Predicting Lithology And Porosity Of Carbonate Reservoirs Using Geostatistical Stochastic Pre-stack Inversion For Geomodeling Constraint

Abstract

This paper describes a methodology to characterize lithology variations impacting the porosity distribution in a carbonate reservoir. We performed a stochastic seismic inversion to obtain multiple realizations of elastic properties discriminating between the target lithologies. These multi-realizations were then used in a supervised lithoseismic classification for obtaining cubes of occurrence probability of lithologies. Finally, a pseudo porosity cube is obtained using a linear combination between the acoustic impedance and the lithology probabilities. The entire workflow is performed in a stratigraphic grid layeringconsistent with geomodeling grid. Such capability is important for further use of the results as 3D constraint during the geomodel infilling. Lithology probability cubes show proportions in agreement with vertical facies proportions observed from well data.

Lessons Learnt From a 3D Seismic Reprocessing in a Middle East Carbonate Field

“…These two lithologies can be discriminated by elastic properties inverted from seismic amplitudes in order to optimize the porosity modeling driven by seismic data (Pernia et al, 2014). The reservoir displays complex lithology variations represented by thick limestones and dolostones with some thin dolomitic high permeability drains developments.…”