Interferometric body-wave retrieval from ambient noise after polarization filtering: application to shallow reflectivity imaging
Interferometric body-wave retrieval from ambient noise after polarization filtering: application to shallow reflectivity imaging
复制标题
偏振滤波后从环境噪声中检索干涉体波：在浅反射率成像中的应用
作者：
Deepankar Dangwal;M. Behm
从地面站记录的环境噪声中干涉恢复体波通常会受到表面波能量主导的挑战，特别是在以人类活动为主的环境中（例如自然资源开采、交通、基础设施建设）。因此，对于稀疏且不规则分布的接收器网络来说，沉积层等浅层结构的环境噪声成像仍然是一项艰巨的任务。我们演示了如何使用偏振滤波从连续三分量记录中自动提取陡峭倾斜的 P 波，从而改善被动体波成像。作为一种单站方法，该技术不依赖于密集的接收器阵列，因此非常适合在水库水力增产、CO_2 封存和废水处理注入等任务的监测过程中收集的数据。我们将该方法应用于在惠灵顿油田（美国堪萨斯州）获取的连续数据集，其中局部和区域地震活动以及其他形式的环境噪声提供了 15 个短周期接收器记录的丰富的表面波和体波能量源。我们使用自相关推导接收器阵列下方的浅层（<1公里）反射率结构，并使用测井和主动地震数据验证我们的工作流程和结果。光线追踪分析和波形建模表明，对于真实的环境噪声体波源分布，需要考虑转换后的剪切波，因为它们可以投影到垂直分量上，并可能导致对 P 波反射率结构的误解。总的来说，我们的研究表明偏振滤波显着改善了自相关和站间互相关的无源体波成像。它减少了时变噪声源分布的影响，因此对于延时环境噪声干涉测量也可能有用。
Interferometric retrieval of body waves from ambient noise recorded at surface stations is usually challenged by the dominance of surface-wave energy, in particular in settings dominated by anthropogenic activities (e.g., natural resource exploitation, traffic, infrastructure construction). As a consequence, ambient noise imaging of shallow structures such as sedimentary layers remains a difficult task for sparse and irregularly distributed receiver networks. We demonstrate how polarization filtering can be used to automatically extract steeply inclined P-waves from continuous three-component recordings and in turn improves passive body-wave imaging. Being a single-station approach, the technique does not rely on a dense receiver array and is therefore well suited for data collected during surveillance monitoring for tasks such as reservoir hydraulic stimulation, CO_2 sequestration, and wastewater disposal injection. We apply the method on a continuous dataset acquired in the Wellington oilfield (Kansas, US), where local and regional seismicity, and other forms of ambient noise provide an abundant source of both surface- and body-wave energy recorded at 15 short-period receivers. We use autocorrelation to derive the shallow (lt; 1 km) reflectivity structure below the receiver array and validate our workflow and results with well logs and active seismic data. Raytracing analysis and waveform modeling indicates that converted shear waves need to be taken into account for realistic ambient noise body-wave source distributions, as they can be projected on the vertical component and might lead to misinterpretation of the P-wave reflectivity structure. Overall, our study suggests that polarization filtering significantly improves passive body-wave imaging on both autocorrelation and interstation crosscorrelation. It reduces the impact of time-varying noise source distributions and is therefore also potentially useful for time-lapse ambient noise interferometry.