ABSTRACT In the fields of oil and gas exploration, various quantitative seismic interpretation techniques have been developed to identify lithology and pore fluids based on the rock physics. However, discrimination between oil and brine in pores is often difficult because the seismic response of oil and brine are similar. Poisson impedance (PI) is an effective indicator for distinguishing oil from brine in pores. Target correlation coefficient analysis (TCCA) is widely used to calculate the “c” factor of PI. However, PI analysis using the TCCA method can lead to misinterpretation when the resistivity log is affected by lithology and porosity, as well as the pore fluid type. To overcome this problem, we developed a more effective PI workflow composed of three steps that focus on lithology impedance, porosity impedance, and fluid impedance. In each step, we exclude the unnecessary area for hydrocarbon exploration such as shale, tight, and brine-saturated areas. We applied our method to marine field data that contained shale and tight intervals and demonstrated that the proposed approach can be used to identify potential oil reservoirs more effectively from seismic data.

中文翻译：

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使用泊松阻抗分析的有效工作流程估算孔隙流体

摘要 在油气勘探领域，已经开发了各种定量地震解释技术来识别基于岩石物理的岩性和孔隙流体。然而，由于油和卤水的地震响应相似，因此区分孔隙中的油和卤水往往很困难。泊松阻抗（PI）是区分孔隙中油和盐水的有效指标。目标相关系数分析 (TCCA) 被广泛用于计算 PI 的“c”因子。然而，当电阻率测井受到岩性和孔隙度以及孔隙流体类型的影响时，使用 TCCA 方法进行 PI 分析会导致误解。为了克服这个问题，我们开发了一个更有效的 PI 工作流程，由三个步骤组成，重点是岩性阻抗、孔隙度阻抗和流体阻抗。在每一步中，我们都排除了不必要的油气勘探区域，如页岩、致密和盐水饱和区。我们将我们的方法应用于包含页岩和致密层段的海洋现场数据，并证明所提出的方法可用于更有效地从地震数据中识别潜在的油藏。