Machine Learning Ready Induced Seismicity Data

<p>This dataset contains previously published data on induced seismicity that has been processed to be machine learning ready.<br> <br> The data contains time series of the cumulative number of seismic events in certain areas and the corresponding pressures induced from injecting fluids into the ground. The natural task is to forecast future seismicity given past seismicity and pressures. These datasets aim to require as little seismology experience as necessary to prepare the data for forecasting algorithms.&nbsp;<br> <br> Data is provided for different locations. For Decatur Illinois, the seismic data was taken from&nbsp;Williams-Stroud et al., 2018 and the pressure data originated from&nbsp;Luu et al., 2022. Data aggregated over the whole region lies in the temporal_datasets/decatur_illinois/ folder. The region was further subdivided into subregions and the corresponding data stored separately (e.g. in loc1).&nbsp;&nbsp;</p> <p>The&nbsp;Kansas data originated from Cochran et al., 2018 and is further divided into subregions.&nbsp;</p> <p>The Cushing, Oklahoma is adapted from&nbsp;Skoumal et al., 2020.&nbsp;</p> <p>Each seismic file contains the following columns:&nbsp;epoch latitude longitude depth easting northing magnitude. The epoch corresponds to the number of seconds since a certain date (e.g.&nbsp;November 17, 2011 for Decatur).&nbsp;Each seismic event corresponds to one row in the file.&nbsp;<br> <br> Each pressure file contains&nbsp; the following columns: epoch pressure dpdt. dpdt is the derivative of pressure.&nbsp;</p>