Pub Date : 2024-11-01DOI: 10.1016/j.jappgeo.2024.105542
Hannah Ritchie , Ian Holman , Justus Nyangoka , Paul Bauman , Alison Parker
Sand dams, composed of recent alluvial aquifers behind concrete dam walls, are a water management technique in drylands. However, their level of hydraulic connectivity with their surrounding weathered basement aquifer is debated. This study aims to constrain this hydrogeological uncertainty in order to better understand their ability to meet water needs and improve dryland water security. The study is the first to use 2D geophysics (Electrical Resistivity Tomography) to provide evidence of seepage from sand dams at three mature and three newly built sites. A generally greater hydraulic connectivity was found between sand dams and their surrounding aquifer than has been assumed in some previous studies, with sites providing at least some local recharge rather than existing as isolated storage structures. This improved understanding is beneficial for both site selection and the performance of sand dams and can help ensure that maximum benefits are derived from the construction of a sand dam depending on its intended purpose.
{"title":"Insights from electrical resistivity tomography on the hydrogeological interaction between sand dams and the weathered basement aquifer","authors":"Hannah Ritchie , Ian Holman , Justus Nyangoka , Paul Bauman , Alison Parker","doi":"10.1016/j.jappgeo.2024.105542","DOIUrl":"10.1016/j.jappgeo.2024.105542","url":null,"abstract":"<div><div>Sand dams, composed of recent alluvial aquifers behind concrete dam walls, are a water management technique in drylands. However, their level of hydraulic connectivity with their surrounding weathered basement aquifer is debated. This study aims to constrain this hydrogeological uncertainty in order to better understand their ability to meet water needs and improve dryland water security. The study is the first to use 2D geophysics (Electrical Resistivity Tomography) to provide evidence of seepage from sand dams at three mature and three newly built sites. A generally greater hydraulic connectivity was found between sand dams and their surrounding aquifer than has been assumed in some previous studies, with sites providing at least some local recharge rather than existing as isolated storage structures. This improved understanding is beneficial for both site selection and the performance of sand dams and can help ensure that maximum benefits are derived from the construction of a sand dam depending on its intended purpose.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105542"},"PeriodicalIF":2.2,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-20DOI: 10.1016/j.jappgeo.2024.105547
G. Pavankumar, Akashdeep Barman, M. Demudu Babu, Raj Sunil Kandregula, N.N. Chakravarthi, Ajay Manglik
The young active Himalayan mountain is characterized by steep slope and dissected topography in overall compressive tectonic setting. The mountain belt has primarily coarse textured soil with poor water holding capacity and is highly prone to erosion. The erosion not only affects many ecosystems located at downstream but also has detrimental effects on the critical zone (CZ). In the present study, we have carried out DC electrical resistivity study in the Pranmati catchment of the Alaknanda basin, a Himalayan critical zone in the Lesser Himalaya, to understand the pattern of soil erosion, transportation and deposition by characterizing the bedrock architecture and hence regolith thickness. A total of 6 electrical resistivity tomogram (ERT) profiles were laid at two locations in the catchment, one in a plain grassland and another at a crop field located on a hill slope of >25o. The study area in the Baijnath klippe, consists of quartz-biotite gneisses with layers of quartz mica-schist enclosed by thrust faults. Electrical resistivity sections of the downslope grassland site show a sharp resistivity contrast between the southwest and northeast transects suggesting south-eastern increase in dip of the bedrock, oblique to the north-east facing surface topography and a thick regolith (> 10 m). The resistivity sections of the site located on the hillslope yield a very thin layer of regolith (< 2 m) indicating significant soil erosion and high weathering of the bedrock. We propose that the water–rock interaction within the porous regolith facilitated by subsurface water circulation might be a potential source for the thick regolith. The observations substantiate existing hypotheses for the evolution and development of deep critical zones. From the results, it has been hypothesized that the bedrock architecture and water channel paths within the CZ together control the regolith thickness.
{"title":"Geophysical characterization of the bedrock and regolith in the Pranmati basin critical zone, Uttarakhand Himalaya","authors":"G. Pavankumar, Akashdeep Barman, M. Demudu Babu, Raj Sunil Kandregula, N.N. Chakravarthi, Ajay Manglik","doi":"10.1016/j.jappgeo.2024.105547","DOIUrl":"10.1016/j.jappgeo.2024.105547","url":null,"abstract":"<div><div>The young active Himalayan mountain is characterized by steep slope and dissected topography in overall compressive tectonic setting. The mountain belt has primarily coarse textured soil with poor water holding capacity and is highly prone to erosion. The erosion not only affects many ecosystems located at downstream but also has detrimental effects on the <em>critical zone (CZ)</em>. In the present study, we have carried out DC electrical resistivity study in the Pranmati catchment of the Alaknanda basin, a Himalayan critical zone in the Lesser Himalaya, to understand the pattern of soil erosion, transportation and deposition by characterizing the bedrock architecture and hence regolith thickness. A total of 6 electrical resistivity tomogram (ERT) profiles were laid at two locations in the catchment, one in a plain grassland and another at a crop field located on a hill slope of >25<sup>o</sup>. The study area in the Baijnath klippe, consists of quartz-biotite gneisses with layers of quartz mica-schist enclosed by thrust faults. Electrical resistivity sections of the downslope grassland site show a sharp resistivity contrast between the southwest and northeast transects suggesting south-eastern increase in dip of the bedrock, oblique to the north-east facing surface topography and a thick regolith (> 10 m). The resistivity sections of the site located on the hillslope yield a very thin layer of regolith (< 2 m) indicating significant soil erosion and high weathering of the bedrock. We propose that the water–rock interaction within the porous regolith facilitated by subsurface water circulation might be a potential source for the thick regolith. The observations substantiate existing hypotheses for the evolution and development of deep critical zones. From the results, it has been hypothesized that the bedrock architecture and water channel paths within the CZ together control the regolith thickness.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105547"},"PeriodicalIF":2.2,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-19DOI: 10.1016/j.jappgeo.2024.105543
Ling Li , Zhizhang Wang , Weifang Wang , Wentian Fan , Zhiheng Zhang
Deep reservoirs associated with gravity-flows are garnering considerable attention. Predicting reservoirs deposited by nearshore subaqueous fans is challenging and often underreported in seismic sedimentology analysis. Utilizing post-stack seismic attributes is a quick and straightforward method for quantitatively characterizing these reservoirs. However, reservoir prediction deteriorates when dealing with complex sedimentary volumes and intricate tectonic development. Spectral decomposition (SD) offers an alternative approach to optimize the seismic data. The frequency-dependent S-transform (ST) holds great potential in seismic interpretation. SD based on the ST was employed in the seismic sedimentary characterization of steep slope complex fan reservoirs. Three fourth-order sequence stratigraphic boundaries and three complex fans were ideally shown on seismic frequency decomposition profiles. A 20 Hz seismic sedimentology analysis frequency was determined by comparing three spectral decomposition results following the well-seismic reflection analysis. The internal architectures of fan deltas and the individual outlines of nearshore subaqueous fans were more distinguishable in 20-Hz frequency decomposition data than in full-frequency data. The progradation direction of steep slope fans can be better recognized in frequency decomposition profiles compared to full-frequency seismic data. Three factors influence the seismic sedimentary characterization and prediction of steep slope fans when employing SD. The ability of the ST to preserve phase is crucial for improving the imaging quality of the amplitude attribute. Sedimentary mechanisms control the sedimentary features of steep slope fans, impacting the imaging of seismic attributes. While channelized fan deltas can be better identified, unchannelized nearshore subaqueous fan deposits, which exhibit more heterogeneous sedimentary characteristics, present limitations. The unique volcanic evolution is another factor that impacts the image of the root-mean-square (RMS) attribute. Despite demonstrating excellent local adaptability in signal analysis, the S-transform cannot fully compensate for the combined effects of faults and sedimentary heterogeneity in nearshore subaqueous fans.
与重力流相关的深层储层正受到广泛关注。预测近岸水下扇沉积的储层具有挑战性，在地震沉积学分析中往往报告不足。利用叠后地震属性是定量描述这些储层特征的快速而直接的方法。然而，在处理复杂的沉积体积和错综复杂的构造发展时，储层预测会恶化。频谱分解（SD）为优化地震数据提供了另一种方法。频率相关的 S 变换（ST）在地震解释中具有巨大潜力。在对陡坡复杂扇形储层进行地震沉积特征描述时，采用了基于 ST 的频谱分解。在地震频率分解剖面上理想地显示了三个四阶层序地层边界和三个复合扇。通过比较井震反射分析后的三个频谱分解结果，确定了 20 赫兹的地震沉积分析频率。与全频数据相比，20 赫兹频率分解数据更能区分扇三角洲的内部结构和近岸水下扇的个体轮廓。与全频地震数据相比，频率分解剖面能更好地识别陡坡扇的渐变方向。使用频率分解数据时，有三个因素会影响陡坡扇的地震沉积特征描述和预测。ST 保留相位的能力对于提高振幅属性的成像质量至关重要。沉积机制控制着陡坡扇的沉积特征，影响着地震属性的成像。渠道化的扇形三角洲可以更好地识别，而非渠道化的近岸水下扇形沉积则表现出更多的异质沉积特征，因此存在局限性。独特的火山演化是影响均方根（RMS）属性图像的另一个因素。尽管 S 变换在信号分析中表现出出色的局部适应性，但它无法完全补偿近岸水下扇形沉积中断层和沉积异质性的综合影响。
{"title":"Spectral decomposition predicts the distribution of steep slope fans in the rift basin of eastern China","authors":"Ling Li , Zhizhang Wang , Weifang Wang , Wentian Fan , Zhiheng Zhang","doi":"10.1016/j.jappgeo.2024.105543","DOIUrl":"10.1016/j.jappgeo.2024.105543","url":null,"abstract":"<div><div>Deep reservoirs associated with gravity-flows are garnering considerable attention. Predicting reservoirs deposited by nearshore subaqueous fans is challenging and often underreported in seismic sedimentology analysis. Utilizing post-stack seismic attributes is a quick and straightforward method for quantitatively characterizing these reservoirs. However, reservoir prediction deteriorates when dealing with complex sedimentary volumes and intricate tectonic development. Spectral decomposition (SD) offers an alternative approach to optimize the seismic data. The frequency-dependent S-transform (ST) holds great potential in seismic interpretation. SD based on the ST was employed in the seismic sedimentary characterization of steep slope complex fan reservoirs. Three fourth-order sequence stratigraphic boundaries and three complex fans were ideally shown on seismic frequency decomposition profiles. A 20 Hz seismic sedimentology analysis frequency was determined by comparing three spectral decomposition results following the well-seismic reflection analysis. The internal architectures of fan deltas and the individual outlines of nearshore subaqueous fans were more distinguishable in 20-Hz frequency decomposition data than in full-frequency data. The progradation direction of steep slope fans can be better recognized in frequency decomposition profiles compared to full-frequency seismic data. Three factors influence the seismic sedimentary characterization and prediction of steep slope fans when employing SD. The ability of the ST to preserve phase is crucial for improving the imaging quality of the amplitude attribute. Sedimentary mechanisms control the sedimentary features of steep slope fans, impacting the imaging of seismic attributes. While channelized fan deltas can be better identified, unchannelized nearshore subaqueous fan deposits, which exhibit more heterogeneous sedimentary characteristics, present limitations. The unique volcanic evolution is another factor that impacts the image of the root-mean-square (RMS) attribute. Despite demonstrating excellent local adaptability in signal analysis, the S-transform cannot fully compensate for the combined effects of faults and sedimentary heterogeneity in nearshore subaqueous fans.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105543"},"PeriodicalIF":2.2,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-18DOI: 10.1016/j.jappgeo.2024.105545
Zhenjiao Jiang , Jinxin Wang , Xuanyi Chen
Identification of 3D realistic aquifer structures is essential for predicting physicochemical processes in groundwater systems. However, the characterization of highly heterogeneous aquifers remains challenging because it relies on the effective fusion of multiple geophysical data sources having wide areal coverage, as well as downhole geophysical data featuring high resolution. This study establishes a novel 3D convolutional neural network model to generate aquifer structure from 3D seismic data, constrained by sparse downhole sonic and lithology logs. In the model, the data fusion procedure is designed to follow the logics of conventional manual interpretation of multiple geophysical data, and to address the 3D spatial relationships between geophysical data and lithology. The method is implemented in a typical fluvial aquifer featuring coarse paleovalley sediments (sandstone) embedded in the tight surrounding rocks (claystone), in order to identify channelized sandstone from low-permeability claystone. It is confirmed that the proposed model reliably generates 3D aquifer structures based on seismic amplitudes, downhole sonic and lithology logs. The method is compared to traditional machine learning models that focus on 1D conversion from geophysical attributes to lithology. The results show that the newly-developed model performs more robustly and accurately because the use of 3D convolution allows considering the relationships between seismic amplitude, sonic velocity and lithology in both vertical and horizontal directions. Moreover, the inclusion of sonic logs constraint in the model, following the logics of manual seismic data interpretation, significantly improves the model accuracy. The method can find broad applications for the characterization of subsurface heterogeneity even featuring non-gaussian permeability distribution like the demonstrated fluvial aquifer.
{"title":"An interpretation-based convolution neural network framework for geophysical data fusion and aquifer structure identification","authors":"Zhenjiao Jiang , Jinxin Wang , Xuanyi Chen","doi":"10.1016/j.jappgeo.2024.105545","DOIUrl":"10.1016/j.jappgeo.2024.105545","url":null,"abstract":"<div><div>Identification of 3D realistic aquifer structures is essential for predicting physicochemical processes in groundwater systems. However, the characterization of highly heterogeneous aquifers remains challenging because it relies on the effective fusion of multiple geophysical data sources having wide areal coverage, as well as downhole geophysical data featuring high resolution. This study establishes a novel 3D convolutional neural network model to generate aquifer structure from 3D seismic data, constrained by sparse downhole sonic and lithology logs. In the model, the data fusion procedure is designed to follow the logics of conventional manual interpretation of multiple geophysical data, and to address the 3D spatial relationships between geophysical data and lithology. The method is implemented in a typical fluvial aquifer featuring coarse paleovalley sediments (sandstone) embedded in the tight surrounding rocks (claystone), in order to identify channelized sandstone from low-permeability claystone. It is confirmed that the proposed model reliably generates 3D aquifer structures based on seismic amplitudes, downhole sonic and lithology logs. The method is compared to traditional machine learning models that focus on 1D conversion from geophysical attributes to lithology. The results show that the newly-developed model performs more robustly and accurately because the use of 3D convolution allows considering the relationships between seismic amplitude, sonic velocity and lithology in both vertical and horizontal directions. Moreover, the inclusion of sonic logs constraint in the model, following the logics of manual seismic data interpretation, significantly improves the model accuracy. The method can find broad applications for the characterization of subsurface heterogeneity even featuring non-gaussian permeability distribution like the demonstrated fluvial aquifer.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105545"},"PeriodicalIF":2.2,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The propagation of seismic waves within the near-surface weathering layers, characterized by their low-quality factors (Q), is often accompanied by strong attenuation and dispersion phenomena. Among these, the Rayleigh wave, with its sensitivity to dispersion, has proven to be a powerful tool for near-surface exploration. We propose a novel approach for simulating Rayleigh wave propagation in such low-Q media. Our method uses the time-domain fractional wave equation with memory effect, based on Kjartansson's constant-Q (CQ) model, for accurate characterization of the propagation process. To solve numerically the wave equation with the fractional derivatives, we employ a finite-difference method combined with the auxiliary differential equation-perfectly matched layer (ADE-PML) and the acoustic-elastic boundary approach (AEA). The algorithm's high computational accuracy is verified through comparison with the conventional integer-order wave equation based on the nearly constant-Q (NCQ) models in strong attenuation media. The research in this paper deepens our understanding of the propagation characteristics of Rayleigh waves in strongly weathering layers. This new method strongly supports those seismic imaging and inversion methods depending on seismic modeling, including the reverse time migration and the full waveform inversion of the internal structure of low-Q media.
{"title":"Modeling Rayleigh wave in viscoelastic media with constant Q model using fractional time derivatives","authors":"Jianyu Fan, Peimin Zhu, Wei Cai, Zhiwei Xu, Yuefeng Yuan","doi":"10.1016/j.jappgeo.2024.105544","DOIUrl":"10.1016/j.jappgeo.2024.105544","url":null,"abstract":"<div><div>The propagation of seismic waves within the near-surface weathering layers, characterized by their low-quality factors (<em>Q</em>), is often accompanied by strong attenuation and dispersion phenomena. Among these, the Rayleigh wave, with its sensitivity to dispersion, has proven to be a powerful tool for near-surface exploration. We propose a novel approach for simulating Rayleigh wave propagation in such low-<em>Q</em> media. Our method uses the time-domain fractional wave equation with memory effect, based on Kjartansson's constant-<em>Q</em> (CQ) model, for accurate characterization of the propagation process. To solve numerically the wave equation with the fractional derivatives, we employ a finite-difference method combined with the auxiliary differential equation-perfectly matched layer (ADE-PML) and the acoustic-elastic boundary approach (AEA). The algorithm's high computational accuracy is verified through comparison with the conventional integer-order wave equation based on the nearly constant-<em>Q</em> (NCQ) models in strong attenuation media. The research in this paper deepens our understanding of the propagation characteristics of Rayleigh waves in strongly weathering layers. This new method strongly supports those seismic imaging and inversion methods depending on seismic modeling, including the reverse time migration and the full waveform inversion of the internal structure of low-<em>Q</em> media.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105544"},"PeriodicalIF":2.2,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sandstones are the most common reservoir rocks, providing reservoirs for oil and gas and serving as reservoirs for groundwater. The Gulf of Mexico is known for its sand-shale mixtures and potential for its oil and hydrate gas resources in sandstone units. Understanding these variations is essential for assessing hydrocarbon potential and unconventional prospectivity. In this study, we utilized the Elastic, Electrical, and Radioactive (EER) properties of rocks for lithological categorization of well logging data, leading to the development of a novel rock physics template. The electrical and radioactive properties of the rocks facilitated a broad lithological classification, while their elastic characteristics helped distinguish between porous and low-porosity zones. Electrical and radioactive properties are utilized for well data classification because in sandstone formations, there is a decrease in log gamma and an increase in log resistivity. As a result, these opposing shifts in the two geophysical logs enhance the spread of data points on the lithological resistivity-gamma ray scatter plot, thereby simplifying the process of lithological categorization. Ultimately, the well logging data was sorted into three distinct categories: low shale sands (shale volume < 30 %), sand-shale mixtures (shale volume = 30 to 80 %), and shale-dominated areas. Subsequently, the Thomas Stieber model was employed to identify the types of clay minerals present in both sandstones and sand-shale mixtures. The model's findings revealed that dispersed type clay minerals are predominantly found in sandstones, with laminar and structured types being relatively rare. However, in sand-shale mixtures, both dispersed and laminar clays observed.
{"title":"Practical approach for sand-shale mixtures classification based on rocks multi-physical properties","authors":"Saeed Aftab, Rasoul Hamidzadeh Moghadam, Navid Shad Manaman","doi":"10.1016/j.jappgeo.2024.105546","DOIUrl":"10.1016/j.jappgeo.2024.105546","url":null,"abstract":"<div><div>Sandstones are the most common reservoir rocks, providing reservoirs for oil and gas and serving as reservoirs for groundwater. The Gulf of Mexico is known for its sand-shale mixtures and potential for its oil and hydrate gas resources in sandstone units. Understanding these variations is essential for assessing hydrocarbon potential and unconventional prospectivity. In this study, we utilized the Elastic, Electrical, and Radioactive (EER) properties of rocks for lithological categorization of well logging data, leading to the development of a novel rock physics template. The electrical and radioactive properties of the rocks facilitated a broad lithological classification, while their elastic characteristics helped distinguish between porous and low-porosity zones. Electrical and radioactive properties are utilized for well data classification because in sandstone formations, there is a decrease in log gamma and an increase in log resistivity. As a result, these opposing shifts in the two geophysical logs enhance the spread of data points on the lithological resistivity-gamma ray scatter plot, thereby simplifying the process of lithological categorization. Ultimately, the well logging data was sorted into three distinct categories: low shale sands (shale volume < 30 %), sand-shale mixtures (shale volume = 30 to 80 %), and shale-dominated areas. Subsequently, the Thomas Stieber model was employed to identify the types of clay minerals present in both sandstones and sand-shale mixtures. The model's findings revealed that dispersed type clay minerals are predominantly found in sandstones, with laminar and structured types being relatively rare. However, in sand-shale mixtures, both dispersed and laminar clays observed.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105546"},"PeriodicalIF":2.2,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-17DOI: 10.1016/j.jappgeo.2024.105538
Tuanfu Gui , Juzhi Deng , Guang Li , Hui Chen , Hui Yu , Min Feng
The magnetotelluric (MT) sounding is a common geophysical exploration technique, but it is highly polluted by various types of cultural noise. In the realm of MT data processing, traditional techniques often rely on the quality of the measured MT data. Conventional MT time domain denoising methods tend to eliminate valuable signals, potentially leading to unreliable resistivity estimates. To address this concern, we propose employing machine learning to effectively suppress strong noise interference in MT data, thereby preventing the loss of valuable signals. We augment this approach with mathematical morphological filtering (MMF) to capture low-frequency signals, preserving their integrity. We constructed a signal sample library based on a substantial volume of signal samples. Through consistent training, we establish a support vector machine (SVM) classification model that distinguishes high-quality signal fragments from noisy signals. Subsequently, we use adaptive K-singular value decomposition (K-SVD) dictionary learning to extract noise profiles and suppress noisy signals. To validate the feasibility of our method, we apply machine learning to measured data from two distinct observation areas. The measured data were analyzed and processed, and the results were compared with the robust results. This method can effectively eliminate large-scale strong interference in time domain sequences and preserve more low-frequency slow change information and high-quality signals in the reconstructed signals. The apparent resistivity phase curve of synthetic data is smoother and more continuous, and the data quality in the low-frequency range is significantly improved. The results can more accurately and reliably reflect underground electrical structure information.
{"title":"De-noising magnetotelluric data based on machine learning","authors":"Tuanfu Gui , Juzhi Deng , Guang Li , Hui Chen , Hui Yu , Min Feng","doi":"10.1016/j.jappgeo.2024.105538","DOIUrl":"10.1016/j.jappgeo.2024.105538","url":null,"abstract":"<div><div>The magnetotelluric (MT) sounding is a common geophysical exploration technique, but it is highly polluted by various types of cultural noise. In the realm of MT data processing, traditional techniques often rely on the quality of the measured MT data. Conventional MT time domain denoising methods tend to eliminate valuable signals, potentially leading to unreliable resistivity estimates. To address this concern, we propose employing machine learning to effectively suppress strong noise interference in MT data, thereby preventing the loss of valuable signals. We augment this approach with mathematical morphological filtering (MMF) to capture low-frequency signals, preserving their integrity. We constructed a signal sample library based on a substantial volume of signal samples. Through consistent training, we establish a support vector machine (SVM) classification model that distinguishes high-quality signal fragments from noisy signals. Subsequently, we use adaptive K-singular value decomposition (K-SVD) dictionary learning to extract noise profiles and suppress noisy signals. To validate the feasibility of our method, we apply machine learning to measured data from two distinct observation areas. The measured data were analyzed and processed, and the results were compared with the robust results. This method can effectively eliminate large-scale strong interference in time domain sequences and preserve more low-frequency slow change information and high-quality signals in the reconstructed signals. The apparent resistivity phase curve of synthetic data is smoother and more continuous, and the data quality in the low-frequency range is significantly improved. The results can more accurately and reliably reflect underground electrical structure information.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105538"},"PeriodicalIF":2.2,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The migration of free-surface related multiples can enhance subsurface illumination and improve overall imaging quality. However, this process encounters two main challenges: crosstalk artefacts resulting from the cross-correlation of non-reflection-related wavefields, and the increased computational burden of imaging different orders of multiples. We propose a novel method that simultaneously and efficiently migrates both primary and multiple reflections while mitigating crosstalk artefacts. The method employs a reformulated two-way wave-equation depth extrapolation scheme that simplifies up/down wavefield separation through straightforward summation and subtraction operations at each depth step. Two innovative algorithms are integrated into this scheme: a generalized up/down separation algorithm, and a simultaneous migration algorithm of primary and free-surface-related multiples. The up/down separation algorithm efficiently separates the up- and down-going wavefields into primary wavefield and multiple reflections of various orders at the measurement surface. The simultaneous migration algorithm then pairs these components as two-way quantities, allowing for efficient depth extrapolation using a unified propagator, followed by effective decomposition into corresponding one-way components for imaging. Numerical experiments conducted on synthetic models, including a two-dimensional two-layer model and the Sigsbee 2B model, as well as on real seismic data from a gas hydrates bearing zone, demonstrate that the proposed method simultaneously migrate both primary and multiple reflections with reduced crosstalk artefacts and limited computational overhead.
{"title":"Efficient simultaneous migration of primary and free-surface related multiples using reformulated two-way wave-equation depth extrapolation scheme","authors":"Zhongkui Dai, Jiachun You, Wei Liu, Naide Pan, Jianlong Yuan","doi":"10.1016/j.jappgeo.2024.105541","DOIUrl":"10.1016/j.jappgeo.2024.105541","url":null,"abstract":"<div><div>The migration of free-surface related multiples can enhance subsurface illumination and improve overall imaging quality. However, this process encounters two main challenges: crosstalk artefacts resulting from the cross-correlation of non-reflection-related wavefields, and the increased computational burden of imaging different orders of multiples. We propose a novel method that simultaneously and efficiently migrates both primary and multiple reflections while mitigating crosstalk artefacts. The method employs a reformulated two-way wave-equation depth extrapolation scheme that simplifies up/down wavefield separation through straightforward summation and subtraction operations at each depth step. Two innovative algorithms are integrated into this scheme: a generalized up/down separation algorithm, and a simultaneous migration algorithm of primary and free-surface-related multiples. The up/down separation algorithm efficiently separates the up- and down-going wavefields into primary wavefield and multiple reflections of various orders at the measurement surface. The simultaneous migration algorithm then pairs these components as two-way quantities, allowing for efficient depth extrapolation using a unified propagator, followed by effective decomposition into corresponding one-way components for imaging. Numerical experiments conducted on synthetic models, including a two-dimensional two-layer model and the Sigsbee 2B model, as well as on real seismic data from a gas hydrates bearing zone, demonstrate that the proposed method simultaneously migrate both primary and multiple reflections with reduced crosstalk artefacts and limited computational overhead.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105541"},"PeriodicalIF":2.2,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-13DOI: 10.1016/j.jappgeo.2024.105537
L. De Giorgi , G. Leucci , M. Lazzari
Controlled forensic geophysical research involving GPR has proven to be a valuable resource, and the information gathered from these studies has been applied to forensic casework. The probability of detecting a grave for a longer postmortem interval differs with the soil type and the materials added to the grave with the body. In the studied case a detailed GPR survey was conducted in the Basilica della Trinità at Venosa a village located about 40 km north from Potenza (Basilicata, Italy).
Unfortunately during the restoration works of the Basilica, there was a cement spill inside a sarcophagus containing human remains. The necessity to perform the genetic analysis of medieval human remains to reconstruct the distribution of the original line of descent of the Norman noble families aimed the need to understand whether or not there was a body inside the sarcophagus and, if so, its exact position.
The radar profiles from this survey showed the clear amplitude contrast anomalies, emanated from the corpses. The strongest amplitude contrasts are observed at around 0.2–0.5 m depth which is consistent with the depth of the buried corp.
{"title":"Searching medieval human remains using ground penetrating radar: A case study in Venosa (Basilicata, Southern Italy)","authors":"L. De Giorgi , G. Leucci , M. Lazzari","doi":"10.1016/j.jappgeo.2024.105537","DOIUrl":"10.1016/j.jappgeo.2024.105537","url":null,"abstract":"<div><div>Controlled forensic geophysical research involving GPR has proven to be a valuable resource, and the information gathered from these studies has been applied to forensic casework. The probability of detecting a grave for a longer postmortem interval differs with the soil type and the materials added to the grave with the body. In the studied case a detailed GPR survey was conducted in the Basilica della Trinità at Venosa a village located about 40 km north from Potenza (Basilicata, Italy).</div><div>Unfortunately during the restoration works of the Basilica, there was a cement spill inside a sarcophagus containing human remains. The necessity to perform the genetic analysis of medieval human remains to reconstruct the distribution of the original line of descent of the Norman noble families aimed the need to understand whether or not there was a body inside the sarcophagus and, if so, its exact position.</div><div>The radar profiles from this survey showed the clear amplitude contrast anomalies, emanated from the corpses. The strongest amplitude contrasts are observed at around 0.2–0.5 m depth which is consistent with the depth of the buried corp.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105537"},"PeriodicalIF":2.2,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-13DOI: 10.1016/j.jappgeo.2024.105539
Jun Wang, Shuai Wang, BaoDi Liu
Suppressing random noise is critical for revealing real subsurface structures. Convolutional neural networks (CNNs), the leading seismic data denoising methods, excel at extracting local features but struggle to capture global representations. Unet can extract and reuse multi-scale features, aiding in the precise detection of details and semantic information; however, being based on convolutional operations, it struggles to capture global information. To capture global representations, researchers normally employ Transformers in high-level visual tasks, owing to their self-attention mechanisms. This paper introduces a method for mining multi-scale local and global information based on hybrid-gated Unet (HGUnet), which integrates Transformer, CNN, and Unet architectures to enhance the feature representation capability for seismic random noise suppression tasks. HGUnet comprises hybrid-gated blocks (HGB) embedded within a U-shaped architecture, employing a concurrent structure of Octave convolution and lightweight multi-head self-attention mechanism to efficiently extract multi-scale local and global features simultaneously. Moreover, at the conclusion of the HGB, to precisely leverage information and reduce computing costs, a gated feedforward network is designed to retain valuable information and prune redundancies for feature fusion. Synthetic and field experimental results demonstrate that HGUnet improves denoising quality over traditional and CNN methods without adding significant computing costs.
{"title":"Seismic random noise suppression via mining multi-scale local and global information","authors":"Jun Wang, Shuai Wang, BaoDi Liu","doi":"10.1016/j.jappgeo.2024.105539","DOIUrl":"10.1016/j.jappgeo.2024.105539","url":null,"abstract":"<div><div>Suppressing random noise is critical for revealing real subsurface structures. Convolutional neural networks (CNNs), the leading seismic data denoising methods, excel at extracting local features but struggle to capture global representations. Unet can extract and reuse multi-scale features, aiding in the precise detection of details and semantic information; however, being based on convolutional operations, it struggles to capture global information. To capture global representations, researchers normally employ Transformers in high-level visual tasks, owing to their self-attention mechanisms. This paper introduces a method for mining multi-scale local and global information based on hybrid-gated Unet (HGUnet), which integrates Transformer, CNN, and Unet architectures to enhance the feature representation capability for seismic random noise suppression tasks. HGUnet comprises hybrid-gated blocks (HGB) embedded within a U-shaped architecture, employing a concurrent structure of Octave convolution and lightweight multi-head self-attention mechanism to efficiently extract multi-scale local and global features simultaneously. Moreover, at the conclusion of the HGB, to precisely leverage information and reduce computing costs, a gated feedforward network is designed to retain valuable information and prune redundancies for feature fusion. Synthetic and field experimental results demonstrate that HGUnet improves denoising quality over traditional and CNN methods without adding significant computing costs.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105539"},"PeriodicalIF":2.2,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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