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首页> 外文期刊>Seismological research letters >Seismology with Dark Data: Image-Based Processing of Analog Records Using Machine Learning for the Rangely Earthquake Control Experiment
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Seismology with Dark Data: Image-Based Processing of Analog Records Using Machine Learning for the Rangely Earthquake Control Experiment

机译:具有暗数据的地震学:基于图像的模拟记录处理使用机器学习的震荡地震控制实验

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Before the digital era, seismograms were recorded in analog form and read manually by analysts. The digital era represents only about 25% of the total time span of instrumental seismology. Analog data provide important constraints on earthquake processes over the long term, and in some cases are the only data available. The media on which analog data are recorded degrades with time and there is an urgent need for cost-effective approaches to preserve the information they contain. In this study, we work directly with images by constructing a set of image-based methods for earthquake processing, rather than pursue the usual approach of converting analog data to vector time series. We demonstrate this approach on one month of continuous Develocorder films from the Rangely earthquake control experiment run by the U.S. Geological Survey (USGS). We scan the films into images and compress these into low-dimensional feature vectors as input to a classifier that separates earthquakes from noise in a defined feature space. We feed the detected event images into a short-term average/long-term average (STA/ LTA) picker, a grid-search associator, and a 2D image correlator to measure both absolute arrival times and relative arrival-time differences between events. We use these measurements to locate the earthquakes using hypoDD. In the month that we studied, we identified 40 events clustered near the injection wells. In the original study, Raleigh et al. (1976) identified only 32 events during the same period. Scanning without vectorizing analog seismograms represents an attractive approach to archiving these perishable data. We demonstrated that it is possible to carry out precision seismology directly on such images. Our approach has the potential for wide application to analog seismograms.
机译:在数字时代之前,地震图以模拟形式记录并通过分析师手动读取。数字时代仅占仪器地震学总时间跨度的约25%。模拟数据在长期内为地震过程提供了重要的约束,在某些情况下,唯一可用的数据。模拟数据的媒体随时间记录的时间,并且迫切需要经济有效的方法来保护它们所包含的信息。在这项研究中,我们通过构建用于地震处理的一组基于图像的方法来直接使用图像,而不是追求将模拟数据转换为向量时间序列的通常方法。我们在由美国地质调查(USGS)经营的朗奇地震控制实验中的一个月连续开发电影中展示了这种方法。我们将胶片扫描到图像中并将其压缩成低维特征向量,作为输入到分类器的输入,该分类器将地震分离在定义的特征空间中的噪声。我们将检测到的事件图像馈送到短期平均值/长期平均值(STA / LTA)拾取器,网格搜索associator和2D图像相关器,以测量绝对到达时间和事件之间的相对到达时间差异。我们使用这些测量来定位使用Hypodd的地震。在我们研究的月份,我们确定了40个赛事聚集在注射孔附近。在原始研究中,Raleigh等人。 (1976)在同一时期内只确定了32个事件。扫描而不向量化模拟地震图代表了归档这些易腐数据的有吸引力的方法。我们证明,可以直接在这些图像上进行精密地震学。我们的方法具有广泛应用于模拟地震图。

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