Journal of Applied Geophysics最新文献

A study on seismic data acquisition techniques in the U-shaped valley of Yarlung Zangbo River

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-04-22 DOI: 10.1016/j.jappgeo.2025.105750

Jun Zhang , Rongyi Qian , Zhenning Ma , Xiaoqiong Lei , Xu Liu , Jianyu Ling , Guibin Zhang

The Yarlung Zangbo River, as the most prominent waterway on the Tibetan Plateau, plays pivotal role in investigating the tectonic evolution and hydrological processes of the Tibetan Plateau. The Second Tibetan Plateau Expedition focused on the high-resolution seismic exploration of the depositional structure within the U-shaped valley of the Yarlung Zangbo River. Confronted with the unique surface conditions of the valley, characterized by extensive cobblestone riverbanks, aeolian deposits, and steep mountainous terrain, coupled with the swift flow and broad expanse of the Yarlung Zangbo River channel, this study initially employed a methodology based on full-wavefield numerical simulation. An analysis of the formation process of intersecting event of reflection wave induced by the U-shaped valley was conducted. This elucidated the impact of the valley substrate interface characterized by varying inclinations on reflection waves. Moreover, addressing challenges posed by seismic data gaps resulting from river-induced interference, the study designed a geometry to mitigate issues arising from diffracted and converted waves. This approach proved conducive to achieving high-precision imaging of the valley morphology. Subsequently, considering the stringent ecological constraints in the Qinghai-Tibet region, where traditional destructive seismic sources are impractical, the study explored the utilization of unmanned aerial vehicle (UAV) seismic sources. This innovative approach overcame the constraints of conducting seismic wave stimulation in locally complex areas such as river channels, aeolian sand regions, and steep mountainous terrain. In conjunction with lightweight and efficient nodal geophones, the study successfully executed a cost-effective, high-quality data acquisition experiment. The obtained seismic reflection data on riverbank deposits exhibit a reliable high signal-to-noise ratio (SNR), offering a geophysical foundation for investigating the formation and evolution of the Yarlung Zangbo River during the Second Tibetan Plateau Expedition.

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引用次数: 0

Sequential 3D inversion strategy of airborne geophysical survey data for exploration of ore mineral deposits overlapped by layers with heterogeneous conductivity and magnetic susceptibility

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-04-17 DOI: 10.1016/j.jappgeo.2025.105738

Marina G. Persova, Yuri G. Soloveichik, Anastasia P. Sivenkova, Denis V. Vagin, Dmitry S. Kiselev, Yulia I. Koshkina

We present a sequential 3D inversion strategy for airborne electromagnetic and magnetic survey data when searching for areas characterized by high values of conductivity and magnetic susceptibility, in a situation where these are overlapped by layers with heterogeneous conductivity and magnetic susceptibility. We explore the possibility of obtaining equivalent models for magnetic survey data (i.e. models that are quite different from each other but give the same data responses). It is shown that for relatively deep bodies overlapped by heterogeneous (in magnetic properties) layers, only an upper estimate of their magnetic susceptibility is possible. A sequential 3D inversion strategy of electromagnetic (EM) and magnetic data is proposed. An important component of this strategy is a two-stage 3D EM data inversion, which allows the high-precision reconstruction of the geometry and depth of local conductive bodies underlying heterogeneous conductivity layers. The final stage of the strategy is to determine whether the discovered local bodies may have enhanced magnetic properties. To test the proposed approach, we use data from an airborne geophysical survey performed in the Creighton area (Canada) in search for polymetallic ores. The sequential 3D inversion is carried out for an airborne electromagnetic survey dataset and two magnetic survey datasets at different flying height levels. Comparison with drilling data indicates that the proposed sequential 3D inversion strategy allows not only identification of prospective areas, but also improves planning of well drilling trajectories.

我们提出了一种针对机载电磁和磁勘测数据的顺序三维反演策略，用于搜索具有高电导率和磁感应强度特征的区域，以及这些区域与具有异质电导率和磁感应强度的地层重叠的情况。我们探讨了获得磁力勘测数据等效模型的可能性（即模型之间存在很大差异，但给出的数据响应相同）。结果表明，对于由异质（磁特性）层重叠的相对较深的岩体，只能对其磁感应强度进行上限估算。提出了电磁（EM）和磁数据的顺序三维反演策略。该策略的一个重要组成部分是两阶段三维电磁数据反演，可高精度重建异质导电层下局部导电体的几何形状和深度。该策略的最后阶段是确定已发现的局部体是否可能具有增强磁性。为了测试所提出的方法，我们使用了在克里顿地区（加拿大）为寻找多金属矿而进行的航空地球物理勘测数据。我们对不同飞行高度下的一个机载电磁勘测数据集和两个磁性勘测数据集进行了顺序三维反演。与钻探数据的比较表明，所提出的顺序三维反演策略不仅可以确定远景区，还可以改进钻井轨迹的规划。

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引用次数: 0

A novel approach for identifying sweet spots in tight reservoir fracturing engineering based on physical-data dual drive

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-04-17 DOI: 10.1016/j.jappgeo.2025.105735

Huohai Yang , Fuwei Li , Wei Wang , Yu Fu , Qinxi Tang , Jie Yang , Binghong Xie

Reservoir engineering sweet spot identification is a crucial prerequisite for fracture interval selection and hydraulic fracturing design. Rock mechanical parameters serve as key indicators for evaluating engineering sweet spots. To accurately predict the rock mechanical parameters of tight reservoirs, a physics-informed NSGA-PINN (Non-dominated Sorting Genetic Algorithm combined with Physics-Informed Neural Networks) model was developed, achieving prediction accuracies exceeding 90 % for four rock mechanical parameters, outperforming purely data-driven models such as RF (Random Forest), CatBoost, LightGBM, and BPNN (Back Propagation Neural Network). On this basis, an intelligent evaluation method for engineering sweet spots was established by integrating mechanical parameters and brittleness index, and a fracturing sweet spot calculation model was constructed using a combined weighting approach. The results indicate that the physics-informed neural network model exhibits superior generalization and robustness, and the calculated sweet spot index shows a 91.2 % correlation with post-fracturing gas well productivity, demonstrating the reliability of the proposed method. This approach can be effectively applied to the efficient development of gas reservoirs in the target block.

油藏工程甜点识别是压裂间隔选择和水力压裂设计的重要前提。岩石力学参数是评价工程甜点的关键指标。为了准确预测致密储层的岩石力学参数，开发了物理信息NSGA-PINN（非优势排序遗传算法与物理信息神经网络相结合）模型，对四个岩石力学参数的预测精度超过90%，优于RF（随机森林）、CatBoost、LightGBM和BPNN（反向传播神经网络）等纯数据驱动模型。在此基础上，综合力学参数和脆性指数，建立了工程甜点智能评价方法，并采用组合加权法构建了压裂甜点计算模型。结果表明，物理信息神经网络模型具有良好的概括性和鲁棒性，计算出的甜点指数与压裂后气井产能的相关性达到 91.2%，证明了所提方法的可靠性。该方法可有效应用于目标区块气藏的高效开发。

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引用次数: 0

3D inversion of airborne transient electromagnetic data using deep learning 利用深度学习对机载瞬变电磁数据进行三维反演

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-04-16 DOI: 10.1016/j.jappgeo.2025.105737

Shuowei Zhang , Rui Liu , Hao Feng , Zhihong Wang , Shangbin Liu , Yan Luo , Ziqiang Zheng , Huaifeng Sun

One-dimensional (1D) airborne transient electromagnetic (ATEM) inversion is still the most popular method applied in field data because the conventional three-dimensional (3D) method requires forward calculations during the inversion process, which is time-consuming, and the inversion results are highly influenced by the initial model. Moreover, the conventional 3D inversion process is unstable and susceptible to converging to local optima. However, the true underground structure is 3D, we need a 3D inversion to study the structure details. We present a novel deep-learning framework, ATEM3D-Net, designed for the 3D inversion of ATEM data. ATEM3D-Net leverages an encoder-decoder architecture that integrates 3D U-Net with ConvLSTM to perform an end-to-end mapping from electromagnetic response data to subsurface resistivity models, where the ConvLSTM can learn the spatiotemporal dependencies of ATEM data to obtain better inversion results. Furthermore, we optimize the network training strategy to make the network converge to the global optimal. We evaluate the performance of ATEM3D-Net using both forward modeling data and field model synthetic data, demonstrating its superior ability to handle noise and its generalization across different geological settings.

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引用次数: 0

An iterative laterally constrained inversion scheme for time-domain airborne electromagnetic data

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-04-16 DOI: 10.1016/j.jappgeo.2025.105729

Congde Lu , Jian Wang , Song Huang

The airborne electromagnetic (AEM) methods have been widely used in mineral prospecting, groundwater exploration, oil and gas resource investigation, and for many other purposes. Although the technical advances in 3D inversion are impressive, it is often not feasible to invert the field data from large AEM surveys with the huge amount of data. At present, 1D inversion and the quasi-2D inversion method based on the 1D model with imposed lateral continuity have been applied to invert the field data in AEM industry. In this paper, we propose a laterally constrained inversion scheme for time domain AEM data, based on a lateral correlation which effectively achieves both vertical and lateral smoothness. Firstly, all points of a survey line are inverted independently rather than simultaneously which is computationally very efficient. Secondly, at each iterative computation at each survey point, the inversion results of adjacent survey points at this iteration are used as the reference model to improve lateral continuity and convergence. Finally, the iterative termination condition considers the total data residual of all soundings of a survey line instead of one survey point for improving the overall performance of the inversion results. The experimental results of synthetic and field data show that the proposed inversion scheme can achieve better inversion results with moderate computational cost.

机载电磁（AEM）方法已广泛应用于矿产勘探、地下水勘探、石油和天然气资源调查以及许多其他用途。尽管三维反演的技术进步令人印象深刻，但要反演数据量巨大的大型 AEM 勘测的野外数据往往并不可行。目前，一维反演和基于强加横向连续性的一维模型的准二维反演方法已被应用于 AEM 行业的野外数据反演。本文提出了一种基于横向相关性的时域 AEM 数据横向约束反演方案，可有效实现垂直和横向平滑。首先，勘测线的所有点都是独立反演，而不是同时反演，这在计算上非常高效。其次，在每个勘测点的每次迭代计算中，都使用相邻勘测点在本次迭代中的反演结果作为参考模型，以提高横向连续性和收敛性。最后，迭代终止条件考虑了一条测线上所有测点的总数据残差，而不是一个测点，以提高反演结果的整体性能。合成数据和实地数据的实验结果表明，所提出的反演方案能以适中的计算成本获得较好的反演结果。

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引用次数: 0

Ground-roll attenuation in high-dimensional domain using multi-scale decomposition and attention mechanism network 利用多尺度分解和注意力机制网络实现高维领域的地面滚动衰减

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-04-15 DOI: 10.1016/j.jappgeo.2025.105736

Tingshang Yan, Yongshou Dai, Zhenjie Wang

Ground-roll attenuation is a critical step for enhancing the signal-to-noise ratio of seismic data, serving as an essential prerequisite for achieving precise subsurface imaging. Due to the overlap of ground-roll and useful signals in both the t-x and frequency domains, coupled with the high amplitude of ground-roll, existing methods often struggle to remove strong ground-roll without damaging useful signals. To address this issue, we propose a ground-roll attenuation method that integrates multi-scale decomposition and attention mechanism network, reframing the ground-roll attenuation problem in the t-x domain as the prediction of ground-roll coefficients in a high-dimensional transform domain. Given the differences in frequency and propagation direction between ground-roll and useful signals, we employ the Non-Subsampled Shearlet Transform, which provides multi-scale and multi-directional decomposition capabilities, to decompose seismic data containing ground-roll into multiple subbands, thereby reducing the overlap between ground-roll and useful signals. This enables the network to more easily and accurately extract ground-roll while retaining useful signals. Furthermore, to effectively extract ground-roll coefficients from subbands at different scales, we propose a Multi-Scale Attention Network. The network features a multi-branch structure with convolutional kernels of various sizes, enabling the capture of waveform features across different scales. An attention mechanism is then used to select and fuse feature maps from different branches, further enhancing the network's ability to capture information across scales. Experimental results both on synthetic and field data demonstrate that, the proposed method outperforms a conventional method and two advanced deep learning methods, achieving superior ground-roll attenuation while better preserving useful signals.

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引用次数: 0

Integrating geophysical methods, InSAR, and field observations to address geological hazards and buried archaeological features in urban landscapes

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-04-14 DOI: 10.1016/j.jappgeo.2025.105726

Leonardo Maria Giannini , Siham Younsi , Benedetto Burchini , Rita Deiana , Giorgio Cassiani , Paolo Ciampi

This study addresses the limited application of integrated geophysical and remote sensing methods in detecting and characterizing underground voids in volcanic settings, while literature primarily focused on karst sinkholes. It investigates a collapse-affected area near the historical center of Civita Castellana (Viterbo, Italy), where volcanic deposits and subsurface cavities were identified through boreholes and field surveys. The study aims to estimate the spatial configuration of hypogeal environments using non-invasive surface and near-surface geophysical techniques. A multi-scale and multi-source approach was employed, integrating electrical resistivity tomography (ERT), ground penetrating radar (GPR), and (interferometric synthetic aperture radar) InSAR. ERT, using a dipole-dipole configuration across four profiles with 1 m inter-electrode spacing, revealed high-resistivity anomalies (>400 Ohm·m) linked to buried cavities at depths of 2–6 m. The largest void spans approximately 4 m² with resistivity values exceeding 900 Ohm·m. GPR surveys, performed with a 100 MHz antenna along 10 transects, corroborated ERT results by delineating subsurface discontinuities and void geometries down to 10 m depth. InSAR provided large-scale subsidence patterns, highlighting localized zones with downward displacement rates up to −10.0 mm/year, aligning with geophysical findings and suggesting a continuous cave network contributing to surface instability. The results underscore the effectiveness of combining ERT, GPR, and InSAR for detecting underground voids in urbanized volcanic settings. This integration enables precise delineation of subsurface geometries and enhances risk assessment. The findings have considerable implications for urban planning, hazard mitigation, and cultural heritage preservation, offering critical insights into hypogeal environments in archaeologically and historically significant areas.

{"title":"Integrating geophysical methods, InSAR, and field observations to address geological hazards and buried archaeological features in urban landscapes","authors":"Leonardo Maria Giannini , Siham Younsi , Benedetto Burchini , Rita Deiana , Giorgio Cassiani , Paolo Ciampi","doi":"10.1016/j.jappgeo.2025.105726","DOIUrl":"10.1016/j.jappgeo.2025.105726","url":null,"abstract":"<div><div>This study addresses the limited application of integrated geophysical and remote sensing methods in detecting and characterizing underground voids in volcanic settings, while literature primarily focused on karst sinkholes. It investigates a collapse-affected area near the historical center of Civita Castellana (Viterbo, Italy), where volcanic deposits and subsurface cavities were identified through boreholes and field surveys. The study aims to estimate the spatial configuration of hypogeal environments using non-invasive surface and near-surface geophysical techniques. A multi-scale and multi-source approach was employed, integrating electrical resistivity tomography (ERT), ground penetrating radar (GPR), and (interferometric synthetic aperture radar) InSAR. ERT, using a dipole-dipole configuration across four profiles with 1 m inter-electrode spacing, revealed high-resistivity anomalies (>400 Ohm·m) linked to buried cavities at depths of 2–6 m. The largest void spans approximately 4 m<sup>2</sup> with resistivity values exceeding 900 Ohm·m. GPR surveys, performed with a 100 MHz antenna along 10 transects, corroborated ERT results by delineating subsurface discontinuities and void geometries down to 10 m depth. InSAR provided large-scale subsidence patterns, highlighting localized zones with downward displacement rates up to −10.0 mm/year, aligning with geophysical findings and suggesting a continuous cave network contributing to surface instability. The results underscore the effectiveness of combining ERT, GPR, and InSAR for detecting underground voids in urbanized volcanic settings. This integration enables precise delineation of subsurface geometries and enhances risk assessment. The findings have considerable implications for urban planning, hazard mitigation, and cultural heritage preservation, offering critical insights into hypogeal environments in archaeologically and historically significant areas.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"238 ","pages":"Article 105726"},"PeriodicalIF":2.2,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143835405","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}

引用次数: 0

Integrated 2D time-lapse resistivity tomography and spontaneous potential surveys demonstrate seasonal, use-related patterns of seepage from a water-supply canal system

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-04-14 DOI: 10.1016/j.jappgeo.2025.105708

Mohamed A. Khalil , Douglas R. Hallum , R.M. Joeckel , Michael Krondak

The imperative of ensuring structural integrity and maintaining operational safety of hydraulic structures while managing surface water for power generation, food and fiber production, groundwater storage, and preservation of the natural environment drives a worldwide need for locating seepage associated with such structures. This paper is a case study of the geophysical assessment of seepage from the Sutherland Supply Canal and the connecting Paxton Siphon Inlet in subhumid to semiarid western Nebraska, USA. We employed 2D electrical resistivity tomography and self-potential methods to identify and characterize numerous potential seepage zones beneath these structures under both full-canal conditions (August 2023) and subsequent empty-canal conditions (October 2023). Our time-lapse analysis of the two 2D resistivity data sets exhibited a relative increase in the resistivity ratio of the potential seepage zones under empty-canal conditions of up to 700 (i.e., seven times of the magnitude of the resistivity determined in August) and a desaturation of about 26 % relative to saturation under full-canal conditions. These results indicate that a hydraulic connection exists between the canal and the potential seepage zones under it. Furthermore, self-potential data outlined the recharge and discharge zones under the canal according to positive and negative polarity of the drift-referred to base self-potential data. Our integrated time-lapse approach is non-invasive, time- and cost-effective, and easily repeatable; therefore, it is applicable to the assessment of seepage in irrigation canals, siphons, and dams worldwide.

在管理地表水用于发电、粮食和纤维生产、储存地下水以及保护自然环境的同时，必须确保水力结构的完整性并维护其运行安全，这就促使全世界都需要对与此类结构相关的渗流进行定位。本文是对美国内布拉斯加州西部亚湿润到半干旱地区萨瑟兰补给运河和相连的帕克斯顿虹吸进水口渗流进行地球物理评估的案例研究。我们采用二维电阻率层析成像和自电位方法，在满运河条件下（2023 年 8 月）和随后的空运河条件下（2023 年 10 月），确定并描述了这些结构下方的众多潜在渗流区。我们对两组二维电阻率数据进行的延时分析表明，在空运河条件下，潜在渗流区的电阻率比值相对增加高达 700（即是 8 月份测定的电阻率比值的七倍），相对于全运河条件下的饱和度，脱饱和度约为 26%。这些结果表明，运河与其下的潜在渗流区之间存在水力联系。此外，自电位数据根据漂流物的正负极性（即基础自电位数据）勾勒出了运河下的补给区和排泄区。我们的综合延时方法具有非侵入性、省时、成本效益高和易于重复等特点，因此适用于全球灌溉渠道、倒虹吸管和水坝的渗流评估。

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引用次数: 0

Analytical solution for temperature-depth in geothermal reservoirs with mixed heat conduction types: A case study from the Huainan Coalfield, Anhui Province, China

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-04-14 DOI: 10.1016/j.jappgeo.2025.105727

Yuan Zhang , Shan Wu , Haifeng Lu , Fusheng Zha

Temperature measurements in geothermal reservoirs plays a crucial role in understanding the source of subsurface thermal energy storage and the extraction of geothermal power. However, deploying a multitude of monitoring points during underground drilling results in substantial measurement expenses. To address this challenge, a simplified analytical model is often utilized to estimate the temperature distribution throughout the formation. This estimation relies on wellhead and bottom-hole temperatures, as well as parameters related to the formation's thermal properties. Nevertheless, the varying distribution of groundwater across different zones alters the heat transfer process. Temperature calculations considering multiple transfer processes are still limited. Therefore, in this paper we first formulate two common types of heat transfer models: conduction and convection-conduction. By integrating these two types of heat transfer, we characterize and calculate the temperature distribution for geothermal reservoirs in a manner more aligned with reservoir conditions. To validate the model's accuracy, we compare its calculated results with temperature measurements obtained from geothermal wells in Huainan Coalfield. The results demonstrate that the developed model is highly applicable and exhibits strong simulation accuracy, with the maximum error between the analytical solutions and the measured temperature curve being less than 0.5 °C. This model is particularly suitable for capturing the actual heat transfer behavior in the geothermal reservoir as geothermal water ascends. Furthermore, it can be employed to invert the volume flow rate of geothermal water, highlighting its significance in geothermal development engineering.

地热储层的温度测量在了解地下热能存储源和提取地热能方面起着至关重要的作用。然而，在地下钻探过程中部署大量监测点会产生大量测量费用。为了应对这一挑战，通常采用简化的分析模型来估算整个地层的温度分布。这种估算依赖于井口和井底温度，以及与地层热特性相关的参数。然而，地下水在不同区域的不同分布会改变传热过程。考虑到多种传热过程的温度计算仍然有限。因此，本文首先提出了两种常见的传热模型：传导和对流-传导。通过整合这两种传热方式，我们以更符合储层条件的方式描述和计算了地热储层的温度分布。为了验证模型的准确性，我们将其计算结果与淮南煤田地热井的温度测量结果进行了比较。结果表明，所开发的模型适用性强，模拟精度高，分析解与实测温度曲线之间的最大误差小于 0.5 °C。该模型尤其适用于捕捉地热储层中地热水上升时的实际传热行为。此外，该模型还可用于反演地热水的体积流量，在地热开发工程中具有重要意义。

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引用次数: 0

Seismological geothermometer. Part II: Neural network modeling of the temperature prediction from seismic velocity data in the upper crust

IF 2.2 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

Journal of Applied Geophysics

Pub Date : 2025-04-12 DOI: 10.1016/j.jappgeo.2025.105724

Viacheslav V. Spichak, Olga K. Zakharova

The temperature prediction accuracy in the upper crust from the seismic velocity data is estimated by neural network modeling. To this end, we used a 2-D temperature model built earlier along the northern Tien Shan latitudinal profile up to a depth of 27 km. We modeled the temperature prediction at depths beneath boreholes and at large distances from the locations where the initial data were available. The estimation of the temperature prediction from the V_P and V_S at depths below the boreholes indicated that the relative accuracy decreases when the ratio (N) between the target and borehole depths increases. As a whole, at any ratio N, the accuracy of the temperature prediction from V_S is higher than that from V_P. In particular, the average relative errors increase when N growths from 2 to 10 in the ranges 6.8–28.4 % and 5.1–20.1 % when using V_P or V_S, respectively. Assessment of the temperature prediction from V_P and V_S in other locations indicated that at distances up to 16 km, the prediction errors are 7.4 % and 5.7 %, respectively. When this distance is increased 4 times, relative errors are increased 2–3 times. We conclude that the neural network temperature prediction from the seismic velocity data (especially, V_S) could be carried out with sufficient accuracy both beneath boreholes and at large distances and therefore could be used as a seismological geothermometer.

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引用次数: 0