Characterization and probabilistic estimation of tight carbonate reservoir properties using quantitative geophysical approach: a case study from a mature gas field in the Middle Indus Basin of Pakistan

Abstract

In this study a tight carbonate gas reservoir of early Eocene (S1 formation) is studiedfor litho-facies estimation and probabilistic estimation of reservoir properties predictionusing quantitative geophysical approach from a mature gas field in the Middle IndusBasin, onshore Pakistan. Quantitative seismic reservoir characterization approachrelied on well based litho-facies re-classification, Amplitude Variation with Offset (AVO)attributes analysis and Pre-Stack simultaneous inversion attributes constrained withcustomized well-log and seismic data (gathers) conditioning. Three main litho-facies(hydrocarbon bearing limestone, tight limestone and shale) are classified estimatedbased on the precise analysis of well data using petrophysical properties. AVOattributes (intercept and gradient) conveniently inspection for amplitude behavior(reflection coefficients) of the possible AVO (class I), fluids and lithologycharacteristics. Probable litho-facies (tight limestone and shale) are estimated usingwell based litho-facies classification and inverted seismic attributes (p-impedance anddensity) from pre-stack simultaneous inversion in a Bayesian framework. Additionally,petrophysical properties (clay volume and porosity) are derived from probabilisticneural network approach using well logs and pre-stack inverted attributes (pimpedanceand density) constrained with sample-based seismic attributes(instantaneous, windowed frequency, filters, derivatives, integrated and time).