Spherical multifocusing method for irregular topography

Geophysics ◽  
2019 ◽  
Vol 84 (4) ◽  
pp. V233-V243
Author(s):  
Dingyue Chang ◽  
Cai Zhang ◽  
Tianyue Hu ◽  
Dan Wang
Keyword(s):  
Signal To Noise Ratio ◽  
Seismic Exploration ◽  
Data Set ◽  
Near Surface ◽  
The Past ◽  
Wide Range ◽  
Common Reflection Surface ◽  
Static Corrections ◽  
The Common ◽  
Irregular Topography

Moveout correction for irregular topography has been a longstanding challenge in processing seismic exploration data. Irregular topography usually results in large moveout among traces, a low signal-to-noise ratio (S/N), and difficulty in modeling near-surface velocities. Conventional normal moveout (NMO) corrections and elevation static methods are imprecise and tend to introduce significant errors for large offsets. Over the past two decades, several multiparameter time corrections and stacking techniques to reduce noise and improve resolution have been proposed in place of the classic NMO and common-midpoint stack. These include the common-reflection-surface (CRS), common-offset CRS, nonhyperbolic CRS, implicit CRS, multifocusing (MF), irregular surface MF (IS-MF), spherical MF (SMF), and common-offset MF methods. Various CRS-type operators that consider the top-surface topography have been proposed. For MF-type operators, only IS-MF can be applied directly to the irregular topography with no elevation statics required. In this study, we have developed a new MF formulation, modifying the SMF method to consider nonzero elevations of sources and receivers and we corrected moveout of nonplanar data directly without prior elevation static corrections. The proposed extension combines the sensitivity to spherical reflectors of SMF with the applicability of the IS-MF method to irregular topography. We investigated the behavior of the new operator using a physical model data set and compared the results with those from the conventional IS-MF method. The results revealed that the new operator is more robust over a wide range of source and receiver elevations and has advantages on strongly curved interfaces. We also confirmed the potential of the proposed approach by comparing stacking results for a real-land data set with a low S/N.

Nonlinear beamforming for enhancement of 3D prestack land seismic data

Geophysics ◽  
2020 ◽  
Vol 85 (3) ◽  
pp. V283-V296 ◽  
Author(s):  
Andrey Bakulin ◽  
Ilya Silvestrov ◽  
Maxim Dmitriev ◽  
Dmitry Neklyudov ◽  
Maxim Protasov ◽  
...  
Keyword(s):  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Noise Removal ◽  
Sensor Data ◽  
Reservoir Properties ◽  
Near Surface ◽  
3D Data ◽  
Common Reflection Surface ◽  
Single Sensor ◽  
The Common

We have developed nonlinear beamforming (NLBF), a method for enhancing modern 3D prestack seismic data acquired onshore with small field arrays or single sensors in which weak reflected signals are buried beneath the strong scattered noise induced by a complex near surface. The method is based on the ideas of multidimensional stacking techniques, such as the common-reflection-surface stack and multifocusing, but it is designed specifically to improve the prestack signal-to-noise ratio of modern 3D land seismic data. Essentially, NLBF searches for coherent local events in the prestack data and then performs beamforming along the estimated surfaces. Comparing different gathers that can be extracted from modern 3D data acquired with orthogonal acquisition geometries, we determine that the cross-spread domain (CSD) is typically the most convenient and efficient. Conventional noise removal applied to modern data from small arrays or single sensors does not adequately reveal the underlying reflection signal. Instead, NLBF supplements these conventional tools and performs final aggregation of weak and still broken reflection signals, where the strength is controlled by the summation aperture. We have developed the details of the NLBF algorithm in CSD and determined the capabilities of the method on real 3D land data with the focus on enhancing reflections and early arrivals. We expect NLBF to help streamline seismic processing of modern high-channel-count and single-sensor data, leading to improved images as well as better prestack data for estimation of reservoir properties.

scholarly journals Analyze COVID-19 CT images based on evolutionary algorithm with dynamic searching space

2021 ◽  
Author(s):  
Yunhong Gong ◽  
Yanan Sun ◽  
Dezhong Peng ◽  
Peng Chen ◽  
Zhongtai Yan ◽  
...  
Keyword(s):  
Common Sense ◽  
Expert Knowledge ◽  
State Of The Art ◽  
Data Set ◽  
The Past ◽  
Computed Tomography Images ◽  
Intensive Use ◽  
Hospital Resources ◽  
The Common ◽  
Ct Data

AbstractThe COVID-19 pandemic has caused a global alarm. With the advances in artificial intelligence, the COVID-19 testing capabilities have been greatly expanded, and hospital resources are significantly alleviated. Over the past years, computer vision researches have focused on convolutional neural networks (CNNs), which can significantly improve image analysis ability. However, CNN architectures are usually manually designed with rich expertise that is scarce in practice. Evolutionary algorithms (EAs) can automatically search for the proper CNN architectures and voluntarily optimize the related hyperparameters. The networks searched by EAs can be used to effectively process COVID-19 computed tomography images without expert knowledge and manual setup. In this paper, we propose a novel EA-based algorithm with a dynamic searching space to design the optimal CNN architectures for diagnosing COVID-19 before the pathogenic test. The experiments are performed on the COVID-CT data set against a series of state-of-the-art CNN models. The experiments demonstrate that the architecture searched by the proposed EA-based algorithm achieves the best performance yet without any preprocessing operations. Furthermore, we found through experimentation that the intensive use of batch normalization may deteriorate the performance. This contrasts with the common sense approach of manually designing CNN architectures and will help the related experts in handcrafting CNN models to achieve the best performance without any preprocessing operations

scholarly journals Theoretical Models for Interpreting the Dielectric Behaviour of HF-doped Ice

1978 ◽  
Vol 21 (85) ◽  
pp. 123-141 ◽  
Author(s):  
G. C. Camplin ◽  
J. W. Glen ◽  
J. G. Paren
Keyword(s):  
Single Crystals ◽  
Electrical Conduction ◽  
Fluoride Concentration ◽  
Theoretical Models ◽  
Data Set ◽  
Wide Range ◽  
Yield Values ◽  
Full Knowledge ◽  
The Common ◽  
Ice Lattice

AbstractTo understand the recent dielectric measurements made on HF-doped ice single crystals requires a full knowledge of the concentration of electrical defects present in ice and their subsequent interactions. Previous interpretations of the behaviour of HF-doped ice have concentrated upon specific features in isolation, whereas this paper presents analyses of a data set of 139 temperature and impurity combinations from 17 HF-doped ice single crystals. The interpretation of the behaviour of these crystals is in terms of several possible theoretical models. All models are based upon the common assumptions that HF molecules enter the ice lattice substitutionally and that excess Bjerrum and ionic defects can be formed at the HF sites. They also use the theory of electrical conduction in ice by Jaccard (1959) and the defect equilibria analysis in ice by Kroger (1974).All models yield values for the concentration, mobility, energy of formation and charges for the different types of electrical defect considered to be generated.From the model which assumes that only three fluorine centres exist, the approximate derived values of the mobility and charge for the L-defect and positive ionic defect are as follows: μL = 5 × 10-8 m2 V-1 s-1 at 273 K, eDL = 0.44e; μ+ = 2.7 × 10-8 m2 V-1 s-1 at 273 K, e± 0.73e.Finally, using the derived defect conductivities and the Jaccard theory of electrical conduction, the relaxation tune of HF-doped ice has been successfully predicted over a wide range of temperature and fluoride concentration.

Refraction wavefield migration

Geophysics ◽  
2020 ◽  
Vol 85 (6) ◽  
pp. Q27-Q37
Author(s):  
Yang Shen ◽  
Jie Zhang
Keyword(s):  
Signal To Noise Ratio ◽  
Surface Velocity ◽  
Data Set ◽  
Near Surface ◽  
Depth Migration ◽  
Reflection Data ◽  
Imaging Tool ◽  
Imaging Results ◽  
Migration Method ◽  
Single Method

Refraction methods are often applied to model and image near-surface velocity structures. However, near-surface imaging is very challenging, and no single method can resolve all of the land seismic problems across the world. In addition, deep interfaces are difficult to image from land reflection data due to the associated low signal-to-noise ratio. Following previous research, we have developed a refraction wavefield migration method for imaging shallow and deep interfaces via interferometry. Our method includes two steps: converting refractions into virtual reflection gathers and then applying a prestack depth migration method to produce interface images from the virtual reflection gathers. With a regular recording offset of approximately 3 km, this approach produces an image of a shallow interface within the top 1 km. If the recording offset is very long, the refractions may follow a deep path, and the result may reveal a deep interface. We determine several factors that affect the imaging results using synthetics. We also apply the novel method to one data set with regular recording offsets and another with far offsets; both cases produce sharp images, which are further verified by conventional reflection imaging. This method can be applied as a promising imaging tool when handling practical cases involving data with excessively weak or missing reflections but available refractions.

Slant f-k transform of multichannel seismic surface wave data

Geophysics ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. A19-A24 ◽  
Author(s):  
Aleksander S. Serdyukov ◽  
Aleksander V. Yablokov ◽  
Anton A. Duchkov ◽  
Anton A. Azarov ◽  
Valery D. Baranov
Keyword(s):  
Surface Wave ◽  
Seismic Data ◽  
Signal To Noise Ratio ◽  
Velocity Estimation ◽  
Seismic Exploration ◽  
Spectral Processing ◽  
Near Surface ◽  
Frequency Time Representation ◽  
Time Representation ◽  
S Transform

We have addressed the problem of estimating surface-wave phase velocities through the spectral processing of seismic data. This is the key step of the well-known near-surface seismic exploration method, called multichannel analysis of surface waves. To increase the accuracy and ensure the unambiguity of the selection of dispersion curves, we have developed a new version of the frequency-wavenumber ([Formula: see text]-[Formula: see text]) transform based on the S-transform. We obtain the frequency-time representation of seismic data. We analyze the obtained S-transform frequency-time representation in a slant-stacking manner but use a spatial Fourier transform instead of amplitude stacking. Finally, we build the [Formula: see text]-[Formula: see text] image by analyzing the spatial spectra for different steering values of the surface-wave group velocities. The time localization of the surface-wave packet at each frequency increases the signal-to-noise ratio because of an exclusion of noise in other time steps (which does not fall in the effective width of the corresponding wavelet). The new [Formula: see text]-[Formula: see text] transform, i.e., the slant [Formula: see text]-[Formula: see text] (SFK) transform, renders a better spectral analysis than the conventional [Formula: see text]-[Formula: see text] transform and yields more accurate phase-velocity estimation, which is critical for the surface-wave analysis. The advantages of the SFK transform have been confirmed by synthetic- and field-data processing.

scholarly journals Time-lapse difference static correction using prestack crosscorrelations: 4D seismic image enhancement case from Ketzin

Geophysics ◽  
2014 ◽  
Vol 79 (6) ◽  
pp. B243-B252 ◽  
Author(s):  
Peter Bergmann ◽  
Artem Kashubin ◽  
Monika Ivandic ◽  
Stefan Lüth ◽  
Christopher Juhlin
Keyword(s):  
Seismic Data ◽  
Time Lapse ◽  
Data Sets ◽  
Storage Site ◽  
Data Set ◽  
Near Surface ◽  
Static Correction ◽  
Seismic Image ◽  
Static Corrections ◽  
4D Seismic

A method for static correction of time-lapse differences in reflection arrival times of time-lapse prestack seismic data is presented. These arrival-time differences are typically caused by changes in the near-surface velocities between the acquisitions and had a detrimental impact on time-lapse seismic imaging. Trace-to-trace time shifts of the data sets from different vintages are determined by crosscorrelations. The time shifts are decomposed in a surface-consistent manner, which yields static corrections that tie the repeat data to the baseline data. Hence, this approach implies that new refraction static corrections for the repeat data sets are unnecessary. The approach is demonstrated on a 4D seismic data set from the Ketzin [Formula: see text] pilot storage site, Germany, and is compared with the result of an initial processing that was based on separate refraction static corrections. It is shown that the time-lapse difference static correction approach reduces 4D noise more effectively than separate refraction static corrections and is significantly less labor intensive.

A Seismic Network to Monitor the 2020 EGS Stimulation in the Espoo/Helsinki Area, Southern Finland

2021 ◽  
Author(s):  
Annukka E. Rintamäki ◽  
Gregor Hillers ◽  
Tommi A. T. Vuorinen ◽  
Tuija Luhta ◽  
Jonathan M. Pownall ◽  
...  
Keyword(s):  
Seismic Analysis ◽  
Signal To Noise Ratio ◽  
Public Awareness ◽  
Seismic Network ◽  
Geothermal System ◽  
Induced Earthquakes ◽  
Data Set ◽  
Short Period ◽  
Wide Range ◽  
Good Signal

Abstract We present the deployment of a seismic network in the Helsinki capital area of Finland that was installed to monitor the response to the second stimulation phase of an ∼6-kilometer-deep enhanced geothermal system in 2020. The network consists of a dozen permanent broadband stations and more than 100, predominantly short-period, temporary stations. This 2020 deployment is characterized by a mix of single stations and arrays with diverse configurations. It covers a larger area and exhibits a smaller azimuthal gap compared with the network that monitored the first stimulation in 2018. We surveyed the outcropping rocks at one of the large array sites to study surface expressions of shear or weakness zones that are possibly connected to the stimulated volume at depth. We link the relatively large number of macroseismic reports received during the stimulation to an increased public awareness of the project together with an increased sensitivity because the second stimulation occurred during the local COVID-19 mobility restrictions. The spatial distribution of the reports seems to be controlled by the radiation pattern of the induced earthquakes and hence by the stress state in the reservoir. The continuous records contain strong energy at high frequencies above 50 Hz that is attributed to anthropogenic processes in the densely populated urban area. However, the exceptionally low attenuation of the bedrock yields good signal-to-noise ratio seismograms of the induced small events, the largest of which was magnitude ML 1.2. The signal quality of the obtained noise correlation functions is similarly very good. The data set has been collected to underpin a wide range of seismic analysis techniques for complementary scientific studies of the evolving reservoir processes and the induced event properties. These scientific studies should inform the legislation and educate the public for transparent decision making around geothermal power generation.

Advances in surface-wave tomography for near-surface applications

2021 ◽  
Vol 40 (8) ◽  
pp. 567-575
Author(s):  
Myrto Papadopoulou ◽  
Farbod Khosro Anjom ◽  
Mohammad Karim Karimpour ◽  
Valentina Laura Socco
Keyword(s):  
Surface Wave ◽  
Wave Velocity ◽  
P Wave ◽  
Seismic Exploration ◽  
S Wave ◽  
Data Set ◽  
Near Surface ◽  
Processing Times ◽  
Spatial Coverage ◽  
Wave Tomography

Surface-wave (SW) tomography is a technique that has been widely used in the field of seismology. It can provide higher resolution relative to the classical multichannel SW processing and inversion schemes that are usually adopted for near-surface applications. Nevertheless, the method is rarely used in this context, mainly due to the long processing times needed to pick the dispersion curves as well as the inability of the two-station processing to discriminate between higher SW modes. To make it efficient and to retrieve pseudo-2D/3D S-wave velocity (VS) and P-wave velocity (VP) models in a fast and convenient way, we develop a fully data-driven two-station dispersion curve estimation, which achieves dense spatial coverage without the involvement of an operator. To handle higher SW modes, we apply a dedicated time-windowing algorithm to isolate and pick the different modes. A multimodal tomographic inversion is applied to estimate a VS model. The VS model is then converted to a VP model with the Poisson's ratio estimated through the wavelength-depth method. We apply the method to a 2D seismic exploration data set acquired at a mining site, where strong lateral heterogeneity is expected, and to a 3D pilot data set, recorded with state-of-the-art acquisition technology. We compare the results with the ones retrieved from classical multichannel analysis.

scholarly journals A generalized view on normal moveout

Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. V335-V349 ◽  
Author(s):  
Benjamin Schwarz ◽  
Dirk Gajewski
Keyword(s):  
Seismic Events ◽  
Velocity Analysis ◽  
The Past ◽  
Dual Representations ◽  
Optical Projection ◽  
Passive Seismic ◽  
Common Reflection Surface ◽  
The Common ◽  
Ray Geometry ◽  
Insight Into

Although in the past, in the context of stacking, traveltime moveout was only formulated in individual common-midpoint (CMP) gathers, multiparameter stacking uses normal moveout (NMO) approximations that span several neighboring CMPs. Multiparameter expressions such as the common reflection surface (CRS) or multifocusing are parameterized in terms of local slopes and curvatures of emerging wavefronts rather than effective velocities, which makes these approaches appear conceptually different from conventional velocity analysis. As a consequence, the unifying nature of multiparameter NMO is still not well-appreciated. In addition, CRS and multifocusing show distinctly different behavior in that they respond differently to the overburden heterogeneity and curvature of the target interface, and they either are or are not susceptible to moveout stretch. In our work, we seek to demystify the wavefront picture by demonstrating that the conventional and multidimensional NMO operators can conveniently be derived from the same auxiliary straight-ray geometry, either representing the optical projection or formulated in an effective replacement medium. Following the early work of de Bazelaire, we suggest a simple transformation between both domains and introduce generalized dual representations of the hyperbolic CRS, multifocusing, and the two recently introduced double-square-root expressions implicit CRS and nonhyperbolic CRS. In addition, we evaluate a generalized finite-offset NMO expression that can likewise be applied to active-source diffraction data and passive seismic events. Synthetic examples suggest unification, conveniently explain the origin of moveout stretch, and indicate that the joint use of different NMO approximations offers new insight into the character and origin of different wavefield components.

scholarly journals Theoretical Models for Interpreting the Dielectric Behaviour of HF-doped Ice

1978 ◽  
Vol 21 (85) ◽  
pp. 123-141 ◽  
Author(s):  
G. C. Camplin ◽  
J. W. Glen ◽  
J. G. Paren
Keyword(s):  
Single Crystals ◽  
Electrical Conduction ◽  
Fluoride Concentration ◽  
Theoretical Models ◽  
Data Set ◽  
Wide Range ◽  
Yield Values ◽  
Full Knowledge ◽  
The Common ◽  
Ice Lattice

Abstract To understand the recent dielectric measurements made on HF-doped ice single crystals requires a full knowledge of the concentration of electrical defects present in ice and their subsequent interactions. Previous interpretations of the behaviour of HF-doped ice have concentrated upon specific features in isolation, whereas this paper presents analyses of a data set of 139 temperature and impurity combinations from 17 HF-doped ice single crystals. The interpretation of the behaviour of these crystals is in terms of several possible theoretical models. All models are based upon the common assumptions that HF molecules enter the ice lattice substitutionally and that excess Bjerrum and ionic defects can be formed at the HF sites. They also use the theory of electrical conduction in ice by Jaccard (1959) and the defect equilibria analysis in ice by Kroger (1974). All models yield values for the concentration, mobility, energy of formation and charges for the different types of electrical defect considered to be generated. From the model which assumes that only three fluorine centres exist, the approximate derived values of the mobility and charge for the L-defect and positive ionic defect are as follows: μ L = 5 × 10-8 m2 V-1 s-1 at 273 K, eDL = 0.44e; μ + = 2.7 × 10-8 m2 V-1 s-1 at 273 K, e ± 0.73 e . Finally, using the derived defect conductivities and the Jaccard theory of electrical conduction, the relaxation tune of HF-doped ice has been successfully predicted over a wide range of temperature and fluoride concentration.

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