Formation evaluation in low porosity, low salinity, and high temperature reservoirs poses many challenges. The environment is hostile to many logging tools due to their temperature limits and there is greater uncertainty related to petrophysical parameters compared with conventional formations. Additionally, in low porosity and low salinity reservoirs, resistivity contrast between hydrocarbon and water filled rocks is often missing. This extended abstract presents a case study from offshore WA where a petrophysical model has been created with logging while drilling measurements including spectroscopy data to improve estimation of mineralogy, clay volume and porosity, thereby reducing saturation evaluation uncertainty. Spectroscopy measurements can be analysed to derive dry weight elemental concentrations of various elements such as silicon, calcium, iron, and sulfur. These concentrations have been subsequently used as input to compute a multi-mineral petrophysical model using a least squares inversion technique. We demonstrate that spectroscopy can be used independently to obtain an accurate volume of clay instead of gamma ray, spontaneous potential, or porosity logs. Moreover, matrix properties such as grain density, which enhance the accuracy of porosity estimation derived from bulk density, are also derived from spectroscopy dataset. Good agreement with core validates the petrophysical model. Also demonstrated is how the petrophysical model reduces the uncertainty in clay volume and porosity, from which more accurate water saturation can be derived in these tight reservoirs. Calibrating the spectroscopy information to core data allows the mineralogical and geological model to be extended to the intervals where core data are not available.