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Lithology and fluid prediction by quantitative seismic data analysis - theory and a case study

机译：定量地震数据分析的岩性与流体预测-理论与案例研究。

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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 high-pressure/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.
机译：利用岩石物理学理论，出光开发了定制化技术，用于通过深入控制的地震数据分析（SDA）预测岩性和流体。所应用的各种技术已经融合，强调了对AVO和弹性阻抗交叉图中地震数据的定量解释，并使用附近的测井数据进行了校准。通过扰动储层和流体属性进行建模匹配的“方案分析”，提供了岩石物理学理论，以区分页岩背景的砂岩和碳酸盐岩储层。此外，成功的分析预测了碳氢化合物的潜在积累。由于物理性质的细微变化，这种技术对于深埋的低孔隙度储层的可靠性降低。案例研究的一个深埋储层避免了在高压/高温条件下沉降过程中的过度压实，该压实保留了足够的SDA信息以区分孔隙流体。在X井发现天然气之后，出光立即将内部岩石物理学技术应用于X井的二维地震线，以研究角堆地震中含气储层的特征。随后，出光设计了一种特殊的AVO方法，以在地震数据中与测井数据以及岩石物理学理论相一致地突出显示砂岩和碳酸盐岩储层。我们称它们为“砂岩堆栈”和“碳酸盐堆栈”。这些部分揭示了在全层剖面中看不见的额外潜在储层，一直延伸到X井底部。在随后的3D地震采集中，类似技术的应用不仅实现了详细的构造解释，而且还绘制了所有潜在储层的图。本文演示了作为AVO实现的岩性堆栈中的不同特征，同样，它是利用弹性阻抗反演提取岩石物理模板（RPT）中潜在储层的方法。首先，我们基于各种岩石物理学理论，讨论AVO分析和RPT解释的基本前提。此后，以实际数据集进行的案例研究证明了目标储层物理性质和流体饱和度的提取方法。

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