scholarly journals Autocorrelation of the ground vibration recorded by the SEIS-InSight seismometer on Mars for imaging and monitoring applications

2021 ◽  
Author(s):  
Nicolas Compaire ◽  
Ludovic Margerin ◽  
Raphaël F. Garcia ◽  
Marie Calvet ◽  
Baptiste Pinot ◽  
...  
Keyword(s):  
Seismic Waves ◽  
Signal To Noise Ratio ◽  
Ground Vibration ◽  
Velocity Model ◽  
Temporal Variations ◽  
Seismic Events ◽  
Ambient Vibrations ◽  
Ground Response ◽  
Arrival Times ◽  
Single Station

<p>Since early February 2019, the SEIS seismometer deployed at the surface of Mars in the framework of the NASA-InSight mission has been continuously recording the ground motion at Elysium Planitia. In this work, we take advantage of this exceptional dataset to put constraints on the crustal properties of Mars using seismic interferometry (SI). This method use the seismic waves, either from background vibrations of the planet or from quakes, that are scattered in the medium in order to recover the ground response between two seismic sensors. Applying the principles of SI to the single-station configuration of SEIS, we compute, for each Sol (martian day) and each local hour, all the components of the time-domain autocorrelation tensor of random ambient vibrations in various frequency bands. A similar computation is performed on the diffuse waveforms generated by more than a hundred Marsquakes. For imaging application a careful signal-to-noise ratio analysis and an inter-comparison between the two datasets are applied. These analyses suggest that the reconstructed ground responses are most reliable in a relatively narrow frequency band around 2.4Hz, where an amplification of both ambient vibrations and seismic events is observed. The average Auto-Correlation Functions (ACFs) from both ambient vibrations and seismic events contain well identifiable seismic arrivals, that are very consistent between the two datasets. We interpret the vertical and horizontal ACFs as the ground reflection response below InSight for the compressional waves and the shear waves respectively. We propose a simple stratified velocity model of the crust, which is most compatible with the arrival times of the detected phases, as well as with previous seismological studies of the SEIS record. The hourly computation of the ACFs over one martian year also allows us to study the diurnal and seasonal variations of the reconstructed ground response with a technique call Passive Image Interferometry (PII). In this study we present measurements of the relative stretching coefficient between consecutive ACF waveforms and discuss the potential origins of the observed temporal variations.</p>

scholarly journals Identification of Similar Seismic Waves Using the Phase-Only Correlation Function and Wavelet Transform

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4527
Author(s):  
Hirokazu Moriya
Keyword(s):  
Acoustic Emission ◽  
Correlation Function ◽  
Wavelet Transform ◽  
Seismic Waves ◽  
Seismic Events ◽  
Significant Information ◽  
Arrival Times ◽  
S Waves ◽  
Seismic Waveforms ◽  
Fracture Systems

Accurately determined acoustic emission (AE) locations provide significant information on fracture systems, such as the orientation of fractures in a geothermal reservoir. To determine the relative source locations among a group of seismic events, similar AE waveforms must be detected and the relative arrival times of the P and S waves must be determined. In this paper, a method to identify similar AE waveforms is proposed, in which wavelet transform scalograms are used to determine the phase-only correlation function. The proposed method was applied to arbitrarily selected seismic waveforms, and its feasibility was evaluated by comparing the results with those obtained when the phase-only correlation function was obtained by using Fourier transform results.

Arrival-time picking uncertainty: Theoretical estimations and their application to microseismic data

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. U65-U76
Author(s):  
Ivan Abakumov ◽  
Aurelian Roeser ◽  
Serge A. Shapiro
Keyword(s):  
Seismic Waves ◽  
Arrival Time ◽  
Signal To Noise Ratio ◽  
Estimation Error ◽  
Additive White Gaussian Noise ◽  
Accurate Determination ◽  
Microseismic Monitoring ◽  
High Signal ◽  
Arrival Times ◽  
Velocity Models

Traveltime-based methods depend on the accurate determination of the arrival times of seismic waves. They further benefit from information on the uncertainty with which the arrival times are determined. Among other applications, arrival-time uncertainties are used to weight data in inversion algorithms and to define the resolution of reconstructed velocity models. The most physically meaningful approaches for the estimation of arrival-time uncertainties are based on probabilistic formulations. The two approaches for the assessment of the lower bound of arrival-time uncertainties, the Cramér–Rao Bound (CRB) and the Ziv–Zakai Bound (ZZB), have been reviewed. The CRB determines the minimum-achievable estimation error under the assumption of a high signal-to-noise ratio (S/N) but underestimates said error for small S/N. The ZZB provides a better result for noisy data because it utilizes a priori information. The CRB and ZZB require knowledge of the spectral variance of the signal, which often is hard to determine in seismic experiments. Furthermore, both bounds assume additive white Gaussian noise (AWGN), which does not hold for seismic data. To overcome these problems, alternative expressions have been proposed, which yield comparable estimates as CRB and ZZB but are solely based on the S/N and the dominant period in the data. Moreover, a recipe to correct the S/N and account for the difference between the seismic noise and AWGN has been provided. For a case study of downhole microseismic monitoring, it is determined that the new expressions provide station-dependent arrival-time uncertainties, which are used as weights to improve source location uncertainties.

scholarly journals Obtaining reliable localizations with Time Reverse Imaging: limits to array design, velocity models and signal-to-noise ratios

2018 ◽  
Author(s):  
Claudia Werner ◽  
Erik H. Saenger
Keyword(s):  
Signal To Noise Ratio ◽  
Scale Up ◽  
Velocity Model ◽  
Source Location ◽  
Seismic Events ◽  
Complex Velocity ◽  
Signal To Noise ◽  
Velocity Models ◽  
Wide Range ◽  
Noise Ratio

Abstract. Time Reverse Imaging (TRI) is evolving into a standard technique for localizing and characterizing seismic events. In recent years, TRI has been applied to a wide range of applications from the lab scale over the field scale up to the global scale. No identification of events and their onset times is necessary when localizing events with TRI. Therefore, it is especially suited for localizing quasi-simultaneous events and events with a low signal-to-noise ratio. However, in contrast to more regularly applied localization methods, the prerequisites for applying TRI are not sufficiently known. To investigate the significance of station distributions, complex velocity models and signal-to-noise ratios for the localization quality, numerous simulations were performed using a finite difference code to propagate elastic waves through three-dimensional models. Synthetic seismograms were reversed in time and re-inserted into the model. The time-reversed wavefield backpropagates through the model and, in theory, focuses at the source location. This focusing was visualized using imaging conditions. Additionally, artificial focusing spots were removed with an illumination map specific to the setup. Successful localizations were sorted into four categories depending on their reliability. Consequently, individual simulation setups could be evaluated by their ability to produce reliable localizations. Optimal inter-station distances, minimum apertures, relations between array and source location, heterogeneities of inter-station distances and total number of stations were investigated for different source depth as well as source types. Additionally, the quality of the localization was analysed when using a complex velocity model or a low signal-to-noise ratio. Finally, an array in Southern California was investigated for its ability to localize seismic events in specific target depths while using the actual velocity model for that region. In addition, the success rate with recorded data was estimated. Knowledge about the prerequisites for using TRI enables the estimation of success rates for a given problem. Furthermore, it reduces the time needed for adjusting stations to achieve more reliable localizations and provides a foundation for designing arrays for applying TRI.

scholarly journals Seismic model of central and eastern Lesser Himalaya of Nepal

1985 ◽  
Vol 3 ◽  
Author(s):  
M. R. Pandey
Keyword(s):  
Velocity Distribution ◽  
Seismic Waves ◽  
Seismic Velocity ◽  
Velocity Model ◽  
Moho Depth ◽  
Seismic Events ◽  
Apparent Velocity ◽  
Lesser Himalaya ◽  
Origin Time ◽  
Layer Velocity

ABSTRACT The apparent velocity distribution of the local seismic of lesser Himalaya of central and Eastern Nepal allows to derive a three layered local seismic velocity model with first layer velocity of 5.6 Km/Sec, second layer of 6.5 Km/sec. and Moho discontinuity with 8.1 Km/sec. The first arrivals of different local phases of seismic waves are consistent with 20-23 Km thickness of the first layer and with crustal thickness of 55Km. The seismic events are confined to the first layer. Local velocity model derived after the seismic event of 6 Oct 1981, origin time 19 hr 18 mn 17 sec, by modelling the first arrivals and PMP (Moho reflection) arrivals within the interval of distance 138-218 Km confirms the velocity model derived from apparent velocity distribution. However, apparent velocity distribution of local seismic events occurring south of the line joining approximately Pokhara to Udayapur in plan does not seem to fit the theoretical distribution corresponding to the above three layered model with events within first layer. The apparent velocity of these events may be explained either (a) by the confinement of the focus of the events to the second layer or, (b) by the variation of the seismic velocity model with Moho depth at 35- 40 Km. i.e. with a normal Indian peninsular crust thickness.

ARRU Phase Picker: Attention Recurrent-Residual U-Net for Picking Seismic P- and S-Phase Arrivals

2021 ◽  
Author(s):  
Wu-Yu Liao ◽  
En-Jui Lee ◽  
Dawei Mu ◽  
Po Chen ◽  
Ruey-Juin Rau
Keyword(s):  
Human Error ◽  
Seismic Waves ◽  
Multiple Scales ◽  
Signal To Noise Ratio ◽  
Source Parameters ◽  
Seismic Source ◽  
Earthquake Location ◽  
P Waves ◽  
Arrival Times ◽  
Unseen Data

Abstract Seismograms are convolution results between seismic sources and the media that seismic waves propagate through, and, therefore, the primary observations for studying seismic source parameters and the Earth interior. The routine earthquake location and travel-time tomography rely on accurate seismic phase picks (e.g., P and S arrivals). As data increase, reliable automated seismic phase-picking methods are needed to analyze data and provide timely earthquake information. However, most traditional autopickers suffer from low signal-to-noise ratio and usually require additional efforts to tune hyperparameters for each case. In this study, we proposed a deep-learning approach that adapted soft attention gates (AGs) and recurrent-residual convolution units (RRCUs) into the backbone U-Net for seismic phase picking. The attention mechanism was implemented to suppress responses from waveforms irrelevant to seismic phases, and the cooperating RRCUs further enhanced temporal connections of seismograms at multiple scales. We used numerous earthquake recordings in Taiwan with diverse focal mechanisms, wide depth, and magnitude distributions, to train and test our model. Setting the picking errors within 0.1 s and predicted probability over 0.5, the AG with recurrent-residual convolution unit (ARRU) phase picker achieved the F1 score of 98.62% for P arrivals and 95.16% for S arrivals, and picking rates were 96.72% for P waves and 90.07% for S waves. The ARRU phase picker also shown a great generalization capability, when handling unseen data. When applied the model trained with Taiwan data to the southern California data, the ARRU phase picker shown no cognitive downgrade. Comparing with manual picks, the arrival times determined by the ARRU phase picker shown a higher consistency, which had been evaluated by a set of repeating earthquakes. The arrival picks with less human error could benefit studies, such as earthquake location and seismic tomography.

scholarly journals A Comparative Study of 3D UE Positioning in 5G New Radio with a Single Station

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1178
Author(s):  
Bo Sun ◽  
Bo Tan ◽  
Wenbo Wang ◽  
Elena Simona Lohan
Keyword(s):  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Time Estimation ◽  
Satellite System ◽  
Base Station ◽  
Rectangular Array ◽  
Single Station ◽  
5G Network ◽  
Autonomous Machines ◽  
3D Positioning

The 5G network is considered as the essential underpinning infrastructure of manned and unmanned autonomous machines, such as drones and vehicles. Besides aiming to achieve reliable and low-latency wireless connectivity, positioning is another function provided by the 5G network to support the autonomous machines as the coexistence with the Global Navigation Satellite System (GNSS) is typically supported on smart 5G devices. This paper is a pilot study of using 5G uplink physical layer channel sounding reference signals (SRSs) for 3D user equipment (UE) positioning. The 3D positioning capability is backed by the uniform rectangular array (URA) on the base station and by the multiple subcarrier nature of the SRS. In this work, the subspace-based joint angle-time estimation and statistics-based expectation-maximization (EM) algorithms are investigated with the 3D signal manifold to prove the feasibility of using SRSs for 3D positioning. The positioning performance of both algorithms is evaluated by estimation of the root mean squared error (RMSE) versus the varying signal-to-noise-ratio (SNR), the bandwidth, the antenna array configuration, and multipath scenarios. The simulation results show that the uplink SRS works well for 3D UE positioning with a single base station, by providing a flexible resolution and accuracy for diverse application scenarios with the support of the phased array and signal estimation algorithms at the base station.

Kinematic interpretation in the prestack depth‐migrated domain

Geophysics ◽  
1997 ◽  
Vol 62 (4) ◽  
pp. 1226-1237 ◽  
Author(s):  
Irina Apostoiu‐Marin ◽  
Andreas Ehinger
Keyword(s):  
Signal To Noise Ratio ◽  
Velocity Model ◽  
Point Of View ◽  
Prestack Depth Migration ◽  
Depth Migration ◽  
Velocity Models ◽  
Time Domain Data ◽  
And Migration ◽  
Point To Point ◽  
Homogeneous Media

Prestack depth migration can be used in the velocity model estimation process if one succeeds in interpreting depth events obtained with erroneous velocity models. The interpretational difficulty arises from the fact that migration with erroneous velocity does not yield the geologically correct reflector geometries and that individual migrated images suffer from poor signal‐to‐noise ratio. Moreover, migrated events may be of considerable complexity and thus hard to identify. In this paper, we examine the influence of wrong velocity models on the output of prestack depth migration in the case of straight reflector and point diffractor data in homogeneous media. To avoid obscuring migration results by artifacts (“smiles”), we use a geometrical technique for modeling and migration yielding a point‐to‐point map from time‐domain data to depth‐domain data. We discover that strong deformation of migrated events may occur even in situations of simple structures and small velocity errors. From a kinematical point of view, we compare the results of common‐shot and common‐offset migration. and we find that common‐offset migration with erroneous velocity models yields less severe image distortion than common‐shot migration. However, for any kind of migration, it is important to use the entire cube of migrated data to consistently interpret in the prestack depth‐migrated domain.

scholarly journals Fluid activity detection in geothermal areas using a single seismic station by monitoring horizontal-to-vertical spectral ratios

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kyosuke Okamoto ◽  
Hiroshi Asanuma ◽  
Hiro Nimiya
Keyword(s):  
Carbon Capture ◽  
Seismic Station ◽  
Carbon Capture And Storage ◽  
Fluid Flows ◽  
Temporal Variations ◽  
Geothermal Field ◽  
Spectral Ratios ◽  
Subsurface Structures ◽  
Geothermal Fields ◽  
Single Station

AbstractSubsurface structure survey based on horizontal-to-vertical (H/V) spectral ratios is widely conducted. The major merit of this survey is its convenience to obtain a stable result using a single station. Spatial variations of H/V spectral ratios are well-known phenomena, and it has been used to estimate the spatial fluctuation in subsurface structures. It is reasonable to anticipate temporal variations in H/V spectral ratios, especially in areas like geothermal fields, carbon capture and storage fields, etc., where rich fluid flows are expected, although there are few reports about the temporal changes. In Okuaizu Geothermal Field (OGF), Japan, dense seismic monitoring was deployed in 2015, and continuous monitoring has been consistent. We observed the H/V spectral ratios in OGF and found their repeated temporary drops. These drops seemed to be derived from local fluid activities according to a numerical calculation. Based on this finding, we examined a coherency between the H/V spectral ratios and fluid activities in OGF and found a significance. In conclusion, monitoring H/V spectral ratios can enable us to grasp fluid activities that sometimes could lead to a relatively large seismic event.

Novel Method for Detecting Weak AE Signals Based on the Similarity of Time-Frequency Spectra

Geophysics ◽  
2021 ◽  
pp. 1-62
Author(s):  
Wencheng Yang ◽  
Xiao Li ◽  
Yibo Wang ◽  
Yue Zheng ◽  
Peng Guo
Keyword(s):  
Mathematical Morphology ◽  
Signal To Noise Ratio ◽  
Critical Role ◽  
Real Data ◽  
Monitoring Method ◽  
Frequency Spectra ◽  
Arrival Times ◽  
Time Frequency ◽  
Fracturing Process ◽  
Ae Signals

As a key monitoring method, the acoustic emission (AE) technique has played a critical role in characterizing the fracturing process of laboratory rock mechanics experiments. However, this method is limited by low signal-to-noise ratio (SNR) because of a large amount of noise in the measurement and environment and inaccurate AE location. Furthermore, it is difficult to distinguish two or more hits because their arrival times are very close when AE signals are mixed with the strong background noise. Thus, we propose a new method for detecting weak AE signals using the mathematical morphology character correlation of the time-frequency spectrum. The character in all hits of an AE event can be extracted from time-frequency spectra based on the theory of mathematical morphology. Through synthetic and real data experiments, we determined that this method accurately identifies weak AE signals. Compared with conventional methods, the proposed approach can detect AE signals with a lower SNR.

Rayleigh waves from high-gain long-period stations: Signal extraction, amplitude determination, and separation of overlapping wave trains

1975 ◽  
Vol 65 (6) ◽  
pp. 1761-1778 ◽  
Author(s):  
Eduard Berg
Keyword(s):  
Rayleigh Waves ◽  
Signal To Noise Ratio ◽  
High Gain ◽  
Clear Separation ◽  
Novaya Zemlya ◽  
Oceanic Surface ◽  
Single Station ◽  
Wave Trains ◽  
Short Time

abstract For a signal-to-noise ratio between 0.2 and 0.1 on the original single-component records, amplitudes for Rayleigh waves over oceanic paths of 155° at station MAT and 98° at station KIP have been determined as 12 mμ and 24 mμ peak-to-peak, respectively, with a standard error of less than 11 per cent. In each case the processed correlation signal is the highest in a half-hour record. The method makes use of preliminary high-pass filtering and normalized reference earthquake-matched filtering, and takes full advantage of the well-dispersed oceanic surface wave. The method also provides high resolution of co-located events with short time separation, or of widely spaced events with Rayleigh waves arriving nearly simultaneously at a single station, when the summed vertical and radial matched filtered components are used. Examples include: (1) clear separation and amplitude determination at stations KIP and MAT of two MS = 6.5 earthquakes located 0.7° and 145 sec apart off the coast of central Chile; (2) clear separation at station KIP of a Novaya Zemlya mb = 4.8 event from interfering Rayleigh waves of an mb = 5.0 Kermadec Island earthquake arriving 120 to 140 sec prior to the searched event, with almost complete elimination of interference on the summed vertical and radial processed components; and (3) clear separation at station KIP of two co-located mb = 4.4 and 4.5 earthquakes 6 min apart off the coast of Chile, with determination of their amplitudes in the presence of interfering Rayleigh waves from two central Alaska earthquakes, the first (mb = 4.1) arriving 15 min prior to the first Chile Rayleigh wave and the second between the two Chile arrivals. The single-station threshold reached (10 and 25 digital units, p-p) for stations MAT and KIP at 155° and 98°, respectively, corresponds to an MS = 3.3 and probably can be improved further.

Sign in / Sign up

Export Citation Format

Share Document