[en] This paper concerns the problem of predicting the maximum expected earthquake magnitude $\mathrm{\mu <!--\; ??\; -->}$ in a future time interval $T_{\text{f}}$ given a catalog covering a time period $T$ in the past. Different studies show the divergence of the confidence interval of the maximum possible earthquake magnitude $m_{\text{max}}$ for high levels of confidence (Salamat et al. 2017). Therefore, $m_{\text{max}}$ should be better replaced by $\mathrm{\mu <!--\; ??\; -->}$ (Holschneider et al. 2011). In a previous study (Salamat et al. 2018), $\mathrm{\mu <!--\; ??\; -->}$ is estimated for an instrumental earthquake catalog of Iran from 1900 onwards with a constant level of completeness $\left(m_0=5.5\right)$. In the current study, the Bayesian methodology developed by Zöller et al. (2014, 2015) is applied for the purpose of predicting $\mathrm{\mu <!--\; ??\; -->}$ based on the catalog consisting of both historical and instrumental parts. The catalog is first subdivided into six subcatalogs corresponding to six seismotectonic zones, and each of those zone catalogs is subsequently subdivided according to changes in completeness level and magnitude uncertainty. For this, broad and small error distributions are considered for historical and instrumental earthquakes, respectively. We assume that earthquakes follow a Poisson process in time and Gutenberg–Richter law in the magnitude domain with a priori unknown $a$ and b values which are first estimated by Bayes’ theorem and subsequently used to estimate $\mathrm{\mu <!--\; ??\; -->}$. Imposing different values of $m_{\text{max}}$ for different seismotectonic zones namely Alborz, Azerbaijan, Central Iran, Zagros, Kopet Dagh and Makran, the results show considerable probabilities for the occurrence of earthquakes with $M_w\ge <!--\; ???\; -->7.5$ in short $T_{\text{f}}$ , whereas for long $T_{\text{f}}$, $\mathrm{\mu <!--\; ??\; -->}$ is almost equal to $m_{\text{max}}$.

[en] Groningen is the largest onshore gas field under production in Europe. The pressure depletion of the gas field started in 1963. In 1991, the first induced micro-earthquakes have been located at reservoir level with increasing rates in the following decades. Most of these events are of magnitude less than 2.0 and cannot be felt. However, maximum observed magnitudes continuously increased over the years until the largest, significant event with $M_L=3.6$ was recorded in 2014, which finally led to the decision to reduce the production. This causal sequence displays the crucial role of understanding and modeling the relation between production and induced seismicity for economic planing and hazard assessment. Here we test whether the induced seismicity related to gas exploration can be modeled by the statistical response of fault networks with rate-and-state-dependent frictional behavior. We use the long and complete local seismic catalog and additionally detailed information on production-induced changes at the reservoir level to test different seismicity models. Both the changes of the fluid pressure and of the reservoir compaction are tested as input to approximate the Coulomb stress changes. We find that the rate-and-state model with a constant tectonic background seismicity rate can reproduce the observed long delay of the seismicity onset. In contrast, so-called Coulomb failure models with instantaneous earthquake nucleation need to assume that all faults are initially far from a critical state of stress to explain the delay. Our rate-and-state model based on the fluid pore pressure fits the spatiotemporal pattern of the seismicity best, where the fit further improves by taking the fault density and orientation into account. Despite its simplicity with only three free parameters, the rate-and-state model can reproduce the main statistical features of the observed activity.

[en] One of the crucial components in seismic hazard analysis is the estimation of the maximum earthquake magnitude and associated uncertainty. In the present study, the uncertainty related to the maximum expected magnitude μ is determined in terms of confidence intervals for an imposed level of confidence. Previous work by Salamat et al. (Pure Appl Geophys 174:763-777, 2017) shows the divergence of the confidence interval of the maximum possible magnitude m_max for high levels of confidence in six seismotectonic zones of Iran. In this work, the maximum expected earthquake magnitude μ is calculated in a predefined finite time interval and imposed level of confidence. For this, we use a conceptual model based on a doubly truncated Gutenberg-Richter law for magnitudes with constant b-value and calculate the posterior distribution of μ for the time interval T_f in future. We assume a stationary Poisson process in time and a Gutenberg-Richter relation for magnitudes. The upper bound of the magnitude confidence interval is calculated for different time intervals of 30, 50, and 100 years and imposed levels of confidence α = 0.5, 0.1, 0.05, and 0.01. The posterior distribution of waiting times T_f to the next earthquake with a given magnitude equal to 6.5, 7.0, and 7.5 are calculated in each zone. In order to find the influence of declustering, we use the original and declustered version of the catalog. The earthquake catalog of the territory of Iran and surroundings are subdivided into six seismotectonic zones Alborz, Azerbaijan, Central Iran, Zagros, Kopet Dagh, and Makran. We assume the maximum possible magnitude m_max = 8.5 and calculate the upper bound of the confidence interval of μ in each zone. The results indicate that for short time intervals equal to 30 and 50 years and imposed levels of confidence 1 − α = 0.95 and 0.90, the probability distribution of μ is around μ = 7.16 − 8.23 in all seismic zones.