Model Space Exploration for Determining Landslide Source History from Long-Period Seismic Data

The coefficients that synthesize seismic data via the hyperbolic Radon transform (HRT) are estimated by solving a linear-inverse problem. In the classical HRT, the computational cost of the inverse problem is proportional to the size of the data and the number of Radon coefficients. We have developed a strategy that significantly speeds up the implementation of time-domain HRTs. For this purpose, we have defined a restricted model space of coefficients applying hard thresholding to an initial low-resolution Radon gather. Then, an iterative solver that operated on the restricted model space was used to estimate the group of coefficients that synthesized the data. The method is illustrated with synthetic data and tested with a marine data example.

Download Full-text

LONG-PERIOD SURFACE-RELATED MULTIPLE SUPPRESSION IN 2D MARINE SEISMIC DATA USING PREDICTIVE DECONVOLUTION AND COMBINATION OF SURFACE-RELATED MULTIPLE ELIMINATION AND PARABOLIC RADON FILTERING

10.32008/geolinks2021/b1/v3/30 ◽

2021 ◽

Author(s):

Pimpawee Sittipan ◽

Pisanu Wongpornchai

Keyword(s):

Seismic Data ◽

Seismic Reflection ◽

Petroleum Reservoirs ◽

The United States ◽

Multiple Reflections ◽

Long Period ◽

Predictive Deconvolution ◽

Short Period ◽

Marine Seismic ◽

Multiple Elimination

Some of the important petroleum reservoirs accumulate beneath the seas and oceans. Marine seismic reflection method is the most efficient method and is widely used in the petroleum industry to map and interpret the potential of petroleum reservoirs. Multiple reflections are a particular problem in marine seismic reflection investigation, as they often obscure the target reflectors in seismic profiles. Multiple reflections can be categorized by considering the shallowest interface on which the bounces take place into two types: internal multiples and surface-related multiples. Besides, the multiples can be categorized on the interfaces where the bounces take place, a difference between long-period and short-period multiples can be considered. The long-period surface-related multiples on 2D marine seismic data of the East Coast of the United States-Southern Atlantic Margin were focused on this research. The seismic profile demonstrates the effectiveness of the results from predictive deconvolution and the combination of surface-related multiple eliminations (SRME) and parabolic Radon filtering. First, predictive deconvolution applied on conventional processing is the method of multiple suppression. The other, SRME is a model-based and data-driven surface-related multiple elimination method which does not need any assumptions. And the last, parabolic Radon filtering is a moveout-based method for residual multiple reflections based on velocity discrimination between primary and multiple reflections, thus velocity model and normal-moveout correction are required for this method. The predictive deconvolution is ineffective for long-period surface-related multiple removals. However, the combination of SRME and parabolic Radon filtering can attenuate almost long-period surface-related multiple reflections and provide a high-quality seismic images of marine seismic data.

Download Full-text

Time-Lapse Monitoring of Daily Velocity Changes in Binchuan, Southwestern China, Using Large-Volume Air-Gun Source Array Data

Seismological Research Letters ◽

10.1785/0220210160 ◽

2022 ◽

Author(s):

Yi Luan ◽

Hongfeng Yang ◽

Baoshan Wang ◽

Wei Yang ◽

Weitao Wang ◽

...

Keyword(s):

Large Volume ◽

Seismic Data ◽

Temporal Changes ◽

Air Pressure ◽

Southwestern China ◽

Long Period ◽

Air Gun ◽

Velocity Variations ◽

Velocity Changes ◽

Source Array

Abstract Temporal changes of seismic velocities in the Earth’s crust can be induced by stress perturbations or material damage from reasons such as strong ground motion, volcanic activities, and atmospheric effects. However, monitoring the temporal changes remains challenging, because most of them generally exist in small travel-time differences of seismic data. Here, we present an excellent case of daily variations of the subsurface structure detected using a large-volume air-gun source array of one-month experiment in Binchuan, Yunnan, southwestern China. The seismic data were recorded by 12 stations within ∼10 km away from the source and used to detect velocity change in the crust using the deconvolution method and sliding window cross-correlation method, which can eliminate the “intercept” error when cutting the air-gun signals and get the real subsurface variations. Furthermore, the multichannel singular spectral analysis method is used to separate the daily change (∼1 cycle per day) from the “long-period” change (<1 cycle per day) or noise. The result suggests that the daily velocity changes at the two nearest stations, 53277 (offset ∼700 m) and 53278 (offset ∼2.3 km), are well correlated with air temperature variation with a time lag of 5.0 ± 1.5 hr, which reflects that the velocity variations at the subsurface are likely attributed to thermoelastic strain. In contrast, both daily and long-period velocity changes at distant stations correlate better with the varying air pressure than the temperature, indicating that the velocity variations at deeper depth are dominated by the elastic loading of air pressure. Our results demonstrate that the air-gun source is a powerful tool to detect the velocity variation of the shallow crust media.

Download Full-text

An optimum data editing technique for the reduction of noise in multi-channel geophysical data

Bulletin of the Seismological Society of America ◽

10.1785/bssa0740031059 ◽

1984 ◽

Vol 74 (3) ◽

pp. 1059-1078

Author(s):

P. A. Tyraskis ◽

O. G. Jensen ◽

D. E. Smylie ◽

J. A. Linton

Keyword(s):

Time Series ◽

Spectral Analysis ◽

Seismic Data ◽

Data Model ◽

Optimum Interpolation ◽

Long Period ◽

Data Editing ◽

Spectral Peaks ◽

Data Gaps ◽

The Individual

Abstract We develop a data editing method, for the optimum interpolation of multichannel time series containing time-coincident data gaps, in one, several, or all channels based upon the autoregressive data model. The method is applied to a set of very long-period seismic data recorded during the 19 August 1977 Indonesian earthquake, which shows several unassociated bursts of noise. Spectral analysis following editing and interpolation of the record indicates existence of systematic signals with periods higher than 1 hr and perhaps as long as 2 hr. The individual spectral peaks in this subseismic band have not been identified.

Download Full-text

Constrained Full Waveform Inversion for Borehole Multicomponent Seismic Data

Geosciences ◽

10.3390/geosciences9010045 ◽

2019 ◽

Vol 9 (1) ◽

pp. 45

Author(s):

Marwan Charara ◽

Christophe Barnes

Keyword(s):

Inverse Problem ◽

Spatial Correlation ◽

Seismic Data ◽

Waveform Inversion ◽

Synthetic Data ◽

Model Space ◽

Elastic Model ◽

Full Waveform Inversion ◽

Spatial Correlations ◽

Full Waveform

Full-waveform inversion for borehole seismic data is an ill-posed problem and constraining the problem is crucial. Constraints can be imposed on the data and model space through covariance matrices. Usually, they are set to a diagonal matrix. For the data space, signal polarization information can be used to evaluate the data uncertainties. The inversion forces the synthetic data to fit the polarization of observed data. A synthetic inversion for a 2D-2C data estimating a 1D elastic model shows a clear improvement, especially at the level of the receivers. For the model space, horizontal and vertical spatial correlations using a Laplace distribution can be used to fill the model space covariance matrix. This approach reduces the degree of freedom of the inverse problem, which can be quantitatively evaluated. Strong horizontal spatial correlation distances favor a tabular geological model whenever it does not contradict the data. The relaxation of the spatial correlation distances from large to small during the iterative inversion process allows the recovery of geological objects of the same size, which regularizes the inverse problem. Synthetic constrained and unconstrained inversions for 2D-2C crosswell data show the clear improvement of the inversion results when constraints are used.

Download Full-text

The Seismic Research Observatory

Bulletin of the Seismological Society of America ◽

10.1785/bssa0660062049 ◽

1976 ◽

Vol 66 (6) ◽

pp. 2049-2068 ◽

Cited By ~ 2

Author(s):

Jon Peterson ◽

Howell M. Butler ◽

L. Gary Holcomb ◽

Charles R. Hutt

Keyword(s):

Seismic Data ◽

Broad Band ◽

Computer Processing ◽

Preliminary Evaluation ◽

Digital Recording ◽

Digital Form ◽

Data Resource ◽

Long Period ◽

Period Data ◽

Mass Position

abstract Thirteen advanced seismograph systems, called Seismic Research Observatories (SRO), are being installed as part of a program to upgrade the worldwide seismic data network. The SRO system was created by combining a recently developed broad-band borehole seismometer and a software-controlled recording system. The seismometers are being installed at a depth of 100 meters to avoid wind-generated noise in the long-period band. A seismometer output that is flat in acceleration between periods of 1 and 50 sec is used to produce both short- and long-period data that are recorded on analog drum recorders and in digital form on magnetic tape. Very-long-period data, obtained from the seismometer mass position output, can be recorded as well. Digital recording of gain-ranged data provides an amplitude of nearly 120 dB. Preliminary evaluation of the SRO data system indicates that major design objectives have been met. The network of SRO stations will be an important new data resource for seismological investigations, especially for those studies that require computer processing of the data.

Download Full-text

Tomographic filtering of mantle circulation models via the generalised inverse: A way to account for seismic data uncertainty

10.5194/egusphere-egu2020-9728 ◽

2020 ◽

Author(s):

Bernhard S.A. Schuberth ◽

Roman Freissler ◽

Christophe Zaroli ◽

Sophie Lambotte

Keyword(s):

Seismic Data ◽

Inverse Operator ◽

Synthetic Data ◽

Circulation Model ◽

Model Space ◽

Seismic Inversion ◽

Data Uncertainty ◽

Earth Model ◽

Model Parameters ◽

Noise Component

For a comprehensive link between seismic tomography and geodynamic models, uncertainties in the seismic model space play a non-negligible role. More specifically, knowledge of the tomographic uncertainties is important for obtaining meaningful estimates of the present-day thermodynamic state of Earth's mantle, which form the basis of retrodictions of past mantle evolution using the geodynamic adjoint method. A standard tool in tomographic-geodynamic model comparisons nowadays is tomographic filtering of mantle circulation models using the resolution operator R associated with the particular seismic inversion of interest. However, in this classical approach it is not possible to consider tomographic uncertainties and their impact on the geodynamic interpretation.&#160;Here, we present a new method for 'filtering' synthetic Earth models, which makes use of the generalised inverse operator G&#8224;, instead of using R. In our case, G&#8224; is taken from a recent global SOLA Backus&#8211;Gilbert S-wave tomography. In contrast to classical tomographic filtering, the 'imaged' model is constructed by computing the Generalised-Inverse Projection (GIP) of synthetic data calculated in an Earth model of choice. This way, it is possible to include the effects of noise in the seismic data and thus to analyse uncertainties in the resulting model parameters. In order to demonstrate the viability of the method, we compute a set of travel times in an existing mantle circulation model, add specific realisations of Gaussian, zero-mean seismic noise to the synthetic data and apply G&#8224;.&#160; &#160; Our results show that the resulting GIP model without noise is equivalent to the mean model of all GIP realisations from the suite of synthetic 'noisy' data and also closely resembles the model tomographically filtered using R. Most important, GIP models that include noise in the data show a significant variability of the shape and amplitude of seismic anomalies in the mantle. The significant differences between the various GIP realisations highlight the importance of interpreting and assessing tomographic images in a prudent and cautious manner. With the GIP approach, we can moreover investigate the effect of systematic errors in the data, which we demonstrate by adding an extra term to the noise component that aims at mimicking the effects of uncertain crustal corrections. In our presentation, we will finally discuss ways to construct the model covariance matrix based on the GIP approach and point out possible research directions on how to make use of this information in future geodynamic modelling efforts.

Download Full-text

Villamaninite, a case of noncubic pyrite-type structure

Acta Crystallographica Section B Structural Science ◽

10.1107/s0108768196002996 ◽

1996 ◽

Vol 52 (6) ◽

pp. 899-904 ◽

Cited By ~ 4

Author(s):

C. Marcos ◽

A. Paniagua ◽

D. B. Moreiras ◽

S. García-Granda ◽

M. R. Díaz

Keyword(s):

Crystal Structure ◽

Model Space ◽

Spectroscopic Studies ◽

Structural Refinement ◽

Cubic Symmetry ◽

Long Period ◽

Ionic Substitution ◽

Single Crystal Study ◽

Refinement Process ◽

Cation Sites

This paper reports the results obtained in a study of the crystal structure of two villamaninite samples from Villamanín (León, Spain), labeled (1) and (2). Villamaninite, (Cu,Ni,Co,Fe)(S,Se)2, is a pyrite-type disulfide. Different long-period elements, including Au, in ionic substitution are also observed. Previous authors have assumed a cubic Pa{\bar 3} symmetry for this mineral. The result of our single-crystal study shows a deviation from the cubic symmetry Pa{\bar 3} pyrite-type to a pseudocubic symmetry, which is in agreement with the observed optical anisotropy shown by both samples. The structural refinement process leads to a monoclinic model, space group P1211, with a = 5.709 (2), b = 5.707 (2), c = 5.708 (2) Å, β = 90.01 (1)° for sample (1),° and a = 5.704 (3), b = 5.703 (3), c = 5.704 (3) Å, β = 89.99 (2)° for sample (2), with Z = 4. Previous Mössbauer spectroscopic studies stating two different cation sites for Au support the monoclinic model.

Download Full-text