Journal of Applied Geophysics最新文献

{"title":"Three-dimensional anisotropic modelling of magnetotelluric data to determine the boundary between cap rock and reservoir formation: A case study of the Sarab field, Iran","authors":"Mohammad Filbandi Kashkouli ,&nbsp;Matthew J. Comeau ,&nbsp;Milad Farshad ,&nbsp;Abolghasem Kamkar-Rouhani","doi":"10.1016/j.jappgeo.2025.106077","DOIUrl":"10.1016/j.jappgeo.2025.106077","url":null,"abstract":"<div><div>Reservoirs of interest for resource exploration, including geothermal and hydrocarbon reservoirs, commonly have an impermeable cap, which traps fluids below. Identifying this boundary is important for resource development. The cap rock for hydrocarbon reservoirs in southwest Iran contains evaporites and thus some geophysical exploration methods, specifically seismic reflection, have faced problems recovering subsurface information in this environment. As an alternative, we generate an electrical resistivity model from magnetotelluric (MT) data. Furthermore, we consider three-dimensional triaxial electrical anisotropy, which is rarely done. The study objectives are to a) define and map the boundary between the cap rock and the principal reservoir, b) characterize geological and tectonic formations in the area, and c) analyze the tectonic factors influencing the evolution of the region. A total of 359 MT measurements were acquired across the Sarab field in an array consisting of five profiles separated by &gt;2000 m with a measurement spacing of &gt;200 m. Transient electromagnetic (TEM) measurements were co-located with the MT measurements at 181 locations and used to correct for static shifts. Isotropic and anisotropic inversions of the MT data were performed, using all impedance tensor elements. The anisotropic electrical resistivity model exhibits both a significantly better alignment with the depths of geological formations known from drilling data and a better fit to the data. Therefore, the boundary between the primary cap rock and principal reservoir, the Gachsaran and Asmari formations, is defined and mapped across the survey area. In addition, major tectonic and fault-related features in the region are identified.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106077"},"PeriodicalIF":2.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928697","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}

{"title":"Interferometric synthetic aperture sonar for high-resolution seafloor mapping and imaging in contrasting geomorphological and benthic settings","authors":"Caroline Gini ,&nbsp;John W. Jamieson ,&nbsp;Craig J. Brown ,&nbsp;Brian Carroll ,&nbsp;Richard Charron ,&nbsp;David Shea ,&nbsp;Katleen Robert","doi":"10.1016/j.jappgeo.2025.106087","DOIUrl":"10.1016/j.jappgeo.2025.106087","url":null,"abstract":"<div><div>Seafloor exploration for geological or biological studies ideally requires high resolution survey data over a large area. However, there is a trade-off between resolution and coverage using conventional acoustic imaging and mapping techniques. The recent development of interferometric synthetic aperture sonar (InSAS), which provides high resolution imagery and bathymetry (3 and 25 cm/pixel, respectively) over large areas of seafloor, and has primarily been used for military and commercial purposes, opens the door for new applications for geological mapping, and seafloor classification and monitoring. For these applications, the processing steps, survey parameters and requirements for InSAS surveying, compared to conventionally used techniques such as multibeam echosounders and side-scan sonars, are not well defined. In this study, we describe and discuss the results of InSAS surveys in two contrasting geological and benthic settings: a relatively flat continental shelf, and a topographically complex mid-ocean ridge. Features of sizes down to 6 cm were identified on the imagery, including lava flow crust lineations, bedrock sedimentary bedding, gravels, and discarded rope. We found that seafloor features &lt;1 m high were better imaged than taller features, such as hydrothermal vents or faults. We test and quantify survey parameters necessary to optimize data quality for effective use for scientific applications. Our results indicate that seafloor bathymetry is the most important consideration to maximize likelihood of data generation success and data quality when planning InSAS surveys.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106087"},"PeriodicalIF":2.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928776","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}

{"title":"Research on multi-physics field collaborative detection methods for concealed fire zones: Based on variable-temperature magnetic-dielectric-resistive characteristics","authors":"Xiaokun Zhao ,&nbsp;Jun Ge ,&nbsp;Wencai Wang ,&nbsp;An Zhang ,&nbsp;Yuhua Bai ,&nbsp;Yong Liu ,&nbsp;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":"2026-03-01","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}

{"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 ,&nbsp;Juzhi Deng ,&nbsp;Fasheng Lou ,&nbsp;Yang Gao ,&nbsp;Zequn Wen ,&nbsp;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 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.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106088"},"PeriodicalIF":2.1,"publicationDate":"2026-03-01","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}

{"title":"A data-driven approach for identification of coal-related lithofacies using single and meta-learner ensemble classifiers from well-log data: A case study from Sohagpur coal field, India","authors":"Rupam Roy ,&nbsp;Dip Kumar Singha ,&nbsp;Sayan Ghosh ,&nbsp;Laraib Abbas ,&nbsp;Debjeet Mondal","doi":"10.1016/j.jappgeo.2025.106073","DOIUrl":"10.1016/j.jappgeo.2025.106073","url":null,"abstract":"<div><div>This study focuses on building a set of classification models based on single Machine Learning (ML) classifiers, followed by utilization of the trained single classifiers to construct optimized homogeneous, heterogeneous, and stacked ensemble learners to predict coal, carbonaceous shale, and non-coal lithofacies solely based on a set of high resolution conventional well-log data. A total of 6 lithofacies were considered as classes set as the target variable, along with 5 variables as input features obtained from well-log data from 3 wells (well-1, well-2, and well-3) to construct the training data. A couple of wells (well-4, 5) were utilized as blind testing wells to evaluate all 12 classification models, one of them (well-4) having a true litholog. A high inherent imbalance was observed in the class distribution for both the training as well as blind testing datasets. The imbalance issue was resolved by utilizing the class weight parameter assigned to certain classifiers and randomly removing the dominant (the sandstone) class through a random under-sampling operation in Python. The trained single classifiers, despite having overall good performance on blind datasets, were poor at identifying the coal, sandy shale, shaly coal, and carbshale. However, the trained heterogeneous ensemble is proven to be the best classifier among the 12, both class-wise and in terms of overall accuracy (more than 90 %), and the stacked ensemble learner is the second best, as far as coal, carbshale, and shaly coal are concerned. In the case of the homogeneous ensemble learners, the class-wise prediction performance has improved considerably, and all the homogeneous ensemble learners have performed better than their respective single classifier counterparts. This study successfully verified the usefulness of stacked, homogeneous, and heterogeneous ensemble meta learners over the single classifier models, for coal, non-coal, and carbonaceous lithofacies identification, both class-wise and in an overall manner.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106073"},"PeriodicalIF":2.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928694","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}

{"title":"Microseismic identification and effectiveness assessment of hydraulic-fracturing–induced roof cutting using an STFT–CNN framework","authors":"Haowei Tian ,&nbsp;Zhizhong Jiang ,&nbsp;Zhenqian Ma ,&nbsp;Zhijie Wen ,&nbsp;Shaojie Zuo ,&nbsp;Yu Liu ,&nbsp;Jinhui Li ,&nbsp;Wenjian Wang ,&nbsp;Mingying Wang ,&nbsp;Youchi Jin","doi":"10.1016/j.jappgeo.2025.106078","DOIUrl":"10.1016/j.jappgeo.2025.106078","url":null,"abstract":"<div><div>During underground mining of solid mineral deposits, hard roofs can induce large-scale strata pressure disasters, posing severe threats to mine safety. Hydraulic-fracturing-based roof-cutting technology offers a means of weakening hard roofs by severing key structural connections, thereby altering the roof structure and reducing the likelihood of roof-related accidents. However, limitations remain in accurately characterizing fracture propagation and evaluating the effectiveness of hydraulic fracturing roof cutting. In this study, a coal mine in southwestern China was selected as the engineering site. By integrating hydraulic-fracturing roof cutting with microseismic monitoring, a hydraulic-fracturing microseismic event recognition model based on the Short-Time Fourier Transform (STFT) and Convolutional Neural Networks (CNN) was developed. Time-frequency analysis revealed that different microseismic signal types exhibit distinct dominant frequency ranges, with hydraulic-fracturing signals concentrated at 130–200 Hz. The proposed STFT–CNN model achieved a recognition accuracy exceeding 92 %. Microseismic source-location and kernel density analyses indicated that hydraulic-fracturing-induced fractures propagated symmetrically along the borehole axis, with an effective influence range of approximately ±5 m horizontally and ± 10 m vertically, and some fractures extending downward into the coal seam. Analysis of microseismic energy evolution showed abrupt energy surges when the working face advanced 1–2 m past the roof-cutting boreholes, with more than three high-magnitude events typically occurring about 3 m behind the working face. Overall, the field results demonstrate that hydraulic fracturing effectively weakened the hard roof and successfully facilitated controlled roof collapse, thereby enhancing the safety of underground coal extraction.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106078"},"PeriodicalIF":2.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928775","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}

{"title":"Triple-duty distributed acoustic sensing in urban environments: Concurrent subsurface imaging, pipeline diagnostics, and traffic surveillance","authors":"Ao Song ,&nbsp;Aichun Liu ,&nbsp;Zhixiang Li ,&nbsp;Guanzhong Liu ,&nbsp;Aipeng Guo ,&nbsp;Junfeng Jiang","doi":"10.1016/j.jappgeo.2026.106117","DOIUrl":"10.1016/j.jappgeo.2026.106117","url":null,"abstract":"<div><div>This study presents an innovative application of Distributed Acoustic Sensing (DAS) by repurposing urban sewer pipelines into a large-scale sensing network through the deployment of fiber-optic cables. This approach facilitates three major applications: subsurface imaging, pipeline blockage detection, and urban traffic monitoring. Using passive seismic interferometry on ambient noise signals acquired via the in-pipe fiber, we reconstructed high-resolution shear-wave velocity profiles of the shallow urban subsurface. Combined analysis of field data and numerical simulations identified characteristic patterns associated with pipeline blockages in cross-correlations (CCs), which were validated through closed-circuit television (CCTV) inspections. For traffic monitoring, vehicle-induced vibrations were processed using seismic attribute analysis and a U-Net convolutional neural network, enabling precise vehicle trajectory identification and speed estimation based on Hilbert instantaneous amplitude attributes. The results demonstrate that the proposed DAS-based method offers a non-invasive, cost-effective, and scalable solution for integrated urban monitoring, providing a sustainable alternative to traditional point-based sensing and enabling continuous, large-scale infrastructure assessment in densely populated areas.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106117"},"PeriodicalIF":2.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038842","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}

{"title":"High-resolution elastic full-waveform inversion using dual-channel CNN and Kolmogorov–Arnold network","authors":"Faxuan Wu,&nbsp;Yang Li,&nbsp;Zhenwu Fu,&nbsp;Bo Han,&nbsp;Yong Chen","doi":"10.1016/j.jappgeo.2026.106095","DOIUrl":"10.1016/j.jappgeo.2026.106095","url":null,"abstract":"<div><div>Elastic full-waveform inversion (EFWI) can provide high-resolution subsurface structures and physical properties by iteratively matching observed and synthetic data. However, the success of EFWI relies on the availability of a good initial model and high signal-to-noise ratio observed data with sufficient low-frequency information, both of which are often challenging to obtain in practical applications. In addition, the coupling of different parameters degrades the inversion result. Recently, inversion methods based on physics-informed deep neural networks (DNN) have proven effective in mitigating the issue of multiple local minima caused by inaccurate initial models, missing low-frequency information, and noisy seismic data. However, existing DNN-based approaches commonly rely on fixed activation functions (e.g., rectified linear unit). In addition, their capacity to represent high-frequency components – namely, fine-scale structural details – is inherently limited due to spectral bias. These limitations may, in turn, impede their broader applicability. To mitigate this issue, we propose a model reparameterized EFWI method based on a dual-channel convolutional neural network (CNN) and Kolmogorov–Arnold networks (KAN) to enhance the reconstruction of fine-scale structural details. Specifically, our network incorporates KAN into the U-Net architecture, where CNN and KAN operate in dual channels to efficiently capture nonlinear relationships in the data. The hybrid network maps an initial model to the subsurface parameter model, with the output of the network serving as input for partial differential equations (PDEs) to generate synthetic data. Various numerical examples are conducted to investigate the performance of the inversion method, including its ability to mitigate the parameter crosstalk issue, the effect of noise and missing low-frequency information, and the influence of different initial models and network inputs. The numerical results demonstrate that, by combining CNN’s fixed activation functions with KAN’s inherently learnable activations, our method – despite a modest increase in computational cost – outperforms both EFWI and CNN-based reparameterized EFWI in reconstruction accuracy and convergence efficiency.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106095"},"PeriodicalIF":2.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980131","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}

{"title":"Petrophysics and mass balance integration for alteration detection in orogenic gold exploration","authors":"Yasaman Nemati ,&nbsp;J. Christian Dupuis ,&nbsp;Benoit Quesnel ,&nbsp;Bernard Giroux ,&nbsp;Richard Smith ,&nbsp;Georges Beaudoin","doi":"10.1016/j.jappgeo.2026.106114","DOIUrl":"10.1016/j.jappgeo.2026.106114","url":null,"abstract":"<div><div>This study explores the integration of petrophysical and geochemical data to characterize hydrothermal alteration in mafic and ultramafic rocks, with a focus on the Augmitto-Bouzan orogenic gold deposit in the Abitibi Greenstone Belt. Employing established mass balance techniques using zirconium (Zr) as the immobile reference element, we quantified element mobility during alteration processes. Due to the absence of original komatiite protolith data, we compiled geochemical compositions from published sources across the Superior Province and applied bootstrapping to derive a representative baseline for mass balance calculations, which were then correlated with petrophysical logs from multiple boreholes to identify modification signatures. The analysis reveals robust correlations: potassium enrichment aligns with elevated gamma-ray responses, carbonate alteration is marked by increased CaO and reduced density, and magnetic susceptibility decreases correspond to Fe-Mg depletion and sulfide mineralization. These observations demonstrate systematic links between geochemical changes and petrophysical data, showing that petrophysical logs can serve as high-resolution, cost-effective proxies for alteration mapping, offering a scalable framework for exploration targeting in orogenic gold systems hosted in ultramafic rocks. The methodology bridges traditional geochemistry and in-situ measurements of physical properties, improving subsurface characterization and supporting the development of data-driven exploration tools while advancing our understanding of processes associated with gold mineralization.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106114"},"PeriodicalIF":2.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079089","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}

{"title":"A proposed brittleness index model based on shale multicomponent digital cores","authors":"Haitao Wang ,&nbsp;Fuqiang Lai ,&nbsp;Min Wang ,&nbsp;Zhaohui Huang ,&nbsp;Zhangxiong Zhu ,&nbsp;Yuejiao Liu ,&nbsp;Xianfeng Tan ,&nbsp;Huaimin Dong ,&nbsp;Ye Yang","doi":"10.1016/j.jappgeo.2026.106110","DOIUrl":"10.1016/j.jappgeo.2026.106110","url":null,"abstract":"<div><div>The exploitation of organic shale reservoirs depends on the brittleness affected by lamination, fracture, porosity, and minerals. However, the existing brittleness index for petroleum only considers mineral types and requires comprehensive characterization. Therefore, a multicomponent model was constructed by inserting a planar fracture, planar lamination, and gas saturation model into a multimineral model using the Markov-chain Monte Carlo method. The elastic parameters were calculated using a finite element method, and the sensitivity of the parameters to the brittleness index defined by the Young's modulus and Poisson's ratio was determined using Morris screening and analytical hierarchy process methods. The investigation indicated that the development of brittle minerals and fracture porosity increased the brittleness index and, Young's modulus and decreased the Poisson's ratio, whereas the fracture width decreased the brittleness index, Gas saturation increases the brittleness index. A new comprehensive brittleness index was proposed in which the sensitivity decreased from the dip angle, azimuthal angle of fracture, dip angle of lamination, width and length of fracture, mineral types, width, and azimuthal angle of lamination to gas saturation. The proposed brittleness model was applied to a shale reservoir and is helpful in further identifying zones for hydraulic fracturing.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"246 ","pages":"Article 106110"},"PeriodicalIF":2.1,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079200","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}