Seismic Characteristics Research Articles

Deformation Behavior and Seismic Characteristics of Sandy Facies Opalinus Clay During Triaxial Deformation Under Dry and Wet Conditions

Unconsolidated, undrained triaxial deformation tests were performed on sandy facies Opalinus Clay at 50 MPa confining pressure to characterize the effect of water and microfabric orientation on the deformation behavior, mechanical properties, and P-wave velocity evolution. Dry and wet (≈ 8 and > 95% initial water saturation, respectively) samples with 12.6 ± 0.4 vol% porosity were deformed parallel and perpendicular to the bedding direction at a constant strain rate of 5 × 10–6 s−1. Dry samples revealed semi-brittle behavior and exhibited strain localization at failure, while deformation was more ductile at saturated conditions, promoting stable, slow faulting. Peak strength, Young’s modulus, and number of cumulative acoustic emissions decreased significantly for wet samples compared to dry samples; the opposite was observed for Poisson’s ratio. P-wave velocity anisotropy was significantly altered by differential stress, primarily due to the interplay between pore and fracture closure and stress-induced microcrack formation. For samples that were deformed perpendicular to bedding, we observed a reduction and reversal of P-wave velocity anisotropy with increasing differential stress, whereas anisotropy of parallel samples increased. The results suggest that water saturation reduces the pressure at the brittle-ductile transition and that the elastic properties and anisotropy of sandy facies Opalinus Clay can be significantly altered in an anisotropic stress field, e.g., adjacent to fault zones or tunnel excavations. Changes in elastic anisotropy are primarily controlled by the orientation between the pre-existing microfabric and the maximum principal stress direction, stress magnitude, and the degree of water saturation.

Nonlinear seismic response of seabed with terrain variation and seawater-seabed coupling

Understanding the seismic characteristics of submarine sites and conducting seismic response analysis for such locations are crucial for the safety of marine engineering. However, due to a shortage of strong motion records, the ground motion of offshore earthquakes has not yet been fully characterized. The actual seabed conditions are highly intricate, necessitating consideration of factors such as the dynamic coupling effect between seawater and seabed, the strong nonlinearity of seafloor soft sediments, and the diverse nature of natural submarine terrain. In this study, the modified Davidenkov dynamic constitutive model is used to simulate the nonlinear behavior of the soil. The Coupled Acoustic-Structure method is utilized to simulate the interaction between seawater and seabed. Three typical and simplified terrains, namely flat terrain, valley terrain, and hilly terrain, are individually modeled. The measured seafloor ground motions with different frequency components are used as bidirectional seismic excitations input from the bedrock. The amplification factor in terms of CAV is introduced to evaluate the amplification of seismic ground motion characteristics at seabed surface with respect to those at the bedrock surface. The acceleration response spectra in both horizontal and vertical directions, as well as the corresponding vertical-to-horizontal response spectral ratios, at the representative points are obtained, respectively. Several key findings are consistent with the features of the observed offshore and onshore earthquake ground motions. Numerical examples are presented to illustrate the different influence rules of terrain condition, overlying water depth, and seismic intensity on the nonlinear seismic response characteristics.

Characterization of seismicity from different glacial bed types: machine learning classification of laboratory stick-slip acoustic emissions

Abstract Subglacial seismicity presents the opportunity to monitor inaccessible glacial beds at the epicentral location and time. Glaciers can be underlain by rock or till, a first order control on bed mechanics. Velocity-weakening, necessary for unstable slip, has been shown for each bed type, but is much stronger and evolves over more than an order of magnitude longer distances for till beds. Utilizing a de-stiffened double direct shear apparatus, we found conditions for instability at freezing temperatures and high slip rates for both bed types. During stick–slip stress-drops, we recorded acoustic emissions with piezoelectric transducers frozen into the ice. The two populations of event waveforms appear visually similar and overlap in their statistical features. We implemented a suite of supervised machine learning algorithms to classify the bed type of recorded waveforms and spectra, with prediction accuracy between 65–80%. The Random Forest Classifier is interpretable, showing the importance of initial oscillation peaks and higher frequency energy. Till beds have generally higher friction and resulting stress-drops, with more impulsive first arrivals and more high frequency content compared to rock emissions, but rock beds can produce many till-like events. Seismic signatures could enhance interpretation of bed conditions and mechanics from subglacial seismicity.

A High‐Resolution Seismic Catalog for the Southern Apennines (Italy) Built Through Template‐Matching

AbstractThe incompleteness of earthquake catalogs is a well‐known issue caused by our technical limitation in detecting the small‐to very small‐magnitude seismicity falling near or below the background seismic noise. The detection of small‐magnitude events is fundamental for improving our knowledge of geometry and kinematics of seismogenic sources and the spatio‐temporal characteristics of seismicity, thus leading to better models for seismic hazard. Template‐matching (TM) is a powerful technique that, based on similarity measure (cross‐correlation) of seismic waveforms, allows to detect hidden earthquakes that are similar to known events (called templates). The high computational effort often limits such technique to small areas and for short time frames (less than 1 year). In this work, we present the first application of template‐matching at regional scale for the Italian Peninsula, focusing on the Southern Apennines. We use about 3,600 high‐quality events as templates, scanning 6‐year long continuous recordings (2009–2014), at more than 180 stations of the INGV network. About 20,000 new events are found, showing a comparable quality to the template catalog in terms of hypocentral solution, reaching a decrease of the magnitude of completeness of about one unit. To highlight the improved quality of the TM catalog, we report two main examples regarding the Sannio‐Matese area, where TM allowed us to unravel relevant details on the spatio‐temporal distribution of the local seismicity.

Gas Insulated Metal Enclosed Transmission Line (GIL) Seismic Response Analysis

The seismic response analysis of a 550 kV gas-insulated metal-enclosed transmission line (GIL) is carried out to address the seismic performance issues in the design of the GIL. Firstly, the GIL is modeled in three dimensions, and the pre-stressed modal analysis is conducted to obtain the vibration characteristics of the GIL structure. Secondly, the seismic response spectrum analysis is conducted according to the national standard, and the seismic characteristics are obtained to meet the requirement of resisting an earthquake of magnitude 9, but there are problems of relatively large stress distribution and small safety coefficient of the brace. Finally, it is proposed to change the cross-section of the bracket to strengthen the stiffness of the bracket to improve the seismic performance of the GIL equipment, and simulations are carried out to verify the results, which show that increasing the cross-section of the bracket can improve the seismic performance of the equipment.

Static and seismic stability investigation of a bamboo grid reinforced slope with different stepped reinforcing arrangements

Bamboo is primarily used as a soil reinforcement material to build roadways and stabilize slopes and river banks. The current study aims to examine how bamboo grid reinforcing slopes behave in the form of various stepped reinforcing arrangements. The static and seismic characteristics of a slope reinforced with a bamboo grid were examined through 3D numerical analyses employing the finite element program MIDAS GTS NX (340) 2023 v1.1. In this study, the Strength Reduction Method (SRM), a crucial technique in finite element analysis, is utilized to compute the factor of safety and displacement in static stability analysis. Seismic stability analysis is conducted using non-linear time history analysis, examining the changes in critical slope parameters in response to seismic excitation. Three distinct arrangements of bamboo grids were employed to enhance slope stability. Static stability analysis, considering the factor of safety and deformation, was conducted for various bamboo grid-reinforced slope arrangements. Additionally, a comprehensive seismic analysis was performed specifically for the type 2 bamboo grid reinforcement arrangement, using the seismic record from the 1971 San Fernando Down earthquake. The safety factor increases by 52.10%, 68.67%, and 62.65% for type 1, 2, and 3 arrangements, respectively, compared to the unreinforced slope. Consequently, the type 2 bamboo grid-reinforced slope arrangement exhibits superior stability in terms of the safety factor. The lateral displacement of the type 2 arrangement is minimal compared to other types. Furthermore, a bamboo grid-reinforced slope with a vertical spacing of 1.5 m demonstrates less deformation than slopes with different vertical spacings. The seismic stability of the slope body surpasses other sections of the bamboo grid-reinforced slope.

Characterization of seismicity and precursor monitoring in northern Baja California using RESNOM data

Northern Baja California, Mexico, is part of the boundary between the Pacific and North American plates, and the relative motion between these plates causes seismicity that has attained a recorded magnitude M7.3. This seismicity represents a hazard for towns and cities located in this area and, in order to be able to contribute to the hazard estimation, we propose to establish monitoring of possible precursors to major earthquakes.We will use data from the RESNOM seismological network, operated by CICESE, to monitor the area between longitudes −117.4° and −114.5°, and latitudes 30.5° and 33.2°.Since the study area presents a complex array of seismogenic regions, we define three regions for monthly precursor monitoring, based on long-term epicentral spatial distributions, together with geological and tectonic considerations. We propose monthly monitoring because it is a good tradeoff between useful temporal definition and having enough events for evaluation of statistical measures.We are monitoring monthly two types of measures, those that can be directly evaluated from data for each month (number of events/day, released seismic moment/day, and average magnitude and depth), and measures requiring more processing and larger amounts of data (direct clustering, clustering from apparent velocities, Poisson entropy, and fractal dimensions D0, D1, and D2).We estimate that coverage is adequate from 2005 to date (June 2023), and monitoring of data over this period suggests that, for two of the regions, it may be possible to identify precursory activity before earthquakes with magnitudes M≥7.0 and, possibly M≥6.0. The third region, however, needs improved network seismographic coverage for monitoring to be effective. There are not enough recorded strong and major earthquakes to be able to estimate reliability for precursory signals yet.Monitoring will continue indefinitely and may evolve to consider more or different measures and/or regions. We hope that this monitoring may help in identifying regions of interest for detailed observation and, eventually, to help in the estimation of seismic hazard in northern Baja California.

Three-dimensional broadband simulation of near-fault seismic ground motion considering complete source-path-site effect: Modeled by fast multipole indirect boundary element method

Efficient and accurate numerical methods are essential for analyzing seismic wave propagation and amplification in near-fault complex sites. Understanding the complete process of ground motion simulation, including fault rupture, path propagation, and near-surface complex site response, is crucial for studying earthquake damage mechanisms, seismic zoning, and designing large-scale engineering structures. In this study, we propose a fast multipole indirect boundary element method (FMIBEM) to achieve broadband and high-efficiency simulation, enabling a comprehensive analysis of the complete process involving seismic ground motion. The FMIBEM significantly reduces the computational and storage costs associated with 3D near-fault complex site seismic wave scattering problems to O(N). We validate the accuracy of the method by comparing it with the analytical solution. Compared to the conventional indirect boundary element method (IBEM), our proposed method reduces computational time by over 95 % and storage costs by nearly 90 %. FMIBEM greatly enhances the efficiency of the boundary element method for simulating seismic wave scattering in near-fault complex sites. To demonstrate the effectiveness of our approach, we apply the FMIBEM method to two typical 3D near-fault complex site examples of seismic wave scattering. The simulation results successfully capture both the local site amplification effect and the characteristic near-fault seismic features, such as the hanging wall effect, permanent displacement effect, and large velocity pulse.

Advancing Quantitative Seismic Characterization of Physical and Anisotropic Properties in Shale Gas Reservoirs with an FCNN Framework Based on Dynamic Adaptive Rock Physics Modeling

Quantitative seismic methods are crucial for understanding shale gas reservoirs. This study introduces a dynamic adaptive rock physics model (DARPM) designed to systematically quantify the relationship between physical parameters and elastic parameters within shale formations. The DARPM uniquely adapts to changes in formation dip angle, allowing adaptive reservoir property assessment. An innovative adaptive rock physics inversion methodology is subsequently proposed to compute values for reservoir physical and seismic anisotropy parameters. This is achieved using well log data and building upon the foundation laid by the established DARPM. We introduce the RPM-FCNN (rock physics model—fully connected neural network) framework, seamlessly integrating the DARPM with the corresponding inversion results into a comprehensive model. This framework facilitates a quantitative analysis of the nonlinear relationship between elastic and reservoir physical parameters. Utilizing the trained RPM-FCNN framework, the spatial distribution of reservoir and seismic anisotropic characteristics can be precisely characterized. Within this framework, the organic matter mixture aspect ratio indicates the continuity of organic matter, while the organic matter porosity reveals the maturity of organic matter. Simultaneously, seismic anisotropy characteristics signify the degree of stratification within the reservoirs. This method, therefore, establishes a robust foundation for identifying favorable areas within shale gas reservoirs.

Accessing Near-Field Strong Ground Motions Using a Multi-Scheme Method in the Kalawenguquan Fault, Xinjiang, China

The middle segment of the Kalawenguquan fault has been active since the Holocene, with a maximum credible earthquake magnitude of MS 7.5. We established two source models based on empirical relationships, as well as geological, geomorphological, and seismic characteristics. Taking into account the uncertainties of simulation parameters, we adopted the stochastic finite-fault method to calculate all combinations of a multi-scheme simulation. The effects of different source models, initial rupture points, and site locations on the prediction of ground motion parameters were analyzed. The results indicate that when a site is located on a smaller asperity and is a certain distance from the largest asperity, the simulation results are higher. For different sites, when the initial rupture point is located near the smaller rather than the larger asperity, the acceleration response spectra are higher. Our results show that the relationships between the initial rupture points, asperities, and sites have a significant impact on the simulation results. Therefore, our study highlights the relevance of determining the initial rupture point and source model to obtain a reasonable evaluation for near-field strong ground motion simulations at major infrastructures.

Technology Focus: Seismic (February 2024)

2023 wrapped up nicely with COP28 in Dubai. The key highlights were the commitments by both governments and the private sector to zero-methane production by 2030, net-zero greenhouse gas emissions from operations by 2050, and triple renewable power-generation capacity and double energy efficiency in this decade. There has been tremendous progress on our collective journey toward cleaner energy production, and now we must take it a notch higher. In the past couple of years, JPT’s Seismic feature has been marked by highly innovative seismic techniques and machine-learning work flows focused on reduction of carbon footprint; frontier exploration, expanding heartlands and brownfield development; and improved seismic survey, imaging, and attribute analysis for reservoir characterization and fracture diagnostics, which are in line with the COP28 pledges. This year’s feature is no different. Recent technical-paper titles have further shown the steady increase in the application of advanced seismic techniques and machine learning to mature “stranded” and “advantaged” hydrocarbon-bearing accumulations to production; improve carbon capture, storage, and leak detection; and analyze naturally and artificially induced fractured reservoirs and seismicity. The selected papers are reflective of these themes. In addition, some remarkable applications of seismic techniques are presented in the recommended papers. They include the following: - 2D nonlinear seismic site response analyses used to determine if the capacity of a silty sedimentation could support the load of a pipeline end termination in the event of an earthquake - The results of a pilot test of the Marine Vibrator, an industry-leading seismic-survey technique - High-resolution modeling to infer if an increase in seismicity is caused by an increase in pore pressure from wastewater injection in the Fort Worth Basin of north central Texas - 4D time/depth shifts and strain signals successfully used to estimate pressure depletion in the Gulf of Mexico Others are applying advanced measurement and modeling techniques to optimally place a long horizontal injector well in multilayered heterogeneous sandstone reservoirs and predicting reservoir presence from seismic velocity and pore-pressure prediction. These topics will supply the insights that will help us achieve the COP28 targets while we look forward to more exciting innovations in 2024. Recommended additional reading at OnePetro: www.onepetro.org. OTC 32267 Seismic Stability Assessment of a Mudmat on Liquefiable Seabed by Brian Carlton, Norwegian Geotechnical Institute, et al. OTC 32393 Predicting Reservoir Presence From Seismic Velocity Mapping and Pore-Pressure Prediction by Matthew James Legg, Shell OTC 32741 Marine Vibrator Milestone: A Pilot Seismic Survey by R. Alfaro, TotalEnergies, et al. SPE 212951 High-Resolution Modeling of Pore-Pressure Change, Fault Slip Potential, and Induced Seismicity in the Fort Worth Basin by Changqing Yao, Texas A&M University, et al. URTeC 3870451 Impact of Fracture Roughness on Fines Migration and Fracture-Aperture Growth in Calcareous Shale Rocks During Acidized Corefloods by Hasan J. Khan, King Fahd University of Petroleum and Minerals, et al.

Quantitative seismic fracture characterization of a sandstone reservoir — Decatur, Illinois Basin

The Illinois Basin Decatur Project, a carbon capture and sequestration task, was undertaken to sequester 1 million tonnes of CO2 into a sandstone reservoir. A 3D seismic survey was conducted to characterize the reservoir. A geomodel was developed from seismic data, inversion results, and well data to geostatistically map the storage potential of the reservoir. However, no fracture model was created or utilized in this exercise. Fractures inherently influence the porosity and permeability of a reservoir. Ignoring them in reservoir characterization is not an optimal reservoir management practice. The image-log interpretation from a few vertical wells drilled in the area shows the bedding plane dips, but no fracture has been identified. However, the lack of fracture crossings in a few vertical wells does not imply that a formation is devoid of fractures altogether. Hence, seismic fracture characterization (leveraging the dense 3D seismic data) is necessary for a reservoir characterization exercise. We utilized the publicly available Decatur 3D seismic data set to run a seismic fracture characterization workflow to delineate potential fracture corridors present in the reservoir. We calculated three edge detection attributes (structural tensor, structure-oriented semblance, and structural dip) in combination to delineate the fracture lineaments. Our workflow extracts several quantitative measures of the seismic lineaments such as dip, azimuth, area, and length, which can be analyzed statistically. The principal focus of this work is to find a way forward to integrate the fractures from seismic data in a geologic model that can be utilized in simulations. Based on our interpretation of seismic fractures, we created a discrete fracture network that can be a building block for creating a finer-resolution fracture model. We also explored the fractal characteristics of seismic-derived fracture lineaments as a way forward for generating discrete fracture networks.

The MW5.5 earthquake on August 6, 2023, in Pingyuan, Shandong, China: A rupture on a buried fault

On August 6, 2023, a magnitude MW5.5 earthquake struck Pingyuan County, Dezhou City, Shandong Province, China. This event was significant as no large earthquakes had been recorded in the region for over a century, and no active fault had been previously identified. This study collects 1309 P-wave arrival times and 866 S-wave arrival times from 74 seismic stations less than 200 km to the epicenter to constrain the spatial distribution of the mainshock and its 125 early aftershocks by the double difference earthquake relocation method, and selects 864 P-waveforms from 288 stations located within 800 km of the epicenter to constrain the focal mechanism solution of the mainshock through centroid moment tensor inversion. The relocation and the inversion indicate, the Pingyuan MW5.5 earthquake was caused by a rupture on a buried fault, likely an extensive segment of the Gaotang fault. This buried fault exhibited a dip of approximately 75° to the northwest, with a strike of 222°, similar to the Gaotang fault. The rupture initiated at the depth of 18.6 km and propagated upward and northeastward. However, the ground surface was not broken. The total duration of the rupture was ∼6.0 s, releasing the scalar moment of 2.5895 × 1017 N·m, equivalent to MW5.54. The moment rate reached the maximum only 1.4 seconds after the rupture initiation, and the 90% scalar moment was released in the first 4.6 s. In the first 1.4 seconds of the rupture process, the rupture velocity was estimated to be 2.6 km/s, slower than the local S-wave velocity. As the rupture neared its end, the rupture velocity decreased significantly. This study provides valuable insights into the seismic characteristics of the Pingyuan MW5.5 earthquake, shedding light on the previously unidentified buried fault responsible for the seismic activity in the region. Understanding the behavior of such faults is crucial for assessing seismic hazards and enhancing earthquake preparedness in the future.

Seismic Landslide Susceptibility Assessment Using Newmark Displacement Based on a Dual-Channel Convolutional Neural Network

Landslide susceptibility assessment (LSA) is an essential tool for landslide hazard warning. The selection of earthquake-related factors is pivotal for seismic LSA. In this study, Newmark displacement (Dn) is employed as the earthquake-related factor, providing a detailed representation of seismic characteristics. On the algorithmic side, a dual-channel convolutional neural network (CNN) model is built, and the last classification layer is replaced with two machine learning (ML) models to facilitate the extraction of deeper features related to landslide development. This research focuses on Beichuan County in Sichuan Province, China. Fifteen landslide predisposing factors, including hydrological, geomorphic, geological, vegetation cover, anthropogenic, and earthquake-related features, were extensively collected. The results demonstrate some specific issues. Dn outperforms conventional earthquake-related factors such as peak ground acceleration (PGA) and Arias intensity (Ia) in capturing seismic influence on landslide development. Under the same conditions, the OA improved by 5.55% and AUC improved by 0.055 compared to the PGA; the OA improved by 3.2% and AUC improved by 0.0327 compared to the Ia. The improved CNN outperforms ML models. Under the same conditions, the OA improved by 4.69% and AUC improved by 0.0467 compared to RF; the OA improved by 4.47% and AUC improved by 0.0447 compared to SVM. Additionally, historical landslides validate the reasonableness of the landslide susceptibility maps. The proposed method exhibits a high rate of overlap with the historical landslide inventory. The proportion of historical landslides in the very high and high susceptibility zones exceeds 87%. The method not only enhances accuracy but also produces a more fine-grained susceptibility map, providing a reliable basis for early warning of seismic landslides.

Carbonate platform or volcanic mound? Seismic characterization of a synrift buildup along the outer high of the Lüderitz Basin, Namibia

Carbonate platform or volcanic mound? Seismic characterization of a synrift buildup along the outer high of the Lüderitz Basin, Namibia

Advanced Seismic Data Analysis: Comparative study of Machine Learning and Deep Learning for Data Prediction and Understanding

This study delves into the application of machine learning (ML) and deep learning (DL) techniques for the analysis of seismic data, aiming to identify and categorize patterns and anomalies within seismic events. Using a robust dataset, we applied three distinct clustering approaches: K-Means, DBSCAN, and an Autoencoder-based method, each offering unique perspectives on the data. K-Means clustering provided a fundamental partitioning of the data into five predefined clusters, facilitating the identification of broad seismic patterns. DBSCAN, a density-based clustering algorithm, offered insights into the spatial distribution and density of seismic events, adeptly pinpointing anomalies and outliers that signify unusual seismic activity. The Autoencoder, leveraging deep learning, excelled in capturing complex and non-linear relationships within the data, revealing subtle patterns not immediately apparent through traditional methods. The effectiveness of these clustering techniques was quantitatively evaluated using the Silhouette Score and the Davies-Bouldin Score, alongside visual assessments through PCA and t-SNE for dimensionality reduction. The results indicated that while K-Means provided clear partitioning, DBSCAN excelled in outlier detection, and the Autoencoder offered a balanced approach with its nuanced analysis capabilities. Our comprehensive analysis underscores the significance of employing a multi-methodological approach in seismic data analysis, as each method contributes uniquely to the understanding of seismic events. The insights gained from this study are valuable for enhancing predictive models and improving disaster risk management strategies in seismology. Future research directions include the integration of additional seismic features, validation against larger datasets, and the development of hybrid models to further refine the predictive accuracy of seismic event analysis.

Statistical Features of Seismicity Associated with Large Earthquakes on the Chinese Continent between 2008 and 2019 Based on Newly Detected Catalogs

Abstract The Chinese continent is seismically active and is an important region for analyzing statistical behaviors of large intraplate earthquake sequences. A systematic and detailed record of large earthquake sequences provides the basis for such analysis in a tectonically complex region. In this study, using a graphic processing units-accelerated matched filter technique, we detected up to five times more events than standard earthquake catalogs to generate newly detected catalogs for 32 Ms≥6.0 earthquakes on the Chinese continent from October 2008 to December 2019. The statistical analysis of the newly detected high-resolution catalogs showed that strike-slip mainshocks have higher potential to have anomalous foreshock sequences but are followed by fewer aftershocks than those with other faulting styles. We also provided an example for the 2014 Yingjiang, Yunnan, earthquake sequence, in which the b-value shows a reduction for foreshock sequences and is followed by a recovery in the aftershock period. Our detected catalogs can be used to further study statistical behaviors of earthquake sequences, which is essential for understanding earthquake interaction and improving seismic hazard assessment on the Chinese continent and around the world.

Seismicity characteristics of the Gulf of Aqaba seismogenic zone and their hazard implications in northwestern Saudi Arabia

The seismogenic characteristics of the Gulf of Aqaba zone have been assessed using the maximum likelihood method to estimate various earthquake recurrence parameters. These parameters encompass the β-value, annual recurrence rate (λ), and maximum probable magnitude (Mmax). This assessment has identified three sub-seismogenic zones, each corresponding to specific structural faults within the Gulf. These zones are associated with the Aragonese, Arnona and Aqaba faults, delineating pull-apart basin structures in the Gulf of Aqaba. An updated earthquake catalogue has been compiled using a unified moment magnitude (Mw) scale to improve the analysis, established by developing two empirical relationships. According to the findings of this study, there is a possibility that the Aragonese seismogenic zone could experience an earthquake with a maximum magnitude of 7.7, highlighting a significant seismic hazard in the region. While acknowledging the inherent uncertainties in this assessment, a probabilistic seismic hazard was calculated for hard rock conditions within a spatial area divided into elementary cells, each measuring 0.1°×0.1°. The highest peak ground acceleration (PGA) is associated with a spectral frequency of 5.0 to 10.0 Hz and could significantly impact building codes in the region. The spatial distribution variations of seismic hazard corresponding to the proposed sub-seismogenic zones indicate a high degree of crustal heterogeneity and seismotectonic complexity. This comprehensive assessment contributes to understanding seismic hazards that may import from the Gulf of Aqaba seismogenic zone.

Elimination of seismic characteristics of solid-filled in ultra-deep fractured-vuggy reservoirs

A large number of high-quality fractured-vuggy reservoirs (FVRs) are buried in ultra-deep (6500–9000 m) carbonate layers in the Tarim Basin, represented by the strong “beaded” reflection (SBR) on seismic profiles. This characteristic corresponds to the vast majority of high yield oil and gas wells, but there have also been a number of instances where the reservoir was filled with solid, leading to exploration failure. To avoid drilling failure, it is crucial to accurately identify fake reservoirs using geophysical methods. This paper proposes a novel method to eliminate the seismic characteristics of solid-filled in FVRs. Based on the waveform component decomposition (WCD) data, combined with drilling and logging data, an adaptive component reconstruction (ACR) can be completed to distinguish whether the reservoir is filled with solid or not, achieving the goal of eliminating the seismic characteristics of filling. Firstly, supervised WCD is performed on the target seismic data. Then, the waveform characteristics, which indicate the difference in the FVRs filled with solids, are combined accordingly with the sensitive attribute characteristics (instantaneous amplitude, heterogeneous anomalies, arc length, etc.) of each component data, and the feature templates of filled and non-filled FVRs are defined. Finally, the information entropy method is applied to optimise the component set that can distinguish the solid filled and non-filled FVRs and complete the component reconstruction. Forward modelling shows that this method can effectively distinguish the characteristics of FVRs that have been filled by solids from those that not. This method has achieved favourable results in the M block in the Tarim Basin. Successfully removed some or all the characteristic information of solid filled reservoirs confirmed by drilling from seismic data. The effectiveness of the method in identifying solid filled reservoirs has been confirmed by drilling, and the prediction rate of FVRs non-filled with solids has increased from 78% to 95%. This method can be used for reference in blocks with similar geological characteristics.

Multifractal temporal analysis of seismicity of the Trans-Alboran shear zone

This study provides a temporal analysis of the seismicity occurring before three significant energetic earthquakes recorded in the Al Hoceima, Morocco, area: earthquakes in 1994 (Mw 6.0), 2004 (Mw 6.4), and 2016 (Mw 6.3). The analysis is based on the multifractal seismicity characteristics in the Trans-Alboran shear zone. For the computation of the multifractal spectrum f(α)-α, two measurements were considered, the temporal distribution of earthquakes and the temporal distribution of energy released by the earthquakes. In addition, the quantities D1 (entropy), D+∞ (dimension of the large measurements), R (α0-αmax) and L (αmin-α0), from the multifractal spectrum, were also defined. The obtained results prove that maximum values in the fractal dimensions D1 and D+∞ appear just before the occurrence of the largest earthquakes in the multifractal spectrum computed from the earthquake-released energy. This particular trend, which is connected to the maximum values, is also noticeable before the occurrence of seismicity, which is less energetic for earthquakes with magnitudes above Mw 4.5, and may be evidence that the dynamic and geometrical properties of seismicity are associated.