Machine Learning Reveals Additional Hydraulic Fracture‐Induced Seismicity in the Eagle Ford Shale

Abstract

AbstractA recent study found ∼90% of earthquakes in the Eagle Ford shale in Texas from 2014 to 2018 were spatiotemporally related to hydraulic fracturing (HF) wells. Since then, earthquakes have remained prevalent, including a new region of seismicity in Live Oak county. We sought to perform a deeper exploration of how HF has contributed to recent seismicity using template matching and repeating signal detection (RSD), which employs machine learning to search for repeating earthquakes with the potential to find something different than the template catalog. RSD identified new bursts of seismicity with a shorter S‐P time (∼2 s) than the previous catalog (>4 s), which temporally correlated with HF near station N4 735B. The short S‐P events have smaller magnitudes (ML < 2.0), consistent with the idea that HF‐induced seismicity in the Eagle Ford is likely more pervasive than previously reported, but detection is limited by the density of stations. RSD and template matching identified 1,600 earthquakes correlated with HF from 2019 to February 2020. We confirmed newly detected HF‐induced seismicity in Live Oak county did not occur until January 2019. Despite similar cumulative volume prior to and after 2019, the onset of detectable seismicity did not occur until HF injection exceeded 2 million barrels per month over this area, supporting the notion that injection flux is a stronger influence on the seismicity occurrence than cumulative volume. When considering the full catalog, the likelihood of seismicity also correlated with proximity to mapped faults, with 13% of wells <2 km from faults having seismicity compared to only 3% of wells >2 km.