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- Title
Multivariate Statistical Appraisal of Regional Susceptibility to Induced Seismicity: Application to the Permian Basin, SW United States.
- Authors
Hicks, Stephen P.; Goes, Saskia; Whittaker, Alexander C.; Stafford, Peter J.
- Abstract
Induced earthquake sequences are typically interpreted through causal triggering mechanisms. However, studies of causality rarely consider large regions and why some regions experiencing similar anthropogenic activities remain largely aseismic. Therefore, it can be difficult to forecast seismic hazard at a regional scale. In contrast, multivariate statistical methods allow us to find the combinations of factors that correlate best with seismicity, which can help form the basis of hypotheses that can be subsequently tested with physical models. While strong correlations do not necessarily equate to causality, such a statistical approach is particularly important for large regions with newly emergent seismicity comprising multiple distinct clusters and multifaceted industrial operations. Recent induced seismicity in the Permian Basin provides an excellent test‐bed for multivariate statistical analyses because the main causal industrial and geological factors driving earthquakes in the region remain highly debated. Here, we use logistic regression to retrospectively predict the spatial variation of seismicity across the western Permian Basin. We reproduce the broad distribution of seismicity using a combination of both industrial and geological factors. Our model shows that the proximity to neotectonic faults west of the Delaware Basin is the most important factor that contributes to induced seismicity. The second‐most important factor is salt‐water disposal at shallow depths, with hydraulic fracturing playing a less dominant role. The higher tectonic stressing, together with a poor correlation between seismicity and large‐volume deep salt‐water disposal wells, indicates a very different mechanism of induced seismicity compared to that in Oklahoma. Plain Language Summary: Industrial operations that involve either extraction or injection of fluids deep in the ground can perturb the stress along natural weaknesses in the ground known as geological faults. This change of stress may cause earthquakes, some of which may be strong enough to be felt at the surface. The Permian Basin in West Texas has seen a recent uptick in earthquake rates, and it remains highly debated as to whether the earthquakes are mainly caused by injection of waste fluids, hydraulic fracturing for hydrocarbons, or the long‐term conventional extraction of oil and gas. The vast quantity of industrial wells in the area makes it difficult to separate these factors. Without knowing these driving factors, it is difficult to forecast the hazard posed by these induced earthquakes. In this study, we use a statistical technique, which often forms the basis of machine learning algorithms, to hindcast the spatial distribution of earthquake occurrence in 2017–2020 in the Permian Basin. This analysis tells us that wastewater disposal into shallow geological layers plays a major role in causing the regional seismicity. We also find that recently active geological faults in the region indicate a higher background tectonic stressing, which also help to drive the intense induced seismicity in the region. Key Points: We use multivariate logistic regression to determine the factors that appear to correlate with induced seismicity in the Permian BasinA combination of industrial and geological features can explain the first‐order spatial distribution of seismicityProximity to neotectonic faults and shallow wastewater disposal are the main factors that correlate with the seismicity distribution
- Subjects
PERMIAN Basin (Tex. &; N.M.); INDUCED seismicity; ANTHROPOGENIC effects on nature; HYDRAULIC fracturing; MACHINE learning; PLATE tectonics
- Publication
Journal of Geophysical Research. Solid Earth, 2021, Vol 126, Issue 12, p1
- ISSN
2169-9313
- Publication type
Article
- DOI
10.1029/2021JB022768