Current efforts to predict porosity and permeability in sandstones prior to drilling are focused on empirical and process-oriented models. Empirical predictions are based on the correlation between porosity and permeability and a limited number of parameters obtained from calibration data sets or estimated from appropriate geologic models. Of these parameters, the most important are detrital composition, grain size, sorting, and temperature history or pressure history or both. Despite its limitations, the empirical approach provides accurate predrill predictions of reservoir quality in many sandstones containing not only primary but also secondary porosity and permeability. Predictions of the average porosity and permeability of target sandstones are arbitrarily defined h re as accurate if they fall within +/- 2% porosity of the mean measured porosity and within the same order of magnitude as the mean measured permeability in a sample population representing the interval of interest. The effectiveness of the empirical predictive approach is illustrated by case studies from the Taranaki basin (New Zealand) and Yacheng field (People's Republic of China). These studies indicate that empirical predictions are basin specific or even play specific, and require at least some understanding of fundamental processes affecting reservoir quality of a given sandstone target.

Process-oriented approaches attempting to model the effect of diagenesis on reservoir quality are hampered by inadequate quantitative understanding of the processes responsible for preserving primary porosity and generating secondary porosity and permeability. Until adequate quantification of the sandstone diagenesis processes is achieved, empirical models have a distinct advantage over process-oriented models in providing reliable predictions of reservoir quality in many sandstone intervals.