Seismic-Q imaging for petroleum reservoir characterization

用于石油储层表征的地震 Q 成像

• 批准号: 216825-2013
• 负责人: Lines, Laurence
• 金额: $ 1.97万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=523601
• 关键词: Seismic; imaging; petroleum; reservoir; characterization

The Canadian production of heavy oil involves the competing considerations of huge economic impact, world energy demands, and minimization of environmental impact. Enhanced petroleum reservoir characterization should benefit all of these objectives by utilizing geological, geophysical and reservoir production data. Enhanced oil recovery (EOR) involves a unique set of challenges that include the descriptions of the reservoir lithology and the heavy oil viscosity. In this research program, the applicant will use seismic data to characterize the geology and the fluid viscosity between boreholes. The 3-D reverse-time depth migration (RTM) of seismic data obtained prior to EOR will provide a high-resolution image of the reservoir geology. The seismic delineation of sand versus shale will greatly improve the placement of wells and the scheduling of EOR processes such as steam injection. The dynamic estimation of reservoir fluid viscosity between boreholes will optimize the EOR processes themselves. One of the project's main goals is to estimate interwell viscosity by the analysis of seismic-Q (inverse attenuation). This can be achieved by computing Q tomograms from transmitted seismic arrivals. Rock physics models and lab measurements can then convert Q tomograms to viscosity tomograms. While determining seismic-Q is challenging, it is believed that its estimation in a time-lapse sense should provide valuable information about changing oil viscosity in the reservoir in both time and space. Good estimates of Q can also improve the seismic images through use of RTM with Q included in the wave equation. Both the resolution of geological features with conventional seismic analysis and the seismic estimation of reservoir fluid viscosity should greatly aid in improving the reservoir characterization of heavy oil fields. To the best of our knowledge, there has never previously been such a complete and innovative use of geophysical data to enhance the dynamic modeling of oil reservoirs. Given the scientific expertise, availability of state-of-the-art software and access to industry data, there are few university programs anywhere that can offer the HQP training in geophysical reservoir characterization as outlined in this proposal.

加拿大的重油生产涉及巨大的经济影响、世界能源需求和环境影响最小化等相互竞争的考虑。 通过利用地质、地球物理和油藏生产数据，增强石油油藏表征应该有利于所有这些目标。 提高石油采收率 (EOR) 涉及一系列独特的挑战，其中包括油藏岩性和重油粘度的描述。 在该研究计划中，申请人将使用地震数据来表征地质和钻孔之间的流体粘度。 在 EOR 之前获得的地震数据的 3D 逆时深度偏移 (RTM) 将提供储层地质的高分辨率图像。砂岩与页岩的地震圈定将极大地改善井的布置以及注蒸汽等 EOR 过程的调度。 井眼间储层流体粘度的动态估计将优化 EOR 过程本身。 该项目的主要目标之一是通过地震 Q（逆衰减）分析来估计井间粘度。 这可以通过根据传输的地震波计算 Q 断层图来实现。 然后，岩石物理模型和实验室测量可以将 Q 断层图转换为粘度断层图。 虽然确定地震 Q 值具有挑战性，但人们相信，其在时移意义上的估计应该提供有关油藏中石油粘度在时间和空间上变化的有价值的信息。 对 Q 的良好估计还可以通过使用 RTM 将 Q 包含在波动方程中来改善地震图像。 常规地震分析的地质特征解析和储层流体粘度的地震估计都将极大地有助于改善稠油油田的储层表征。 据我们所知，以前从未如此完整和创新地利用地球物理数据来增强油藏的动态建模。 鉴于科学专业知识、最先进软件的可用性以及对行业数据的访问，几乎没有任何大学项目可以提供本提案中概述的地球物理储层表征方面的 HQP 培训。