Pub Date : 2025-02-28DOI: 10.1016/j.jappgeo.2025.105673
Xiaofang Liao , Junxing Cao , Feng Tan , Jachun You
Seismic horizon picking is a critical step in seismic interpretation and is often labor-intensive and time-consuming, particularly in three-dimensional (3D) volume interpretation. We formulated the task of automatically selecting horizon surfaces from 3D seismic data as a 3D seismic image segmentation problem and developed a method based on a volumetric transformer network. The network uses 3D seismic subvolumes as inputs and outputs the probabilities of several horizon classes. Horizon surfaces can be extracted using postprocessing segmentation probabilities. Because the full annotation of a 3D subvolume is tedious and time-consuming, we utilize a masked loss strategy that allows us to label a few two-dimensional (2D) slices per training subvolume such that the network can learn from partially labeled subvolumes and create dense volumetric segmentation. We also used data augmentation and transfer learning to improve the prediction accuracy with the limited availability of training data. For two public 3D seismic datasets, the proposed method yielded accurate results for 3D horizon picking, and the use of transfer learning improved the accuracy of the results.
{"title":"Automatic 3D horizon picking using a volumetric transformer-based segmentation network","authors":"Xiaofang Liao , Junxing Cao , Feng Tan , Jachun You","doi":"10.1016/j.jappgeo.2025.105673","DOIUrl":"10.1016/j.jappgeo.2025.105673","url":null,"abstract":"<div><div>Seismic horizon picking is a critical step in seismic interpretation and is often labor-intensive and time-consuming, particularly in three-dimensional (3D) volume interpretation. We formulated the task of automatically selecting horizon surfaces from 3D seismic data as a 3D seismic image segmentation problem and developed a method based on a volumetric transformer network. The network uses 3D seismic subvolumes as inputs and outputs the probabilities of several horizon classes. Horizon surfaces can be extracted using postprocessing segmentation probabilities. Because the full annotation of a 3D subvolume is tedious and time-consuming, we utilize a masked loss strategy that allows us to label a few two-dimensional (2D) slices per training subvolume such that the network can learn from partially labeled subvolumes and create dense volumetric segmentation. We also used data augmentation and transfer learning to improve the prediction accuracy with the limited availability of training data. For two public 3D seismic datasets, the proposed method yielded accurate results for 3D horizon picking, and the use of transfer learning improved the accuracy of the results.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"236 ","pages":"Article 105673"},"PeriodicalIF":2.2,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562111","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 : 2025-02-27DOI: 10.1016/j.jappgeo.2025.105681
Hao Zhang , Xulong Cai , Peng Ni , Bowen Qin , Yuquan Ni , Zhiqiang Huang , Fubin Xin
The coalbed methane content (CBM) is a key parameter for the evaluation and efficient exploration and development of coalbed methane reservoirs. The traditional gas content experiment methods are time-consuming, costly, weak in generalization ability and large in calculation error. Therefore, accurate, efficient and low-cost calculation of CBM content is of great significance in CBM development. In this paper, the coalbed methane prediction model is constructed by exploring the hidden geological information between coalbed methane content and logging parameters. Firstly, principal component analysis and person method are used to analyze the correlation between each logging parameter, and then compound parameters are constructed to improve the correlation between each parameter. Finally, BP neural network model is used to build a CBM content prediction model based on compound logging parameters. On this basis, the prediction results of BP neural network model are compared with KNN, Ridge regression, random forest, XGBoost and other machine learning models, and the determination coefficient, root-mean-square error and relative error are used to evaluate the model. The results show that BP neural network is more suitable for constructing CBM prediction model with complex logging parameters, and the prediction effect is good, the relative error is 4.5 %, and the prediction accuracy is improved by about 61 % compared with other models. This model has potential application in the field CBM reservoir development, can predict the gas content of coal seam quickly and accurately, speed up the CBM reservoir development process, and provide a new method for coal seam exploration and reservoir logging evaluation.
{"title":"Prediction of coalbed methane content based on composite logging parameters and PCA-BP neural network","authors":"Hao Zhang , Xulong Cai , Peng Ni , Bowen Qin , Yuquan Ni , Zhiqiang Huang , Fubin Xin","doi":"10.1016/j.jappgeo.2025.105681","DOIUrl":"10.1016/j.jappgeo.2025.105681","url":null,"abstract":"<div><div>The coalbed methane content (CBM) is a key parameter for the evaluation and efficient exploration and development of coalbed methane reservoirs. The traditional gas content experiment methods are time-consuming, costly, weak in generalization ability and large in calculation error. Therefore, accurate, efficient and low-cost calculation of CBM content is of great significance in CBM development. In this paper, the coalbed methane prediction model is constructed by exploring the hidden geological information between coalbed methane content and logging parameters. Firstly, principal component analysis and person method are used to analyze the correlation between each logging parameter, and then compound parameters are constructed to improve the correlation between each parameter. Finally, BP neural network model is used to build a CBM content prediction model based on compound logging parameters. On this basis, the prediction results of BP neural network model are compared with KNN, Ridge regression, random forest, XGBoost and other machine learning models, and the determination coefficient, root-mean-square error and relative error are used to evaluate the model. The results show that BP neural network is more suitable for constructing CBM prediction model with complex logging parameters, and the prediction effect is good, the relative error is 4.5 %, and the prediction accuracy is improved by about 61 % compared with other models. This model has potential application in the field CBM reservoir development, can predict the gas content of coal seam quickly and accurately, speed up the CBM reservoir development process, and provide a new method for coal seam exploration and reservoir logging evaluation.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"236 ","pages":"Article 105681"},"PeriodicalIF":2.2,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552613","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 : 2025-02-27DOI: 10.1016/j.jappgeo.2025.105683
Xingli Zhang, Qian Mao, Ruiyao Yu, Ruisheng Jia
Rock burst disasters in coal mines have become a growing concern, posing significant risks to operational safety. Utilizing historical microseismic data to predict future microseismic events can provide effective prediction and early warning for rock bursts. This study proposes a multivariate microseismic sensitive features prediction network model named Deformer, which can accurately predict multiple sensitive feature values extracted from microseismic monitoring data and provide data support for the early warning and prevention of rock bursts. Deformer integrates Transformer and signal decomposition methods, considering both feature and temporal correlations. It enables a comprehensive and in-depth analysis of the relationships among multi-dimensional sensitive features and the temporal evolution of each feature. We extract three characteristic values from the microseismic monitoring data of a coal mine in Shandong Province: daily total energy, daily maximum energy, and daily average energy, and predict the daily maximum energy. By comparing with various classical time series prediction models, Deformer achieved the best results in mean square error (MSE), mean absolute error (MAE), the coefficient of determination (R2), root mean square error (RMSE), and Theil's inequality coefficient (TIC), proving Deformer's significant advantage in predicting microseismic sensitive features. Additionally, testing on various public datasets, such as those for electricity and weather, further validates the model's generalization capability.
{"title":"A multivariate time series prediction model for microseismic characteristic data in coal mines","authors":"Xingli Zhang, Qian Mao, Ruiyao Yu, Ruisheng Jia","doi":"10.1016/j.jappgeo.2025.105683","DOIUrl":"10.1016/j.jappgeo.2025.105683","url":null,"abstract":"<div><div>Rock burst disasters in coal mines have become a growing concern, posing significant risks to operational safety. Utilizing historical microseismic data to predict future microseismic events can provide effective prediction and early warning for rock bursts. This study proposes a multivariate microseismic sensitive features prediction network model named Deformer, which can accurately predict multiple sensitive feature values extracted from microseismic monitoring data and provide data support for the early warning and prevention of rock bursts. Deformer integrates Transformer and signal decomposition methods, considering both feature and temporal correlations. It enables a comprehensive and in-depth analysis of the relationships among multi-dimensional sensitive features and the temporal evolution of each feature. We extract three characteristic values from the microseismic monitoring data of a coal mine in Shandong Province: daily total energy, daily maximum energy, and daily average energy, and predict the daily maximum energy. By comparing with various classical time series prediction models, Deformer achieved the best results in mean square error (MSE), mean absolute error (MAE), the coefficient of determination (R<sup>2</sup>), root mean square error (RMSE), and Theil's inequality coefficient (TIC), proving Deformer's significant advantage in predicting microseismic sensitive features. Additionally, testing on various public datasets, such as those for electricity and weather, further validates the model's generalization capability.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"236 ","pages":"Article 105683"},"PeriodicalIF":2.2,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534215","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 : 2025-02-25DOI: 10.1016/j.jappgeo.2025.105669
Peiran Duan , Yan Huang , Fei Li , Juan Chen , Yulong Ma , Bingluo Gu
The Ordos Basin, known as ‘China's Golden Triangle of Energy’, is the second-largest sedimentary basin in China and is abundant in oil and gas resources. Due to the presence of a thick loess and the high costs associated with high-density data acquisition, merging existing 3D seismic data is the most efficient approach for exploring its expansive areas. The current research focus on the largest 3D merged seismic data set, covering 3100 km2 in the southwestern part of the Ordos Basin. This area was divided into three blocks, each processed independently at different periods and merged using post-stack merge processing. However, a significant issue with this approach is the discrepancy in the closure observed at the boundaries of seismic profiles, which reduces the reliability of imaging complex structures near the edges. To address this issue, our study proposes a mega-merge processing (MMP) for the Ordos Basin. This MMP aims to resolve the imaging inaccuracies around profile edges and deliver high-quality, consistent pre-stack 3D imaging results, facilitating subsequent tectonic interpretations and reservoir predictions. The MMP methodology comprises four key technologies: (a) first arrival tomographic inversion constrained by micro-logging for static correction; (b) a novel pre-stack fidelity denoising technology according to different noise types for abnormal energy interference and other noise; (c) a broadband consistency processing flow, incorporating wavelet consistency with sonic logs, amplitude consistency, and broadband processing, enhanced by near-surface Q-compensation and a surface-consistent deconvolution technique; and (d) effective Q-value modelling and the pre-stack time migration (PSTM) is adapted in the OVT domain. The effectiveness of our MMP approach is validated using large-scale 3D seismic data from a loess plateau area in the southwest Ordos Basin. The results demonstrate that the MMP successfully eliminates time and energy discrepancies present in the original seismic data, which were due to varying acquisition parameter influenced by differences in source and receiver conditions. Additionally, it resolves issues related to uneven spatial sampling, refines Q-field modelling precision, and reduces matching errors between seismic and sonic logs, thereby enhancing the resolution and accuracy of seismic imaging. Consequently, this improvement facilitates a more precise delineation of fault system and deepens the understanding of the paleo-topographic characteristics of the Chang 7 in the Mesozoic era.
{"title":"Mega-merge processing with attenuation compensation from 3D pre-stack seismic data: A case study from A loess plateau area, southwest of Ordos Basin, China","authors":"Peiran Duan , Yan Huang , Fei Li , Juan Chen , Yulong Ma , Bingluo Gu","doi":"10.1016/j.jappgeo.2025.105669","DOIUrl":"10.1016/j.jappgeo.2025.105669","url":null,"abstract":"<div><div>The Ordos Basin, known as ‘China's Golden Triangle of Energy’, is the second-largest sedimentary basin in China and is abundant in oil and gas resources. Due to the presence of a thick loess and the high costs associated with high-density data acquisition, merging existing 3D seismic data is the most efficient approach for exploring its expansive areas. The current research focus on the largest 3D merged seismic data set, covering 3100 km<sup>2</sup> in the southwestern part of the Ordos Basin. This area was divided into three blocks, each processed independently at different periods and merged using post-stack merge processing. However, a significant issue with this approach is the discrepancy in the closure observed at the boundaries of seismic profiles, which reduces the reliability of imaging complex structures near the edges. To address this issue, our study proposes a mega-merge processing (MMP) for the Ordos Basin. This MMP aims to resolve the imaging inaccuracies around profile edges and deliver high-quality, consistent pre-stack 3D imaging results, facilitating subsequent tectonic interpretations and reservoir predictions. The MMP methodology comprises four key technologies: (a) first arrival tomographic inversion constrained by micro-logging for static correction; (b) a novel pre-stack fidelity denoising technology according to different noise types for abnormal energy interference and other noise; (c) a broadband consistency processing flow, incorporating wavelet consistency with sonic logs, amplitude consistency, and broadband processing, enhanced by near-surface <em>Q</em>-compensation and a surface-consistent deconvolution technique; and (d) effective <em>Q</em>-value modelling and the pre-stack time migration (PSTM) is adapted in the OVT domain. The effectiveness of our MMP approach is validated using large-scale 3D seismic data from a loess plateau area in the southwest Ordos Basin. The results demonstrate that the MMP successfully eliminates time and energy discrepancies present in the original seismic data, which were due to varying acquisition parameter influenced by differences in source and receiver conditions. Additionally, it resolves issues related to uneven spatial sampling, refines <em>Q</em>-field modelling precision, and reduces matching errors between seismic and sonic logs, thereby enhancing the resolution and accuracy of seismic imaging. Consequently, this improvement facilitates a more precise delineation of fault system and deepens the understanding of the paleo-topographic characteristics of the Chang 7 in the Mesozoic era.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"236 ","pages":"Article 105669"},"PeriodicalIF":2.2,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143488338","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 : 2025-02-23DOI: 10.1016/j.jappgeo.2025.105670
Mansoure Montahaei, Elham Zare
Great Kavir, located in the northern part of the Central Iran depression, is the largest salt desert in Iran with groups of clustered salt diapirs in its northwestern part. The Nasr-Abad salt diapir in the Shurab diapiric group is the largest buried salt diapir in this region, whose geometry at depth and surrounding structure are rarely known. In this study, we investigate a broadband magnetotelluric (MT) dataset recorded at 37 stations distributed along a 14 km, SW-NE profile to characterize the geometry, substratum, and overburden of the Nasr-Abad salt diapir. The spatially distributed MT responses obtained in this study are associated with geological structures at depths of less than 25 km. The measurements were used to generate a crustal-scale resistivity model of the study area, which correlates well with the known lithostratigraphy of the region. The resistivity model reveals a dipping resistive body that has been uplifted from a deep resistive layer to shallower depths. The geometry of this body indicates a well-defined base and a northeastward dip, suggesting that it corresponds to the Nasr-Abad buried salt diapir. We applied various numerical tests to verify geologically important model features and constrain their properties. The results identify a basement fault with significant vertical throw in the southwestern part of the profile and demonstrate an approximately symmetric shape for the Nasr-Abad buried salt diapir.
{"title":"Crustal-scale structure of the Nasr-Abad buried salt diapir in northwest Central Iran from a profile magnetotelluric dataset","authors":"Mansoure Montahaei, Elham Zare","doi":"10.1016/j.jappgeo.2025.105670","DOIUrl":"10.1016/j.jappgeo.2025.105670","url":null,"abstract":"<div><div>Great Kavir, located in the northern part of the Central Iran depression, is the largest salt desert in Iran with groups of clustered salt diapirs in its northwestern part. The Nasr-Abad salt diapir in the Shurab diapiric group is the largest buried salt diapir in this region, whose geometry at depth and surrounding structure are rarely known. In this study, we investigate a broadband magnetotelluric (MT) dataset recorded at 37 stations distributed along a 14 km, SW-NE profile to characterize the geometry, substratum, and overburden of the Nasr-Abad salt diapir. The spatially distributed MT responses obtained in this study are associated with geological structures at depths of less than 25 km. The measurements were used to generate a crustal-scale resistivity model of the study area, which correlates well with the known lithostratigraphy of the region. The resistivity model reveals a dipping resistive body that has been uplifted from a deep resistive layer to shallower depths. The geometry of this body indicates a well-defined base and a northeastward dip, suggesting that it corresponds to the Nasr-Abad buried salt diapir. We applied various numerical tests to verify geologically important model features and constrain their properties. The results identify a basement fault with significant vertical throw in the southwestern part of the profile and demonstrate an approximately symmetric shape for the Nasr-Abad buried salt diapir.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"236 ","pages":"Article 105670"},"PeriodicalIF":2.2,"publicationDate":"2025-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521248","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 : 2025-02-19DOI: 10.1016/j.jappgeo.2025.105668
Xianzhong Li , Jinhao Zhang , Zhenhua Li , Shuai Heng , Shaolei Wang , Yinnan Tian
Understanding the failure characteristics and progressive failure mechanisms of coal-rock combinations under mining-induced stress is crucial for promoting safe and efficient underground mining operations. In this study, uniaxial compression tests were conducted on standard specimens with varying interface angles. Three-dimensional (3D) laser scanning technology was employed to examine the macroscopic failure characteristics, while digital image correlation (DIC) was used to monitor surface displacement fields. Additionally, acoustic emission (AE) technology provided continuous monitoring throughout the testing process. Results show that the crack initiation sites largely correspond to the primary failure areas within the specimens. As the interface angle increases, crack initiation transitions progressively from the coal side to the coal-rock interface, and eventually to the rock side. Notably, the 0° and 90° specimens display distinct failure characteristics, particularly on the coal and concrete sides. Furthermore, the interfacial strength of the coal-rock composite influences the trans-interfacial crack propagation, with low interfacial strength favouring crack extension along the interface and high inter-facial strength prompting crack extension through or halting at the interface. This study provides comprehensive insights into the fracture behavior of concrete composites.
{"title":"Failure characteristics and crack propagation process of coal-rock combinations under mine-induced stress","authors":"Xianzhong Li , Jinhao Zhang , Zhenhua Li , Shuai Heng , Shaolei Wang , Yinnan Tian","doi":"10.1016/j.jappgeo.2025.105668","DOIUrl":"10.1016/j.jappgeo.2025.105668","url":null,"abstract":"<div><div>Understanding the failure characteristics and progressive failure mechanisms of coal-rock combinations under mining-induced stress is crucial for promoting safe and efficient underground mining operations. In this study, uniaxial compression tests were conducted on standard specimens with varying interface angles. Three-dimensional (3D) laser scanning technology was employed to examine the macroscopic failure characteristics, while digital image correlation (DIC) was used to monitor surface displacement fields. Additionally, acoustic emission (AE) technology provided continuous monitoring throughout the testing process. Results show that the crack initiation sites largely correspond to the primary failure areas within the specimens. As the interface angle increases, crack initiation transitions progressively from the coal side to the coal-rock interface, and eventually to the rock side. Notably, the 0° and 90° specimens display distinct failure characteristics, particularly on the coal and concrete sides. Furthermore, the interfacial strength of the coal-rock composite influences the trans-interfacial crack propagation, with low interfacial strength favouring crack extension along the interface and high inter-facial strength prompting crack extension through or halting at the interface. This study provides comprehensive insights into the fracture behavior of concrete composites.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"236 ","pages":"Article 105668"},"PeriodicalIF":2.2,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480346","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 : 2025-02-19DOI: 10.1016/j.jappgeo.2025.105660
Anyu Li , Yueming Ye , Xiangyu Zhu , Tao Liu , Huimin Zhang , Yong Xia
Seismic imaging techniques are essential to geophysical exploration and subsurface characterization, with full wave-equation depth migration (FWDM) emerging as a highly effective method for imaging complex geological structures. However, optimizing FWDM requires a deep understanding of the factors influencing its performance to achieve accurate and detailed subsurface images. To address this need, this study presents a systematic approach to refining FWDM by first providing a comprehensive review of the extrapolation equations and imaging mechanisms that form its foundation. We then introduce a series of numerical tests designed to identify and analyze key factors impacting imaging quality, including migration velocity, wave propagation effect, and numerical stability. Based on these findings, we optimize parameters and apply them to two challenging models, allowing us to assess the improvements in imaging clarity and accuracy. This research not only highlights critical factors affecting FWDM but also demonstrates how targeted optimizations can significantly enhance its effectiveness for advanced subsurface imaging applications.
{"title":"Evaluation of factors influencing full wave equation depth migration","authors":"Anyu Li , Yueming Ye , Xiangyu Zhu , Tao Liu , Huimin Zhang , Yong Xia","doi":"10.1016/j.jappgeo.2025.105660","DOIUrl":"10.1016/j.jappgeo.2025.105660","url":null,"abstract":"<div><div>Seismic imaging techniques are essential to geophysical exploration and subsurface characterization, with full wave-equation depth migration (FWDM) emerging as a highly effective method for imaging complex geological structures. However, optimizing FWDM requires a deep understanding of the factors influencing its performance to achieve accurate and detailed subsurface images. To address this need, this study presents a systematic approach to refining FWDM by first providing a comprehensive review of the extrapolation equations and imaging mechanisms that form its foundation. We then introduce a series of numerical tests designed to identify and analyze key factors impacting imaging quality, including migration velocity, wave propagation effect, and numerical stability. Based on these findings, we optimize parameters and apply them to two challenging models, allowing us to assess the improvements in imaging clarity and accuracy. This research not only highlights critical factors affecting FWDM but also demonstrates how targeted optimizations can significantly enhance its effectiveness for advanced subsurface imaging applications.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"235 ","pages":"Article 105660"},"PeriodicalIF":2.2,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143471199","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 : 2025-02-18DOI: 10.1016/j.jappgeo.2025.105659
Derman Dondurur
This study primarily aims to characterize both the shallow and deep structures of shallow gas accumulations and gas seepage by utilizing multi-resolution seismic data. Additionally, it seeks to establish a link between shallow and deep stratigraphy for these gas accumulations and seepage in the outer İzmir Gulf by employing various seismic attributes, such as average energy, relative acoustic impedance, apparent polarity, sweetness, pseudo-relief as well as complex trace attributes. Multi-resolution seismic datsets have been collectively interpreted to obtain deep and shallow architecture of gassy structures in the outer İzmir Gulf. Chirp and sparker seismic data provided information about the shallow gas accumulations as well as seep structures while multi-channel seismic data reveals deep structural and stratigraphic formation and their possible connection with the shallow fluid-flow structures.
Analyses of seismic data and calculated multi-attribute sections indicate that both biogenic and thermogenic gases co-exist in the outer İzmir Gulf. It is concluded that Uzunada Fault Zone acts as a conduit for fluid escape, facilitating gas seeps in the water column above the fault plane. Specifically, the Chirp datasets acquired in 2008 and 2023 indicate that the gas seep along the Uzunada Fault Zone has been active over a period of 15 years along this fault plane.
Depending on the analyses of seismic datasets, observed gas is classified into two groups in terms of its origin: (1) Biogenic gas generated in-situ within the highstand sediments of the Gediz Delta, and (2) thermogenic gas from deeper reservoirs within the Upper Miocene sediments. It is concluded that the gas from the deltaic sediments in the eastern part of the gulf is biogenic in origin formed as a result of the biogenic degradation of organic matter in terrigenous sediments transported by the Gediz River. The possible thermogenic gas accumulations, on the other hand, is originated from the presumed sandy layers interbedded with shale laminations in the Upper Miocene sediments, and migrate along the fault planes through the Plio-Quaternary sediments and accumulate in the shallow sediments.
{"title":"Multi-resolution seismic analysis of a cold seep from İzmir Gulf, Aegean Sea using seismic attributes","authors":"Derman Dondurur","doi":"10.1016/j.jappgeo.2025.105659","DOIUrl":"10.1016/j.jappgeo.2025.105659","url":null,"abstract":"<div><div>This study primarily aims to characterize both the shallow and deep structures of shallow gas accumulations and gas seepage by utilizing multi-resolution seismic data. Additionally, it seeks to establish a link between shallow and deep stratigraphy for these gas accumulations and seepage in the outer İzmir Gulf by employing various seismic attributes, such as average energy, relative acoustic impedance, apparent polarity, sweetness, pseudo-relief as well as complex trace attributes. Multi-resolution seismic datsets have been collectively interpreted to obtain deep and shallow architecture of gassy structures in the outer İzmir Gulf. Chirp and sparker seismic data provided information about the shallow gas accumulations as well as seep structures while multi-channel seismic data reveals deep structural and stratigraphic formation and their possible connection with the shallow fluid-flow structures.</div><div>Analyses of seismic data and calculated multi-attribute sections indicate that both biogenic and thermogenic gases co-exist in the outer İzmir Gulf. It is concluded that Uzunada Fault Zone acts as a conduit for fluid escape, facilitating gas seeps in the water column above the fault plane. Specifically, the Chirp datasets acquired in 2008 and 2023 indicate that the gas seep along the Uzunada Fault Zone has been active over a period of 15 years along this fault plane.</div><div>Depending on the analyses of seismic datasets, observed gas is classified into two groups in terms of its origin: (1) Biogenic gas generated in-situ within the highstand sediments of the Gediz Delta, and (2) thermogenic gas from deeper reservoirs within the Upper Miocene sediments. It is concluded that the gas from the deltaic sediments in the eastern part of the gulf is biogenic in origin formed as a result of the biogenic degradation of organic matter in terrigenous sediments transported by the Gediz River. The possible thermogenic gas accumulations, on the other hand, is originated from the presumed sandy layers interbedded with shale laminations in the Upper Miocene sediments, and migrate along the fault planes through the Plio-Quaternary sediments and accumulate in the shallow sediments.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"235 ","pages":"Article 105659"},"PeriodicalIF":2.2,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445645","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 accurate prediction of water saturation in reservoir exploration and development remains a significant challenge, particularly in regions like the Middle East with complex carbonate formations such as the Mishrif Formation. While geophysical logging data is widely utilized for this purpose, however, the complex pore structures render Archie's formula unsuitable, leading to non-Archie phenomenon in rock-electrical experiments. Although the electrical efficiency model has been employed in calculating water saturation in carbonate reservoirs, there has been no prior study incorporating electrical porosity for its refinement. This study enhances the conventional electrical efficiency model by introducing the concept of electrical porosity. The improvement aims to mitigate the impact of isolated mold pores and sparse regions of current density distribution on electrical efficiency, focusing on the Mishrif Formation and quantitatively computing water saturation. Initially, the study area is categorized into three distinct rock-physics types of reservoirs using the Winland R35 method, with respective electrical porosities calculated. Subsequently, these results are integrated with the enhanced electrical efficiency model, and trial calculations are performed using geophysical well-logging data, followed by a comparison with core data. The findings reveal that the improved electrical efficiency model yields an average relative error of only 10.36 % compared to core data, whereas the respective errors for Archie's formula and traditional electrical efficiency models are 17.65 % and 20.92 %, indicating enhanced accuracy with the improved approach. Across different reservoir types, a decrease in electrical porosity proportion is observed with diminishing pore-throat radius. Additionally, the consistency of this trend is validated by nuclear magnetic resonance logging data. Lastly, the necessity of reservoir rock-physics type classification for electrical porosity computation is confirmed. For heterogeneous reservoirs, direct calculation of electrical porosity is infeasible, thus underscoring the essential groundwork of reservoir rock-physics type delineation. This study improves water saturation prediction accuracy and applicability by introducing electrical porosity to refine the conventional electrical efficiency model, holding significant implications for the exploration and development of complex reservoirs.
{"title":"Enhanced water saturation evaluation method using an improved electrical efficiency model: A case study of the Mishrif Formation, Iraq","authors":"Jianhong Guo , Zhansong Zhang , Chaomo Zhang , Qing Zhao , Xiao Tang","doi":"10.1016/j.jappgeo.2025.105656","DOIUrl":"10.1016/j.jappgeo.2025.105656","url":null,"abstract":"<div><div>The accurate prediction of water saturation in reservoir exploration and development remains a significant challenge, particularly in regions like the Middle East with complex carbonate formations such as the Mishrif Formation. While geophysical logging data is widely utilized for this purpose, however, the complex pore structures render Archie's formula unsuitable, leading to non-Archie phenomenon in rock-electrical experiments. Although the electrical efficiency model has been employed in calculating water saturation in carbonate reservoirs, there has been no prior study incorporating electrical porosity for its refinement. This study enhances the conventional electrical efficiency model by introducing the concept of electrical porosity. The improvement aims to mitigate the impact of isolated mold pores and sparse regions of current density distribution on electrical efficiency, focusing on the Mishrif Formation and quantitatively computing water saturation. Initially, the study area is categorized into three distinct rock-physics types of reservoirs using the Winland R35 method, with respective electrical porosities calculated. Subsequently, these results are integrated with the enhanced electrical efficiency model, and trial calculations are performed using geophysical well-logging data, followed by a comparison with core data. The findings reveal that the improved electrical efficiency model yields an average relative error of only 10.36 % compared to core data, whereas the respective errors for Archie's formula and traditional electrical efficiency models are 17.65 % and 20.92 %, indicating enhanced accuracy with the improved approach. Across different reservoir types, a decrease in electrical porosity proportion is observed with diminishing pore-throat radius. Additionally, the consistency of this trend is validated by nuclear magnetic resonance logging data. Lastly, the necessity of reservoir rock-physics type classification for electrical porosity computation is confirmed. For heterogeneous reservoirs, direct calculation of electrical porosity is infeasible, thus underscoring the essential groundwork of reservoir rock-physics type delineation. This study improves water saturation prediction accuracy and applicability by introducing electrical porosity to refine the conventional electrical efficiency model, holding significant implications for the exploration and development of complex reservoirs.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"236 ","pages":"Article 105656"},"PeriodicalIF":2.2,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480348","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 : 2025-02-17DOI: 10.1016/j.jappgeo.2025.105658
Alejandro Vargas-Colorado , Mohsen Kazemnia Kakhki , José E. Barradas-Hernández , Sergio Márquez-Domínguez , Franco A. Carpio-Santamaría , José Piña-Flores
A representative velocity profile for Kumamoto city is presented in this study, derived from ambient seismic noise data collected by three sizes sensor arrays SM, M, and LL. Phase and group velocity dispersion curves for both Rayleigh and Love waves were estimated using techniques such as SPAC and cross-correlations. Additionally, Horizontal-to-Vertical Spectral Ratio (HVSR) analysis was performed individually for each array, and the resulting data were averaged to generate a single representative HVSR curve. By employing joint inversion under the diffuse field assumption, dispersion curves and HVSR data were concurrently fitted, allowing for the estimation of a 1D velocity profile. This approach effectively addresses the non-uniqueness inherent in inversion problems. Furthermore, upper modes were identified, and a comparative analysis of dispersion and HVSR curves was conducted against those of an established model, revealing notable discrepancies requiring thorough examination. Subsequently, seismic energy partitioning analysis was carried out, focusing on the vertical component. The findings were correlated with dispersion diagrams to confirm consistency in mode identification.
{"title":"Subsurface structure identification at the blind prediction site of ESG in Kumamoto under the diffuse field assumption","authors":"Alejandro Vargas-Colorado , Mohsen Kazemnia Kakhki , José E. Barradas-Hernández , Sergio Márquez-Domínguez , Franco A. Carpio-Santamaría , José Piña-Flores","doi":"10.1016/j.jappgeo.2025.105658","DOIUrl":"10.1016/j.jappgeo.2025.105658","url":null,"abstract":"<div><div>A representative velocity profile for Kumamoto city is presented in this study, derived from ambient seismic noise data collected by three sizes sensor arrays SM, M, and LL. Phase and group velocity dispersion curves for both Rayleigh and Love waves were estimated using techniques such as SPAC and cross-correlations. Additionally, Horizontal-to-Vertical Spectral Ratio (HVSR) analysis was performed individually for each array, and the resulting data were averaged to generate a single representative HVSR curve. By employing joint inversion under the diffuse field assumption, dispersion curves and HVSR data were concurrently fitted, allowing for the estimation of a 1D velocity profile. This approach effectively addresses the non-uniqueness inherent in inversion problems. Furthermore, upper modes were identified, and a comparative analysis of dispersion and HVSR curves was conducted against those of an established model, revealing notable discrepancies requiring thorough examination. Subsequently, seismic energy partitioning analysis was carried out, focusing on the vertical component. The findings were correlated with dispersion diagrams to confirm consistency in mode identification.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"235 ","pages":"Article 105658"},"PeriodicalIF":2.2,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455011","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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