densities evaluated experimental data laboratory literature. After tuning Peng-Robinson (PR) Soave-Redlich-Kwong (SRK) equations improve their predictions, performance HYSYS process simulator. A marked improvement EOS predictions achieved modifying few parameters. Dew point improved adjusting binary interaction parameters (kij), density Peneloux parameters, both kij enhanced predictions. Dynamic operations tank then performed effect hydrocarbon content gases. Overall, removing all heavier appeared produce very low temperatures during operation, while these components caused an accumulation liquids inside at keel pressure. In addition, simulation attempted system; attempt unsuccessful as system would require major modifications.