Increased rates of seismicity in tectonically quiescent regions like the midcontinent region of the United States have been hypothesized to be related to human activities such as oil and gas production and wastewater injection. It can be difficult to establish how human activities relate to earthquakes, particularly when local seismic networks are not available to provide a high-quality characterization of the seismic sequence in question. Here, we use a multistation waveform crosscorrelation approach to evaluate the relationships between earthquakes associated with the 2011–2012 Youngstown, Ohio, seismic sequence and the injection history of a local wastewater disposal well. By using data recorded by four regional seismic stations 50–200 km (31–124 mi) away from Youngstown, we demonstrate that high-resolution results can be achieved without using costly and scientifically focused local seismic deployments. Compared to the number of events recorded using standard detection methodologies, we realize a 25-fold increase in detected seismicity (282 detected events) during the sequence, and allow us with confidence to interpret a direct link between seismicity and well injection volumes. Using a combination of absolute and relative location techniques, we demonstrate that seismicity migrated from below the injection well toward the west, along a line consistent with a nodal plane of the largest earthquake in the sequence. We are able to separate the seismic sequence into three distinct phases, consistent with changes in injection rates and maximum injection pressures. In addition, using daily injection volume records, we can identify two families of similar earthquakes. The first family occurred early in the sequence and close to the injection well and was followed by a recurrence pattern that lagged injection activity by 1 day. The second family. which occurred later in the sequence and farther from the well, displayed a 4-day lag. We interpret these relationships to be related to pore-pressure diffusion rates within the fault network responsible for the seismicity. Collectively, our technique shows the high quality of results possible when only a few regional seismic stations are available for monitoring.

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