Geophysical Survey

The LOFAR Two-metre Sky Survey (LoTSS) is a deep 120-168 MHz imaging survey that will eventually cover the entire northern sky. Each of the 3170 pointings will be observed for 8 h, which, at most declinations, is sufficient to produce 5 resolution images with a sensitivity of 100 Jy/beam and accomplish the main scientific aims of the survey, which are to explore the formation and evolution of massive black holes, galaxies, clusters of galaxies and large-scale structure. Owing to the compact core and long baselines of LOFAR, the images provide excellent sensitivity to both highly extended and compact emission. For legacy value, the data are archived at high spectral and time resolution to facilitate subarcsecond imaging and spectral line studies. In this paper we provide an overview of the LoTSS. We outline the survey strategy, the observational status, the current calibration techniques, a preliminary data release, and the anticipated scientific impact. The preliminary images that we have released were created using a fully automated but direction-independent calibration strategy and are significantly more sensitive than those produced by any existing large-area low-frequency survey. In excess of 44 000 sources are detected in the images that have a resolution of 25 , typical noise levels of less than 0.5 mJy/beam, and cover an area of over 350 square degrees in the region of the HETDEX Spring Field (right ascension 10h45m00s to 15h30m00s and declination 45 00 00 to 57 00 00 ).

PreviousNext No AccessSEG Technical Program Expanded Abstracts 1984Random noise reductionAuthors: Luis L. CanalesLuis L. CanalesDigicon Geophysical Inc., Englandhttps://doi.org/10.1190/1.1894168 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Permalink: https://doi.org/10.1190/1.1894168FiguresReferencesRelatedDetailsCited byDenoising of distributed acoustic sensing data using supervised deep learningLiuqing Yang, Sergey Fomel, Shoudong Wang, Xiaohong Chen, Wei Chen, Omar M. Saad, and Yangkang Chen28 October 2022 | GEOPHYSICS, Vol. 88, No. 1Random and coherent noise attenuation for 2D land seismic reflection line acquired in Iraq2 October 2022 | NRIAG Journal of Astronomy and Geophysics, Vol. 11, No. 1Random noise attenuation using the novel Estimated Noise Pattern Denoising Algorithm7 November 2022 | Exploration Geophysics, Vol. 12Multi-scale Recurrent-guided Denoising Network for DAS-VSP Background Noise AttenuationMing Cheng, Shaoping Lu, Xintong Dong, and Tie Zhong22 October 2022 | GEOPHYSICS, Vol. 0, No. jaSeismic Shot Gather Denoising by Using a Supervised-Deep-Learning Method with Weak Dependence on Real Noise Data: A Solution to the Lack of Real Noise Data27 May 2022 | Surveys in Geophysics, Vol. 43, No. 5Random noise suppression of seismic data through multi-scale residual dense network21 September 2022 | Acta Geophysica, Vol. 8Q-value estimation of Chang'e-4 lunar penetrating radar data10 September 2022 | Journal of Geophysics and Engineering, Vol. 19, No. 5Preserving signal during random noise attenuation through migration enhancement and local orthogonalizationChao Li and Jinhai Zhang1 August 2022 | GEOPHYSICS, Vol. 87, No. 5Simple framework for the contrastive learning of visual representations-based data-driven tight frame for seismic denoising and interpolationJinghe Li and Xiangling Wu1 August 2022 | GEOPHYSICS, Vol. 87, No. 5Robust fast dictionary learning for seismic noise attenuation16 June 2022 | Geophysical Prospecting, Vol. 70, No. 7Suppression of coherent and random noise using adaptive thresholding method in seismic-while-drillingYue Ma and Yujin Liu15 August 2022Least-squares non-stationary triangle smoothingReem F. 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Gómez, Danilo R. Velis, and Juan I. Sabbione11 November 2019 | GEOPHYSICS, Vol. 85, No. 1Introduction to Denoising and Data Gap Filling of Seismic Reflection Data26 March 2020Singular Spectrum Analysis-Based Time Domain Frequency Filtering26 March 2020Filtering 2D Seismic Data Using the Time Slice Singular Spectral Analysis26 March 2020Denoising the 3D Seismic Data Using Multichannel Singular Spectrum Analysis26 March 2020Seismic Random Noise Attenuation Based on PCC Classification in Transform DomainIEEE Access, Vol. 8Sinusoidal Seismic Noise Suppression Using Randomized Principal Component AnalysisIEEE Access, Vol. 8A Robust Random Noise Suppression Method for Seismic Data Using Sparse Low-Rank Estimation in the Time-Frequency DomainIEEE Access, Vol. 8Data-driven dispersive surface-wave prediction and mode separation using high-resolution dispersion estimationJournal of Applied Geophysics, Vol. 171Random Noise Redunction of Seismic Data in NSCT Domain2-D Seismic Random Noise Attenuation via Self-Paced Nonnegative Dictionary LearningIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 12, No. 12Nonstationary Least-Squares Decomposition With Structural Constraint for Denoising Multi-Channel Seismic DataIEEE Transactions on Geoscience and Remote Sensing, Vol. 57, No. 12Strong random noise attenuation by shearlet transform and time-frequency peak filteringChao Zhang and Mirko van der Baan9 October 2019 | GEOPHYSICS, Vol. 84, No. 6Deep learning for denoisingSiwei Yu, Jianwei Ma, and Wenlong Wang9 October 2019 | GEOPHYSICS, Vol. 84, No. 6Denoising with weak signal preservation by group-sparsity transform learningXiaojing Wang, Bihan Wen, and Jianwei Ma9 October 2019 | GEOPHYSICS, Vol. 84, No. 6Least-Squares Gaussian Beam Transform for Seismic Noise AttenuationIEEE Transactions on Geoscience and Remote Sensing, Vol. 57, No. 11White noise attenuation of seismic trace by integrating variational mode decomposition with convolutional neural networkHao Wu, Bo Zhang, Tengfei Lin, Fangyu Li, and Naihao Liu9 September 2019 | GEOPHYSICS, Vol. 84, No. 5Three-parameter prestack seismic inversion based on L1-2 minimizationLingqian Wang, Hui Zhou, Yufeng Wang, Bo Yu, Yuanpeng Zhang, Wenling Liu, and Yangkang Chen24 August 2019 | GEOPHYSICS, Vol. 84, No. 5Spectral structure-oriented filtering of seismic data with self-adaptive pathsJulián L. Gómez and Danilo R. Velis8 August 2019 | GEOPHYSICS, Vol. 84, No. 5Vector-valued seismic data denoising via widely-linear autoregressive modelsBreno Bahia and Mauricio D. Sacchi1 August 2019Transform learning with group sparsity for random noise attenuationXiaojing Wang and Jianwei Ma1 August 2019A 3D methodology for residual and diffracted multiple attenuationMaiza Bekara, Lian Duan, and Mamdouh Salem1 August 2019Attenuation of random noise using denoising convolutional neural networksXu Si, Yijun Yuan, Tinghua Si, and Shiwen Gao7 August 2019 | Interpretation, Vol. 7, No. 3Non-Subsampled Shearlet Transform Based Seismic Data Denoising via Proximal Classifier with ConsistencyRobust Estimation of Multiple Local Dips via Multidirectional Component AnalysisIEEE Transactions on Geoscience and Remote Sensing, Vol. 57, No. 5Simultaneous Inversion of Shallow Seismic Data for Imaging of Sulfurized Carbonates28 March 2019 | Minerals, Vol. 9, No. 4Computational efficient multidimensional singular spectrum analysis for prestack seismic data reconstructionJinkun Cheng, Mauricio Sacchi, and Jianjun Gao11 February 2019 | GEOPHYSICS, Vol. 84, No. 2Adaptive singular spectrum analysis for seismic denoising and interpolationHojjat Haghshenas Lari, Mostafa Naghizadeh, Mauricio D. Sacchi, and Ali Gholami12 February 2019 | GEOPHYSICS, Vol. 84, No. 2Contourlet Transform Based Seismic Signal Denoising via Multi-scale Information Distillation Network23 August 2019Unsupervised Seismic Random Noise Attenuation Based on Deep Convolutional Neural NetworkIEEE Access, Vol. 7A Sparse Deconvolution Method with L1-norm Regularization and Lateral Continuity ConstraintsJintao Liu, Zhewu Wang, Wuyang Yang, and Xiong Ma11 December 2018Denoising of Petroleum Seismic Exploration Based on Non-Subsampled Shearlet TransformYu Sang, Ping Guo, Shiguang Liu, Zhijun Song, and Dacheng Gao11 December 2018Denoising of pre‐stack seismic data using subspace estimation methods1 October 2018 | IET Signal Processing, Vol. 12, No. 8Spatial Prediction Filtering for Medical Ultrasound in Aberration and Random NoiseIEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol. 65, No. 10A compound method for random noise attenuation11 September 2018 | Geophysical Prospecting, Vol. 66, No. 8Edge-preserving frequency-offset denoising of seismic dataJulián L. Gómez and Danilo R. Velis7 September 2018 | GEOPHYSICS, Vol. 83, No. 5A denoising framework for microseismic and reflection seismic data based on block matchingChao Zhang and Mirko van der Baan29 August 2018 | GEOPHYSICS, Vol. 83, No. 5Random noise attenuation based on residual learning of deep convolutional neural networkXu Si and Yijun Yuan27 August 2018Retracted: Attenuating seismic noise via incoherent dictionary learning25 April 2018 | Journal of Geophysics and Engineering, Vol. 15, No. 4Streaming orthogonal prediction filter in the t-x domain for random noise attenuationYang Liu and Bingxiu Li26 June 2018 | GEOPHYSICS, Vol. 83, No. 4Damped Dreamlet Representation for Exploration Seismic Data Interpolation and DenoisingIEEE Transactions on Geoscience and Remote Sensing, Vol. 56, No. 6Sparse graph-regularized dictionary learning for suppressing random seismic noiseLina Liu, Jianwei Ma, and Gerlind Plonka19 April 2018 | GEOPHYSICS, Vol. 83, No. 3Common Reflection Surface Stack Imaging of the Proterozoic Chambal Valley Vindhyan Basin and Its Boundary Fault in the Northwest India: Constraints on Crustal Evolution and Basin Formation15 May 2018 | Tectonics, Vol. 37, No. 5Prestack structurally constrained impedance inversionHaitham Hamid, Adam Pidlisecky, and Larry Lines10 January 2018 | GEOPHYSICS, Vol. 83, No. 2BIBLIOGRAPHY8 June 2018References14 March 2018Random noise attenuation by planar mathematical morphological filteringWeilin Huang and Runqiu Wang29 November 2017 | GEOPHYSICS, Vol. 83, No. 1Random noise attenuation in 3D seismic data by iterative block tensor singular value thresholdingSeismic Random Noise Attenuation Using Synchrosqueezed Wavelet Transform and Low-Rank Signal Matrix ApproximationIEEE Transactions on Geoscience and Remote Sensing, Vol. 55, No. 11References14 September 2017Noise attenuation in a low-dimensional manifoldSiwei Yu, Stanley Osher, Jianwei Ma, and Zuoqiang Shi24 July 2017 | GEOPHYSICS, Vol. 82, No. 5Signal leakage in f-x deconvolution algorithmsNecati Gülünay25 August 2017 | GEOPHYSICS, Vol. 82, No. 5Spatial prediction filtering for increased penetration depth in synthetic aperture ultrasoundStreaming orthogonal prediction filter in t-x domain for random noise attenuationBingxiu Li, Yang Liu, and Cai Liu17 August 2017Laterally-constrained sparse deconvolution in the mixed domainWei Wang, Guofa Li, Yumin Zhao, Wuyang Yang, and Wanli Wang17 August 2017Seismic data denoising based on online dictionary learning algorithmXin Tian, Kai Zhang, and Zhenchun Li17 August 2017Incoherent noise attenuation via randomized CP decompositionWenlei Gao and Mauricio Sacchi17 August 2017AVO and Seismic Inversion II Complete Session17 August 2017Retracted: Application of variational mode decomposition to seismic random noise reduction13 June 2017 | Journal of Geophysics and Engineering, Vol. 14, No. 4Double Least-Squares Projections Method for Signal EstimationIEEE Transactions on Geoscience and Remote Sensing, Vol. 55, No. 7Shaped multichannel singular spectrum analysis for random noise attenuationZhao Qiang, Du Qizhen*, and Gong Xufei31 May 2017A method of combining coherence-constrained sparse coding and dictionary learning for denoisingPierre Turquais, Endrias G. 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Velis7 September 2016 | GEOPHYSICS, Vol. No. multichannel filter for data and September rank selection for singular spectrum analysis via Chen, Wei Chen, Shaohuan Zu, Weilin Huang, and Zhang1 September noise suppression in seismic data Li, Chen, and September of noise in marine streamer data via and September of seismic data based on method and September analysis for using Wang, Yang Liu, Cai Liu, and September frequency-offset for seismic data and Danilo September Noise Attenuation Complete September Estimation Complete September multichannel singular spectrum analysis for 3D random noise Huang, Runqiu Wang, Yangkang Chen, Li, and Shuwei May 2016 | GEOPHYSICS, Vol. No. data-driven tight frame for seismic data Yu, Jianwei Ma, and Stanley June 2016 | GEOPHYSICS, Vol. No. filtering using transform and adaptive empirical mode decomposition based April 2016 | Geophysical Journal International, Vol. No. of seismic attenuation and prediction of from and a study from the May 2016 | Journal of Geosciences, Vol. 9, No. time-frequency representation for seismic noise reduction using and sparse and March 2016 | GEOPHYSICS, Vol. No. ground-penetrating radar on A of different and their for and January 2016 | GEOPHYSICS, Vol. No. of simultaneous using a median filter in the Geosciences, Vol. Noise and Resolution of Seismic Data Using Geoscience and Remote Sensing Letters, Vol. No. random noise attenuation using shearlet and December | Journal of Geophysics and Engineering, Vol. 12, No. noise attenuation using local and Sergey March | GEOPHYSICS, Vol. No. and noise separation in prestack seismic data using Liu, Sergey Fomel, and Cai September | GEOPHYSICS, Vol. No. and seismic denoising via ensemble empirical mode decomposition and adaptive and Mirko van der August | GEOPHYSICS, Vol. No. in surface microseismic May | GEOPHYSICS, Vol. No. data denoising through and dictionary Liu, and James August | GEOPHYSICS, Vol. No. simultaneous random erratic noise attenuation and interpolation for seismic data by and sparse and David October | GEOPHYSICS, Vol. No. With Multiple Constraints Based on Geoscience and Remote Sensing Letters, Vol. 12, No. attenuation using - the Shuwei Gan, and August mode decomposition based in the Zhang, Shuwei Gan, and August data denoising based on sparse and Wang, and August of surface — August multichannel singular spectrum analysis for 3D random noise Huang, Runqiu Wang, Zhang, and Yangkang August learning for Endrias G. 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Abstract A comparative study of extraction techniques for the selective dissolution of amorphous iron oxides from soils and sediments was conducted using nine iron oxide samples characterized by x‐ray diffraction as model mineral substrates. Several extracting solutions were evaluated as to their efficiency and specificity for dissolving amorphous iron oxides. Solutions examined included (i) 0.175 M (NH 4 ) 2 C 2 O 4 ‐0.100 M H 2 C 2 O 4 (Tamm's reagent) in the dark, (ii) HCl of different concentrations at both room and boiling water temperatures, (iii) 3% H 2 C 2 O 4 at boiling water temperature, (iv) 0.25 M NH 2 OH·HCl‐25% HOAc at 70°C in a shaker hath, and (v) 0.25 M NH 2 OH·HCl‐0.25 M HCl at 70°C in a shaker hath. Some solutions were found inadequate because of attack on other mineral species, dissolution of crystalline iron oxides such as magnetite, lack of specificity, or lengthy reaction time. Using results obtained on amorphous iron oxides by extraction with Tamm's reagent as a standard reference, the 0.25 M NH 2 OH·HCl‐0.25 M HCl combined solution, modified to extract at 50°C for 30 min, was chosen as the most desirable extractant for amorphous iron oxides based on four considerations: (i) only 30 min required for the extraction, (ii) minor dissolution of crystalline iron oxides (< 1% of the total iron), (iii) low slope of the time series dissolution curve, and (iv) results in close agreement with the 0.175 M (NH 4 ) 2 C 2 O 4 ‐0.100 M H 2 C 2 O 4 extraction in the dark. The modified procedure was applied to six geochemical exploration reference samples consisting of soil, sediment, and weathered rock. Results obtained on amorphous iron oxides were in close agreement with those achieved by the acid ammonium oxalate extraction. The application of the extractant to studies of exploration geochemistry and soil active iron ratios is discussed.

Abstract For measurement of water content using TDR, parallel wire transmission lines varying in length from 0.125 to 1 m were installed vertically at planting time at three sites in a corn field. At one of the sites horizontal lines and additional vertical transmission lines with electrical impedance discontinuities were installed for comparison. Measurements of water content using a portable TDR cable tester were made periodically during the growing season. Comparisons of water contents by TDR with those from gravimetric samples showed that generally both were the same values. Standard deviations of differences between TDR and gravimetric values were ± 0.02 m 3 m −3 when measured locations were the same but increased to ± 0.06 m 3 m −3 when measured locations were different. Repeated measurements at the same location were highly correlated, one with another, over the season. Analysis of variance showed that all transmission line types were yielding equivalent values and that the horizontal transmission lines gave the minimum standard error of the mean. Data from transmission lines with impedance discontinuities gave water content profiles from a single measurement but the analyses of the TDR data curves were more complex than for the lines without impedance discontinuities. The variety of transmission line configurations for use in TDR measurement allows considerable flexibility of choice in relation to one's application.

We study Bayesian models and methods for analysing network traffic counts in problems of inference about the traffic intensity between directed pairs of origins and destinations in networks. This is a class of problems very recently discussed by Vardi in a 1996 JASA article, and of interest in both communication and transportation network studies. The current paper develops the theoretical framework of variants of the origin-destination ow problem, and introduces Bayesian approaches to analysis and inference. In the first, the so-called fixed routing problem, traffic or messages pass between nodes in a network, with each message originating at a specific source node, and ultimately moving through the network to a predetermined destination node. All nodes are candidate origin and destination points. The framework assumes no travel time complications, considering only the number of messages passing between pairs of nodes in a specified time interval. The route count, or route flow, problem is to infer the set of actual number of messages passed between each directed origin-destination pair in the time interval, based on the observed counts flowing between all directed pairs of adjacent nodes. Based on some development of the theoretical structure of the problem and assumptions about prior distributional forms, we develop posterior distributions

The CoO/g-C₃N₄p–n heterojunction photocatalysts exhibit enhanced photocatalytic activity and stability under visible light.

ABSTRACT In multiparameter full-waveform inversion (FWI) and specifically one describing the anisotropic behavior of the medium, it is essential that we have an understanding of the parameter resolution possibilities and limits. Because the imaging kernel is at the heart of the inversion engine (the model update), we drew our development and choice of parameters from what we have experienced in imaging seismic data in anisotropic media. In representing the most common (first-order influence and gravity induced) acoustic anisotropy, specifically, a transversely isotropic medium with a vertical symmetry direction (VTI), with the P-wave normal moveout velocity, anisotropy parameters δ, and η, we obtained a perturbation radiation pattern that has limited trade-off between the parameters. Because δ is weakly resolvable from the kinematics of P-wave propagation, we can use it to play the role that density plays in improving the data fit for an imperfect physical model that ignores the elastic nature of the earth. An FWI scheme that starts from diving waves would benefit from representing the acoustic VTI model with the P-wave horizontal velocity, η, and ε. In this representation, the diving waves will help us first resolve the horizontal velocity and then reflections, if the nonlinearity is properly handled, could help us resolve η, and ε could help improve the amplitude fit (instead of the density). The model update wavenumber for acoustic anisotropic FWI is very similar to that for the isotropic case, which is mainly dependent on the scattering angle and frequency.

GPS measurements of interseismic horizontal surface velocities reveal the degree of kinematic coupling of the plate boundary thrust along the Kamchatka subduction zone from about 51° to 57°N latitude. Inversions for the distribution of aseismic slip rate along the ∼15°NW dipping underthrust suggest a nonslipping plate interface in southern Kamchatka above ∼50 km depth, along the segment that ruptured in the M w = 9, 1952 earthquake. North of ∼53°N, the subduction interface experiences significant aseismic slip, consistent with the lower seismic moment release in M ≤ 8.5 earthquakes along this portion of the subduction zone. The GPS velocities are consistent with a boundary element forward model in which historic earthquake rupture zones are represented as locked asperities, surrounded by a zero shear stress subduction interface loaded by plate convergence. Models in which the complete rupture zones of historic earthquakes are considered locked greatly overpredict the degree of kinematic coupling. Reducing the area of the locked model asperities to the central 25% area of historic rupture zones fits the data well, suggesting that large earthquakes involve small fully locked core asperities surrounded by conditionally stable portions of the plate interface. Areas of low aseismic slip rate appear to be roughly correlated with areas of low isostatic gravity anomalies over offshore forearc basins, while less coupled portions of the Kamchatka subduction zone coincide with high‐gravity anomalies offshore of two peninsulas, possibly related to the subduction of the Emperor‐Meji seamount chain and the Kruzenstern fracture zone.

NaCl solution at 1.2 V over 30 min with good cycling stability over 50 cycles. The excellent performance is attributed to the high specific surface area, high conductivity, favorable meso-/microporous structure together with nitrogen and phosphorus heteroatom co-doping, all of which are beneficial for the accommodation of ions and charge transport during the CDI process. More importantly, NPC/rGO exhibits a state-of-the-art CDI performance compared to the commercial benchmark and most of the previously reported carbon materials, highlighting the significance of the MOF nanoparticle-driven assembly strategy and graphene-carbon 2D heterostructures for CDI applications.

The configuration of the Pacific plate subducted beneath the Kamchatka peninsula and the stress distribution in the Kamchatka subduction zone (KSZ) were studied using the catalog of the Kamchatka regional seismic network, focal mechanism solutions estimated from P wave first motions, the formal inversion of long‐period waveforms, and centroid moment tensor solutions. To the south of ∼55°N, the slab shows an approximately constant dip angle of ∼55°. To the north of ∼55°N, the dip of the slab becomes shallower reaching ∼35°. The maximum depth of seismicity, D m , varies from ∼500 km depth near 50°N to ∼300 km depth at ∼55°N. The volcanic front is almost linear along the main part of the KSZ whereas it is sharply shifted landward to the north of ∼55°N. The variation of D m is apparently consistent with the standard empirical relation D m =ƒ(ϕ), where ϕ is the thermal parameter of the subducted slab. To the north of ∼55°N, the slab is offset toward the northwest, and it is sharply deformed in a narrow contorted zone which is ∼30 km wide (∼56°N, ∼161°E). To the north of this contortion, D m decreases to ∼100 km. The landward shift of the northern part of the slab is reflected by a sharp deviation of the volcanic front to the northwest which follows the ∼90–160 km isodepth range of the subducted slab. The observed value of D m in the northern segment significantly diverges from the global relation D m =ƒ(ϕ). We interpret this as an effective decrease of the thermal thickness of the subducted lithosphere.

Abstract Over Cyprus there is one of the largest recorded gravity anomalies which reaches a maximum of over +250 mgal. This paper records the main geological features of the island, investigates the source of the gravity anomaly and correlates both lines of evidence in support of an hypothesis on the evolution and structure of the area. The topography of Cyprus, which lies in the north-eastern Mediterranean, is dominated by two east-west mountain ranges separated by the low-lying central plain of Mesaoria. The northern, Kyrenia range is part of the southernmost arc of the Tauro-Dinaric Alps, whilst the southern Troodos range is an igneous massif composed of basic and ultrabasic rocks of plutonic and extrusive character. The Troodos rocks fall logically into three main units: (a) the Sheeted Intrusive Complex; (b) the Troodos Plutonic Complex; and (c) the Troodos Pillow Lava Series. The Sheeted Intrusive Complex forms the major part of the Troodos massif and is a north-south basic dyke swarm cutting basic lavas. The dykes range in thickness from 1 to 15 ft. and form over 90% of the complex. Abundant evidence is available to substantiate the intrusive nature of this dyke complex. Its unique concentration and regularity is attributed to repeated intrusion coupled with intense erosion. The north-south orientation of the intrusives is thought to be due to the east-west tensional stress that was dominant throughout the evolution of the massif. The central part of the massif is occupied by the Troodos Plutonic Complex, a layered ultrabasic complex of batholithic dimensions in which the rock types range from central dunites and peridotites outwards through melagabbros and olivine gabbros to gabbros and granophyres. Field, mineralogical and geophysical data indicate that the parent material was of peridotitic composition. Although gabbros are, by far, the most abundant rocks exposed, it is considered that these represent but a minor percentage of a vast mass of underlying, high-density, ultrabasic material. Differentiation of the ultrabasic parent material is thought to have resulted in the gradual upward and outward change from central dunites and peridotite through melagabbros and olivine-gabbros to overlying gabbros and granophyres. Forming an incomplete ring around the Sheeted Intrusive Complex is the Troodos Pillow Lava Series, a very thick sequence of pillow lavas and their related intrusives. Although divided into two units on the presence of a partial unconformity, and petrographic differences, the general basaltic nature of the series persists throughout. The series shows an increase in basicity with decreasing age, the main rock type in the lower unit being basalt, whilst olivine basalts predominate in the upper division. There is evidence that this series has resulted from the partial fusion of a rock of peridotitic composition and that the relationship between age and basicity is due to the progressively more complete fusion of the parent material. Serpentines of post-Lower Triassic age and considered to be the initial phase in the igneous activity of the Alpine orogeny are also present in Cyprus, where they appear to have been emplaced as a serpentine ‘magma’. Cyprus is covered by a strong positive gravity anomaly mainly between 100 and 250 mgal. The axis of the anomaly lies over the Troodos massif, runs parallel to the Kyrenia range and extends from Pomos in the west, eastwards to Famagusta; superimposed upon the main anomaly are smaller local anomalies. The gravity field falls off all round Cyprus to less than 100 mgal; no other gravity anomalies of this size have, so far, been found in the eastern Mediterranean. The high-density rocks, which appear to have produced this large anomaly, have the form of a rectangular, near-surface, subhorizontal slice, which measures 120 miles east west by 70 miles north-south and whose centre is displaced about 20 miles to the north-west of the centre of Cyprus. This highdensity mass must be at least 7 miles thick under Mount Olympus, whilst at Pomos a thickness of over 20 miles is estimated; its maximum elevation is at Mount Olympus where the dunites and peridotites of the Troodos Plutonic Complex crop out. A correlation between the ultrabasic rocks of the Troodos Plutonic Complex and the high-density material causing the main anomaly is well substantiated. The geological and geophysical evidence suggests that the Troodos massif evolved in pre-Triassic times as an oceanic volcanic pile situated between the then more widely spaced continental masses of Africa and Eurasia. During the Alpine orogeny these continental masses converged, the southern mass underthrusting the Troodos volcanic pile, and parts of the Eurasian hinterland. The under thrusting took place at such a level that not only the volcanic pile but also part of the upper mantle was uplifted above sea level as an undeformed slice. Intense erosion has denuded the volcanic pile almost to its roots. It is thought that the stratiform Troodos Plutonic Complex might represent upper mantle material, partly fused and differentiated to provide the basic volcanic rocks of the Troodos massif.

Abstract Pulsating auroras show quasi‐periodic intensity modulations caused by the precipitation of energetic electrons of the order of tens of keV. It is expected theoretically that not only these electrons but also subrelativistic/relativistic electrons precipitate simultaneously into the ionosphere owing to whistler mode wave‐particle interactions. The height‐resolved electron density profile was observed with the European Incoherent Scatter (EISCAT) Tromsø VHF radar on 17 November 2012. Electron density enhancements were clearly identified at altitudes >68 km in association with the pulsating aurora, suggesting precipitation of electrons with a broadband energy range from ~10 keV up to at least 200 keV. The riometer and network of subionospheric radio wave observations also showed the energetic electron precipitations during this period. During this period, the footprint of the Van Allen Probe‐A satellite was very close to Tromsø and the satellite observed rising tone emissions of the lower band chorus (LBC) waves near the equatorial plane. Considering the observed LBC waves and electrons, we conducted a computer simulation of the wave‐particle interactions. This showed simultaneous precipitation of electrons at both tens of keV and a few hundred keV, which is consistent with the energy spectrum estimated by the inversion method using the EISCAT observations. This result revealed that electrons with a wide energy range simultaneously precipitate into the ionosphere in association with the pulsating aurora, providing the evidence that pulsating auroras are caused by whistler chorus waves. We suggest that scattering by propagating whistler simultaneously causes both the precipitations of subrelativistic electrons and the pulsating aurora.

PreviousNext No AccessSEG Technical Program Expanded Abstracts 1986FXDECON and complex wiener prediction filterAuthors: Necati GulunayNecati GulunayPetty‐Ray Geophysicalhttps://doi.org/10.1190/1.1893128 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Permalink: https://doi.org/10.1190/1.1893128FiguresReferencesRelatedDetailsCited byRandom Noise Attenuation by Self-supervised Learning from Single Seismic Data11 November 2022 | Mathematical Geosciences, Vol. 79Seismic Shot Gather Denoising by Using a Supervised-Deep-Learning Method with Weak Dependence on Real Noise Data: A Solution to the Lack of Real Noise Data27 May 2022 | Surveys in Geophysics, Vol. 43, No. 5Deep unfolding dictionary learning for seismic denoisingYuhan Sui, Xiaojing Wang, and Jianwei Ma12 September 2022 | GEOPHYSICS, Vol. 0, No. jaAccelerating seismic scattered noise attenuation in offset-vector tile domain: Application of deep learningDawei Liu, Xiaokai Wang, Xiaohai Yang, Haibo Mao, Mauricio D. 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J. S. Grauch, Eric D. Anderson, Samuel J. Heller, Esther K. Stewart, and Laurel G. Woodruff26 October 2020 | Interpretation, Vol. 8, No. 4Random noise reduction using SVD in the frequency domain23 June 2020 | Journal of Petroleum Exploration and Production Technology, Vol. 10, No. 7Nonstationary signal inversion based on shaping regularization for random noise attenuation5 January 2021 | Applied Geophysics, Vol. 17, No. 3A convolutional neural network approach to deblending seismic dataJing Sun, Sigmund Slang, Thomas Elboth, Thomas Larsen Greiner, Steven McDonald, and Leiv-J. Gelius16 January 2020 | GEOPHYSICS, Vol. 85, No. 4Spatially constrained attenuation compensation in the mixed domain15 May 2020 | Geophysical Prospecting, Vol. 68, No. 6Structural complexity‐guided predictive filtering26 February 2020 | Geophysical Prospecting, Vol. 68, No. 5Random noise attenuation via the randomized canonical polyadic decomposition20 November 2019 | Geophysical Prospecting, Vol. 68, No. 3Low‐rank seismic denoising with optimal rank selection for hankel matrices19 November 2019 | Geophysical Prospecting, Vol. 68, No. 3Widely linear denoising of multicomponent seismic data22 August 2019 | Geophysical Prospecting, Vol. 68, No. 2Noise suppression in 2D and 3D seismic data with data-driven sifting algorithmsJulián L. Gómez, Danilo R. Velis, and Juan I. Sabbione11 November 2019 | GEOPHYSICS, Vol. 85, No. 1Data-driven dispersive surface-wave prediction and mode separation using high-resolution dispersion estimationJournal of Applied Geophysics, Vol. 1712-D Seismic Random Noise Attenuation via Self-Paced Nonnegative Dictionary LearningIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 12, No. 12Nonstationary Least-Squares Decomposition With Structural Constraint for Denoising Multi-Channel Seismic DataIEEE Transactions on Geoscience and Remote Sensing, Vol. 57, No. 12Denoising with weak signal preservation by group-sparsity transform learningXiaojing Wang, Bihan Wen, and Jianwei Ma9 October 2019 | GEOPHYSICS, Vol. 84, No. 6Vector-valued seismic data denoising via widely-linear autoregressive modelsBreno Bahia and Mauricio D. Sacchi1 August 2019Strong random noise suppression using low-rank based simultaneously sparse coding, with selective extraction of nonlocal means estimatesWenhan Sun, Qizhen Du, Qiang Zhao, and Liyun Fu1 August 2019Seismic Random Noise Attenuation Using Sparse Low-Rank Estimation of the Signal in the Time–Frequency DomainIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 12, No. 5Robust Estimation of Multiple Local Dips via Multidirectional Component AnalysisIEEE Transactions on Geoscience and Remote Sensing, Vol. 57, No. 5Comparative analysis of 3D RTM Implementation Strategies for an Efficient Use of Memory in a Single GPU:19 December 2018 | CT&F - Ciencia, Tecnología y Futuro, Vol. 8, No. 2Edge-preserving frequency-offset denoising of seismic dataJulián L. Gómez and Danilo R. Velis7 September 2018 | GEOPHYSICS, Vol. 83, No. 5Weighted Multisteps Adaptive Autoregression for Seismic Image DenoisingIEEE Geoscience and Remote Sensing Letters, Vol. 15, No. 9Sparse graph-regularized dictionary learning for suppressing random seismic noiseLina Liu, Jianwei Ma, and Gerlind Plonka19 April 2018 | GEOPHYSICS, Vol. 83, No. 3Common Reflection Surface Stack Imaging of the Proterozoic Chambal Valley Vindhyan Basin and Its Boundary Fault in the Northwest India: Constraints on Crustal Evolution and Basin Formation15 May 2018 | Tectonics, Vol. 37, No. 5An overview of reproducible 3D seismic data processing and imaging using MadagascarCan Oren and Robert L. Nowack10 January 2018 | GEOPHYSICS, Vol. 83, No. 2BIBLIOGRAPHY8 June 2018References14 March 2018Coherent noise suppression by learning and analyzing the morphology of the dataPierre Turquais, Endrias G. Asgedom, and Walter Söllner9 October 2017 | GEOPHYSICS, Vol. 82, No. 6Denoising and improving the quality of seismic data using combination of DBM filter and FX deconvolution11 October 2017 | Arabian Journal of Geosciences, Vol. 10, No. 19Signal leakage in f-x deconvolution algorithmsNecati Gülünay25 August 2017 | GEOPHYSICS, Vol. 82, No. 5Laterally-constrained sparse deconvolution in the mixed domainWei Wang, Guofa Li, Yumin Zhao, Wuyang Yang, and Wanli Wang17 August 2017Double Least-Squares Projections Method for Signal EstimationIEEE Transactions on Geoscience and Remote Sensing, Vol. 55, No. 7A method of combining coherence-constrained sparse coding and dictionary learning for denoisingPierre Turquais, Endrias G. Asgedom, and Walter Söllner27 February 2017 | GEOPHYSICS, Vol. 82, No. 3Attenuation of noise and simultaneous source interference using wavelet denoisingZhou Yu, Ray Abma, John Etgen, and Claire Sullivan5 April 2017 | GEOPHYSICS, Vol. 82, No. 3Robust f - x projection filtering for simultaneous random and erratic seismic noise attenuation25 August 2016 | Geophysical Prospecting, Vol. 65, No. 3Signal extraction using randomized-order multichannel singular spectrum analysisWeilin Huang, Runqiu Wang, Yimin Yuan, Shuwei Gan, and Yangkang Chen28 December 2016 | GEOPHYSICS, Vol. 82, No. 2Singular spectrum analysis and its applications in mapping mantle seismic structure19 December 2016 | Geophysical Journal International, Vol. 208, No. 3A simple method inspired by empirical mode decomposition for denoising seismic dataJulián L. Gómez and Danilo R. Velis7 September 2016 | GEOPHYSICS, Vol. 81, No. 6Adaptive rank selection for singular spectrum analysis via dip decompositionYangkang Chen, Wei Chen, Shaohuan Zu, Weilin Huang, and Dong Zhang1 September 2016Local SNR estimation method for seismic dataBingxiu Li, Dian Wang, Yang Liu, and Cai Liu1 September 2016Seismic Processing: Noise Attenuation Complete Session1 September 2016Damped multichannel singular spectrum analysis for 3D random noise attenuationWeilin Huang, Runqiu Wang, Yangkang Chen, Huijian Li, and Shuwei Gan13 May 2016 | GEOPHYSICS, Vol. 81, No. 4Double-sparsity dictionary for seismic noise attenuationYangkang Chen, Jianwei Ma, and Sergey Fomel3 March 2016 | GEOPHYSICS, Vol. 81, No. 2Sparse time-frequency representation for seismic noise reduction using low-rank and sparse decompositionMohammad Amir Nazari Siahsar, Saman Gholtashi, Amin Roshandel Kahoo, Hosein Marvi, and Alireza Ahmadifard8 March 2016 | GEOPHYSICS, Vol. 81, No. 2Seismic data denoising through multiscale and sparsity-promoting dictionary learningLingchen Zhu, Entao Liu, and James H. 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Green, and Heinrich Horstmeyer7 February 2012 | GEOPHYSICS, Vol. 65, No. 1INDEPTH (International Deep Profiling of Tibet and the Himalaya) multichannel seismic reflection data: Description and availability10 November 1998 | Journal of Geophysical Research: Solid Earth, Vol. 103, No. B11A simple method for migrating narrow aperture, noisy seismic reflection data and application to Project INDEPTH (International Deep Profiling of Tibet and the Himalaya) deep seismic profiles10 August 1997 | Journal of Geophysical Research: Solid Earth, Vol. 102, No. B8Possible upper mantle reflection fabric on seismic profiles from the Tethyan Himalaya: Identification and tectonic interpretation10 November 1996 | Journal of Geophysical Research: Solid Earth, Vol. 101, No. B11Efficient F‐K domain seismic trace interpolation for spatially aliased dataJiuying Guo, Xingyuan Zhou, Huey‐Ju Yang, and Shun Diao10 February 2005Impact of processing on the amplitude versus offset response of a marine seismic data set1Geophysical Prospecting, Vol. 43, No. 3Enhanced random noise removal by inversionRaymond L. Abma10 February 2005Prediction filtering for 3‐D poststack dataN. Gulunay, V. Sudhakar, C. Gerrard, and D. Monk10 February 2005Acquisition and processing techniques to improve the seismic resolution of Tertiary targets29 June 2022 | Geological Society, London, Petroleum Geology Conference Series, Vol. 4, No. 1 SEG Technical Program Expanded Abstracts 1986ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 1986 Pages: 715 publication data© 1986 Copyright © 1986 Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 07 Mar 2005 CITATION INFORMATION Necati Gulunay, (1986), "FXDECON and complex wiener prediction filter," SEG Technical Program Expanded Abstracts : 279-281. https://doi.org/10.1190/1.1893128 Plain-Language Summary PDF DownloadLoading ...

The dipole configuration of the Earth's magnetic field allows for the trapping of highly energetic particles, which form the radiation belts. Although significant advances have been made in understanding the acceleration mechanisms in the radiation belts, the loss processes remain poorly understood. Unique observations on 17 January 2013 provide detailed information throughout the belts on the energy spectrum and pitch angle (angle between the velocity of a particle and the magnetic field) distribution of electrons up to ultra-relativistic energies. Here we show that although relativistic electrons are enhanced, ultra-relativistic electrons become depleted and distributions of particles show very clear telltale signatures of electromagnetic ion cyclotron wave-induced loss. Comparisons between observations and modelling of the evolution of the electron flux and pitch angle show that electromagnetic ion cyclotron waves provide the dominant loss mechanism at ultra-relativistic energies and produce a profound dropout of the ultra-relativistic radiation belt fluxes.

Abstract Curie point temperatures ( T C ) of natural and synthetic magnetic materials are commonly determined in rock magnetism by several measurement methods that can be mutually incompatible and may lead to inconsistent results. Here the common evaluation routines for high‐temperature magnetization and magnetic initial susceptibility curves are analyzed and revised based on Landau's theory of second‐order phase transitions. It is confirmed that in high‐field magnetization curves T C corresponds to the inflection point, below the temperature of maximum curvature or the double‐tangent intersection point. At least four different physical processes contribute to the initial magnetic susceptibility near the ordering temperature. They include variation of saturation magnetization, superparamagnetic behavior, magnetization rotation, and magnetic domain wall motion. Because each of these processes may influence the apparent position of T C , initial susceptibility and high‐field curves can yield deviating estimates of T C . A new procedure is proposed to efficiently determine the temperature variation of several magnetic parameters on a vibrating‐sample magnetometer, by repeatedly measuring quarter‐hysteresis loops during a single heating cycle. This procedure takes measurements during the inevitable waiting time necessary for thermal equilibration of the sample, whereby it is not slower than the commonly performed measurements on a Curie balance. However, it returns saturation magnetization, saturation remanence, high‐field and low‐field slopes, and other parameters as a function of temperature, which provide independent information about T C and other sample properties.

Abstract. We present a general concept of mechanisms of preseismic phenomena in the atmosphere and ionosphere. After short review of observational results we conclude: 1. Upward migration of fluid substrate matter (bubble) can lead to ousting of the hot water/gas near the ground surface and cause an earthquake (EQ) itself in the strength-weakened area; 2. Thus, time and place of the bubble appearance could be random values, but EQ, geochemistry anomaly and foreshocks (seismic, SA and ULF electromagnetic ones) are casually connected; 3. Atmospheric perturbation of temperature and density could follow preseismic hot water/gas release resulting in generation of atmospheric gravity waves (AGW) with periods in a range of 6–60min; 4. Seismo-induced AGW could lead to modification of the ionospheric turbulence and to the change of over-horizon radio-wave propagation in the atmosphere, perturbation of LF waves in the lower ionosphere and ULF emission depression at the ground.

Dynamical predictions of landslide runout require measurements of the basal friction. Here we present the first seismically determined bounds on the frictional coefficients for three large volcanic landslides. The three landslides (Bezymianny, Russia 1956, Sheveluch, Russia 1964 and Mount St. Helens, USA 1980) have masses that vary by a factor of 5 and were all followed immediately by eruptions. We use teleseismic and regional seismic data to show that all three landslides are consistent with an apparent coefficient of friction of 0.2 which corresponds to an actual areally‐averaged frictional coefficient of 0.2–0.6. The apparent friction is independent of the quantity of hot gas subsequently released.

Independent Okhotsk and Amurian microplate motions are tested using velocities from 123 GPS sites (80 from within the proposed OKH and AMU plate boundaries) used to constrain the plate kinematics of northeast Asia. A block modeling approach is used to incorporate both rigid block rotation and near‐boundary elastic strain accumulation effects in a formal inversion of the GPS velocities. Models include scenarios with and without independent OKH and AMU plate motion. Our modeling favors scenarios with independent OKH and AMU motion, based on the application of F‐test statistics. The independent OKH plate rotates 0.231 deg/Myr clockwise with respect to North America about a pole located north of Sakhalin. The modeled AMU plate rotates 0.298 deg/Myr counterclockwise with respect to NAM about a pole located west of the Magadan region. The plate‐motion parameters of the independent plates are consistent with the kinematics inferred from earthquake focal mechanism solutions along their boundaries.

M. More importantly, the N,S-CDs display an unambiguous bioimaging ability in the detection of intracellular temperature and TC with satisfactory results.

Here we present the results of local source tomographic inversion beneath central Java. The data set was collected by a temporary seismic network. More than 100 stations were operated for almost half a year. About 13,000 P and S arrival times from 292 events were used to obtain three‐dimensional (3‐D) Vp , Vs , and Vp / Vs models of the crust and the mantle wedge beneath central Java. Source location and determination of the 3‐D velocity models were performed simultaneously based on a new iterative tomographic algorithm, LOTOS‐06. Final event locations clearly image the shape of the subduction zone beneath central Java. The dipping angle of the slab increases gradually from almost horizontal to about 70°. A double seismic zone is observed in the slab between 80 and 150 km depth. The most striking feature of the resulting P and S models is a pronounced low‐velocity anomaly in the crust, just north of the volcanic arc (Merapi‐Lawu anomaly (MLA)). An algorithm for estimation of the amplitude value, which is presented in the paper, shows that the difference between the fore arc and MLA velocities at a depth of 10 km reaches 30% and 36% in P and S models, respectively. The value of the Vp / Vs ratio inside the MLA is more than 1.9. This shows a probable high content of fluids and partial melts within the crust. In the upper mantle we observe an inclined low‐velocity anomaly which links the cluster of seismicity at 100 km depth with MLA. This anomaly might reflect ascending paths of fluids released from the slab. The reliability of all these patterns was tested thoroughly.