Summary

Induced seismicity in the Groningen gas field in the Netherlands has been related to reservoir compaction caused by gas pressure depletion. In situ measurement of compaction is therefore relevant for seismic hazard assessment. In this study, we investigated the potential of passively recorded deep borehole noise data to detect temporal variations in the Groningen reservoir. Train signals recorded by an array of 10 geophones at reservoir depth were selected from the continuous noise data for two 5-month deployments in 2015. Interferometry by deconvolution was applied to the high-frequency train signals that acted as stable, repetitive noise sources. Direct intergeophone P and S wave traveltimes were then used to construct the P- and S-wave velocity structure along the geophone array. The resulting models agree with independently obtained velocity profiles and have very small errors. Most intergeophone P wave traveltimes showed decreasing traveltimes per deployment period, suggestive of compaction. However, the retrieved traveltime changes are very small, up to tens of microseconds per deployment period, with uncertainties that are of similar size, about 10 microseconds. An unambiguous interpretation in terms of compaction is therefore not warranted, although the 10 μs error per 5-month period is probably smaller than can be achieved from active time-lapse seismic surveys that are commonly used to measure reservoir compaction. The direct P-wave amplitudes of the train-signal deconvolutions were investigated for additional imprints of compaction. Whereas the P-wave amplitudes consistently increased during the second deployment, suggestive of compaction, no such trend was observed for the first deployment, rendering the interpretation of compaction inconclusive. Our results therefore present hints, but no obvious effects of compaction in the Groningen reservoir. Yet, this study demonstrates that the approach of deconvolution interferometry applied to deep borehole data allows monitoring of small temporal changes in the subsurface for stable repetitive noise sources such as trains.

中文翻译：

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用火车噪声研究格罗宁根气藏的压实

概要

荷兰格罗宁根（Groningen）气田引起的地震活动与气压耗尽引起的储层压实有关。因此，压实的现场测量与地震危险性评估有关。在这项研究中，我们调查了被动记录的深井噪声数据检测格罗宁根油藏时间变化的潜力。在2015年的两次连续5个月部署中，从连续噪声数据中选择了由10个地震检波器在储层深度处记录的火车信号。通过反卷积干涉法将高频火车信号用作稳定的重复性噪声源。然后使用直接的地音机P和S波传播时间来构造P-和地震检波器阵列的S波速度结构。所得模型与独立获得的速度分布图一致，并且误差很小。大多数地音测听仪的P波传播时间显示出每个部署周期的传播时间减少，这表明压实。但是，检索到的旅行时间变化非常小，每个部署周期最多几十微秒，不确定性大小相似，约为10微秒。因此，尽管在5个月内10μs的误差可能小于通常用于测量油藏压实度的主动延时地震勘测所能实现的误差，但也不保证对压实度有明确的解释。直接P-研究了火车信号反褶积的波幅，以寻找压实的其他印记。尽管P波振幅在第二次展开过程中持续增加，提示压实，但在第一次展开中未观察到这种趋势，因此对压实的解释尚无定论。因此，我们的结果显示了提示，但格罗宁根水库中的压实没有明显影响。然而，这项研究表明，将反卷积干涉术应用于深井孔数据的方法，可以监视地下的微小时间变化，以获取稳定的重复性噪声源，例如火车。