Post seismic response of repeating aftershocks

The recurrence intervals of repeating earthquakes on the San Andreas Fault in the Loma Prieta aftershock zone follow the characteristic 1/t decay of Omori's law. A model in which these earthquakes occur on isolated patches of the fault that fail in stick-slip with creep around them can explain this observation. In this model the recurrence interval is inversely proportional to the loading rate due to creep. Logarithmic velocity strengthening friction predicts 1/t decay in creep rate following the mainshock. The time dependence of recurrence is inconsistent with a simple viscous constitutive relationship, which predicts an exponential decay of loading rate. Thus, our observations imply postseismic slip at seismogenic depth under a power law rheology. The time dependence of postseismic deformation measured geodetically may be diagnostic of whether postseismic deformation is caused by creep or possible viscoelastic deformation at greater depths

Sea Level Changes Affect Seismicity Rates in a Hydrothermal System Near Istanbul

Small stress changes such as those from sea level fluctuations can be large enough to trigger earthquakes. If small and large earthquakes initiate similarly, high-resolution catalogs with low detection thresholds are best suited to illuminate such processes. Below the Sea of Marmara section of the North Anatolian Fault, a segment of urn:x-wiley:00948276:media:grl65397:grl65397-math-0001150 km is late in its seismic cycle. We generated high-resolution seismicity catalogs for a hydrothermal region in the eastern Sea of Marmara employing AI-based and template matching techniques to investigate the link between sea level fluctuations and seismicity over 6 months. All high resolution catalogs show that local seismicity rates are larger during time periods shortly after local minima of sea level, when it is already rising. Local strainmeters indicate that seismicity is promoted when the ratio of differential to areal strain is the largest. The strain changes from sea level variations, on the order of 30–300 nstrain, are sufficient to promote seismicity

Months-long seismicity transients preceding the 2023 MW 7.8 Kahramanmaraş earthquake, Türkiye

Short term prediction of earthquake magnitude, time, and location is currently not possible. In some cases, however, documented observations have been retrospectively considered as precursory. Here we present seismicity transients starting approx. 8 months before the 2023 MW 7.8 Kahramanmaraş earthquake on the East Anatolian Fault Zone. Seismicity is composed of isolated spatio-temporal clusters within 65 km of future epicentre, displaying non-Poissonian inter-event time statistics, magnitude correlations and low Gutenberg-Richter b-values. Local comparable seismic transients have not been observed, at least since 2014. Close to epicentre and during the weeks prior to its rupture, only scarce seismic activity was observed. The trends of seismic preparatory attributes for this earthquake follow those previously documented in both laboratory stick-slip tests and numerical models of heterogeneous earthquake rupture affecting multiple fault segments. More comprehensive earthquake monitoring together with long-term seismic records may facilitate recognizing earthquake preparation processes from other regional deformation transients

High-resolution image of Calaveras Fault seismicity

By measuring relative earthquake arrival times using waveform cross correlation and locating earthquakes using the double difference technique, we are able to reduce hypocentral errors by 1 to 2 orders of magnitude over routine locations for nearly 8000 events along a 35-km section of the Calaveras Fault. This represents ∼92% of all seismicity since 1984 and includes the rupture zone of the M 6.2 1984 Morgan Hill, California, earthquake. The relocated seismicity forms highly organized structures that were previously obscured by location errors. There are abundant repeating earthquake sequences as well as linear clusters of earthquakes. Large voids in seismicity appear with dimensions of kilometers that have been aseismic over the 30-year time interval, suggesting that these portions of the fault are either locked or creeping. The area of greatest slip in the Morgan Hill main shock coincides with the most prominent of these voids, suggesting that this part of the fault may be locked between large earthquakes. We find that the Calaveras Fault at depth is extremely thin, with an average upper bound on fault zone width of 75 m. Given the location error, however, this width is not resolvably different from zero. The relocations reveal active secondary faults, which we use to solve for the stress field in the immediate vicinity of the Calaveras Fault. We find that the maximum compressive stress is at a high angle, only 13° from the fault normal, supporting previous interpretations that this fault is weak

Laboratory earthquake forecasting. A machine learning competition

Earthquake prediction, the long-sought holy grail of earthquake science, continues to confound Earth scientists. Could we make advances by crowdsourcing, drawing from the vast knowledge and creativity of the machine learning (ML) community? We used Google’s ML competition platform, Kaggle, to engage the worldwide ML community with a competition to develop and improve data analysis approaches on a forecasting problem that uses laboratory earthquake data. The competitors were tasked with predicting the time remaining before the next earthquake of successive laboratory quake events, based on only a small portion of the laboratory seismic data. The more than 4,500 participating teams created and shared more than 400 computer programs in openly accessible notebooks. Complementing the now well-known features of seismic data that map to fault criticality in the laboratory, the winning teams employed unexpected strategies based on rescaling failure times as a fraction of the seismic cycle and comparing input distribution of training and testing data. In addition to yielding scientific insights into fault processes in the laboratory and their relation with the evolution of the statistical properties of the associated seismic data, the competition serves as a pedagogical tool for teaching ML in geophysics. The approach may provide a model for other competitions in geosciences or other domains of study to help engage the ML community on problems of significance

Spatial correlation of aftershock locations and on-fault main shock properties

[1] We quantify the correlation between spatial patterns of aftershock hypocenter locations and the distribution of coseismic slip and stress drop on a main shock fault plane using two nonstandard statistical tests. Test T1 evaluates if aftershock hypocenters are located in low‐slip regions (hypothesis H1), test T2 evaluates if aftershock hypocenters occur in regions of increased shear stress (hypothesis H2). In the tests, we seek to reject the null hypotheses H0: Aftershock hypocenters are not correlated with (1) low‐slip regions or (2) regions of increased shear stress, respectively. We tested the hypotheses on four strike‐slip events for which multiple earthquake catalogs and multiple finite fault source models of varying accuracy exist. Because we want to retain earthquake clustering as the fundamental feature of aftershock seismicity, we generate slip distributions using a random spatial field model and derive the stress drop distributions instead of generating seismicity catalogs. We account for uncertainties in the aftershock locations by simulating them within their location error bounds. Our findings imply that aftershocks are preferentially located in regions of low‐slip (u ≤ equation imageu max) and of increased shear stress (Δσ < 0). In particular, the correlation is more significant for relocated than for general network aftershock catalogs. However, the results show that stress drop patterns provide less information content on aftershock locations. This implies that static shear stress change of the main shock may not be the governing process for aftershock genesis.ISSN:2169-9313ISSN:0148-0227ISSN:2169-935

Aseismic slip and seismogenic coupling along the central San Andreas Fault

International audienceWe use high-resolution Synthetic Aperture Radar- and GPS-derived observations of surfacedisplacements to derive the first probabilistic estimates of fault coupling along the creeping section of theSan Andreas Fault, in between the terminations of the 1857 and 1906 magnitude 7.9 earthquakes. Usinga fully Bayesian approach enables unequaled resolution and allows us to infer a high probability ofsignificant fault locking along the creeping section. The inferred discreet locked asperities are consistentwith evidence for magnitude 6+ earthquakes over the past century in this area and may be associated withthe initiation phase of the 1857 earthquake. As creeping segments may be related to the initiation andtermination of seismic ruptures, such distribution of locked and creeping asperities highlights the centralrole of the creeping section on the occurrence of major earthquakes along the San Andreas Fault