pure and applied geophysics最新文献

Polyphase fault evolution through reactivation is a globally observed phenomenon on passive margins. These structures play a crucial role in petroleum systems, offer vital constraints on rift and passive margin kinematics, and, in certain instances, serve as global markers for far-field stresses. Despite the significance of reactivated faults, understanding their kinematic evolution, existence, extent, and interactions within fault populations is often limited. This underscores the need for comprehensive investigations, including considerations of halokinesis in this process. This study presents a structural interpretation of a relay ramp identified in the Penobscot 3D seismic reflection survey offshore Nova Scotia, Canada. The ramp is characterized by two major SSE-dipping faults accompanied by smaller antithetic and synthetic normal faults with a general ENE-WSW strike. The two major faults exhibit evidence of reverse deformation in their lower sections, transitioning to normal offsets in their upper portions. Smaller faults predominantly affect younger strata without evidence of reactivation. Fault throw analysis indicates coupled movement on the main faults during both reverse and normal deformation intervals. Structural analysis suggests that these structures initially formed as reverse faults due to halokinesis and were subsequently reactivated during oceanward salt migration. The timing of Atlantic margin halokinesis aligns broadly with previously documented large-scale kinematic reorganization periods, suggesting similar kinematic events triggered salt movements in the Penobscot area. The observed kinematic dichotomy at depth is crucial, highlighting the potential oversight of polyphase deformation in areas where seismic data only captures near-surface structures. Recognising salt's role in kinematic reactivation is vital, explaining inversion phenomena and generating economically important trapping structures globally. This study implies that reactivation of structures in passive margins may be more widespread than previously acknowledged, particularly if seismic data only captures upper portions of structures.

This study estimates both hourly and daily Downward Surface Solar Radiation (SSR) in Istanbul while determining the importance of variables on SSR using tree-based machine learning methods, namely Decision Tree (DT), Random Forest (RF), and Gradient Boosted Regression Tree (GBRT). The hourly and daily data of climatic factors for the period between January 2016 and December 2020 are gathered from the European Centre for Medium-Range Weather Forecasts' (ECMWF) ERA5 reanalysis data sets. In addition to the meteorology data, hourly data of selected aerosols are obtained from the Ministry of Environment, Urbanization and Climate Change. Temperature, cloud coverage, ozone level, precipitation, pressure, and two components of wind speeds, PM₁₀, PM_2.5, and SO₂ are utilized to train and test the established models. The model performances are determined with the out-of-bag errors by calculating R-squared, MSE, RMSE, and MBE. The GBRT model is found to be the most accurate model with the lowest error rates. Furthermore, this study provides the variable importance in determining the SSR. Although all models provide different values for the variable importance; temperature, ozone level, cloud coverage, and precipitation are found to be the most important variables in estimating daily SSR. For the hourly estimation, the time of day (hour) becomes the most important factor in addition to temperature, ozone level, and cloud coverage. Finally, this study shows that the tree-based machine learning methods used with these variables to estimate hourly and daily SSR results are very accurate when it is not possible to measure the SSR values directly.

To catalyze transformative advancements in High-energy Physics in the Atmosphere (HEPA), a comprehensive understanding of particle fluxes, electric fields, and lightning occurrences across atmospheric layers is imperative. This paper elucidates the instrumentation and capabilities of the Aragats Space-Environmental Center (ASEC), which encompasses measurement tools for various cosmic ray species, near-surface electric fields, and lightning events integrated across high-mountain research station at slopes of Mt. Aragats and the highest mountains of Eastern Europe and Germany. Through these measurements, we aim to elucidate models of particle acceleration mechanisms and the charge distribution within the lower atmosphere. We introduce an Advanced Data Extraction Infrastructure (ADEI) integrated with sophisticated statistical analysis tools to facilitate rapid access to this wealth of data. Despite the significance of these atmospheric processes, the intricate interplay between thundercloud electrification, lightning activity, wideband radio emissions, and particle fluxes remains poorly understood. A particularly compelling avenue of inquiry lies in exploring the relationship between high-energy atmospheric phenomena, intracloud electric fields, and lightning initiation. Furthermore, investigations into accelerated structures within geospace plasmas hold promise for shedding light on particle acceleration processes, potentially extending to higher energies within analogous structures in cosmic plasmas. This paper also examines practical methodologies for extracting meaningful physical insights from temporal datasets, such as correlating surges in particle flux intensity with variations in near-surface electric field strength and precipitation patterns. Additionally, we explore the utility of wideband field and interferometer antenna signals in this context, offering valuable avenues for further research and analysis. Through these endeavors, we aim to deepen our understanding of high-energy atmospheric processes and their broader implications for terrestrial and cosmic phenomena.

As a technique capable of replacing laboratory experiments, a large number of digital rock simulations have been widely used for the characterization of reservoir petrophysical parameters. For conditions with less coring data, rapid reconstruction of three-dimensional (3D) digital rocks using two-dimensional (2D) pore structure images is an important prerequisite for the accurate calculation of petrophysical parameters. However, the conventional digital rock rapid reconstruction method with poor pore connectivity leads to the erroneous evaluation of key reservoir rock parameters (e.g., permeability and resistivity ). In this study, we used the sequential indicator simulation method as the base data and combined the erosion operation and expansion operation in mathematical morphology to realize the rapid construction of 3D digital rock models with strong pore connectivity . The accuracy of the digital rock model reconstructed by the new method was verified by comparing with the permeability and electrical properties obtained by the CT-based method, sequential indicator simulation method, multi-point statistical method, process-based method, and deep leaning method. This study overcomes the shortcomings of the sequential indicator simulation digital rock reconstruction method in terms of small pore radius and poor pore connectivity, improves the permeability of constructing 3D digital rocks, and lays the foundation for accurate and rapid analysis of petrophysical properties.

To understand the characteristics of seismic waves and tsunamis recorded simultaneously by the ocean-bottom observation networks, the coupling between the solid Earth and the ocean has to be modeled in the presence of gravity. However, previous coupled simulations adopted approximate equations that did not fully incorporate the effects of gravity. In this study, we derived correctly linearized governing equations under gravity and compared them with those of previous studies. Numerical experiments were performed for a two-dimensional P-SV wavefield, using the finite difference method (FDM). To validate the accuracy of the calculated tsunamis, we computed the theoretical tsunami dispersion relation using a propagator matrix and compared it with our results and those of previous studies. We found that our proposed method provided more accurate results than those of previous studies, particularly in the short-period band. We also investigated the applicability of the proposed method to distant tsunamis by examining the difference between calculated and theoretical tsunami phase velocities in the long-period band. The proposed formulation provides accurate results that properly incorporate gravity into the simultaneous simulation of seismic waves and tsunamis.

The 2016 M_w 6.8 Chauk, Myanmar earthquake was one of the largest earthquakes in Myanmar, leading to significant damage to historical monuments and the first earthquake to occur in the instrumental era. In the current study, broadband (0.01–25 Hz) ground motions are simulated in the 4.5° × 4.5° region around the epicenter to investigate the ground-motion characteristics of the event. Towards this goal, deterministically generated low-frequency and stochastically simulated high-frequency ground motions are combined to create three-component broadband seismograms. The simulated ground motions are further compared with the available strong motion data recorded in the near-field and far-field stations. Thus, the efficacy in modeling the ground motions is quantified through the estimation of the goodness of fit between the 5% damped acceleration response spectra obtained from recorded and simulated ground motions. Furthermore, the peak ground acceleration (PGA) of the simulated ground motions for the entire region is presented in the form of a contour map along with its spatial variation with the region's topography. The simulated PGA is further compared with the global ground motion models developed for subduction zone intraslab earthquakes. Most importantly, acceleration time histories are generated at the locations of severely damaged monuments in Bagan and Nyuang-U city, which can further be utilized for nonlinear dynamic analysis of the structures.

The target reliability of mine rock slopes must be scientifically determined, which can fully reflect the safety level of slope stability and plays an essential role in establishing slope reliability design guidelines. Since the design guidelines based on reliability methods have not been established for mine rock slopes, the suggested target reliability values are proposed based on the grey fixed weight clustering and analogy method. Firstly, a new evaluation method of slope safety grade is proposed by considering more influencing factors of slopes. Secondly, the grey fixed weight clustering is used to quantitatively processes the slope reliability data, and the slope safety grade is judged. Then, the target reliability of each grade is obtained by the analogy method. Finally, the equal difference method is applied to set the threshold of allowable failure probability for the minimum service life of slopes, and the reliability of other service life is processed by linear interpolation. The results show that, the target reliability of the maximum service life for grade I, II, III ductile failure is 3.25, 2.75, 2.25, and brittle failure is 3.75, 3.25, 2.75, respectively. the allowable failure probability of the minimum service life for each grade shows that the ductile failure is 1%, 3%, 5% and brittle failure is 0.5%, 1%, 3%, respectively. In addition, the suggested values of Inter-ramp and Bench slopes are also improved, and a case study is conducted in the Jinbao iron mine to illustrate the feasibility of the method and results in this paper.