Characterizing Seismicity in the Raton Basin from 2016-2019

Session: Mechanisms of Induced Seismicity: Pressure Diffusion, Elastic Stressing and Aseismic Slip [Poster]
Type: Poster
Date: 4/29/2020
Time: 08:00 AM
Room: Ballroom
Description: 

Seismicity in the basement rock beneath the Raton Basin has risen sharply in concert with increased production and wastewater injection since 2000. However, because the region is historically seismically active and has a complex tectonic history, the rise in seismicity likely results from combined interactions of natural tectonic and hydrothermal systems with anthropogenic wastewater injection. Seismicity from 2016–2019 is investigated using eight broadband stations spaced ~30 km apart. Prior long-term seismic studies with >70 km station spacing found three dominant earthquake clusters extending in length ~10–25 km and trending N-S with magnitudes ranging 5.3≥M>2. We find >7000 earthquakes with M<4.0 located dominantly within two of the three regions of previously noted seismicity. After relative relocation with hierarchical clustering, we find more distinct linear features that suggest the two largest ~N-S trending clusters of seismicity are composed of multiple shorter faults, some of which exhibit strikes that are rotated with respect to the ~N-S orientation of the composite cluster. Minimal seismicity (<0.2%) is observed in the third cluster which produced the largest recent earthquake (M 5.3 in 2011). Additionally, the largest volume of wastewater injection has shifted from the mid-basin, which hosted the largest recent earthquake, to the northern section of the basin, where we observe increasing seismic activity. Similar to previous results, the majority of earthquakes remain within basement rock with depths 2–6 km below sea level. Full moment tensor inversions for M>2.5 earthquakes reflect mostly NE-SW to NW-SE striking, normal faulting in the Raton Basin which is consistent with regional E-W extension and stress orientation. Overall, the magnitude-frequency distribution during our study period is high (b>1.5) potentially indicative of non-tectonic behavior. Current efforts focus on using a convolutional neural network to help complete the catalog for M<1 earthquakes leading to more robust statistical analysis of seismicity through time and space. 

Presenting Author: Margaret E. Glasgow

Authors