Imaging the Deep Crustal Structure of Central Oklahoma Using Stacking and Inversion of Local Earthquake Waveforms

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.

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Imaging the Deep Crustal Structure of Central Oklahoma Using Stacking and Inversion of Local Earthquake Waveforms

Cited by 2 publications

References 95 publications

New insights on Moho depth and regional lithospheric structure of central Oklahoma based on receiver function analysis from dense seismic networks

New insights on Moho depth and regional lithospheric structure of central Oklahoma based on receiver function analysis from dense seismic networks

Interferometric body-wave retrieval from ambient noise after polarization filtering: Application to shallow reflectivity imaging

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