Abstract

The depth of the reservoir causes an increase in the degree of uncertainty in the prediction of reservoir quality. High frequency is suppressed with depth because Earth functions as a low-pass filter. The seismic amplitudes observed at various interfaces are influenced by spherical divergence, transmission losses, mode conversions, and inter-bed multiples. Seismic data have numerous essential components that must be thoroughly examined during hydrocarbon prospect identification and maturation, including post-critical reflections, events coherency (in near and far offsets), mode conversion, and interbed multiples. Seismic amplitudes are typically derived from 2D/3D seismic data and utilized directly or indirectly for reservoir interpretation and better prediction of subtle geological and geophysical information. To accurately depict subsurface geological features, stratigraphic architecture, and reservoir facies, it should be used in conjunction with the existing paleoenvironment data. When employed alone, the subsurface geophysical data may lead to erroneous interpretation of subsurface lithologies and inaccurate reservoir property predictions. Understanding these factors could help interpreters make better use of seismic data while maturing and de-risking the prospectivity. This study examines the post-drill geophysical characterization of two exploratory wells that were drilled in the deep-water area of the Cauvery Basin, East Coast of India. Analysis and correlation with a discovery well is done to understand the sediment depositional heterogeneity and corresponding seismic amplitude response, primarily for the cemented reservoir (dry well). To discover prospects and subsequently de-risk the existing prospect inventory, a dashboard checklist for in-depth study of seismic and well data has been developed. The top-down geophysical analytical approach that has been presented will aid in defining reservoir characteristics generally, estimating deliverability, and subsequently raising the geological probabilities and chance of success (COS) of any exploration project. The findings of this study allow critical analysis of seismic data to distinguish between softer/slower/possibly better reservoir rocks and hard/fast/tight rocks.

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