Abstract

Net-to-gross (N/G ) is a measure of the amount of sand or pay in the overall reservoir and is used to appraise reservoir quality and the economics associated with reservoir development. As seismic based reservoir characterization technology is advancing in many cases lithology and porosity information derived from seismic inversion can be used to derive an estimate of N/G. In many cases this problem is non unique due to accuracy of seismic inversion and the rock physics nature of the lithology and porosity prediction. Thus as N/G estimates are often used for economic decision-making it is important to associate expected risk or confidence associated with the prediction. In this paper we we present a workflow to compute quantitative estimates of N/G, along with associated uncertainties, from well-log calibrated pre-stack seismic inversion attributes. The main tools we use in this workflow are Seismic (AVO) Inversion, Rock Physics, and Bayesian Statistics. We estimate the N/G from the seismically derived rock properties. We derive the uncertainty in net-to-gross from uncertainties in seismic inversion, reservoir properties, and geologic interpretation.