通过 FWI 对北海埃尔德菲斯克气田的气体云进行结构和延时成像

Zhengxue Li, Leila Bencherif-Soerensen, Per Gunnar Folstad, Brian Macy, Simon Shaw, Baishali Roy
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摘要

摘要 在本研究中,我们探讨了在北海埃尔德菲斯克油田地震遮挡区(SOAs)内进行构造和延时成像所面临的长期挑战。尽管开展了大量地震项目,但结构 A 和结构 B 的地震遮挡区内的成像工作仍然受阻,主要原因是覆盖层中存在膨胀、复杂的气云。为解决这一问题,我们将全波形反演(FWI)应用于三维和四维海底节点(OBN)数据,旨在增强这些区域的构造和延时成像。从传统的速度模型开始,FWI 被用作建立模型的主要工具,捕捉与气体云相关的详细速度变化。然后将改进后的模型输入到基于 Q(质量因子)补偿的反向时间迁移(Q-RTM)伪采集成像流中,以生成明显改善的 SOA 结构图像。此外,我们应用 4D FWI 成功地发现了与 SOAs 内注入和生产历史相一致的延时速度变化,而传统的基于地震的 4D 方法需要良好的图像才能观测到这些变化。
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Structural and time-lapse imaging through gas clouds via FWI at Eldfisk field, North Sea
SUMMARY In this study, we address the persistent challenges of structural and time-lapse imaging within the Seismically Obscured Areas (SOAs) at Eldfisk field, North Sea. Despite numerous seismic programs, imaging efforts within SOAs at structures A and B continue to be hindered, primarily due to the presence of expansive, complex gas clouds in the overburden. To address this, we apply Full-Waveform Inversion (FWI) to 3D and 4D Ocean Bottom Node (OBN) data, aiming to enhance both structural and time-lapse imaging in these areas. Starting with a legacy velocity model, FWI is used as the main tool for model building, capturing detailed velocity changes associated with gas clouds. The refined model is then input into a Q (the quality factor)-compensated Reverse-Time Migration (Q-RTM) pseudo-gather-based imaging flow to generate significantly improved structural images in the SOAs. Additionally, our application of 4D FWI successfully uncovers time-lapse velocity changes that align with the injection and production history within the SOAs, which were not observed by traditional seismic-based 4D methods that require a good image.
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