Seismic ground-roll noise attenuation using deep learning     

Harpreet Kaur  Sergey Fomel  Nam Pham 《Geophysical Prospecting》2020,68(7):2064-2077

We propose to adopt a deep learning based framework using generative adversarial networks for ground-roll attenuation in land seismic data. Accounting for the non-stationary properties of seismic data and the associated ground-roll noise, we create training labels using local time–frequency transform and regularized non-stationary regression. The basic idea is to train the network using a few shot gathers such that the network can learn the weights associated with noise attenuation for the training shot gathers. We then apply the learned weights to test ground-roll attenuation on shot gathers, that are not a part of training input to obtain the desired signal. This approach gives results similar to local time–frequency transform and regularized non-stationary regression but at a significantly reduced computational cost. The proposed approach automates the ground-roll attenuation process without requiring any manual input in picking the parameters for each shot gather other than in the training data. Tests on field-data examples verify the effectiveness of the proposed approach.  相似文献   

Research on Parallel Algorithms for uv-faceting Imaging     

《Chinese Astronomy and Astrophysics》2019,43(3):424-443

The uv-faceting imaging is one of the widely used large field of view imaging technologies, and will be adopted for the data processing of the low-frequency array in the first stage of the Square Kilometre Array (SKA1). Due to the scale of the raw data of SKA1 is unprecedentedly large, the efficiency of data processing directly using the original uv-faceting imaging will be very low. Therefore, a uv-faceting imaging algorithm based on the MPI (Message Passing Interface)+OpenMP (Open Multi-Processing) and a uv-faceting imaging algorithm based on the MPI+CUDA (Compute Unified Device Architecture) are proposed. The most time-consuming data reading and gridding in the algorithm are optimized in parallel. The verification results show that the results of the proposed two algorithms are basically consistent with that obtained by the current mainstream data processing software CASA (Common Astronomy Software Applications), which indicates that the proposed two algorithms are basically correct. Further analysis of the accuracy and total running time shows that the MPI+CUDA method is better than the MPI+OpenMP method in both the correctness rate and running speed. The performance test results show that the proposed algorithms are effective and have certain extensibility.  相似文献   

地磁台站勘选数据处理系统设计     

王莉森  张云昌  殷金平  王江 《地震地磁观测与研究》2020,41(4):217-224

为实现地磁台站场地勘选指标的快速计算和勘选报告的在线保存与查询，提高地磁台站勘选数据处理效率，降低人工处理数据错误率，在现有地磁数据处理软件功能的基础上设计开发地磁台站勘选数据处理系统，以提高勘选的工作效率。  相似文献   

Research note: deblended-data reconstruction using generalized blending and deblending models     

Tomohide Ishiyama  Mohammed Y. Ali  Satoshi Ishikawa  Gerrit Blacquiere  Shotaro Nakayama 《Geophysical Prospecting》2019,67(7):1852-1866

We introduce a concept of generalized blending and deblending, develop its models and accordingly establish a method of deblended-data reconstruction using these models. The generalized models can handle real situations by including random encoding into the generalized operators both in the space and time domain, and both at the source and receiver side. We consider an iterative optimization scheme using a closed-loop approach with the generalized blending and deblending models, in which the former works for the forward modelling and the latter for the inverse modelling in the closed loop. We applied our method to existing real data acquired in Abu Dhabi. The results show that our method succeeded to fully reconstruct deblended data even from the fully generalized, thus quite complicated blended data. We discuss the complexity of blending properties on the deblending performance. In addition, we discuss the applicability to time-lapse seismic monitoring as it ensures high repeatability of the surveys. Conclusively, we should acquire blended data and reconstruct deblended data without serious problems but with the benefit of blended acquisition.  相似文献   

强震动记录H/V谱比法计算处理的若干关键环节     

姚鑫鑫  任叶飞  温瑞智  戴嘉伟 《震灾防御技术》2019,14(4):719-730

强震动记录H/V谱比法自提出以来，已广泛应用于地震工程各研究领域中。但对数据处理的2个关键环节——Taper预处理及傅氏谱平滑未有详细研究。因此，本文针对强震动记录H/V谱比法计算涉及的重要数据处理过程，对四川地区19个强震动台站在汶川地震余震中获取的642组强震动记录开展研究。研究实例表明:S波H/V谱比振幅在周期 < 1s时高于全时程，论证计算H/V谱比时截取S波窗口的必要性；S波窗口的截断会引起傅里叶振幅谱的边瓣效应，若不加以处理，将显著影响低频部分H/V谱比结果，Taper预处理对于消除这种截断误差具有良好效果；在兼顾平滑效果及卓越周期识别准确度的基础上，通过不同带宽的Parzen窗试算，认为0.5Hz带宽宜用于傅里叶H/V谱比曲线平滑。  相似文献   

重磁处理解释系统软件设计与关键实现技术          下载免费PDF全文

郑元满  姚长利  李泽林  刘强 《地球物理学报》2019,62(10):3744-3759

重磁探测是金属矿勘探的主要手段之一，其处理和解释方法技术已得到很大的发展，研发与其相适应的重磁软件是重要的研究课题.在国家863课题的支持下，我们设计并研发了重磁处理解释集成化软件系统.在分析国内外现有软件不足的基础上，我们对重磁软件系统所应具有的操作行为进行了针对性的设计，提出了具有特色的功能设计思路，并进行了针对性的研发实现.为满足深部矿产资源勘探需求和精细化解释需要，提出了更加具有针对性的软件设计解决方案，研发了特色的处理解释模块，核心突出软件的实时可视化和协同交互操作，使软件系统能高效地服务于使用者的目标任务.在优化改进处理、正反演算法的基础上，提出多核并行化方案并实现，提高了软件整体运行速度.最终形成了将数据管理、数据可视化、数据处理及解释有机结合的特色软件系统，为金属矿探测提供了一个高效、有力的工具.  相似文献   

Petrophysics and mineral exploration: a workflow for data analysis and a new interpretation framework     

Michael Dentith  Randolph J. Enkin  William Morris  Cameron Adams  Barry Bourne 《Geophysical Prospecting》2020,68(1):178-199

As mineral exploration seeks deeper targets, there will be a greater reliance on geophysical data and a better understanding of the geological meaning of the responses will be required, and this must be achieved with less geological control from drilling. Also, exploring based on the mineral system concept requires particular understanding of geophysical responses associated with altered rocks. Where petrophysical datasets of adequate sample size and measurement quality are available, physical properties show complex variations, reflecting the combined effects of various geological processes. Large datasets, analysed as populations, are required to understand the variations. We recommend the display of petrophysical data as frequency histograms because the nature of the data distribution is easily seen with this form of display. A petrophysical dataset commonly contains a combination of overlapping sub-populations, influenced by different geological factors. To understand the geological controls on physical properties in hard rock environments, it is necessary to analyse the petrophysical data not only in terms of the properties of different rock types. It is also necessary to consider the effects of processes such as alteration, weathering, metamorphism and strain, and variables such as porosity and stratigraphy. To address this complexity requires that much more supporting geological information be acquired than in current practice. The widespread availability of field portable instruments means quantitative geochemical and mineralogical data can now be readily acquired, making it unnecessary to rely primarily on categorical rock classification schemes. The petrophysical data can be combined with geochemical, petrological and mineralogical data to derive explanations for observed physical property variations based not only on rigorous rock classification methods, but also in combination with quantitative estimates of alteration and weathering. To understand how geological processes will affect different physical properties, it is useful to define three end-member forms of behaviour. Bulk behaviour depends on the physical properties of the dominant mineral components. Density and, to a lesser extent, seismic velocity show such behaviour. Grain and texture behaviour occur when minor components of the rock are the dominate controls on its physical properties. Grain size and shape control grain properties, and for texture properties the relative positions of these grains are also important. Magnetic and electrical properties behave in this fashion. Thinking in terms of how geological processes change the key characteristics of the major and minor mineralogical components allows the resulting changes in physical properties to be understood and anticipated.  相似文献   

Prestack data enhancement with phase corrections in time-frequency domain guided by local multidimensional stacking     

Andrey Bakulin  Dmitri Neklyudov  Ilya Silvestrov 《Geophysical Prospecting》2020,68(6):1811-1818

We present a new approach to enhancing weak prestack reflection signals without sacrificing higher frequencies. As a first step, we employ known multidimensional local stacking to obtain an approximate ‘model of the signal’. Guided by phase spectra from this model, we can detect very weak signals and make them visible and coherent by ‘repairing’ corrupted phase of original data. Both presented approaches – phase substitution and phase sign corrections – show good performance on complex synthetic and field data suffering from severe near-surface scattering where conventional processing methods are rendered ineffective. The methods are mathematically formulated as a special case of time-frequency masking (common in speech processing) combined with the signal model from local stacking. This powerful combination opens the avenue for a completely new family of approaches for multi-channel seismic processing that can address seismic processing of land data with nodes and single sensors in the desert environment.  相似文献   

A high-precision time–frequency analysis for thin hydrocarbon reservoir identification based on synchroextracting generalized S-transform     

Ying Hu  Hui Chen  Hongyan Qian  Xinyue Zhou  Yuanjun Wang  Bin Lyu 《Geophysical Prospecting》2020,68(3):941-954

Improving the seismic time–frequency resolution is a crucial step for identifying thin reservoirs. In this paper, we propose a new high-precision time–frequency analysis algorithm, synchroextracting generalized S-transform, which exhibits superior performance at characterizing reservoirs and detecting hydrocarbons. This method first calculates time–frequency spectra using generalized S-transform; then, it squeezes all but the most smeared time–frequency coefficients into the instantaneous frequency trajectory and finally obtains highly accurate and energy-concentrated time–frequency spectra. We precisely deduce the mathematical formula of the synchroextracting generalized S-transform. Synthetic signal examples testify that this method can correctly decompose a signal and provide a better time–frequency representation. The results of a synthetic seismic signal and real seismic data demonstrate that this method can identify some reservoirs with thincknesses smaller than a quarter wavelength and can be successfully applied for hydrocarbon detection. In addition, examples of synthetic signals with different levels of Gaussian white noise show that this method can achieve better results under noisy conditions. Hence, the synchroextracting generalized S-transform has great application prospects and merits in seismic signal processing and interpretation.  相似文献   

Monitoring soil surface roughness under growing winter wheat with low-altitude UAV sensing: Potential and limitations     

Nils Onnen  Anette Eltner  Goswin Heckrath  Kristof Van Oost 《地球表面变化过程与地形》2020,45(14):3747-3759

Soil surface roughness (SSR) is an important factor in controlling sediment and runoff generation, influencing directly a wide spectrum of erosion parameters. SSR is highly variable in time and space under natural conditions, and characterizing SSR to improve the parameterization of hydrological and erosion models has proved challenging. Our study uses recent technological and algorithmic developments in capturing and processing close aerial sensing data to evaluate how high-resolution imagery can assist the temporally and spatially explicit monitoring of SSR. We evaluated the evolution of SSR under natural rainfall and growing vegetation conditions on two arable fields in Denmark. Unmanned aerial vehicle (UAV) photogrammetry was used to monitor small field plots over 7 months after seeding of winter wheat following conventional and reduced tillage treatments. Field campaigns were conducted at least once a month from October until April, resulting in nine time steps of data acquisition. Structure from motion photogrammetry was used to derive high-resolution point clouds with an average ground sampling distance of 2.7 mm and a mean ground control point accuracy of 1.8 mm. A comprehensive workflow was developed to process the point clouds, including the detection of vegetation and the removal of vegetation-induced point cloud noise. Rasterized and filtered point clouds were then used to determine SSR geostatistically as the standard deviation of height, applying different kernel sizes and using semivariograms. The results showed an influence of kernel size on roughness, with a value range of 0.2–1 cm of average height deviation during the monitoring period. Semivariograms showed a measurable decrease in sill variance and an increase in range over time. This research demonstrated multiple challenges to measuring SSR with UAV under natural conditions with increasing vegetation cover. The proposed workflow represents a step forward in tackling those challenges and provides a knowledge base for future research. © 2020 John Wiley & Sons, Ltd.  相似文献