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).
Highlights
Carbonate rocks are considered as a major host rock for hydrocarbon reservoirs worldwide
Results proved the validity and robustness of quantitative seismic reservoir characterization framework employed to litho-facies and predict petrophysical properties, and helped us to effectively position and plan of high-technology horizontal wells as a part of redevelopment program of the field
Litho-facies are defined at well location based on core sample and area geological information using well-log-based estimates of petrophysical properties
Summary
Carbonate rocks are considered as a major host rock for hydrocarbon reservoirs worldwide. Main objective of this study is to accurately characterize reservoir litho-facies (tight limestone and shale) and petrophysical (clay volume and porosity) properties. Quantitative seismic reservoir characterization approach employed integrates litho-facies classification, AVO attribute analysis and pre-stack simultaneous inversion technique, supported with the customized well-log and seismic data (gathers) conditioning. Results proved the validity and robustness of quantitative seismic reservoir characterization framework employed to litho-facies (tight limestone and shale) and predict petrophysical properties (volume of clay and porosity), and helped us to effectively position and plan of high-technology horizontal wells as a part of redevelopment program of the field. Litho-facies (tight limestone, gas bearing limestone and shale) are defined at well location based on core sample and area geological (depositional and sedimentological) information using well-log-based estimates of petrophysical properties (such as gamma ray, volume of clay and water saturation). Multi-linear Eqs. (1 to 3) are as follows: Reformat & Geometry Building
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