<jats:title /> <jats:p>Digital Oil, which is a full molecular model of crude oil, opens a new era for understanding the behavior of crude oil at a wide range of thermodynamic conditions. In this study, a Digital Oil model for a domestic oil field was constructed based on analytical experiments, including gas chromatography data, elemental composition, molecular weight from gel permeation chromatography, 1H-NMR and 13C-NMR spectroscopy data. The gas and light fraction components were analyzed by gas chromatography, and 109 kinds of molecules, including n-alkanes, iso-alkanes, naphthenes, alkylbenzenes, and polyaromatics (with maximum 3 aromatic rings), were modeled. On the other hand, the heavy fraction and asphaltene components were represented by molecular mixtures using an improved quantitative molecular representation (QMR) method, which were consistent with analytical experiments, such as elemental composition, molecular weight from gel permeation chromatography, 1H-NMR and 13C-NMR spectroscopy data. Due to its low weight concentration of asphaltenes (~0.1 wt%), the Digital Oil (i.e. the live oil) model was constructed by mixing all the above molecular models except for the asphaltene model. With this model, densities of the live oil were calculated at a wide range of pressure under reservoir temperature by molecular dynamics simulations. At pressures above 163 bar, the densities were calculated by assuming single phase. The results show very good agreement with experimental data of the crude oil. At pressures below 163 bar, components in a liquid phase of the Digital Oil were predicted by flash calculations using equation of state (EOS) model at selected pressure conditions. In this case, the calculated densities of the liquid phase also coincided with the densities of the experiment. Thus, we could observe reproducibility of the Digital Oil in terms of density at a wide range of pressure. It provides a good example on using simulation tools across different scales with multi-physics models (i.e. EOS and molecular models). Digital Oil is a versatile tool, which can be applied in both upstream and downstream industries for various problems. Since most of EOS models were developed before new field advancement of asphaltene and heavy oil molecular models (including ours here), attention and hopes were drawn for further application of Digital Oil conception in oil industries.</jats:p>