Abstract
Utilizing the rock-physics theories, Idemitsu has developed customized techniques for prediction of lithology and fluid from insightfully controlled seismic-data analysis (SDA). The various techniques applied have converged, emphasizing quantitative interpretation of seismic data in AVO and elastic-impedance crossplots, calibrating with nearby well-log data. A modeling match by perturbing reservoir and fluid properties, “scenario analysis”, provides rock physics theory to differentiate sandstone and carbonate reservoirs from a shaly background. Furthermore, successful analysis predicts potential accumulations of hydrocarbons.
Such techniques become less reliable for deeply buried, low-porosity reservoirs due to subtle variations in physical properties. A deeply buried reservoir of the case study have avoided excessive compaction during subsidence in a highpressure/high-temperature regime, which retain sufficient SDA information to enable discrimination of pore fluids.
Immediately after gas discoveries in Well X, Idemitsu applied in-house rock-physics techniques to 2D seismic lines across Well X to investigate the character of the gas-bearing reservoirs in angle-stacks seismic. Subsequently, Idemitsu devised a specific AVO method to highlight sandstone and carbonates reservoirs in the seismic data, consistent with the well-log data, along with rock-physics theories. We call them “sandstone stack” and “carbonate stack”. These sections revealed additional potential reservoirs invisible in full-stack sections, continuing below the bottom of Well X. Upon subsequent acquisition of 3D seismic, application of similar techniques enabled not only the detailed structural interpretation, but also mapping of all the potential reservoirs.
This paper demonstrates the different character in lithology stacks as an AVO implementation, likewise, an extraction method for potential reservoirs in a Rock-Physics Template (RPT) using elastic-impedance inversion. First, we discuss basic premises of AVO analysis and in RPT interpretation, based on various rock-physics theories. Thereafter, the case study with actual dataset demonstrates the extraction method of the physical properties of the target reservoirs and fluid saturation.
