Search USGS⌕ Search
Home/Archive/USGS

USGS · 70042484

Source characterization of near-surface chemical explosions at SAFOD

Fred F. Pollitz·Justin Rubinstein·William Ellsworth
View original source ↗Export metadata ↓

Abstract

A series of near‐surface chemical explosions conducted at the San Andreas Fault Observatory at Depth (SAFOD) main hole were recorded by high‐frequency downhole receiver arrays in April 2005. These seismic recordings at depths ranging from the surface to 2.3 km constrain the shallow velocity and attenuation structure as well as the first‐order characteristics of the source. Forward modeling of the explosions indicates that a source consisting of combined explosion, delayed implosion, and second‐order moment‐tensor components (corresponding to a distribution of vertical shear dislocations in the rock directly above the explosion) is sufficient to characterize the generated seismic wave fields to first order. Grid searches over source parameters controlling the nonexplosive components allow for the quantification of distributed vertical shear above the source and the estimation of the moment and time delay of the implosive component relative to the explosion. An estimated implosive to explosive moment ratio of 0.34 to 0.43 indicates a net static moment and positive macroscopic volume change.

Explore related subjects

Bulletin of the Seismological Society of AmericaArticle
90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 32.5° to 42° latitude; -124.4° to -114° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Fred F. Pollitz, Justin Rubinstein, William Ellsworth. 2012-08-08. Source characterization of near-surface chemical explosions at SAFOD. https://doi.org/10.1785/0120110201

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2026

ETAS-positive: Extracting unbiased epidemic-type aftershock models from incomplete earthquake catalogs

Earthquake catalogs are inherently incomplete, and short-term fluctuations in catalog completeness can strongly bias estimates of seismicity parameters. Here, we extend the positive statistics framework recently introduced for estimating Gutenberg–Richter a and b values to the Epidemic-Type Aftershock Sequence (ETAS) model. The approach focuses on complete magnitude–time intervals defined by pairs of earthquakes in which the second event is larger than the first. Comprehensive synthetic tests demonstrate that the proposed ETAS + method retrieves nearly unbiased parameter estimates even from highly incomplete catalogs, whereas parameters obtained using classical estimation approaches are strongly biased. Application to Southern California reveals a similar trend, with the productivity scaling parameter α approaching the b value, consistent with self-similar earthquake triggering within estimation uncertainties. Owing to its robustness against catalog incompleteness and computational efficiency, the ETAS + method provides a powerful new tool for seismicity analysis and earthquake forecasting.

California↗
USGS2026

Efficient physics‐informed ground‐motion simulations with reduced‐order models: CyberShake implications and high‐resolution site terms for southern San Andreas fault earthquakes

Recent advances in Probabilistic Seismic Hazard Analysis (PSHA) leverage physics‐based ground‐motion simulations to estimate seismic hazard, such as the CyberShake project. However, computational costs quickly escalate when performing PSHA for numerous faults or sites and can become prohibitively expensive. To reduce computational demands, CyberShake uses reciprocity and interpolates physics‐informed corrections from simulations conducted at fewer locations, but the accuracy of these interpolations remains poorly quantified. To quantify the interpolation accuracy, we derive high‐resolution, frequency‐dependent site terms for southern California and compare them with interpolated site terms using the CyberShake approach. We accomplish this by performing a set of earthquake point‐source simulations distributed along the nonplanar fault geometry for the southern San Andreas fault (SSAF) extending from Bombay Beach to Lake Hughes. Using SeisSol, we simulate three minutes of viscoelastic seismic wave propagation for these sources and store the horizontal‐component Green’s functions for 480,000 sites. We then use a scientific machine learning approach based on interpolated proper orthogonal decomposition to construct an accurate reduced‐order model of the Green’s functions to efficiently predict effective amplitude spectra (EAS) for finite‐source rupture models of SSAF earthquakes. Using minimum curvature interpolation with tension, as used in CyberShake, we compare the interpolated site terms against our high‐resolution site terms. We identify local discrepancies with EAS differing by up to a factor of approximately three. Furthermore, we identify locations where unexpectedly high or low ground motions are missed when using the interpolated dataset for these earthquakes. We estimate that our approach may be used within CyberShake to reduce the time‐to‐solution by a factor of 336 for the entire earthquake rupture forecast. Our analysis of physics‐based site terms provides more insight into the seismic hazard due to SSAF ruptures and guides future developments by combining high‐performance computing and reduced‐order modeling techniques for PSHA.

California↗