Acta Geophysica最新文献

{"title":"Analysis of global ionospheric TEC disturbances during the October 2024 G5 geomagnetic storm","authors":"Huihui Fan,&nbsp;Shuhui Li,&nbsp;Yu Wang,&nbsp;Junsheng Wu,&nbsp;Ruihao Luo,&nbsp;Lihua Li","doi":"10.1007/s11600-026-01965-7","DOIUrl":"10.1007/s11600-026-01965-7","url":null,"abstract":"<div><p>Using multi-source observational data from GPS receivers, magnetometers, Swarm satellites, and the GUVI/TIMED satellite, this study analyzed the ionospheric total electron content (TEC) response to a G5 geomagnetic storm of October 2024 across the American, European–African, and East Asian–Australian longitudinal sectors. The results reveal significant longitudinal-sector differences and north–south asymmetry in the global ionospheric response. Positive storms predominated in the American sector, associated with strong eastward prompt penetration electric field (PPEF), whereas the European–African and East Asian–Australian sectors were characterized primarily by negative storms driven by thermospheric O/N₂ depletion. The irregularity activity exhibited a clear latitudinal dependence: at high latitudes, the Rate of TEC Index (ROTI) reached values 5–6 times those of quiet periods, with the occurrence rate of ROTI &gt; 0.5 exceeding 70%. Combined analysis of GUVI/TIMED satellite and geomagnetic observation data indicated that the PPEF was the key driver of the initial TEC enhancement in the equatorial anomaly region. In contrast, thermospheric composition changes, specifically a decrease in the O/N₂ ratio, were the primary cause of the subsequent negative storms at middle and high latitudes. Thus, the spatiotemporal evolution of the ionospheric storm is attributed to the nonlinear coupling of multiple processes, including the global ring current, regional current systems, and background thermospheric circulation, which collectively produce pronounced longitudinal-sector variability.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 5","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148661903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive flood hazard index: a probabilistic framework for flood risk assessment","authors":"Ayesah Waseem,&nbsp;Zulfiqar Ali,&nbsp;Muhammad Mohsin,&nbsp;Rizwan Niaz,&nbsp;Naim Ahmad","doi":"10.1007/s11600-026-01963-9","DOIUrl":"10.1007/s11600-026-01963-9","url":null,"abstract":"<div><p>Climate change and global warming are expected to worsen in the future, significantly increasing the severity and frequency of extreme events. This study specifically focuses on floods, which are considered a complex natural hazard. Flooding poses substantial risks to ecosystems, communities, and economies worldwide. In this regard, flood monitoring and forecasting play a vital role in developing effective flood mitigation policies. Although several studies have been conducted in this context, accurate flood forecasts remain elusive. This research proposes a novel index: the adaptive flood hazard index (AFHI), designed to monitor floods more accurately and effectively. The framework of AFHI is based on three phases: (1) computation of standardized precipitation index (SPI) using the <i>K</i> components Gaussian mixture model (KCGMM) to classify the characteristics of the flood, (2) assessment of first-order steady-state probabilities (SSPs) of the Markov chain, (3) development of AFHI by incorporating the severity and probabilities of flood using SSPs. The research utilizes precipitation data from 22 CMIP6 GCMs across 94 locations in Pakistan, spanning longitudes <span>(62^{circ }text {E})</span>–<span>(75^{circ }text {E})</span> and latitudes <span>(24^{circ }text {N})</span>–<span>(37^{circ }text {N})</span>. The outcome of this study revealed 54% area of Pakistan has moderate probability (0.020–0.026) while about 8% area of Pakistan is observed with very high probability (0.033–0.038) of extreme flood for SSP5–8.5 at time scale 48. A large spatial extent of extreme flooding is observed in West Balochistan and East Sindh. Additionally, Gilgit Baltistan and Upper Punjab exhibit a significant risk of flooding hazards during the period 2015–2100.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 5","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148750711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mechanical degradation of limestone under thermo-chemical–mechanical coupling","authors":"Han Zihao,&nbsp;Meldi Suhatril,&nbsp;Huzaifa Hashim","doi":"10.1007/s11600-026-01978-2","DOIUrl":"10.1007/s11600-026-01978-2","url":null,"abstract":"<div><p>Limestone, a representative carbonate rock, plays a crucial role in the safety and long-term stability of deep energy exploitation, geothermal extraction, and underground storage. In engineering environments, it is often subjected to thermo–chemical–mechanical (T–C–M) coupling conditions involving mechanical disturbance, thermal stress, and acidic fluid erosion, leading to progressive deterioration. To elucidate the degradation mechanisms and dominant factors, an L₁₆ orthogonal experiment was conducted, with pre-stress, temperature, and pH at four levels each. Variations in porosity, <i>P</i>-wave velocity, and uniaxial compressive strength (UCS) were analyzed to quantify the coupling effects. The results show that limestone evolves from a dense to a fissured structure under multi-field coupling. Temperature is the primary factor controlling degradation, followed by pre-stress, while acid erosion has a minor effect. UCS decreases by approximately 36% with increasing temperature and slightly with higher pre-stress. The degradation follows a “mechanical-induction–thermal driving–chemical synergy” pattern. A multiple-regression model (R² = 0.986) accurately predicts UCS variations under coupled conditions, providing an effective tool for strength assessment. This study offers new insights into the multi-field deterioration behavior of limestone and supports stability evaluation of surrounding rocks in geothermal reservoirs, deep tunnels, and CO₂ sequestration projects.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 5","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148661900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive flood hazard index: a probabilistic framework for flood risk assessment","authors":"Ayesah Waseem,&nbsp;Zulfiqar Ali,&nbsp;Muhammad Mohsin,&nbsp;Rizwan Niaz,&nbsp;Naim Ahmad","doi":"10.1007/s11600-026-01963-9","DOIUrl":"10.1007/s11600-026-01963-9","url":null,"abstract":"<div><p>Climate change and global warming are expected to worsen in the future, significantly increasing the severity and frequency of extreme events. This study specifically focuses on floods, which are considered a complex natural hazard. Flooding poses substantial risks to ecosystems, communities, and economies worldwide. In this regard, flood monitoring and forecasting play a vital role in developing effective flood mitigation policies. Although several studies have been conducted in this context, accurate flood forecasts remain elusive. This research proposes a novel index: the adaptive flood hazard index (AFHI), designed to monitor floods more accurately and effectively. The framework of AFHI is based on three phases: (1) computation of standardized precipitation index (SPI) using the <i>K</i> components Gaussian mixture model (KCGMM) to classify the characteristics of the flood, (2) assessment of first-order steady-state probabilities (SSPs) of the Markov chain, (3) development of AFHI by incorporating the severity and probabilities of flood using SSPs. The research utilizes precipitation data from 22 CMIP6 GCMs across 94 locations in Pakistan, spanning longitudes <span>(62^{circ }text {E})</span>–<span>(75^{circ }text {E})</span> and latitudes <span>(24^{circ }text {N})</span>–<span>(37^{circ }text {N})</span>. The outcome of this study revealed 54% area of Pakistan has moderate probability (0.020–0.026) while about 8% area of Pakistan is observed with very high probability (0.033–0.038) of extreme flood for SSP5–8.5 at time scale 48. A large spatial extent of extreme flooding is observed in West Balochistan and East Sindh. Additionally, Gilgit Baltistan and Upper Punjab exhibit a significant risk of flooding hazards during the period 2015–2100.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 5","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148750533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction of a seasonal frozen soil capacitance-temperature model based on capacitance tomography and research into the evolution of the temperature field","authors":"Tianhua Liu,&nbsp;Miao Wang,&nbsp;Mingwei Hai","doi":"10.1007/s11600-026-01979-1","DOIUrl":"10.1007/s11600-026-01979-1","url":null,"abstract":"<div><p>The evolution of temperature distributions plays a critical role in governing freeze–thaw phase transitions and the associated alterations in the mechanical properties of seasonally frozen soils. Conventional subsurface temperature measurements are constrained by sparse spatial sampling, structural disturbance, and limited continuous-imaging capability, which restrict noninvasive characterization of frozen soil temperature fields. To overcome these limitations, the present study developed a semi-open capacitance testing apparatus for seasonally frozen soils, grounded in the principles of capacitance tomography. Calibration experiments were conducted to examine the relationship between capacitance and temperature under varying moisture contents and dry densities, with a focus on analyzing capacitance responses throughout the freeze–thaw cycle. The findings reveal that the capacitance of seasonally frozen soils exhibits a characteristic nonlinear “S”-shaped increase as temperature rises, with the most pronounced changes occurring between − 4 and 4 °C. This behavior is primarily attributed to variations in unfrozen water content and equivalent permittivity resulting from ice-water phase transitions. A capacitance–temperature model for seasonally frozen soils was formulated based on a Boltzmann-type function, with model parameters estimated via an orthogonal distance regression algorithm. This approach demonstrated superior fitting accuracy compared to the Levenberg–Marquardt algorithm. Additionally, by integrating multi-electrode capacitance measurements with a linear interpolation algorithm, the study achieved visualization of the temperature field within seasonally frozen soils and identified the temperature-sensitive range under unidirectional freezing conditions. The results show that capacitance responses capture the top-down evolution of the frozen soil temperature field, localize the 0 °C ice front, and track migration of the − 4 to 4 °C sensitive interval. The proposed method provides a nondestructive tool for monitoring seasonally frozen soil temperature fields, identifying freeze–thaw dynamics, and supporting early warning for cold region engineering safety.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 4","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148628563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coseismic magnetic field perturbations recorded during the 23 April 2025 Mw 6.2 Sea of Marmara earthquake, Türkiye","authors":"Elif Çiftçi,&nbsp;Özlem Hacıoğlu","doi":"10.1007/s11600-026-01975-5","DOIUrl":"10.1007/s11600-026-01975-5","url":null,"abstract":"<div><p>The Marmara region, situated along the seismically active North Anatolian Fault Zone (NAFZ) and including the densely populated Istanbul metropolitan area, is considered one of the most critical regions in Türkiye for a future large earthquake. This study investigates coseismic magnetic field perturbations recorded during the Mw 6.2 (KOERI) earthquake of 23 April 2025 in the Sea of Marmara, using geomagnetic data from the Iznik (IZN) observatory together with seismic records from nearby strong-motion stations. The primary aim is to evaluate whether the observed magnetic perturbations reflect physical crustal electromagnetic processes or are more plausibly associated with strong-motion-induced instrumental effects under single-station observational conditions. Transient magnetic disturbances were observed during the mainshock and two subsequent Mw 5.2 aftershocks. These signals appear simultaneously in all three geomagnetic components (H, D, and Z), emerge within the P and S wave arrivals, and exhibit impulsive, short-duration waveforms closely matching the corresponding seismic waveform records. The consistent timing, waveform similarity, and repeatability across multiple events indicate strong coupling between ground motion and the recorded magnetic variations. Rather than indicating a primary crustal electromagnetic source, the observed characteristics are more consistent with strong-motion–induced mechanical instrumental effects, likely caused by mechanical coupling between seismic vibrations and the geomagnetic sensor system or its installation environment. These findings highlight the sensitivity of high-resolution geomagnetic measurements to intense ground motion and demonstrate how synchronous seismic observations can help identify likely motion-induced magnetic artifacts, even under limited observational conditions such as single-station geomagnetic measurements and low sampling rate data. The combined analysis of geomagnetic and seismic data provides a framework for identifying such disturbances and underscores the importance of rigorous instrumental assessment in tectonically active regions such as the NAFZ.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 4","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148615012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated terrain analysis and SWAT-based modeling for assessing hydrological dynamics of the Upper Jhelum River Basin, Pakistan","authors":"Samavia Shahid,&nbsp;Muhammad Nasar-u-Minallah,&nbsp;Muhammad Saad,&nbsp;Muhammad Waqar,&nbsp;Mohamed Hassan Fathima Nuskiya","doi":"10.1007/s11600-026-01980-8","DOIUrl":"10.1007/s11600-026-01980-8","url":null,"abstract":"<div><p>Understanding the interactions among terrain characteristics, land-use dynamics, and hydrological processes is essential for sustainable watershed management, particularly in mountainous river basins experiencing strong hydro-climatic variability and increasing anthropogenic pressure. The Upper Jhelum River Basin (UJRB), a major sub-basin of the Upper Indus Basin (UIB), is highly susceptible to soil erosion, seasonal runoff variability, and land-use changes, necessitating an integrated modeling approach for effective assessment. This study integrated Geographic Information System (GIS)-based terrain analysis with the Soil and Water Assessment Tool (SWAT) to evaluate watershed hydrological dynamics. Terrain indices, including slope, aspect, Stream Power Index (SPI), and Topographic Wetness Index (TWI), were derived from a 30-m Shuttle Radar Topography Mission (SRTM) Digital Elevation Model. The SWAT model was calibrated and validated using observed monthly streamflow data, and model performance was evaluated using the Nash–Sutcliffe efficiency (NSE) and coefficient of determination (R²). Spatial and statistical analyses were conducted to examine runoff and sediment yield responses at sub-basin and hydrological response unit (HRU) levels in relation to terrain attributes and land-use/land-cover (LULC) patterns. The SWAT model demonstrated good performance, achieving an NSE of 0.81 and R² of 0.84 during calibration, and an NSE of 0.78 and R² of 0.81 during validation, indicating satisfactory simulation of monthly streamflow. The results revealed pronounced seasonal variability in streamflow, characterized by a primary peak during the monsoon season and a secondary peak associated with spring snowmelt. Sediment yield analysis identified northern sub-basins as erosion hotspots, largely due to steep slopes and elevated SPI values. Statistical analyses confirmed that slope, SPI, and LULC were the dominant factors controlling hydrological response and erosion processes across the basin. The integrated GIS–SWAT framework effectively captured the complex interactions between terrain features, land-use patterns, and hydrological processes in the Upper Jhelum River Basin. The findings underscore the need for targeted soil conservation measures, reforestation initiatives, and land-use planning in erosion-prone sub-basins. The originality of this study lies in the systematic linkage of multiple terrain indices with SWAT outputs at sub-basin and HRU scales, providing a robust, spatially explicit basis for informed watershed management and policy development in data-scarce mountainous regions.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 4","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148614716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electrical resistivity tomography for water-bearing structures incorporating the interference distribution pattern of steel arch in tunnels","authors":"Lichao Nie,&nbsp;Yu Zhou,&nbsp;Zhicheng Song,&nbsp;Zhi-Qiang Li,&nbsp;Guoan Chu,&nbsp;Shuo Zhang","doi":"10.1007/s11600-026-01976-4","DOIUrl":"10.1007/s11600-026-01976-4","url":null,"abstract":"<div><p>As underground infrastructure expands into increasingly complex geological environments, ensuring construction safety against unforeseen hazards has become a paramount engineering priority. In tunnel engineering, water-bearing geological anomalies represent the primary cause of severe water and mud inrush disasters. While advanced geological prediction using the direct current (DC) resistivity method is a crucial preventative measure, its accuracy is often severely compromised by electromagnetic interference from widely distributed steel arch supports. To address this, this study proposes a novel Bayesian inversion imaging approach. Based on 3D forward modeling, we quantitatively establish that steel arch-induced interference approximately follows a zero-mean Gaussian distribution. By embedding the likelihood function of this interference directly into the inversion objective function using a maximum a posteriori (MAP) framework, we eliminate the need for traditional preliminary denoising steps. Numerical simulations verify that the proposed method accurately reconstructs the geometry and location of low-resistivity anomalies at distances of 10 m and 20 m ahead of the face, significantly outperforming conventional scaling coefficient methods. Field application in the Xianglu Mountain No. 2 Tunnel of the Central Yunnan Water Diversion Project successfully identified potential water-bearing structures within 20 m ahead of the tunnel face. The quantitative predictions were highly consistent with the actual excavation records, indicating that the proposed method can significantly improve the safety, efficiency, and reliability of resistivity-based advanced geological prediction.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 4","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148614718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of sustainable groundwater management under climate change scenarios using an integrated MODFLOW-NSGA-II framework: a case study of Sidi Okba Region, Algeria","authors":"Amina Maansri,&nbsp;Abdelhamid Messameh,&nbsp;Mohamed R. Torkomany","doi":"10.1007/s11600-026-01970-w","DOIUrl":"10.1007/s11600-026-01970-w","url":null,"abstract":"<div><p>The present research evaluates the long-term sustainability of groundwater resources in the Mio-Pliocene aquifer of the Sidi Okba region (Algeria) under evolving climatic conditions. A numerical groundwater flow model was developed using the MODFLOW code, calibrated under steady-state (2006) and transient-state (2006–2010) conditions, and subsequently validated (2011–2012). The model reproduced observed heads with good agreement (<i>R</i>² = 0.993; RMSE = 1.42), within the limits of available monitoring data. Sensitivity analysis indicated that the aquifer’s hydraulic response is predominantly influenced by hydraulic conductivity, specific yield, and pumping rates. Future projections for 2020–2050 period were conducted under SSP2-4.5 and SSP5-8.5 climate scenarios, incorporating climate-induced recharge variability while maintaining constant pumping rates to isolate the hydraulic impact of recharge from anthropogenic stresses. The simulations suggest limited sensitivity of drawdown to projected recharge variability under the assumed pumping conditions, predicting a stable drawdown of approximately 6.9 m. The optimization results indicate a potential increase in simulated pumping capacity under the imposed constraints, although these outcomes remain contingent on model assumptions and data availability. An optimization framework using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) was implemented to maximize groundwater withdrawal while satisfying irrigation demands under the SSP5-8.5 scenario. Operational constraints were defined for 424 wells, limiting the maximum allowable drawdown to 25% of the available water column above the screen top. The optimization results revealed a potential increase in the total pumping rate from 144.9 million m³/year to 344.5 million m³/year, representing a 137% enhancement in water supply capacity. Under this optimized regime, the maximum cumulative drawdown reached 7.2 m, reflecting a marginal 4.6% increase in drawdown compared to the pre-optimization stage. These findings suggest that strategic abstraction management could potentially accommodate increasing water requirements. However, these outcomes should be interpreted as model-based scenarios rather than definitive indicators, given the inherent uncertainties in storage parameters and the limited observation well network.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 4","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148614715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prior-constrained closed-loop dual network for semi-supervised pre-stack seismic inversion","authors":"Xudong Ke,&nbsp;Zhou Zhao,&nbsp;Chuanhui Li,&nbsp;Fanchang Zhang","doi":"10.1007/s11600-026-01973-7","DOIUrl":"10.1007/s11600-026-01973-7","url":null,"abstract":"<div><p>To address the issues that deep learning inversion relies heavily on labeled data and tends to produce results inconsistent with geological principles, this paper proposes a semi-supervised closed-loop dual-network pre-stack seismic inversion method based on prior constraints. The method builds a closed-loop dual-network framework based on residual networks. By coupling the forward and inversion networks in an end-to-end manner and incorporating a cycle-consistency loss, hard physical constraints from forward modeling are imposed. Furthermore, a loss-function embedding fusion strategy is designed, where low-frequency data are treated as pseudo-labels for unlabeled samples to construct an independent loss term. This term is then combined through tunable weights with the supervised loss and the cycle-consistency loss, ultimately forming a multi-objective joint optimization paradigm that integrates “hard physical constraints” and “soft low-frequency constraints.” Validation on synthetic data and real field data demonstrates that the method can be efficiently trained with only a limited amount of well-log data. The inversion results exhibit high vertical resolution, clearly delineated formation boundaries, and a profile energy distribution that conforms to geological patterns, showing strong agreement with the true model and blind well data. This approach effectively mitigates the limitation of scarce labeled data, enhances the physical plausibility and interpretability of the inversion results, and provides reliable technical support for high-precision seismic interpretation and detailed reservoir characterization.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 4","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148614238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}