Abstract
Abstract The integrated study of seismic attributes and inversion analysis can provide a better understanding for predicting the hydrocarbon-bearing zones even in extreme heterogeneous reservoirs. This study aims to delineate and characterize the gas saturated zone within the reservoir (Cretaceous C-sand) interval of Sawan gas field, Middle Indus Basin, Pakistan. The hydrocarbon bearing zone is well identified through the seismic attribute analysis along a sand channel. The sparse-spike inversion analysis has efficiently captured the variations in reservoir parameter (P-impedance) for gas prospect. Inversion results indicated that the relatively lower P-impedance values are encountered along the predicted sand channel. To further characterize the reservoir, geostatistical techniques comprising multiattribute regression and probabilistic neural network (PNN) analysis are applied to predict the effective porosity of reservoir. Comparatively, the PNN analysis predicted the targeted property more efficiently and applied its estimations on entire seismic volume. Furthermore, the geostatistical estimations of PNN analysis significantly predicted the gas-bearing zones and confirmed the sand channel as a major contributor of gas accumulation in the area. These estimates are in appropriate agreement with each other, and the workflow adopted here can be applied to various South Asian regions and in other parts of the world for improved characterization of gas reservoirs.
Highlights
The integrated study of seismic attributes and inversion analysis can provide a better understanding for predicting the hydrocarbon-bearing zones even in extreme heterogeneous reservoirs
To further characterize the reservoir, porosity is estimated in the inter-well region using multiattribute regression and the probabilistic neural network (PNN) analysis within the C-sand interval
The high amplitude anomalies of seismic attributes predicted the sand channel at the targeted reservoir depth level trending in SW to NE direction
Summary
Abstract: The integrated study of seismic attributes and inversion analysis can provide a better understanding for predicting the hydrocarbon-bearing zones even in extreme heterogeneous reservoirs. The hydrocarbon bearing zone is well identified through the seismic attribute analysis along a sand channel. The geostatistical estimations of PNN analysis significantly predicted the gas-bearing zones and confirmed the sand channel as a major contributor of gas accumulation in the area. These estimates are in appropriate agreement with each other, and the workflow adopted here can be applied to various South Asian regions and in other parts of the world for improved characterization of gas reservoirs
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