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Knowledge of pressure-dependent static and dynamic moduli of porous reservoir rocks is of key importance for evaluating geological setting of a reservoir in geo-energy applications. We examined experimentally the evolution of static and dynamic bulk moduli for porous Bentheim sandstone with increasing confining pressure up to about 190 MPa under dry and water-saturated conditions. The static bulk moduli (Ks) were estimated from stress–volumetric strain curves while dynamic bulk moduli (Kd) were derived from the changes in ultrasonic P- and S- wave velocities (~ 1 MHz) along different traces, which were monitored simultaneously during the entire deformation. In conjunction with published data of other porous sandstones (Berea, Navajo and Weber sandstones), our results reveal that the ratio between dynamic and static bulk moduli (Kd/Ks) reduces rapidly from about 1.5 − 2.0 at ambient pressure to about 1.1 at high pressure under dry conditions and from about 2.0 − 4.0 to about 1.5 under water-saturated conditions, respectively. We interpret such a pressure-dependent reduction by closure of narrow (compliant) cracks, highlighting that Kd/Ks is positively correlated with the amount of narrow cracks. Above the crack closure pressure, where equant (stiff) pores dominate the void space, Kd/Ks is almost constant. The enhanced difference between dynamic and static bulk moduli under water saturation compared to dry conditions is possibly caused by high pore pressure that is locally maintained if measured using high-frequency ultrasonic wave velocities. In our experiments, the pressure dependence of dynamic bulk modulus of water-saturated Bentheim sandstone at effective pressures above 5 MPa can be roughly predicted by both the effective medium theory (Mori–Tanaka scheme) and the squirt-flow model. Static bulk moduli are found to be more sensitive to narrow cracks than dynamic bulk moduli for porous sandstones under dry and water-saturated conditions.

The East Anatolian Fault Zone (EAFZ) represents a plate boundary extending over ∼500 km between the Arabian and Anatolian plates. Relative plate motion occurs with slip rates ranging from 6 to 10 mm/yr and has resulted in destructive earthquakes in eastern Turkey as documented by historical records. In this study, we investigate the seismic activity along the EAFZ and fault kinematics based on recordings from a densified regional seismic network providing the best possible azimuthal coverage for the target region. We optimize a reference 1‐D velocity model using a grid‐search approach and re‐locate hypocenters using the Double‐Difference earthquake relocation technique. The refined hypocenter catalog provides insights into the kinematics and internal deformation of the fault zone down to a resolution ranging typically between 100 and 200 m. The distribution of hypocenters suggests that the EAFZ is characterized by NE‐SW and E‐W oriented sub‐segments that are sub‐parallel to the overall trend of the fault zone. Faulting mechanisms are predominantly left‐lateral strike‐slip and thus in good correlation with the deformation pattern derived from regional GPS data. However, we also observe local clusters of thrust and normal faulting events, respectively. While normal faulting events typically occur on NS‐trending subsidiary faults, thrust faulting is restricted to EW‐trending structures. This observation is in good accordance with kinematic models proposed for evolving shear zones. The observed spatiotemporal evolution of hypocenters indicates a systematic migration of micro‐ and moderate‐sized earthquakes from the main fault into adjacent fault segments within several days documenting progressive interaction between the major branch of the EAFZ and its secondary structures. Analyzing the pre versus post‐seismic phase for M > 5 events we find that aftershock activities are initially spread to the entire source region for several months but start to cluster at the central part of the main shock rupture thereafter. Key Points The seismicity and fault kinematics of the East Anatolian Fault Zone (EAFZ) Segmentation of the fault zone based on precise locations Characterization of spatiotemporal evolution of the seismicity along the EAFZ

Rocks exhibit astonishing time-dependent mechanical properties, like memory of experienced stress or slow dynamics , a transient recovery of stiffness after a softening induced by almost any type of loading. This softening and transient recovery is observed in the subsurface and in buildings after earthquakes, or in laboratory samples. Here, we investigate the anisotropy of nonlinear elastic effects in a sandstone sample under uniaxial loading. We report that slow dynamics is observed independently of propagation direction, while the acoustoelastic effect shows the expected anisotropy originating from the opening and closing of cracks. From this, we argue that slow dynamics is caused by the sliding of oblique grain-to-grain contacts and the resulting changes in frictional properties, as empirically described by rate-and-state friction and observed in laboratory experiments across block contacts. We establish a connection between the nonclassical nonlinearity of heterogeneous materials and the framework of rate-and-state friction, providing an explanation for the elusive origin of slow dynamics, and adding a different perspective for monitoring very early stages of material failure when deformation is still distributed in the bulk and begins to coalesce towards a fracture. The anisotropy of acoustic velocity changes is investigated and modelled during damage and recovery sequences in sandstone. The results highlight the role of sliding and aging of oblique grain-to-grain contacts in temporal changes of elastic properties, a phenomenon known as slow dynamics.

Analysis of earthquake rupture directivity provides key information for seismic hazard and risk assessment, particularly for faults near urban areas. We analyze directivity patterns for 31 well‐constrained ML≥${M}_{L}\\mathit{\\ge }$  3.5 earthquakes along the Main Marmara Fault, in direct proximity to Istanbul. We calculate source mechanisms with a waveform modeling approach and analyze earthquake directivity from apparent source‐time functions using empirical Green's functions. Most of the strike‐slip earthquakes to the west of the Princes Islands segment display a predominantly asymmetric rupture toward the east with the median directivity trending 85°, consistent with the Main Marmara Fault strike. Consequently, earthquake ground shaking may be more pronounced toward Istanbul. This holds potentially for a large earthquake on the Main Marmara Fault which is late in its seismic cycle. Our results motivate the importance of evaluating the impact of eastward asymmetric ruptures on the probabilistic seismic hazard and risk assessment around Istanbul. Plain Language Summary Analyzing how earthquakes release the accumulated strain energy in space can help us understand the resulting shaking in particular locations. We studied 31 earthquakes with magnitudes ML≥${M}_{L}\\mathit{\\ge }$  3.5 that occurred along the North Anatolian Fault in the Marmara region near Istanbul, northwestern Türkiye. We derived orientations of fault planes using focal‐mechanism inversion, as well as the direction in which the seismic energy release is focused (rupture directivity). We find that most of the analyzed earthquakes display strike‐slip movement, matching the orientation of the GPS‐derived deformation field in this area, which is different from previous studies proposing dominantly normal faulting kinematics, particularly on the western part of the Main Marmara Fault. We also find that earthquakes to the west of the Princes Islands south of Istanbul radiate seismic energy mostly toward the east. This also suggests that the ground shaking from the earthquakes could be stronger toward Istanbul and weaker in the opposite direction. Our findings show that it is important to consider how earthquake ruptures propagate when evaluating the earthquake risk, especially near urban areas. Key Points Directivities of 31 ML${M}_{L}$3.5–5.7 earthquakes along the Marmara seismic gap were estimated from apparent source‐time function variations 72% of strongly asymmetric earthquakes show directivity toward the east, implying higher ground motions toward the Istanbul region The rupture directivities are consistent with right‐lateral east–west trending source mechanisms at the Main Marmara Fault

We investigate the influence of fault roughness on physical damage prior to large laboratory rock failure and the evolution of the local stress field surrounding the fault zone as macroscopic shear slip approaches. To achieve this, we analyze acoustic emission (AE) data from displacement‐driven rock friction experiments conducted on porous sandstone samples containing either a saw‐cut (smooth) or a rough fault. Using high‐quality AE‐derived focal mechanisms and two stress tensor inversion approaches–one considering double‐couple (DC) components and the other one incorporating non‐DC components, we examine the temporal evolution of the local stress tensor for both smooth and rough faults. Our results show no significant differences between the two stress inversion methods, indicating that non‐DC components have no significant influence on the resulting stress tensors in our experiments. As macroscopic shear slip approaches, the principal stress axes surrounding the fault zone gradually rotate, regardless of the initial fault roughness. The observed evolution of stress tensors correlates with the evolving partitioning between volumetric and shear deformation, as derived from moment tensor inversion of AEs. Compared to the smooth fault, the rough fault exhibits higher local stress heterogeneity and more erratic fluctuations in AE source‐related parameters as loading progresses. Plain Language Summary We study how the surface roughness of a fault affects the physical damage that occurs before large laboratory earthquakes and how the stress field around the fault zone evolves. To do this, we perform laboratory rock friction experiments on porous sandstone samples containing either a smooth or a rough fault, and then analyze sub‐millimeter‐scale earthquakes, that is, Acoustic Emissions (AEs), generated during the loading process. The analysis of AEs conveys information on the kinematics of micro‐rupture processes occurring around the fault zone and the local stress field surrounding it. As the applied macroscopic stress increases, the direction of the local stress field rotates over time, irrespective of the fault roughness. Compared to the smooth fault, the rough fault displays a more heterogeneous stress field. This study may be helpful in better understanding how earthquakes and fault slip perturb the surrounding stress field around the fault zone. Key Points We study local stress evolution during initial loading toward fault steady‐state slip using samples cut by faults with varying roughness The stress regime within the fault zone transitions from dominant compaction to shear during the loading process regardless of the fault roughness Fault roughness causes inhomogeneity in local stress orientation and physical damage, and prolonged volumetric deformation within the fault zone

Predicting large earthquakes remains a significant challenge due to the complexity of fault systems and the variability of preparatory processes. We introduce an unsupervised machine learning framework to categorize seismicity patterns and identify, when present, seismicity transients preceding large earthquakes. We focus on five large earthquakes and extract seismo-mechanical features per families of events, defined as clustered events in space, time and magnitude. Here we show that for those cases displaying a preparatory phase, specific long-lasting families belonging to a critical category signalling an upcoming earthquake occur during the preparatory phase. Compared to other periods, critical categories reflect a higher spatial-temporal localization, earthquake interaction and strain release. The method will not detect such a transient for earthquakes with no detectable seismic preparatory phase. Finally, we demonstrate that the method is capable of identifying preparatory phases (when present), showing potential for operational earthquake forecasting. An unsupervised machine learning approach identifies patterns in earthquake activity preceding some large events, revealing critical clustering and interactions in space and time, with potential for improved earthquake forecasting.

Recent advances in artificial intelligence have enhanced the detection and identification of transient low-amplitude signals across the entire frequency spectrum, shedding light on deformation processes preceding natural hazards. This study investigates low-frequency, low-amplitude signals preceding the 2023 M 7.8 Kahramanmaraş earthquake in Türkiye. Using a deep neural network, we extract key features from the spectrograms of continuous seismic signals and employ unsupervised clustering to reveal distinct transient patterns. We identify an increased occurrence of low-frequency tremor-like signals during the six months preceding the mainshock. However, the location of these signals suggests that their origin is not tectonic, but rather related to anthropogenic activities at cement plants along the Narlı Fault, where the M 7.8 mainshock nucleated. Such findings highlight the importance of understanding the origin of patterns detected by machine-learning methods and the large variety of seismic signals due to anthropogenic activities. Furthermore, the search for the origin of the tremor-like signals motivated an investigation into the local seismicity around the Narlı Fault. The resulting extended seismicity catalog suggests that seismicity in this area arises from a combination of tectonic and anthropogenic processes.

Given its intense seismic activity and damaging earthquake generation potential, the western part of the North Anatolian Fault constitutes a serious natural hazard. As a result, the fault is monitored with a broad range of seismological and geodetic instrumentation making it a natural laboratory environment for scientific studies. One of the long-term projects in this region is GONAF (Geophysical Borehole Observatory at the North Anatolian Fault) which is the first borehole seismometer network project in Turkey. GONAF is a joint research project that started in 2011 as joint initiative of the Turkish Ministry of Interior, Disaster and Emergency Management Presidency AFAD and GFZ and the German Research Center for Geoscience Helmholtz Center Potsdam. The aim of GONAF is to detect, examine, and monitor the microseismic activity in the region and to observe the physical processes before, during and after a large Marmara earthquake (M > 7.0) that is expected to rupture the western part of the North Anatolian Fault, below the Marmara Sea along the Princes Islands segment or even further to the west. For this purpose, the permanent GONAF observatory was established consisting of 7 borehole seismometer arrays installed down to a depth of 300 m. In this paper, we report on regional stress changes in the western part of the North Anatolian Fault Zone (NAFZ) using instrumental data and the Coulomb stress method. We also present preliminary results of the observation and evaluation of microseismic activity obtained from the GONAF observatory. For the automatic evaluation of real-time data, Seiscomp3, RTQUAKE, and Earthworm Softwares were used. Within the scope of automatic earthquake detection studies, between March, 2016 and November, 2017, a total of 2568 earthquakes were detected using the RTQUAKE software. Of these, 1459 could be analyzed. While the magnitude of the analyzed earthquakes varies between 0.8 and 4.2, the depth of these events ranges from 2 to 30 km.

A passive seismic monitoring campaign was carried out in the frame of a CO2-Enhanced Oil Recovery (EOR) pilot project in Alberta, Canada. Our analysis focuses on a two-week period during which prominent downhole pressure fluctuations in the reservoir were accompanied by a leakage of CO2 and CH4 along the monitoring well equipped with an array of short-period borehole geophones. We applied state of the art seismological processing schemes to the continuous seismic waveform recordings. During the analyzed time period we did not find evidence of induced micro-seismicity associated with CO2 injection. Instead, we identified signals related to the leakage of CO2 and CH4, in that seven out of the eight geophones show a clearly elevated noise level framing the onset time of leakage along the monitoring well. Our results confirm that micro-seismic monitoring of reservoir treatment can contribute towards improved reservoir monitoring and leakage detection.

The Marmara section of the North Anatolian Fault Zone (NAFZ) runs under water and is located less than 20 km from the 15-million-person population center of Istanbul in its eastern portion. Based on historical seismicity data, recurrence times forecast an impending magnitude M>7 earthquake for this region. The permanent GONAF (Geophysical Observatory at the North Anatolian Fault) has been installed around this section to help capture the seismic and strain activity preceding, during, and after such an anticipated event.