Conventional total magnetic intensity (TMI) anomaly continuation typically approximate the difference between the measured total magnetic field and the main field modulus as the projection of the magnetic vector in the direction of the main field. However, in regions with high TMI anomaly amplitudes, using conventional linear approximation multi-layer equivalent source models results in significant continuation errors. This paper presents a nonlinear multi-layer equivalent source method for magnetic anomaly continuation, which utilizes an iterative technique. The technique begins by analyzing the physical significance of the magnetic anomaly modulus and subsequently constructs the model based on this interpretation. The iterative process is optimized using an adaptive conjugate gradient method. The findings demonstrate that, in high-amplitude areas, the differences in TMI anomaly modulus and approximate projections need to be taken into account. Moreover, the method proposed in this paper enhances continuation accuracy, with its accuracy advantage becoming more pronounced as the continuation distance increases.
{"title":"Nonlinear multi-layer equivalent source continuation method in strong magnetic fields","authors":"Jinkai Feng, Shanshan Li, Xu Feng, Haopeng Fan, Xinxing Li, Diao Fan","doi":"10.1016/j.jappgeo.2025.106089","DOIUrl":"10.1016/j.jappgeo.2025.106089","url":null,"abstract":"<div><div>Conventional total magnetic intensity (TMI) anomaly continuation typically approximate the difference between the measured total magnetic field and the main field modulus as the projection of the magnetic vector in the direction of the main field. However, in regions with high TMI anomaly amplitudes, using conventional linear approximation multi-layer equivalent source models results in significant continuation errors. This paper presents a nonlinear multi-layer equivalent source method for magnetic anomaly continuation, which utilizes an iterative technique. The technique begins by analyzing the physical significance of the magnetic anomaly modulus and subsequently constructs the model based on this interpretation. The iterative process is optimized using an adaptive conjugate gradient method. The findings demonstrate that, in high-amplitude areas, the differences in TMI anomaly modulus and approximate projections need to be taken into account. Moreover, the method proposed in this paper enhances continuation accuracy, with its accuracy advantage becoming more pronounced as the continuation distance increases.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106089"},"PeriodicalIF":2.1,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038838","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 : 2026-01-08DOI: 10.1016/j.jappgeo.2026.106106
Zhimei Kang , Yukun Liu , Xiaolong Wang , Yulin Du
Well logging data serve as a crucial bridge connecting seismic data and geological interpretation, playing an indispensable role in hydrocarbon exploration and resource evaluation. However, the complex heterogeneity of reservoirs and the high-temperature, high-pressure conditions in deep and ultradeep often lead to wellbore instability, formation loss, and technical constraints, which in turn cause severe data gaps and distortions during log acquisition. Traditional well log reconstruction methods, such as empirical models and multivariate fitting, generally suffer from reliance on subjective experience, low prediction accuracy, and poor model adaptability when dealing with such complex reservoirs. To address these challenges, this study proposes a novel log reconstruction model (Bi-LSTM-SAM-TTT) that integrates Bi-directional Long Short-Term Memory (Bi-LSTM) networks, a Self-Attention Mechanism (SAM), and Test-Time Training (TTT) algorithms. Geological stratification and depth information are incorporated as prior knowledge during model training, effectively strengthening the sequential correlation between geological features and logging data, and significantly improving reconstruction accuracy. By comparing multi-variate fitting, LSTM, Bi-LSTM, and Bi-LSTM-SAM methods, the results demonstrate that the Bi-LSTM-SAM-TTT model achieves the best performance in reconstructing three key logging curves: resistivity (RD), density (DEN), and acoustic interval transit time (DTC). Compared with the LSTM model, the proposed model reduces the RMSE by 46.1% (RD), 39.6% (DEN), and 39.5% (DTC), respectively, while the coefficient of determination (R2) increases to above 0.92 for all three curves. In a case study, the R2 values for DTC prediction using the four models were 0.8003, 0.8146, 0.8523, and 0.8843, respectively, with the Bi-LSTM-SAM-TTT model clearly outperforming the others. Moreover, prediction interval analysis under different confidence levels shows that the coverage of the 95% confidence interval exceeds 98%, indicating high predictive reliability of the proposed model. In summary, the Bi-LSTM-SAM-TTT model not only effectively mitigates the problem of missing well log data in ultradeep formations but also exhibits strong robustness and generalization capability, providing a new approach for high-precision well log reconstruction in deep and ultradeep hydrocarbon exploration.
测井资料是连接地震资料和地质解释的重要桥梁，在油气勘探和资源评价中发挥着不可或缺的作用。然而，储层复杂的非均质性，以及深层和超深层的高温高压条件，往往会导致井筒不稳定、地层漏失和技术限制，从而在测井采集过程中造成严重的数据缺口和失真。传统的测井重建方法，如经验模型和多元拟合，在处理此类复杂储层时，普遍存在依赖主观经验、预测精度低、模型适应性差的问题。为了解决这些挑战，本研究提出了一种新的日志重建模型（Bi-LSTM-SAM-TTT），该模型集成了双向长短期记忆（Bi-LSTM）网络、自注意机制（SAM）和测试时间训练（TTT）算法。在模型训练过程中，将地质分层和深度信息作为先验知识，有效加强了地质特征与测井资料的序列相关性，显著提高了重建精度。通过对比多元拟合、LSTM、Bi-LSTM和Bi-LSTM- sam方法，结果表明，Bi-LSTM- sam - ttt模型在重建电阻率（RD）、密度（DEN）和声波间隔透射时间（DTC）三条关键测井曲线方面表现最佳。与LSTM模型相比，该模型的RMSE分别降低了46.1% （RD）、39.6% （DEN）和39.5% (DTC)，三条曲线的决定系数（R2）均提高到0.92以上。在案例研究中，4种模型预测DTC的R2值分别为0.8003、0.8146、0.8523和0.8843，其中Bi-LSTM-SAM-TTT模型明显优于其他模型。此外，不同置信水平下的预测区间分析表明，95%置信区间的覆盖率超过98%，表明所提模型具有较高的预测可靠性。综上所述，Bi-LSTM-SAM-TTT模型不仅有效缓解了超深层地层测井资料缺失的问题，而且具有较强的鲁棒性和泛化能力，为深、超深层油气勘探的高精度测井重建提供了新的途径。
{"title":"A deep learning-based method for well log data reconstruction in marine carbonate reservoirs","authors":"Zhimei Kang , Yukun Liu , Xiaolong Wang , Yulin Du","doi":"10.1016/j.jappgeo.2026.106106","DOIUrl":"10.1016/j.jappgeo.2026.106106","url":null,"abstract":"<div><div>Well logging data serve as a crucial bridge connecting seismic data and geological interpretation, playing an indispensable role in hydrocarbon exploration and resource evaluation. However, the complex heterogeneity of reservoirs and the high-temperature, high-pressure conditions in deep and ultradeep often lead to wellbore instability, formation loss, and technical constraints, which in turn cause severe data gaps and distortions during log acquisition. Traditional well log reconstruction methods, such as empirical models and multivariate fitting, generally suffer from reliance on subjective experience, low prediction accuracy, and poor model adaptability when dealing with such complex reservoirs. To address these challenges, this study proposes a novel log reconstruction model (Bi-LSTM-SAM-TTT) that integrates Bi-directional Long Short-Term Memory (Bi-LSTM) networks, a Self-Attention Mechanism (SAM), and Test-Time Training (TTT) algorithms. Geological stratification and depth information are incorporated as prior knowledge during model training, effectively strengthening the sequential correlation between geological features and logging data, and significantly improving reconstruction accuracy. By comparing multi-variate fitting, LSTM, Bi-LSTM, and Bi-LSTM-SAM methods, the results demonstrate that the Bi-LSTM-SAM-TTT model achieves the best performance in reconstructing three key logging curves: resistivity (RD), density (DEN), and acoustic interval transit time (DTC). Compared with the LSTM model, the proposed model reduces the RMSE by 46.1% (RD), 39.6% (DEN), and 39.5% (DTC), respectively, while the coefficient of determination (R<sup>2</sup>) increases to above 0.92 for all three curves. In a case study, the R<sup>2</sup> values for DTC prediction using the four models were 0.8003, 0.8146, 0.8523, and 0.8843, respectively, with the Bi-LSTM-SAM-TTT model clearly outperforming the others. Moreover, prediction interval analysis under different confidence levels shows that the coverage of the 95% confidence interval exceeds 98%, indicating high predictive reliability of the proposed model. In summary, the Bi-LSTM-SAM-TTT model not only effectively mitigates the problem of missing well log data in ultradeep formations but also exhibits strong robustness and generalization capability, providing a new approach for high-precision well log reconstruction in deep and ultradeep hydrocarbon exploration.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106106"},"PeriodicalIF":2.1,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038840","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 : 2026-01-08DOI: 10.1016/j.jappgeo.2026.106105
Zixin Huang , Qiaomu Luo , Longjun Dong , Longbin Yang , Shenglan Li , Xuewei Li
Thermal effects influence rock stability in geothermal extraction and deep engineering. Wave velocity, as a key physical indicator, provides essential insights into these thermal-induced structural and mechanical changes. This study focused on the behavior and evolution of wave velocity in granite under high-temperature conditions, which is essential for assessing the stability of deep geothermal areas. A novel experimental setup was developed using an internal point heat source to simulate deep geothermal conditions while synchronously recording active ultrasonic pulse signals and temperature data. The analysis includes the anisotropy, temperature sensitivity, attenuation behavior, and spatiotemporal evolution of wave velocity. The results reveal that wave velocity exhibits pronounced anisotropy within the granite, intensifying with increasing temperature. Wave velocity shows a fluctuating decay pattern, with a stable-accelerated-stable trend in cycles of approximately 10 °C before 80 °C. The attenuation was most considerable at the initial heating phase and beyond 80 °C. Using a piecewise linear decay model, we identified critical transition points in the attenuation behavior, marked by a notable change in decay rate before and after the points. Tomographic imaging visualizes the spatial-temporal evolution of the wave velocity field, highlighting localized thermal damage and progressive crack development. The findings provide insights into early instability warnings in deep geological environments and offer theoretical and technical support for the safe extraction of deep mineral and geothermal resources.
{"title":"Real-time wave velocity evolution and thermal damage development in hollow-sphere granite: Insights from progressive heating experiments","authors":"Zixin Huang , Qiaomu Luo , Longjun Dong , Longbin Yang , Shenglan Li , Xuewei Li","doi":"10.1016/j.jappgeo.2026.106105","DOIUrl":"10.1016/j.jappgeo.2026.106105","url":null,"abstract":"<div><div>Thermal effects influence rock stability in geothermal extraction and deep engineering. Wave velocity, as a key physical indicator, provides essential insights into these thermal-induced structural and mechanical changes. This study focused on the behavior and evolution of wave velocity in granite under high-temperature conditions, which is essential for assessing the stability of deep geothermal areas. A novel experimental setup was developed using an internal point heat source to simulate deep geothermal conditions while synchronously recording active ultrasonic pulse signals and temperature data. The analysis includes the anisotropy, temperature sensitivity, attenuation behavior, and spatiotemporal evolution of wave velocity. The results reveal that wave velocity exhibits pronounced anisotropy within the granite, intensifying with increasing temperature. Wave velocity shows a fluctuating decay pattern, with a stable-accelerated-stable trend in cycles of approximately 10 °C before 80 °C. The attenuation was most considerable at the initial heating phase and beyond 80 °C. Using a piecewise linear decay model, we identified critical transition points in the attenuation behavior, marked by a notable change in decay rate before and after the points. Tomographic imaging visualizes the spatial-temporal evolution of the wave velocity field, highlighting localized thermal damage and progressive crack development. The findings provide insights into early instability warnings in deep geological environments and offer theoretical and technical support for the safe extraction of deep mineral and geothermal resources.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106105"},"PeriodicalIF":2.1,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038836","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 : 2026-01-08DOI: 10.1016/j.jappgeo.2025.106091
Xiaokun Zhao , Jun Ge , Wencai Wang , An Zhang , Yuhua Bai , Yong Liu , Weixia Fu
Accurate detection of hidden coal fire areas is crucial for early warning and disaster mitigation, yet single-physics methods often have limitations in scope and applicability. This study proposes a multi-physics cooperative detection approach based on temperature variations, integrating magnetic, dielectric, and resistivity measurements, and verifies it on a large-scale physical simulation platform. The results show that as the fire temperature increases (500–700 °C), the magnetic susceptibility of coal and rocks significantly enhances, raising the magnetic anomaly intensity from 1100nT to 1600nT, effectively delineating fire boundaries. Variable-temperature dielectric measurements reveal a three-stage evolution pattern, with burned-out zones exhibiting reduced permittivity, causing polarity inversion of ground-penetrating radar (GPR) reflections, which can be effectively identified in the 20–24 ns time window. High-density resistivity surveys indicate a distinct transition from high-resistivity anomalies (∼10^5Ω·m) at ambient conditions to low-resistivity anomalies (50 - 200 Ω·m) at elevated temperatures, with inversion results consistent with forward modeling. The integration of magnetic, dielectric, and resistivity methods demonstrates strong complementarity in boundary delineation, void detection, and spatial inversion, ultimately achieving precise localization of fire centers. This study establishes a cooperative multi-physics detection framework for hidden coal fires, providing a new technical approach for integrated detection, disaster early warning, and fire control design, with potential applicability in geothermal monitoring and hydrocarbon leakage detection.
{"title":"Research on multi-physics field collaborative detection methods for concealed fire zones: Based on variable-temperature magnetic-dielectric-resistive characteristics","authors":"Xiaokun Zhao , Jun Ge , Wencai Wang , An Zhang , Yuhua Bai , Yong Liu , Weixia Fu","doi":"10.1016/j.jappgeo.2025.106091","DOIUrl":"10.1016/j.jappgeo.2025.106091","url":null,"abstract":"<div><div>Accurate detection of hidden coal fire areas is crucial for early warning and disaster mitigation, yet single-physics methods often have limitations in scope and applicability. This study proposes a multi-physics cooperative detection approach based on temperature variations, integrating magnetic, dielectric, and resistivity measurements, and verifies it on a large-scale physical simulation platform. The results show that as the fire temperature increases (500–700 °C), the magnetic susceptibility of coal and rocks significantly enhances, raising the magnetic anomaly intensity from 1100nT to 1600nT, effectively delineating fire boundaries. Variable-temperature dielectric measurements reveal a three-stage evolution pattern, with burned-out zones exhibiting reduced permittivity, causing polarity inversion of ground-penetrating radar (GPR) reflections, which can be effectively identified in the 20–24 ns time window. High-density resistivity surveys indicate a distinct transition from high-resistivity anomalies (∼10^5Ω·m) at ambient conditions to low-resistivity anomalies (50 - 200 Ω·m) at elevated temperatures, with inversion results consistent with forward modeling. The integration of magnetic, dielectric, and resistivity methods demonstrates strong complementarity in boundary delineation, void detection, and spatial inversion, ultimately achieving precise localization of fire centers. This study establishes a cooperative multi-physics detection framework for hidden coal fires, providing a new technical approach for integrated detection, disaster early warning, and fire control design, with potential applicability in geothermal monitoring and hydrocarbon leakage detection.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106091"},"PeriodicalIF":2.1,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928696","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 : 2026-01-07DOI: 10.1016/j.jappgeo.2026.106094
Jianguang Han , Hao Zhang
Adaptive focused beam migration represents an advanced imaging technique for seismic wave fields. This method enhances beam energy focus by dynamically adjusting beam width based on velocity information, offering superior imaging capabilities for complex geological structures. Based on previous research on isotropic adaptive focused beam pre-stack depth migration (FB-PSDM), this study introduces anisotropic ray tracing equations to improve seismic wave field imaging in anisotropic media. Furthermore, the proposed method integrates a pre-stack wave field separation technique for multi-component seismic data, resulting in the development of an anisotropic multi-component adaptive FB-PSDM approach. Comparative analysis of single-shot PP-wave and PS-wave migration results in horizontal transversely isotropic with a vertical symmetry axis (VTI) media models demonstrates that the proposed method yields more accurate imaging outcomes compared to conventional isotropic migration methods. Additional validation through PP-wave and PS-wave migration tests on complex-fault transversely isotorpic with a tilted symmetry axis (TTI) medium model and the Marmousi-2 TTI medium model further confirms the superior performance of the proposed method. These results consistently indicate that the anisotropic multi-component adaptive FB-PSDM method significantly outperforms isotropic migration methods in imaging quality for complex anisotropic geological structures.
{"title":"Multi-component seismic imaging using adaptive focused beam migration in transversely isotropic media","authors":"Jianguang Han , Hao Zhang","doi":"10.1016/j.jappgeo.2026.106094","DOIUrl":"10.1016/j.jappgeo.2026.106094","url":null,"abstract":"<div><div>Adaptive focused beam migration represents an advanced imaging technique for seismic wave fields. This method enhances beam energy focus by dynamically adjusting beam width based on velocity information, offering superior imaging capabilities for complex geological structures. Based on previous research on isotropic adaptive focused beam pre-stack depth migration (FB-PSDM), this study introduces anisotropic ray tracing equations to improve seismic wave field imaging in anisotropic media. Furthermore, the proposed method integrates a pre-stack wave field separation technique for multi-component seismic data, resulting in the development of an anisotropic multi-component adaptive FB-PSDM approach. Comparative analysis of single-shot PP-wave and PS-wave migration results in horizontal transversely isotropic with a vertical symmetry axis (VTI) media models demonstrates that the proposed method yields more accurate imaging outcomes compared to conventional isotropic migration methods. Additional validation through PP-wave and PS-wave migration tests on complex-fault transversely isotorpic with a tilted symmetry axis (TTI) medium model and the Marmousi-2 TTI medium model further confirms the superior performance of the proposed method. These results consistently indicate that the anisotropic multi-component adaptive FB-PSDM method significantly outperforms isotropic migration methods in imaging quality for complex anisotropic geological structures.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106094"},"PeriodicalIF":2.1,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928698","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 : 2026-01-07DOI: 10.1016/j.jappgeo.2026.106093
Jinhai Liu , Rui Xu , Kai Zhan , Jiajun Chen , Guangming Li , Chao Kong
Understanding how stress redistribution and structural reactivation evolve during deep coal mining is essential for assessing seismic hazards. In this study, we develop an automated microseismic classification workflow that integrates PhaseNet-based P-wave picking, residual-guided multi-window trimming, short-time Fourier transform (STFT) spectrogram generation and a dynamic-attention convolutional neural network to identify mining-induced and tectonic events in real time. The workflow is first trained and validated on labelled microseismic waveforms, achieving 93% overall accuracy on a five-class test set (blast, microseismic, earthquake, noise and others). We then deploy it on five high-SNR stations (WDZ4–WDZ8) at the 6306 working face of the Dongtan Coal Mine, where it captures the progressive transition from blast-dominated to tectonic-dominated microseismicity as mining advances into faulted zones. This trend, interpreted together with independent geological mapping and published focal-mechanism and stress-inversion results, indicates enhanced stress transfer and structural activation within the surrounding strata. Overall, the results demonstrate that intelligent seismic classification can quantitatively track the coupling between mining activities and geological structures, providing a practical tool for stress monitoring and early warning in deep coal seams.
{"title":"Automated microseismic classification in deep coal seams: Application to stress redistribution and fault reactivation in the Dongtan coal mine","authors":"Jinhai Liu , Rui Xu , Kai Zhan , Jiajun Chen , Guangming Li , Chao Kong","doi":"10.1016/j.jappgeo.2026.106093","DOIUrl":"10.1016/j.jappgeo.2026.106093","url":null,"abstract":"<div><div>Understanding how stress redistribution and structural reactivation evolve during deep coal mining is essential for assessing seismic hazards. In this study, we develop an automated microseismic classification workflow that integrates PhaseNet-based P-wave picking, residual-guided multi-window trimming, short-time Fourier transform (STFT) spectrogram generation and a dynamic-attention convolutional neural network to identify mining-induced and tectonic events in real time. The workflow is first trained and validated on labelled microseismic waveforms, achieving 93% overall accuracy on a five-class test set (blast, microseismic, earthquake, noise and others). We then deploy it on five high-SNR stations (WDZ4–WDZ8) at the 6306 working face of the Dongtan Coal Mine, where it captures the progressive transition from blast-dominated to tectonic-dominated microseismicity as mining advances into faulted zones. This trend, interpreted together with independent geological mapping and published focal-mechanism and stress-inversion results, indicates enhanced stress transfer and structural activation within the surrounding strata. Overall, the results demonstrate that intelligent seismic classification can quantitatively track the coupling between mining activities and geological structures, providing a practical tool for stress monitoring and early warning in deep coal seams.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106093"},"PeriodicalIF":2.1,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928695","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 : 2026-01-03DOI: 10.1016/j.jappgeo.2025.106085
Youbang Lai , Zhipeng Li , Peng Liang , Wenxue Deng , Yang Liu
To reveal the propagation characteristics of acoustic emission (AE) signals in layered rock and their implications for monitoring and interpretation, AE propagation tests were conducted in two directions: in-layer (parallel-to-bedding) and cross-layer (perpendicular-to-bedding). The effects of bedding on AE wave velocity, waveform, spectrum, and time–frequency characteristics were systematically analysed. Results revealed significant anisotropy: the cross-layer wave velocity was approximately 10.61% lower than the in-layer velocity. Propagation through bedding caused pronounced attenuation in amplitude, energy, and ringing count, accompanied by a significant increase in rise time, indicating waveform distortion and dispersion. The dominant frequency decreased from about 120 kHz to 50 kHz, showing strong high-frequency attenuation and energy transfer toward lower frequencies. Frequency-dependent attenuation was most pronounced in the 250–500 kHz range, moderate in 125–250 kHz, and weak below 125 kHz. The attenuation bandwidth for cross-layer propagation (62.5–500 kHz) was broader than that for in-layer propagation (125–500 kHz). These findings demonstrate that bedding interfaces play a critical role in controlling AE signal behaviour, providing a theoretical and experimental basis for improving AE source interpretation and dynamic hazard monitoring in layered rock masses.
{"title":"Stratification effects of acoustic emission signal propagation in stratified rocks: Results from laboratory research","authors":"Youbang Lai , Zhipeng Li , Peng Liang , Wenxue Deng , Yang Liu","doi":"10.1016/j.jappgeo.2025.106085","DOIUrl":"10.1016/j.jappgeo.2025.106085","url":null,"abstract":"<div><div>To reveal the propagation characteristics of acoustic emission (AE) signals in layered rock and their implications for monitoring and interpretation, AE propagation tests were conducted in two directions: in-layer (parallel-to-bedding) and cross-layer (perpendicular-to-bedding). The effects of bedding on AE wave velocity, waveform, spectrum, and time–frequency characteristics were systematically analysed. Results revealed significant anisotropy: the cross-layer wave velocity was approximately 10.61% lower than the in-layer velocity. Propagation through bedding caused pronounced attenuation in amplitude, energy, and ringing count, accompanied by a significant increase in rise time, indicating waveform distortion and dispersion. The dominant frequency decreased from about 120 kHz to 50 kHz, showing strong high-frequency attenuation and energy transfer toward lower frequencies. Frequency-dependent attenuation was most pronounced in the 250–500 kHz range, moderate in 125–250 kHz, and weak below 125 kHz. The attenuation bandwidth for cross-layer propagation (62.5–500 kHz) was broader than that for in-layer propagation (125–500 kHz). These findings demonstrate that bedding interfaces play a critical role in controlling AE signal behaviour, providing a theoretical and experimental basis for improving AE source interpretation and dynamic hazard monitoring in layered rock masses.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106085"},"PeriodicalIF":2.1,"publicationDate":"2026-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980129","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 : 2026-01-02DOI: 10.1016/j.jappgeo.2025.106088
Ronghua Xu , Juzhi Deng , Fasheng Lou , Yang Gao , Zequn Wen , Hui Yu
South Poyang Basin is an important hydrocarbon exploration block in the Lower Yangtze region. The Upper Paleozoic strata are widely distributed with active hydrocarbon anomalies. However, industrial hydrocarbon flow has yet to be achieved. The damage caused by shallow structural adjustments and the lack of clarity in deep geological structures are considered significant factors constraining breakthroughs in oil and gas exploration. This study performed a 2D nonlinear conjugate gradient inversion on 30 magnetotelluric (MT) data points from the north-south opposing thrust area in the Erjia Depression of South Poyang Basin and successfully constructed a detailed resistivity model extending to a depth of 6 km. Then the hydrocarbon accumulation patterns and favorable exploration directions were analyzed by combining imaging results with 2D seismic profiles and previous borehole logs. The results reveal that the Erjia Depression has undergone multiple tectonic events, forming a typical imbricate thrust system. Within this system, the F2 structure is characterized by low-angle thrusting from NW to SE, extending approximately 12.5 km along the NE direction, with its formation period preliminarily constrained to the Indosinian. A stable median apparent resistivity anomaly beneath the thrust nappe suggests the footwall of the nappe is less influenced by structural disruption and the potential presence of an in-situ stratum dating from the Late Permian to Middle Carboniferous (P3-C2). Within this sequence, the Middle Permian carbonate rocks possess key elements for hydrocarbon accumulation: high-quality source rocks, favorable reservoir properties, and ideal burial conditions.The results can provide crucial constraints on the electrical structure and introduce a new technical approach for the deep hydrocarbon exploration in Southern Poyang Basin.
{"title":"Analysis of deep structures and key factors for oil and gas accumulation in the Erjiacun Depression of South Poyang Basin based on magnetotelluric sounding imaging","authors":"Ronghua Xu , Juzhi Deng , Fasheng Lou , Yang Gao , Zequn Wen , Hui Yu","doi":"10.1016/j.jappgeo.2025.106088","DOIUrl":"10.1016/j.jappgeo.2025.106088","url":null,"abstract":"<div><div>South Poyang Basin is an important hydrocarbon exploration block in the Lower Yangtze region. The Upper Paleozoic strata are widely distributed with active hydrocarbon anomalies. However, industrial hydrocarbon flow has yet to be achieved. The damage caused by shallow structural adjustments and the lack of clarity in deep geological structures are considered significant factors constraining breakthroughs in oil and gas exploration. This study performed a 2D nonlinear conjugate gradient inversion on 30 magnetotelluric (MT) data points from the north-south opposing thrust area in the Erjia Depression of South Poyang Basin and successfully constructed a detailed resistivity model extending to a depth of 6 km. Then the hydrocarbon accumulation patterns and favorable exploration directions were analyzed by combining imaging results with 2D seismic profiles and previous borehole logs. The results reveal that the Erjia Depression has undergone multiple tectonic events, forming a typical imbricate thrust system. Within this system, the F<sub>2</sub> structure is characterized by low-angle thrusting from NW to SE, extending approximately 12.5 km along the NE direction, with its formation period preliminarily constrained to the Indosinian. A stable median apparent resistivity anomaly beneath the thrust nappe suggests the footwall of the nappe is less influenced by structural disruption and the potential presence of an in-situ stratum dating from the Late Permian to Middle Carboniferous (P<sub>3</sub>-C<sub>2</sub>). Within this sequence, the Middle Permian carbonate rocks possess key elements for hydrocarbon accumulation: high-quality source rocks, favorable reservoir properties, and ideal burial conditions.The results can provide crucial constraints on the electrical structure and introduce a new technical approach for the deep hydrocarbon exploration in Southern Poyang Basin.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106088"},"PeriodicalIF":2.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145903958","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 Ordos Basin is one of the most resource-rich and critical regions for deep coalbed methane gas within China, in which the efficient development of this methane gas is key to increasing reserves and boosting production. The gas-bearing content of coal–rock systems is largely controlled by their internal architectural configurations. Seismic detection plays a critical role in attempts to convert coalbed methane gas resources into recoverable reserves and increase production capacity. However, unconventional self-sourced and trapped coal–rock gas reservoirs exhibit distinct geological features. Coalbeds are generally characterized by limited thicknesses, complex capping lithologies, and laterally heterogeneous architectures. These complexities hinder a clear understanding of their architectural patterns and seismic response signatures, resulting in underdeveloped seismic detection methods. To address these challenges and achieve high-resolution characterizations of favorable coal–rock architectures, we here focus on a representative area in the Yulin region of the Ordos Basin. By integrating basic geological coal–rock types with gas-enriched architectural features, favorable coal–rock architectures in the study area were classified into three distinct types: dual-layer limestone–coal, integrated mudstone–coal, and integrated sandstone–coal. The geophysical response characteristics of these architectures were then identified using seismic forward modeling of favorable architectural models. After selecting sensitive seismic attributes, a neural network-based multi-attribute clustering method was applied to characterize the spatial distribution of favorable coal–rock facies architectures. In addition, image-processing edge detection techniques were used to delineate the lateral boundaries of each type of architecture. Herein, an innovative methodology is proposed for seismic- and well-data integration to achieve the fine-scale characterization of favorable coal–rock architectures under facies-type and architectural boundaries. Our findings provide both theoretical insights and technical guidance for the efficient exploration and development of coalbed methane gas in the Ordos Basin.
{"title":"Characterization and Applications of Favorable Coal–Rock Architectures Based on Seismic Facies Boundaries: The Ordos Basin","authors":"ZeLei Jiang , Xuri Huang , Dong Zhang , YuCong Huang , Yong Wu","doi":"10.1016/j.jappgeo.2025.106092","DOIUrl":"10.1016/j.jappgeo.2025.106092","url":null,"abstract":"<div><div>The Ordos Basin is one of the most resource-rich and critical regions for deep coalbed methane gas within China, in which the efficient development of this methane gas is key to increasing reserves and boosting production. The gas-bearing content of coal–rock systems is largely controlled by their internal architectural configurations. Seismic detection plays a critical role in attempts to convert coalbed methane gas resources into recoverable reserves and increase production capacity. However, unconventional self-sourced and trapped coal–rock gas reservoirs exhibit distinct geological features. Coalbeds are generally characterized by limited thicknesses, complex capping lithologies, and laterally heterogeneous architectures. These complexities hinder a clear understanding of their architectural patterns and seismic response signatures, resulting in underdeveloped seismic detection methods. To address these challenges and achieve high-resolution characterizations of favorable coal–rock architectures, we here focus on a representative area in the Yulin region of the Ordos Basin. By integrating basic geological coal–rock types with gas-enriched architectural features, favorable coal–rock architectures in the study area were classified into three distinct types: dual-layer limestone–coal, integrated mudstone–coal, and integrated sandstone–coal. The geophysical response characteristics of these architectures were then identified using seismic forward modeling of favorable architectural models. After selecting sensitive seismic attributes, a neural network-based multi-attribute clustering method was applied to characterize the spatial distribution of favorable coal–rock facies architectures. In addition, image-processing edge detection techniques were used to delineate the lateral boundaries of each type of architecture. Herein, an innovative methodology is proposed for seismic- and well-data integration to achieve the fine-scale characterization of favorable coal–rock architectures under facies-type and architectural boundaries. Our findings provide both theoretical insights and technical guidance for the efficient exploration and development of coalbed methane gas in the Ordos Basin.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106092"},"PeriodicalIF":2.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145903959","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 : 2026-01-02DOI: 10.1016/j.jappgeo.2025.106090
Xinlei Cai , Qianyi Li , Xuliang Feng , Yang Zhang , Zheng Li , Tong Luo , Mingpu Fan , Guoqiang Zhang , Mengyao Li
Helium, an important strategic rare gas resource, has a wide range of industrial applications and utilization value. Weihe Basin in central China exhibits considerable potential for the development of helium resource. The origin of helium is predominantly governed by helium source rocks. However, the distribution of helium source rocks in Weihe Basin remains unclear at least. The aeromagnetic survey is an essential method to find out the distribution characteristics of helium source rock. In 2018, Shaanxi Gas Group Co., Ltd. obtained the first helium exploration right of China in the Huazhou-Huayin area of Weihe Basin. Aeromagnetic surveys at a scale of 1:50,000 were conducted in the Huazhou-Huayin area, and yielding high-quality magnetic field data. Using the outcrop of granite pluton nearly study area as a reference, the residual magnetic anomalies potentially associated with helium source rocks were extracted from the magnetic anomalies reduced to the pole. Three-dimensional magnetic susceptibility inversion was performed to delineate the spatial distribution of these source rocks, and the results indicate that Huashan pluton is the primary helium source rock in the Huazhou-Huayin area. The Dafuyu granite body, locating in the west of Huashan pluton, extends approximately 5000 m northward beneath the thick sedimentary cover. The granites encountered in the boreholes may be sporadically distributed by analyzing the magnetic susceptibility and reflection features of two seismic profiles. From the perspective of the distribution feature for the helium source rocks, the future efforts should be focused on the central part of the study area, particularly in the regions where the Dafuyu granite body extends northward into Weihe Basin.
{"title":"Spatial distribution and geological significance of helium source rocks revealed by 3D magnetic inversion in the Huazhou-Huayin area, Weihe Basin","authors":"Xinlei Cai , Qianyi Li , Xuliang Feng , Yang Zhang , Zheng Li , Tong Luo , Mingpu Fan , Guoqiang Zhang , Mengyao Li","doi":"10.1016/j.jappgeo.2025.106090","DOIUrl":"10.1016/j.jappgeo.2025.106090","url":null,"abstract":"<div><div>Helium, an important strategic rare gas resource, has a wide range of industrial applications and utilization value. Weihe Basin in central China exhibits considerable potential for the development of helium resource. The origin of helium is predominantly governed by helium source rocks. However, the distribution of helium source rocks in Weihe Basin remains unclear at least. The aeromagnetic survey is an essential method to find out the distribution characteristics of helium source rock. In 2018, Shaanxi Gas Group Co., Ltd. obtained the first helium exploration right of China in the Huazhou-Huayin area of Weihe Basin. Aeromagnetic surveys at a scale of 1:50,000 were conducted in the Huazhou-Huayin area, and yielding high-quality magnetic field data. Using the outcrop of granite pluton nearly study area as a reference, the residual magnetic anomalies potentially associated with helium source rocks were extracted from the magnetic anomalies reduced to the pole. Three-dimensional magnetic susceptibility inversion was performed to delineate the spatial distribution of these source rocks, and the results indicate that Huashan pluton is the primary helium source rock in the Huazhou-Huayin area. The Dafuyu granite body, locating in the west of Huashan pluton, extends approximately 5000 m northward beneath the thick sedimentary cover. The granites encountered in the boreholes may be sporadically distributed by analyzing the magnetic susceptibility and reflection features of two seismic profiles. From the perspective of the distribution feature for the helium source rocks, the future efforts should be focused on the central part of the study area, particularly in the regions where the Dafuyu granite body extends northward into Weihe Basin.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"245 ","pages":"Article 106090"},"PeriodicalIF":2.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924746","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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