Concept: Earthquake engineering
Just a bit of water enables one to turn a pile of dry sand into a spectacular sandcastle. Too much water however will destabilize the material, as is seen in landslides. Here we investigated the stability of wet sand columns to account for the maximum height of sandcastles. We find that the columns become unstable to elastic buckling under their own weight. This allows to account for the maximum height of the sand column; it is found to increase as the 2/3 power of the base radius of the column. Measuring the elastic modulus of the wet sand, we find that the optimum strength is achieved at a very low liquid volume fraction of about 1%. Knowing the modulus we can quantitatively account for the measured sandcastle heights.
To assess whether recent seismicity is induced by human activity or is of natural origin, we analyze fault displacements on high-resolution seismic reflection profiles for two regions in the central United States (CUS): the Fort Worth Basin (FWB) of Texas and the northern Mississippi embayment (NME). Since 2009, earthquake activity in the CUS has increased markedly, and numerous publications suggest that this increase is primarily due to induced earthquakes caused by deep-well injection of wastewater, both flowback water from hydrofracturing operations and produced water accompanying hydrocarbon production. Alternatively, some argue that these earthquakes are natural and that the seismicity increase is a normal variation that occurs over millions of years. Our analysis shows that within the NME, faults deform both Quaternary alluvium and underlying sediments dating from Paleozoic through Tertiary, with displacement increasing with geologic unit age, documenting a long history of natural activity. In the FWB, a region of ongoing wastewater injection, basement faults show deformation of the Proterozoic and Paleozoic units, but little or no deformation of younger strata. Specifically, vertical displacements in the post-Pennsylvanian formations, if any, are below the resolution (~15 m) of the seismic data, far less than expected had these faults accumulated deformation over millions of years. Our results support the assertion that recent FWB earthquakes are of induced origin; this conclusion is entirely independent of analyses correlating seismicity and wastewater injection practices. To our knowledge, this is the first study to discriminate natural and induced seismicity using classical structural geology analysis techniques.
Earthquakes in unusual locations have become an important topic of discussion in both North America and Europe, owing to the concern that industrial activity could cause damaging earthquakes. It has long been understood that earthquakes can be induced by impoundment of reservoirs, surface and underground mining, withdrawal of fluids and gas from the subsurface, and injection of fluids into underground formations. Injection-induced earthquakes have, in particular, become a focus of discussion as the application of hydraulic fracturing to tight shale formations is enabling the production of oil and gas from previously unproductive formations. Earthquakes can be induced as part of the process to stimulate the production from tight shale formations, or by disposal of wastewater associated with stimulation and production. Here, I review recent seismic activity that may be associated with industrial activity, with a focus on the disposal of wastewater by injection in deep wells; assess the scientific understanding of induced earthquakes; and discuss the key scientific challenges to be met for assessing this hazard.
Seismology is experiencing rapid growth in the quantity of data, which has outpaced the development of processing algorithms. Earthquake detection-identification of seismic events in continuous data-is a fundamental operation for observational seismology. We developed an efficient method to detect earthquakes using waveform similarity that overcomes the disadvantages of existing detection methods. Our method, called Fingerprint And Similarity Thresholding (FAST), can analyze a week of continuous seismic waveform data in less than 2 hours, or 140 times faster than autocorrelation. FAST adapts a data mining algorithm, originally designed to identify similar audio clips within large databases; it first creates compact “fingerprints” of waveforms by extracting key discriminative features, then groups similar fingerprints together within a database to facilitate fast, scalable search for similar fingerprint pairs, and finally generates a list of earthquake detections. FAST detected most (21 of 24) cataloged earthquakes and 68 uncataloged earthquakes in 1 week of continuous data from a station located near the Calaveras Fault in central California, achieving detection performance comparable to that of autocorrelation, with some additional false detections. FAST is expected to realize its full potential when applied to extremely long duration data sets over a distributed network of seismic stations. The widespread application of FAST has the potential to aid in the discovery of unexpected seismic signals, improve seismic monitoring, and promote a greater understanding of a variety of earthquake processes.
Granular dynamics govern earthquakes, avalanches, and landslides and are of fundamental importance in a variety of industries ranging from energy to pharmaceuticals to agriculture. Nonetheless, our understanding of the underlying physics is poor because we lack spatially and temporally resolved experimental measurements of internal grain motion. We introduce a magnetic resonance imaging methodology that provides internal granular velocity measurements that are four orders of magnitude faster compared to previous work. The technique is based on a concerted interplay of scan acceleration and materials engineering. Real-time probing of granular dynamics is explored in single- and two-phase systems, providing fresh insight into bubble dynamics and the propagation of shock waves upon impact of an intruder. We anticipate that the methodology outlined here will enable advances in understanding the propagation of seismic activity, the jamming transition, or the rheology and dynamics of dense suspensions.
Earthquakes normally occur as frictional stick-slip instabilities resulting in catastrophic failure and seismic rupture. Tectonic faults also fail in slow earthquakes with rupture durations of months or more, yet their origin is poorly understood. Here, we present laboratory observations of repetitive, slow stick-slip in serpentinite fault zones and mechanical evidence for their origin. We document a transition from unstable to stable frictional behavior with increasing slip velocity, providing a mechanism to limit the speed of slow earthquakes. We also document reduction of P-wave speed within the active shear zone prior to stick-slip events. If similar mechanisms operate in nature, our results suggest that higher-resolution studies of elastic properties in tectonic fault zones may aid in the search for reliable earthquake precursors.
The subduction zone in Northern Chile is a well identified seismic gap that last ruptured in 1877. The Mw 8.1 Iquique earthquake of 1 April 2014 broke a highly coupled portion of this gap. To understand the seismicity preceding this event, we studied the location and mechanisms of the foreshocks and computed GPS time series at stations located on-shore. Seismicity off-shore Iquique started to increase in January 2014. After 16 March several Mw > 6 events occurred near the low coupled zone. These events migrated northward for about 50 km until the 1 April earthquake occurred. On 16 March on-shore cGPS stations detected a westward motion that we model as a slow slip event situated in the same area where the mainshock occurred.
Natural hazards have a potentially large impact on economic growth, but measuring their economic impact is subject to a great deal of uncertainty. The central objective of this paper is to demonstrate a model-the natural disasters vulnerability evaluation (NDVE) model-that can be used to evaluate the impact of natural hazards on gross national product growth. The model is based on five basic indicators-natural hazards growth rates (αi ), the national natural hazards vulnerability rate (ΩT ), the natural disaster devastation magnitude rate (Π), the economic desgrowth rate (i.e. shrinkage of the economy) (δ), and the NHV surface. In addition, we apply the NDVE model to the north-east Japan earthquake and tsunami of March 2011 to evaluate its impact on the Japanese economy.
A recent dramatic increase in seismicity in the midwestern United States may be related to increases in deep wastewater injection. Here, we demonstrate that areas with suspected anthropogenic earthquakes are also more susceptible to earthquake-triggering from natural transient stresses generated by the seismic waves of large remote earthquakes. Enhanced triggering susceptibility suggests the presence of critically loaded faults and potentially high fluid pressures. Sensitivity to remote triggering is most clearly seen in sites with a long delay between the start of injection and the onset of seismicity and in regions that went on to host moderate magnitude earthquakes within 6 to 20 months. Triggering in induced seismic zones could therefore be an indicator that fluid injection has brought the fault system to a critical state.
Earthquake forecasting is the ultimate challenge for seismologists, because it condenses the scientific knowledge about the earthquake occurrence process, and it is an essential component of any sound risk mitigation planning. It is commonly assumed that, in the short term, trustworthy earthquake forecasts are possible only for typical aftershock sequences, where the largest shock is followed by many smaller earthquakes that decay with time according to the Omori power law. We show that the current Italian operational earthquake forecasting system issued statistically reliable and skillful space-time-magnitude forecasts of the largest earthquakes during the complex 2016-2017 Amatrice-Norcia sequence, which is characterized by several bursts of seismicity and a significant deviation from the Omori law. This capability to deliver statistically reliable forecasts is an essential component of any program to assist public decision-makers and citizens in the challenging risk management of complex seismic sequences.