The main purpose of seismic reservoir characterization is to infer petrophysical properties from seismic data. Seismic inversion is a technique widely used to estimate subsurface elastic parameters to be linked to petrophysical variablesby rock physics models. Kerogen content, porosity, water saturation and effective pressure, are key petrophysical parameters for the characterization of Vaca Muerta formation, and its impacts on elastic parameters were analyzedduring this study. To determine if their variations can be estimated through seismic inversion, the inversion error must be computed. The proposed methodology involves synthetic seismic modeling and inversion of P wave impedance (Ip), P and S wave velocity ratio (Vp/Vs) and density (Rho). Inverted parameters are compared to the model, by means of correlation coefficients and relative errors, defined as the ratio of the root mean square error by the total variation of the elastic parameter. Signal to noise ratio, the angle range and the number of partial stacksare tested to stablish the dependence of the inverted error with the quality of seismic data and the geometry of the inverse problem. Rock physics "soft sediments/friable shale" model, calibrated with well log information, was used to link petrophysical to elastic variables. In a regional scale, measured well log data exhibit a variation of 5% to 15% for porosity, 2% to 16% for kerogen content and 20% to 100% for water saturation. A range of 40 MPa to 10 MPa of effective pressure was stablished to cover from normal pressure to overpressure reservoir scenarios. Acoustic impedance results to be the most sensitive parameter, with variations of 35% for porosity changes, 18% for water saturation variations, 13% for kerogen variations and 11% for pressure variations. Vp/Vs is mainly affected by water saturation (16%), pressure (5%) and kerogen (2.5%), while porosity produced variations lower than 1%. This study demonstrates that expected variations in acoustic impedance for Vaca Muerta reservoirs are above the inversion errors for different scenarios of seismic data quality and geometry of the inverse problem. Vp/Vs inversion strongly depends on the quality of seismic data, and the geometry of the inverse problem. The error for Vp/Vs is higher or comparable to the expected variations. Higher signal to noise ratio and wide-angle coverage is required to obtain minor errors. Density inversion is discarded as it is mainly controlled by the low frequency model, for the angle range coverage with physical meaning for Vaca Muerta.