Acta Geophysica最新文献

{"title":"The potential role of El Niño-Southern Oscillation in triggering Greenland glacial earthquakes","authors":"Bhaskar Kundu,&nbsp;Batakrushna Senapati,&nbsp;Nagaraju Chilukoti,&nbsp;Sambit Sahoo","doi":"10.1007/s11600-025-01541-5","DOIUrl":"10.1007/s11600-025-01541-5","url":null,"abstract":"<div><p>Glacial earthquakes, which are primarily linked to the iceberg calving process, occur more frequently in polar regions with large ice masses. These events are triggered by the sudden movement of glaciers or ice sheets and are highly sensitive to climatic forces. This study focuses on the seasonal and inter-annual patterns of glacial earthquakes from Greenland, investigating the role of the El Niño-Southern Oscillation (ENSO) teleconnection induced by the tropically excited Arctic warming mechanism (TEAM). Our analysis demonstrates that El Niño events elevate surface temperatures over Greenland in winter, driven by increased poleward energy transport in the extra-tropics. This enhanced energy transfer contributes to significant winter warming in the region, establishing a clear link between ENSO-driven climate variability and the frequency of glacial earthquakes.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 3","pages":"2287 - 2297"},"PeriodicalIF":2.3,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the effectiveness of ensemble machine learning approaches for pore pressure prediction using petrophysical log data in carbonate reservoir","authors":"Pydiraju Yalamanchi,&nbsp;Saurabh Datta Gupta,&nbsp;Rajeev Upadhyay","doi":"10.1007/s11600-025-01530-8","DOIUrl":"10.1007/s11600-025-01530-8","url":null,"abstract":"<div><p>Precise estimation of pore pressure (PP) holds significant importance in assessing the geomechanical parameters of reservoirs, playing a crucial role in the planning and execution of drilling and development activities in oil and gas fields. Recognizing its necessity various empirical and intelligent methods have been introduced to enhance the precision of PP prediction. The main objective of this study is to assess the effectiveness of ensemble machine learning (ML) models by conducting a comparative analysis of individual ML models for predicting PP. To identify the most influential input variables for constructing ML models, a feature selection analysis was performed. The findings suggest that a combination of 8-input variables holds the most influence on ML model construction. Three individual ML models namely least-square support vector machine, multi-layer perceptron artificial neural network and decision tree regression (DTR) were employed for PP prediction by using petrophysical log data (8 input variables). The dataset of wells A and B was for training, and testing these models. The results from individual models showed that the DTR algorithm provides the most accurate PP prediction, boasting an <span>({R}^{2})</span> value of 0.972 for training dataset, and an RMSE of 110.698 Psi. The performance of individual models can be enhanced using ensemble models, including simple averaging ensemble (SAE), weighted averaging ensemble (WAE), stacking ensemble (SE), random forest (RF). The results reveal that all ensemble models deliver more accurate PP predictions than individual models. Among them, the RF model stands out with an <span>({R}^{2})</span> of 0.999 for both training and testing datasets. It also demonstrates lower RMSE values of 8.948 Psi, and 21.568 Psi for training, and testing datasets, respectively, making it more accurate than SAE, WAE, SE and individual ML models. Furthermore, the generalization analysis demonstrates that the 8-input variable RF model exhibits excellent performance, providing more accurate PP predictions when applied to the well C dataset within the study area.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 3","pages":"2591 - 2619"},"PeriodicalIF":2.3,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Edge recognition of magnetic anomaly source body based on convolutional neural networks in Red Sea Basin","authors":"Tao Cheng,&nbsp;Weixiang Tao,&nbsp;Xinyi Zhou,&nbsp;Xin Feng,&nbsp;Shuai Wang,&nbsp;Zhaoxi Chen","doi":"10.1007/s11600-025-01537-1","DOIUrl":"10.1007/s11600-025-01537-1","url":null,"abstract":"<div><p>The Red Sea Basin is one of the youngest marine basins, experiencing three stages of rift formation, early magmatic activity, and rift expansion. The fault system and uplift pattern are controversial research points. It can provide effective basis for delineating geological units and dividing fault structures by recognizing the edge information of field source bodies with magnetic anomaly data. However, traditional methods for identifying the boundaries of magnetic anomaly source bodies are affected by factors such as the depth of the source body, magnetization direction, and mutual interference between magnetic anomalies, which can lead to errors in subsequent interpretation work. The latest development of convolutional neural networks has strong feature representation and deep learning capabilities. This paper proposes an edge recognition method based on convolutional neural networks. Firstly, a network architecture for identifying the boundaries of magnetic anomaly sources was designed based on the U-Net network. Then, models with different parameters such as location, scale, quantity, and physical properties were selected to construct a large amount of high-quality sample data for training the network. Finally, a model experiment was designed, taking into account the effects of burial depth and tilted magnetization. The effectiveness of the proposed method was verified by comparing it with traditional edge recognition methods. Finally, based on the geological gravity data of the Red Sea and the Gulf of Aden, the division of the Red Sea and Gulf of Aden fault and uplift system was completed.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 3","pages":"2581 - 2590"},"PeriodicalIF":2.3,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flood vulnerability assessment of buildings using geospatial data and machine learning classifiers","authors":"Tze Huey Tam,&nbsp;Muhammad Zulkarnain Abd Rahman,&nbsp;Sobri Harun,&nbsp;Ismaila Usman Kaoje,&nbsp;Mohd Radhie Mohd Salleh,&nbsp;Mohd Asraff Asmadi","doi":"10.1007/s11600-024-01527-9","DOIUrl":"10.1007/s11600-024-01527-9","url":null,"abstract":"<div><p>Quantifying a building's vulnerability to flooding is crucial for implementing effective structural mitigation strategies. Detailed conventional onsite building damage assessment methods can be time-consuming and unsuitable for rapid assessments, with geospatial data providing a more up-to-date alternative. This study aimed to assess the physical flood vulnerability of buildings in Kota Bharu, Kelantan, Malaysia, using a combination of geospatial data and several machine learning classifiers. A detailed land use and cover classification was performed using high-spatial-resolution satellite imagery and airborne LiDAR to identify affected buildings in the area. Building parameters (height and area) and relevant image features were obtained from the building footprint in the geospatial data and used to classify the vulnerability index with the machine learning classifiers. The estimated vulnerability results were validated using in situ building damage data from previous flood events. The results showed that the combination of geospatial data and the machine learning framework achieved 95% accuracy using the random forest classifier and digitised building footprint. Furthermore, building size was found to be the most important factor in determining vulnerability. This geospatial-based approach to building vulnerability assessment demonstrated a good correlation with in situ flood vulnerability data, indicating its feasibility for rapid and large-scale building flood vulnerability assessments.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 3","pages":"2879 - 2907"},"PeriodicalIF":2.3,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CO2 characterization using seismic inversion based on global optimization techniques for enhanced reservoir understanding: a comparative study","authors":"Ajay Pratap Singh,&nbsp;Ravi Kant,&nbsp;Satya Prakash Maurya,&nbsp;Brijesh Kumar,&nbsp;Nitin Verma,&nbsp;Raghav Singh,&nbsp;Kumar Hemant Singh,&nbsp;Manoj Kumar Srivastava,&nbsp;Gopal Hema","doi":"10.1007/s11600-025-01529-1","DOIUrl":"10.1007/s11600-025-01529-1","url":null,"abstract":"<div><p>Characterization of CO₂ in subsurface reservoirs is an important aspect of ensuring the effectiveness and safety of storage operations. Seismic inversion technique, widely applied in the petroleum industry for tasks such as quantitative reservoir characterization and improved oil recovery, is now finding potential application in estimating the extension of CO₂ plumes within an underground reservoir. Seismic inversion, coupled with global optimization techniques, offers a powerful approach to enhance reservoir understanding in CCS projects. This paper presents a comprehensive study on the application of a global optimization workflow to increase subsurface resolution in the CO₂ storage. Global optimization techniques including simulated annealing and particle swarm optimization are employed to optimize the subsurface model and estimate the P-wave impedance. We used the Sleipner field in the Norwegian North Sea which is extracting gas with high CO₂ content, and for environmental reasons, they have been injecting more than 11 million tons of CO₂ into the Utsira sand saline aquifer above the hydrocarbon reserves since 1996. To monitor the spread of this CO₂ plume and ensure the safety of the upper layers, a series of seven 3D seismic surveys have been conducted. Our study concentrated on vintage data from 1994 (before CO₂ injection) and 1999 and 2006 (after an 8.4 Mt CO₂ injection). The workflow incorporates prior information from well logs, facilitating faster convergence and detailed subsurface representations. The findings suggest that the application of global optimization techniques is advantageous for optimizing earth’s subsurface models, particularly in the context of CO₂ storage initiatives. Although we faced challenges due to the absence of time-lapse well-log data in the specific area of interest, we successfully applied our inverse workflow to generate acoustic impedance data, to the best of our knowledge. These findings offer valuable insights for enhancing the understanding of CO₂ dispersion within a reservoir.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 3","pages":"2551 - 2568"},"PeriodicalIF":2.3,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-accuracy velocity analysis for multiple AVO seismic data","authors":"Yankai Xu,&nbsp;Jiawei Li,&nbsp;Jiao Qi,&nbsp;Siyuan Cao,&nbsp;Hongwei Liu,&nbsp;Weiling Li,&nbsp;Hongduo Zhu","doi":"10.1007/s11600-024-01524-y","DOIUrl":"10.1007/s11600-024-01524-y","url":null,"abstract":"<div><p>The velocity analysis plays an important role in seismic data processing. Although the existing methods have improved noise resistance and accuracy, they are not well applied to data containing multiple amplitude-variations-with-offset (AVO). To solve the problem, we propose a high-accuracy velocity analysis method with polarity correlation in this paper. Firstly, we use singular values of seismic data to construct the weighting function method, which reduced the influence of noise and improved the accuracy of the velocity spectra. Then, a polarity-related information is proposed with multiple AVO and used in the weighting function. Synthetic and field data results show that the proposed method has higher accuracy with strong noise and multiple AVO.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 3","pages":"2569 - 2579"},"PeriodicalIF":2.3,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Method for revealing the violation of synchronization in the operation of geomagnetic observatories of INTERMAGNET network","authors":"Ivan Veniaminovich Vassilyev,&nbsp;Zhassulan Korabayevich Mendakulov,&nbsp;Inna Nikolaevna Fedulina,&nbsp;Beibit Tenelovich Zhumabayev","doi":"10.1007/s11600-024-01528-8","DOIUrl":"10.1007/s11600-024-01528-8","url":null,"abstract":"<div><p>The integration of magnetic observatories of many countries into the INTERMAGNET network has provided researchers with new opportunities to investigate many geophysical processes. The joint processing of measurement evidence from magnetic observatories located in various geolocations makes it possible to better understand the dynamics of the interaction of solar wind with the Earth’s magnetosphere. For the correct interpretation of the dynamics of physical processes, the accuracy of the time reference of measurement results is of great importance. The measurement results of local observatories were transformed to a unified ecliptic coordinate system oriented toward the Sun in order to extract small variations in the magnetic field occurring before the magnetic storm commencement. Before transforming the coordinates, a constant component equal to the average daily value of the magnetic field components was removed from the results of minute-by-minute measurements. Owing to the averaging evidence from 84 magnetic observatories of the INTERMAGNET network, variations in the magnetic field of cosmic origin preceding the magnetic storm commencement were detected. The correlation analysis of these variations recorded by different observatories revealed the presence of time shifts between the data series of different observatories. Only 62% of the observatories had a relative data shift within the range of ± 1 min. Before the joint data processing in order to efficient use of data recorded with a time shift, a method for correcting time shifts has proposed.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 3","pages":"3045 - 3055"},"PeriodicalIF":2.3,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on the prediction of permeability distribution characteristics of shale reservoirs based on current tectonic stress field: case study of the Feng’gang Shale Gas Block III in the northern Guizhou area, China","authors":"Jintao Zhou,&nbsp;Zhonghu Wu,&nbsp;Yujun Zuo,&nbsp;Wentao Wang","doi":"10.1007/s11600-024-01519-9","DOIUrl":"10.1007/s11600-024-01519-9","url":null,"abstract":"<div><p>Prediction studies of the permeability distributions of shale reservoirs are important for advanced predictions of potential shale gas exploration sites. Therefore, accurate predictions of the permeability distributions in these areas are critical to facilitate the efficient exploration and development of shale gas reservoirs. In this paper, using relevant drilling data, a mathematical relationship was established between geostress and shale reservoir permeability. The study revealed that the shale reservoir permeabilities decrease exponentially as the principal stress increases. By integrating the current tectonic stresses in the northern Guizhou area that were obtained from the anelastic strain recovery method measurements, as well as drilling and seismic data, we have developed a reasonable geomechanical model of the study area. On this basis, we established a 3D mathematical model of the shale reservoir in the Niutitang Formation of the Feng’gang Shale Gas Block III via ABAQUS finite element software. The model simulates current tectonic stress field data and predicts the permeability distribution within a reservoir. As a result, we obtain a reliable model for evaluating the permeabilities of shale reservoirs. The results of the simulation show that the current tectonic stresses are influenced by variations in rock features across fracture zones, fold zones, and normal sedimentary layers. Reservoir permeabilities are affected by the current tectonic stress and complex geological structures. Notably, high permeability values are typically concentrated along fracture zones and at their intersections with sedimentary layers, with the highest values occurring at the endpoints of fracture zones and where two fracture zones meet. Some fold zones exhibit gradual increases in permeability outwards from the damage zone caused by the disruptive effect of the fracture zone.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 3","pages":"2269 - 2286"},"PeriodicalIF":2.3,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of seismic stress changes in the northern part of the Zagros in Iran","authors":"Samira Mousaviyan,&nbsp;Mehrdad Mostafazadeh","doi":"10.1007/s11600-024-01489-y","DOIUrl":"10.1007/s11600-024-01489-y","url":null,"abstract":"<div><p>The Zagros tectonic zone is one of the most active seismic regions in the convergence process of the Arabian and Eurasian plates. In this region, the northern part shows less seismic activity, but it has gained more attention after the Ezgeleh earthquake on November 12, 2017, with <i>M</i>_<i>w</i> = 7.4. In this study, the stress inversion of focal mechanisms has been used to quantitatively and qualitatively analyze the stress. The b-value in the northern part of the Zagros region has been calculated in three morphotectonic units. Moreover, in order to evaluate spatial and magnitude distribution of earthquakes in the Zagros region, we used maximum likelihood method. According to the results of the inversion of 154 focal mechanisms with a moment magnitude equal or greater than 5, the maximum stress axis is generally preserved in the northeast-southwest direction in each of the five subregions. Deviations in stress axis from the convergence axis of the Arabian plate and the Iranian continent were happened. Comparison of the relative stress values before (<i>R</i> = 0.49) and after (<i>R</i> = 0.91) the Ezgeleh earthquake shows that the differential stress (σ₁-σ₃) in zone 2 has reached the maximum value before the main shock. Based on the morphotectonic classification in the Zagros region to Imbricated Zone, Simply Folded Belts, Mountain Front Fault, we calculated the seismic parameter b, equal to (1.06, 1.10, 1.13) in each part, respectively. These results show that the distribution of stress in the entire Zagros area is not uniform, and the level of seismicity varies according to the geological structure of the region. About the stress ratio (R), as can be seen in Tables 3 and 4, in zone 2, the amount of R is very low before the main shock (<i>R</i> = 0.49). However, in complete catalog, this value reached to (<i>R</i> = 0.91). Therefore, the stress ratio (<i>R</i>), can be another factor that shows the full of stressed region. When <i>R</i> value decreased, it means that the differential stress (<i>σ</i>₁-<i>σ</i>₃) increased (Eq. 1) in that region.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 3","pages":"2245 - 2267"},"PeriodicalIF":2.3,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of climate change on land use and relationship with land surface temperature: representative case study in Iraq","authors":"Bassim Mohammed Hashim,&nbsp;Amer Naji Ahmed Alnaemi,&nbsp;Maitham Abdulla Sultan,&nbsp;Esam Abd Alraheem,&nbsp;Suhair Abdulsattar Abduljabbar,&nbsp;Bijay Halder,&nbsp;Shamsuddin Shahid,&nbsp;Zaher Mundher Yaseen","doi":"10.1007/s11600-024-01514-0","DOIUrl":"10.1007/s11600-024-01514-0","url":null,"abstract":"<div><p>Iraq is one of the five countries most affected by high temperatures, low precipitation, drought, and desertification hazards. In this research, Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) images of Basra, southern Iraq, were used from 1986 to 2021. The relationships between Land Surface Temperature (LST), Normalized Difference Vegetation Index, and Normalized Difference Built-up Index were examined to determine the impacts of LST on Land Use/Land Cover (LULC) changes and to estimate future changes under projected temperature and precipitation scenarios for Representative Concentration Pathways (RCP4.5 and RCP8.5) scenarios from 2010 to 2091. The results indicated significant changes in different LULC categories in Basra from 1986 to 2021. Orchards and swampy areas (especially in Hawiza, Msahab, and Salal marshes) decreased by 45%, mostly converting to built-up or barren areas. The sand area increased by 15.6%. The built-up area increased rapidly from 1217 to 1371 km², a 12.7% increase. Most of the built-up and barren areas in the north, center, and south of Basra province recorded LST values less than 50 °C, especially in gas-flaring areas in petroleum locations. The overall accuracy of LULC was 90% in 1986 and 88% in 2021, while the kappa coefficients were 0.797 in 1986 and 0.848 in 2021. Based on RCP4.5 and RCP8.5 scenarios, the values of the temperature increase in both scenarios by 1.7 °C in 2050 and 2.2 °C in 2091 in Basra. Due to Basra's significance to Iraq’s economy, society, and politics, the findings of this study will be helpful to city planners and decision-makers in future development of Basra province.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 3","pages":"3025 - 3043"},"PeriodicalIF":2.3,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}