Geological Data Research Articles

A Perspective on the Rupture States of Complex Earthquake Scenarios in the 2023 USGS Seismicity Model for the Western U.S. Faults

Abstract The 2023 U.S. Geological Survey (USGS) seismicity model for faults in the western United States (USGS-SMF-WUS) includes many earthquake scenarios (EQS) that rupture multifault sections (MFS), reflecting decades of observations that large crustal earthquakes often rupture sections of different neighboring faults in complex ways. Many of the complex MFS scenarios include rupture sections, on different faults, that are not contiguous, with spacing up to 15 km. The USGS-SMF-WUS uses an inversion methodology, referred to as magnitude-rate optimization, to optimally formulate the occurrence rates of the EQS in such a way that they collectively release the accumulating seismic moment rates on faults, at subsection level, defined by various types of geologic, geodetic, and seismologic data and constraints. This raises questions about the treatment of the MFS scenarios in the USGS-SMF-WUS regarding their rupture states and how that could potentially impact the magnitude-rate optimization and ground motions (GMs) for hazard analysis. Among many different possible rupture states for the MFS earthquakes, the two extreme scenarios could be visualized as (1) a series of noncontiguous sections rupturing in such a way that their total seismic moment and GM footprints are scaled with the sum of their rupture areas and (2) a series of noncontiguous triggered events, grouped together based on the spacing between the participating fault sections and other criteria, each releasing seismic moment and generating GM footprints that are scaled with its own rupture area. It will be shown later that the average slips on the participating sections for these two extreme rupture states would not be the same. In addition, the GM footprints from these two rupture states would be different and the differences are frequency dependent. This is especially the case when considering the complexity of rupture directivity on the participating fault sections in the USGS-SMF-WUS. It is the objective of this study to explore and discuss the implications of the triggered rupture state assumption in estimating the average slips and GM footprints of the MFS earthquakes in the USGS-SMF-WUS.

Палеотектонический анализ отложений нижнеапшеронской литофациальной пачки Астраханского Прикаспия

The paleotectonic analysis of the Apsheron deposits of the Astrakhan Caspian Sia is considered. The main at-tention is paid to the analysis of the deposits of the lower Apsheron lithofacies unit, which includes the study of the thickness of the deposits, the construction of maps of thicknesses and trend values, as well as the analysis of the wave pattern of seismic works carried out in the territory of the Astrakhan Caspian Sia. The results of the study showed that during the Lower Apsheron time, significant tectonic processes took place in the region, including the growth of salt domes and the formation of alluvial fans. These processes had a significant impact on sedimentation and the distribution of sediment thicknesses. The conclusions about the influence of salt dome tectonics on sedimentation, as well as the role of paleorelief in the formation of local thickness anomalies are presented as well. The results obtained are important for understanding the geological history of the region and assessing its oil and gas potential. The data presented in the article are based on the analysis of geological data, including seismic data, and the use of paleotectonic analysis methods. The article describes in detail the research methods and provides examples of specific results obtained during the work.

Enhancing weathered slope stability assessment through the integration of slake durability index, elastic modulus of knocking ball, and electrical resistivity tomography.

This research assesses the stability of sedimentary rock slopes in Teloi, Sik, Kedah, by focusing on the mechanical properties of the rock layers and their susceptibility to weathering. Key tests include the slake durability index (SDI), elastic modulus of knocking ball (Ekb), and electrical resistivity tomography (ERT). The incorporation of electrical resistivity tomography (ERT) data through the virtual reality platform facilitates the visualization of subsurface conditions. The variability of strength characteristic of interbedded sedimentary rocks leads to the differential weathering of rock layers, which causes deterioration on the slope structure. The testing revealed significant variability in rock strength, with sandstone displaying higher durability (Id > 17.1%) and elasticity (Ekb: 0.97 to 29.31 GPa) compared to shale and siltstone, which exhibited lower durability and elasticity (Id < 2.2%, Ekb: 0.2 to 2.2 GPa). Utilizing the Wenner array setup, three distinct electrical resistivity lines were established to evaluate subsurface anomalies. The ERT profiles revealed variations in electrical resistivity among different rock types, identifying areas of weaker material, which are siltstone and shale, while high resistivity areas indicate sandstone. Kinematic analysis through the stereonet process revealed direct toppling as the primary failure mechanism, driven by the critical orientations of joint sets J1, J2, and J3. This aligns with on-site observations of hanging sandstone blocks prone to toppling failure. The findings of this research show that the slake durability index (SDI) and the elastic modulus of the knocking ball (Ekb) enhance the assessment of mechanical properties and weathering resistance of interbedded sedimentary rocks. The virtual reality platform was particularly helpful in analyzing and visualizing the sub-surface conditions and enhancing the evaluation of complex geological data. As a conclusion, this integrated method was helpful in the comprehensive geotechnical evaluation of the slopes, enabling the selection of effective stabilization measures by assessing the differential weathering of interbedded sedimentary rock and identifying potential failure zones.

Failure Mechanism and Control Technology of the Primary Support for Asymmetric Deformation Disaster of Deep Tunnel

Asymmetric large deformation disasters inevitably occur when highway tunnels cross active fault zones. Relying on the Nanlangshan No.1 Tunnel Project, the mechanism of asymmetric deformation is analyzed based on the in-situ engineering geology and tunnel monitoring data, and numerical calculations are used for verification. Based on the results of asymmetric large deformation disaster analysis, the control scheme of double-layer primary support is proposed, and the design is optimized with numerical calculation before engineering practice. The conclusions are as follows: 1. The original primary support program cannot withstand the asymmetric surrounding rock pressure, and the slip of the weak interlayer in the engineering geology is the main reason for the asymmetric deformation disaster in the tunnel. 2. According to the results of the numerical calculations, the tilted weak interlayer greatly reduces the stability of the surrounding rock, which leads to the local bending damage in the left shoulder of the tunnel, and the local shear deformation damage in the right arch girdle. 3. When using the double-layer primary support program, the appropriate delay of support timing for the second layer of primary support can effectively decrease the tunnel asymmetric deformation. However, if the second layer of primary support lag distance is too large, it will also lead to tunnel deformation convergence larger, or support failure and other issues. So, it is recommended that the second layer of primary support lags behind the first layer of primary support by 2 m to be applied.

Innovative multi-generation system producing liquid hydrogen and oxygen: Thermo-economic analysis and optimization using machine learning optimization technique

This research investigates the multi-objective optimization of a geothermal-driven multi-generation system designed to produce liquid hydrogen and oxygen as its primary outputs. The system incorporates a Proton Exchange Membrane (PEM) Electrolyzer alongside a modified ejector-based Organic Rankine Cycle to generate the required Energy (heating bar, cooling bar, electricity and hydrogen). Case studies were conducted in three distinct locations: Zanjan in Iran, Aarhus in Denmark, and San Bernardino in the United States, utilizing actual geological and meteorological data for accuracy. Simulations were executed applied Engineering Equation Solver & optimization of the system was carried out to enhance performance by focusing on the objective functions of system exergy efficiency and cost reduction. This was accomplished by utilizing response surface methodology (RSM) along with Minitab software (MS).To optimize the system, six decision variables were identified as critical parameters influencing performance. The optimization results indicated that the system can achieve an exergy efficiency of 53.74 % while maintaining a cost rate of $31.56 per hour. The overall cost rate for the geothermal system was determined to be $54.50 per hour, with $10.10 per hour allocated to hydrogen production and $44.40 per hour to electricity generation. Site-specific analyses highlighted San Bernardino as the most favorable location for implementing this system, projecting an annual production of 90.8 tons of liquid hydrogen and 208.3 kg of oxygen. In August, the geothermal system in San Bernardino can produce up to 7691.6 kg/h of liquid hydrogen, while in December, production decreases to 7402.8 kg/h, marking the lowest output for the year. In contrast, Zanjan and Aarhus demonstrated lower production capacities, underscoring the system's feasibility as dependent on site-specific conditions.

Shallow Reverse Moderate Earthquakes in the Weiyuan Shale Gas Field, Sichuan Basin, China, Related to Hydraulic Fracturing

Abstract The Weiyuan shale gas field in the stable southern Sichuan basin, China, has experienced increasing seismicity since systematic hydraulic fracturing (HF) operations in 2015. Three Mw≥4.4 shallow earthquakes occurred in the Weiyuan area between September 2019 and February 2020, yet their seismogenic faults, rupture models, and relationship with HF are unknown. In this study, we first obtain the high-resolution coseismic deformation fields of these three events and then invert their slip distribution. The result shows that all three events are shallow high-dip reverse events under the contractional Weiyuan anticline environment with peak slips of 158, 68, and 34 cm and at depths of 4, 3, and 1.6 km, respectively. The spatial relationship between seismogenic faults, horizontal wells, as well as geological data reveals that pore-pressure diffusion due to the HF may be the main mechanism of the 8 September 2019 and the 18 December 2019 events, whereas the 16 February 2020 event may be attributed to the poroelastic stress perturbation caused by the HF. Our study highlights that HF activities and regional geological characteristics jointly influence the properties of earthquakes in the Sichuan basin.

Applications in utilizing soil gas geochemistry along with geological and geophysical data to construct helium exploration statistical models

Applications in utilizing soil gas geochemistry along with geological and geophysical data to construct helium exploration statistical models

Early Paleogene alkaline magmatism in the Subandean Ranges of Jujuy Province

The Zapla Range (Jujuy province) represents the southern edge of the central Andean Subandean Ranges in Argentina. In the northernmost area of the Zapla Range, basaltic rocks are interbedded in the Mealla Formation. These volcanic units form part of the post-rift magmatism of the Salta rift basin, which mainly focused on the Lomas de Olmedo sub-basin to the east. In this paper, six of these basaltic occurrences are characterized on the basis of new geological, petrographic and geochemical data, in order to explore their emplacement, petrogenesis and possible tectonic setting during rift evolution. Peperites in the upper contact of sills evidence the interaction between basalts and unconsolidated or poorly consolidated wet sediments. This implies that there was concomitance between sedimentation and subsurface magma emplacement, suggesting a Paleocene age for the magmatic event according to zircon U-Pb data available for Mealla Formation rocks. Other basaltic units show hipocrystalline textures and lack peperites at the top, which points to their extrusive nature. Additionally, some of these lava flows are spatially associated with pyroclastic deposits that reveal the occurrence of explosive hydrovolcanic eruptions. The study rocks are classified as alkaline basalts and basanites with high Mg# and Ni- and Cr-rich compositions, close to primitive magmas. They show affinity with continental intraplate settings. The analyses of Ba/Nb, Nb/La, (La/Yb)N, (La/Sm)N, (Gd/Yb)N and (Dy/Yb)N ratios, as well as normalized trace and rare earth element patterns, suggests a genesis by low degrees of partial melting of a residual garnet-bearing mantle source. Therefore, basalts from this part of the Subandean Ranges evidence a magmatic episode probably linked to an extensional reactivation stage of the Salta Group rift system in the Lomas de Olmedo depocenter during the Paleocene (∼60 Ma).

Subduction retreat recorded in the southern Beishan orogenic collage of the Central Asian Orogenic Belt: New evidence from deep seismic reflection profiling

The crustal and upper mantle structure of the Beishan orogenic collage, which serves as the southern part of the middle Central Asian Orogenic Belt, provides crucial insights into the history of the multiple openings and closings of the Paleo-Asian Ocean during the Paleozoic. There is considerable dispute over the eventual closure position, timing, and subduction polarity of the Paleo-Asian Ocean, particularly in the southern Beishan orogenic collage. The main cause of these controversies is the lack of a high-resolution lithospheric structure in this area. In this study, we first present a 140-km-long, high-resolution seismic reflection profile taken across the northern Dunhuang Block and the southern Beishan orogenic collage. The seismic imaging provides new constraints on the structure of the lower crust, the Moho, and the upper mantle beneath the southernmost Central Asian Orogenic Belt. A subhorizontal reflector in the middle crust, two sets of north-dipping reflectors from the lower crust to the upper mantle, and several south-dipping reflectors in the upper crust in the northern part of the profile were imaged. Based on our study and other geological, chronological, and geophysical data, we propose that the two sequences of north-dipping reflectors from the lower crust to the upper mantle represent two stages of north-dipping subduction of the southern branch of the Paleo-Asian Ocean. The first stage in the southern Beishan orogenic collage is Late Silurian−Early Devonian, and the second stage is late Carboniferous−Early Permian. The two-stage subduction process gave rise to the Huaniushan arc and the subsequent Shibanshan arc, respectively. These findings provide new constraints on the controversial subduction polarity and the multistage amalgamation of the microcontinental blocks and arcs in the southern Central Asian Orogenic Belt.

Timing of the subduction initiation and ophiolite emplacement of the inner Tauride Ocean: Insight from the Pınarbaşı ophiolite in Central Türkiye

Late Cretaceous ophiolites are widespread in southern Türkiye, including the Tauride Belt Ophiolites and the Central Anatolian Ophiolites. Here, we report new geological, geochemical, geochronological, and zircon isotopic data from ophiolitic rocks of the Pınarbaşı ophiolite (Eastern Tauride Belt). The Pınarbaşı ophiolite forms incomplete sequences, with its mantle section dominated by serpentinized harzburgite and chromitites, while the crustal section comprises ultramafic and mafic cumulates. Whole-rock and mineral chemistry data suggest a supra-subduction zone origin. LA-ICP-MS zircon U-Pb age of 88.2 ± 0.4 Ma (MSWD = 0.84) was obtained from a plagiogranite dyke cutting serpentinized peridotite of the Pınarbaşı ophiolite. Another, U-Pb zircon crystallization age of 96.8 ± 0.6 Ma (MSWD = 1.53) was obtained from a plagiogranite dyke within the mélange of the Pınarbaşı ophiolite. Hafnium isotope compositions of these zircons (εHf(t) = +26.4 to +3.1) suggest a depleted to slightly enriched mantle source. The formation ages of the crustal rocks (gabbro, plagiogranite, and dolerite) of the Cretaceous ophiolites in the Tauride Belt from this and previous ophiolite occurrences, suggest that supra-subduction zone ophiolites in the Inner Tauride Ocean formed during the period ∼101–87 Ma. On the other hand, the peak metamorphism of the metamorphic sole rocks is reported to have occurred around ∼104 Ma. According to all available petrogenetic and geochronological data, it is considered that the supra-subduction zone crust developed shortly (∼ 3–4 Myr) after the initiation of intra-oceanic subduction and this lasted ∼10–15 Myr.

ANALYSIS OF GRANITE ROCK WEATHERING IN THE PARMONANGAN AREA USING LANDSAT 8 SATELLITE IMAGERY

A research has been conducted to analyze the weathering of granite rocks in the Parmonangan area using Lansat 8 satellite imagery which aims to determine the distribution of rocks, weathering processes, and types of rock forming elements in Parmonangan District, North Tapanuli Regency. The method used is using shp geologic map data and Lansat-8 image data processed using Arcgis Map 10.6.1 to determine the distribution of rocks and land cover. XRF is used to identify compounds and rock-forming elements. The results obtained by the rock distribution of the parmonangan area are in the form of the Kluet Formation, Sibolga Complex and Toba Tuff. Land cover in the parmonagan area has differences from 2016 to 2024. Open land in 2024 has increased and the cloud cover obtained has also increased. The rock elements found are Al2O3 (25.31), SiO2 (24.97), K2O (1.56), TiO2 (0.81), Mn2O (30.66), Fe2O3 (4.66), ZrO2, (0.21), Sb2O3 (0.16), and BaO (0.17).

Deep Forest Modeling: An Interpretable Deep Learning Method for Mineral Prospectivity Mapping

AbstractAccurate mineral prediction is crucial for reducing costs and uncertainties in mineral discovery and extraction. The use of artificial intelligence and big data has advanced mineral prediction into intelligent forecasting. Machine learning methods have shown significant promise in enhancing outcomes. Currently, neural network‐based approaches dominate deep learning (DL), but they lack interpretability and have high modeling complexity, making them less effective for complex problems and time‐consuming. Deep Forest, an innovative DL paradigm, addresses these issues by dynamically adjusting complexity and providing importance assessments for predictive factors. This study focuses on the North American Cordillera, known for its rich geological data and potential for porphyry copper deposits (PCDs). Predictions are made using Deep Forest with factors like Euclidean distance between faults and magmatic rock, fault line density, gravity anomalies, and stream‐sediment geochemical data. Deep neural networks, random forest, convolutional neural networks, transformer model and graph convolutional networks are also used for comparison. Deep Forest shows high performance and can avoid the black box problem of DL without relying on other tools in DL, providing a new perspective for the development and application of other non‐neural network DL models for mineral prediction. Feature importance analysis shows that geological structure and magmatism significantly influence PCD prediction. Elevated levels of elements like Al, Co, and Cr in stream sediments help identify mineralization‐related alterations. These findings underscore Deep Forest's capability to accurately and efficiently guide mineral exploration, highlighting its potential as a promising approach for mineral prospecting.

Structure of the basement of the near-Laptev part of the Eurasian basin according to geological and geophysical data

The near-Laptev part of the Eurasian basin is the area of transition from modern spreading to intraplate rifting. We propose an approach to the construction of a 3D model of the basement of the Laptev Sea part of the Eurasian basin based on the linkage of all currently available geological and geophysical data. The structure of the acoustic basement of the Eurasian basin is characterized by alternating troughs and highs in cross-section. The sparse seismic data do not allow us to directly trace the strike of these structures, but they can be correlated with the linearity established by gravity and magnetic data and related to the sequential opening of the basin. For the Laptev Sea part of the Eurasian basin, where linearity is no longer traceable from magnetic data, we propose a method of determining the strike of the basement structures on the basis of seismic stratigraphic analysis. The new 3D model of the acoustic basement in the studied area provided the basis for the tectonic scheme of the entire Eurasian basin. The model reflects the main stages of basin development: continental rifting up to 56 Ma, normal spreading 56–45 Ma, ultra-slow spreading 45–34 Ma, ultra-ultra-slow spreading 34–20 Ma. The southern part of the study area is overlain by a sedimentary cover with an age of 20 Ma and younger, which is associated with the cessation of spreading here no later than 20 Ma.

Financial Risk Early Warning Model Combining SMOTE and Random Forest for Internet Finance Companies

At present, there have been many achievements on enterprise financial risk early warning model, but relatively few early warning studies focusing on the Internet industry. Research shows that the model has stable recognition accuracy and good prediction performance. The improved SMOTE algorithm based on PCA can realize the equalization of unbalanced data sets and use random forest as a classifier to classify and predict geological data. Because the noise data in the original data set may cause the change of the data distribution after interpolation, it is proposed to combine the PCA algorithm and the SMOTE algorithm, first perform noise reduction and dimension reduction, and then perform data interpolation to improve the classification performance of imbalanced data sets. my country's Internet financial listed companies conduct experiments on research samples, algorithm can better improve the classification accuracy and provide new ideas for the classification and prediction of unbalanced data.

Delineation of groundwater potential zones using multi-criteria analysis (AHP), frequency ratios (RF), remote sensing and GIS: a case study of the Batcham municipality (west Cameroon)

Groundwater resource management and development should be done sustainably, which calls for accurate assessment based on new methods and scientific principles. There is an increasing demand for potable water supplies, to meet the woefully inadequate domestic water needs in the Batcham municipality (west of Cameroun). The dearth of knowledge on sustainable management of water resources is to blame for this predicament. As integrated methodologies are not used in groundwater exploration programs, the current problem has gotten worse. Innovative scientific principles of groundwater resource exploration are required to effectively counteract the non-rationalization of water and the problem of unacceptable failure rates in drilled water borehole development. This will improve the appropriate and sustainable use of these resources. Therefore, the goal of this research is to map groundwater potential zones by utilizing readily available datasets and remote sensing (RS), GIS, Frequency Ratios (FR), and multi-criteria analysis (AHP) techniques. The database used is made up of geological data, hydroclimatic data, well data, and satellite images. Each of the methods used is based on the study of the relationships between the factors controlling the groundwater potential. Among these factors, ten (10) were retained based on previous work; these are slope, elevation, land use, land cover, lineament density, drainage density, topographic wetness index, curvature, geology, rainfall, and the static water level. The AHP allowed, according to the user's expertise, to assign weights to each factor controlling the water potential. The FR made it possible to study the relationships linking each variable with high flow rates. The thematic layers obtained were integrated into a GIS environment to generate the groundwater potential map. Four classes of groundwater potential have been identified: bad, moderate, good, and excellent. The bad classes represent 8.32% and 11.21%; moderate 36.57% and 28.70%; good 43.55% and 38.93%; and excellent 11.56% and 21.16%, for the AHP and FR models, respectively. The overlying of wells with high flow rates on areas of excellent groundwater potential shows perfect concordance, which validated the final map. Likewise, the resulting map was validated by sensitivity curve analysis, and the receiver operating characteristic (ROC) curve from which result accuracy was obtained is 70.63% and 80.28% for the AHP method and FR method, respectively. Finally, the FR model outperformed the AHP model in terms of performance and it is possible to use these dependable models to describe groundwater potential zones in the other regions of Cameroon.

Comprehensive Basin Analysis and Petroleum Potential Evaluation of Ayoluengo Oil Field, Basque-Cantabrian Basin, Spain

This study presents a comprehensive basin analysis and petroleum potential evaluation of the Ayoluengo oil field in the Basque-Cantabrian Basin, Spain. Using an integrated approach combining geological, geophysical, and geochemical data, we analyzed the basin's evolution and petroleum system elements. The dataset included 2D and 3D seismic data, well logs, formation tops, and geophysical maps. Our analysis revealed a complex structural framework characterized by salt diapirism and halokinetic structures. Well log interpretation and sequence stratigraphic analysis identified two genetic sequences with associated systems tracts. Four reservoir units were mapped, with the main structural traps related to salt diapirs. Seismic facies analysis highlighted high-amplitude convergent (CBH) and high- and low-amplitude convergent (CBHL) facies as the most promising for reservoir quality. The study identified one play (Jurassic) and two prospects: Lias Limestone (80% geologic chance of success) and Carniolas Dolomite (85% geologic chance of success). Volumetric calculations estimate significant hydrocarbon potential, with STOIIP (Stock Tank Oil Initially In Place) ranging from 3.4 to 4.2 x 10^16 barrels for the Lias Limestone reservoir and 1.26 to 1.56 x 10^16 barrels for the Carniolas Dolomite reservoir.

Synergistic application of digital outcrop characterization techniques and deep learning algorithms in geological exploration

In order to meet the needs of geologists for the analysis of data characterizing field outcrops (rock sections or formations exposed on the ground surface), this study developed a field digital outcrop visualization platform based on Cesium (a 3D geospatial visualization technology) digital outcrop characterization technology. The platform was developed based on WebGL (a protocol for rendering interactions on web pages), which overcame the shortcomings of traditional software in terms of visualization, cross-device, cross-platform, and ease of use. Firstly, UAV inclined photography is used for data collection, which transforms a large amount of geological data into an intuitive 3D geological model, while the visualization platform provides rich measurement and mapping tools for the identified features, which more intuitively displays the outcrop information, helps geological explorers to understand the geological conditions in the field more quickly and comprehensively, and improves the analysis efficiency and ease-of-use of outcrop characterization data. Combined with the improved VGG19 (a deep convolutional neural network architecture) algorithm model, it has excellent performance in dealing with the fine texture and complex structure of rocks, which significantly improves the accuracy of lithology identification. The synergistic application of this technology provides geologists with a faster and more comprehensive means to understand the geological conditions in the field. The reliability of combining the Cesium digital outcrop characterization technology with the VGG19 lithology identification algorithm in geological exploration is verified through case studies. The synergistic application of this technology will greatly enhance the efficiency and ease of analysis of outcrop characterization in the field, and provide new perspectives for future research in geosciences.

Analysis on dynamic characteristics of dam material and seismic response of embankment dam in Longyang Reservoir

PurposeThe geological conditions of Longyang Reservoir are complex and it is located in strong earthquake area. In order to determine its seismic characteristics, the seismic response and residual deformation of embankment dam should be studied to provide calculation basis for dam design and construction.Design/methodology/approachBased on the geological survey data of Longyang Reservoir, the dam filling materials are tested by dynamic deformation tests, and the equivalent linear constitutive model parameters of the filling materials are obtained. Based on Duncan-Chang E-B model, the stress state of embankment dam in Longyang Reservoir before earthquake is calculated, and the dynamic response and earthquake residual deformation of embankment dam in Longyang Reservoir under earthquake condition are calculated by using equivalent linear model and Shen Zhu-jiang’s residual deformation model.FindingsThe results show that with the increase of dynamic shear strain, the dynamic shear modulus decreases and the damping ratio increases. The scatter plot between dynamic shear modulus and dynamic shear strain, and the scatter plot between damping ratio and dynamic shear strain under different confining pressures show strips. The calculation results shows that the acceleration of embankment dam in Longyang Reservoir increases with the increase of dam height, and the acceleration distribution has obvious amplification effect. Combined with the maximum dynamic shear strain during the earthquake and the state before the earthquake, the maximum vertical residual deformation of embankment dam in Longyang Reservoir is 2.98 cm which occurs at the top of the dam, calculated by the Shen Zhu-jiang’s residual deformation model.Originality/value Finite element calculation model parameters of embankment dam are obtained by dynamic triaxial tests. Seismic dynamic responses and residual deformation of embankment dam are analyzed. With the increase of dam height, the acceleration distribution shows an obvious amplification effect. The vertical displacement of embankment dam is larger along the dam axis and decreases in the upstream and downstream direction. The maximum horizontal displacement of embankment dam occurs in the middle of upstream and downstream dam slopes.Highlights(1)Finite element calculation model parameters of embankment dam are obtained by dynamic triaxial tests.(2)Seismic dynamic responses and residual deformation of embankment dam are analyzed.(3)With the increase of dam height, the acceleration distribution shows an obvious amplification effect.(4)The vertical displacement of embankment dam is larger along the dam axis and decreases in the upstream and downstream direction.(5)The maximum horizontal displacement of embankment dam occurs in the middle of upstream and downstream dam slopes.

Evaluation of the geochemical background of soil in a hyper-arid zone using a multivariate statistical methodology: The case of the city of Antofagasta in the Atacama Desert

This study investigates the geochemical background and factors influencing the variability of 19 environmentally relevant elements in the soils of Antofagasta, Chile, a region known for its extensive mining activities. Employing robust multivariate statistical techniques on a dataset of 94 soil samples, we identified four main factors explaining 70% of the total variance in elemental concentrations. These four factors reflect the influence of Jurassic volcanic rocks, intrusive rocks, marine sediments, and mafic to intermediate intrusive rocks. Cluster analysis revealed three distinct geochemical populations, each reflecting a unique combination of natural and anthropogenic influences. We established background concentrations for each element within these clusters using robust statistical methods. Geostatistical analysis, employing inverse distance weighted interpolation, produced factor distribution maps that, when integrated with geological data, provided insights into lithological and anthropogenic influences on soil geochemistry. Our findings highlight the complex interplay between natural geological processes, the region's unique arid climate, and anthropogenic activities in shaping the geochemical landscape of Antofagasta. This study contributes to the understanding of geochemical backgrounds in mining-intensive, arid regions and provides a methodological framework applicable to similar environments worldwide.

Development of GIS-based framework for reservoir data management and quality evaluation

Abstract Accurately measuring and understanding reservoirs is critical for ensuring successful reservoir development, reservoir development evaluation have become an increasingly important issue in reservoir development engineering and present many challenges, particularly when attempting to integrate and visualize multiple types of data. This paper presents the methodologies, techniques and integrated services adopted for the design and implementation of A quantitative oil and gas reservoir data management and evaluation system. The system is an integrated application based on petroleum geology and GIS technology for managing, displaying, administering and analyzing petroleum geological data. In addition, the system is capable of evaluating reservoir quality and input data quality which provides effective recommendations for the design and preparation of reservoir development programs. In this study, a GIS-based quantitative evaluation module was developed considering both reservoir and input data quality. In this case, the reservoir quality index is determined by five major elements, and the input data quality is determined by the quality of six data sources. The weights of each element are determined by principal component analysis (PCA). Developed a raw data output processing software in C# using ArcGIS engine functions, which automatically generates visual maps and reservoir quality assessment information. The feasibility of the platform is verified by using the geological data of Linfen gas field Formation in the eastern slope of Shanxi. The integrated framework system proposed in this study enables decision-makers and the publics to quickly response to oil reservoir development events and allows an easy adaptation to other regional and scientific domains related to real-time monitoring and evaluating.