scholarly journals Passive seismic data processing with no prior information: Estimating the crustal shear-wave velocity model of the South Lokichar Basin (Kenya) through integration of ambient seismic noise and teleseismic earthquake data

2020 ◽  
Author(s):  
D. Giannopoulos ◽  
C. Orfanos ◽  
K. Leontarakis ◽  
A. Lois ◽  
K. Polychronopoulou ◽  
...  
Keyword(s):  
Data Processing ◽  
Shear Wave Velocity ◽  
Seismic Data ◽  
Seismic Noise ◽  
Prior Information ◽  
Velocity Model ◽  
Ambient Seismic Noise ◽  
Seismic Data Processing ◽  
Passive Seismic ◽  
Earthquake Data

Automatic passive seismic data processing with no prior information: the contribution of Surface Wave Tomography

First Break ◽  
2016 ◽  
Vol 34 (7) ◽  
Author(s):  
Christos Orfanos ◽  
Konstantinos Leontarakis ◽  
Athanasios Lois ◽  
Katerina Polychronopoulou ◽  
Nikos Martakis
Keyword(s):  
Surface Wave ◽  
Data Processing ◽  
Seismic Data ◽  
Prior Information ◽  
Surface Wave Tomography ◽  
Seismic Data Processing ◽  
Passive Seismic ◽  
Wave Tomography

Shear wave velocity model of the ABANICO formation underlying The santiago City Metropolitan Area, chile, using ambient seismic noise tomography

2020 ◽  
Author(s):  
J Salomón ◽  
C Pastén ◽  
S Ruiz ◽  
F Leyton ◽  
M Sáez ◽  
...  
Keyword(s):  
Shear Wave ◽  
Wave Velocity ◽  
Metropolitan Area ◽  
Shear Wave Velocity ◽  
Seismic Noise ◽  
Velocity Model ◽  
Dispersion Curves ◽  
Ambient Seismic Noise ◽  
Travel Times ◽  
Abanico Formation

Summary The seismic response of the Santiago City, the capital of Chile with more than 5.5 million inhabitants, is controlled by the properties of the shallower quaternary deposits and the impedance contrast with the underlying Abanico formation, among other factors. In this study, we process continuous records of ambient seismic noise to perform an ambient seismic noise tomography with the aim of defining the shallower structure of the Abanico formation underneath the densely populated metropolitan area of Santiago, Chile. The seismic signals were recorded by a network consisting of 29 broadband seismological stations and 12 accelerograph stations, located in a 35 × 35 km2 quadrant. We used the average coherency of the vertical components to calculate dispersion curves from 0.1 to 5 Hz and Bootstrap resampling to estimate the variance of the travel times. The reliable frequency band of the dispersion curves was defined by an empirical method based on sign normalization of the coherency real part. The ambient noise tomography was solved on a domain discretized into 256 2 × 2 km2 cells. Using a regularized weighted least squares inversion, we inverted the observed travel-times between stations, assuming straight ray paths, in order to obtain 2D phase velocity maps from 0.2 Hz to 1.1 Hz, linearly spaced every 0.05 Hz, in 157 of the 256 square cells of the domain. In each square cell with information, dispersion curves were assembled and used to invert shear wave velocity profiles, which were interpolated using the ordinary Kriging method to obtain a 3D shear wave velocity model valid from 0.6 to 5 km depth. The 3D velocity model shows that the Abanico formation is stiffer in the south of the study area with larger velocity anomalies towards the shallower part of the model. The value of the shear wave velocity narrows with depth, reaching an average value of 3.5 km/s from 3 to 5 km depth.

Applying the Horizon Based Tomography Method to Update Interval Velocity Model, Identify The Structure of Pre-Stack Depth Migration 3D and Estimate The Hydrocarbon Reserve In SBI Field of North West Java Basin

2014 ◽  
Vol 69 (6) ◽  
Author(s):  
Sudra Irawan ◽  
Sismanto Sismanto ◽  
Adang Sukmatiawan
Keyword(s):  
Data Processing ◽  
Seismic Data ◽  
Velocity Model ◽  
Research Area ◽  
Seismic Data Processing ◽  
West Java ◽  
North West ◽  
Depth Migration ◽  
Interval Velocity ◽  
Tomography Method

Seismic data processing is one of the three stages in the seismic method that has an important role in the exploration of oil and gas. Without good data processing, it is impossible to get seismic image cross section for good interpretation. A research using seismic data processing was done to update the velocity model by horizon based tomography method in SBI Field, North West Java Basin. This method reduces error of seismic wave travel time through the analyzed horizon because the existence velocity of high lateral variation in research area. There are three parameters used to determine the accuracy of the resulting interval velocity model, namely, flat depth gathers, semblance residual moveout that coincides with the axis zero residual moveout, and the correspondence between image depth (horizon) with wells marker  (well seismic tie). Pre Stack Depth Migration (PSDM) form interval velocity model and updating using horizon-based tomography method gives better imaging of under-surfaced structure results than PSDM before using tomography. There are three faults found in the research area, two normal faults have southwest-northeast strike and the other has northwest-southeast strike. The thickness of reservoir in SBI field, North West Java Basin, is predicted between 71 to 175 meters and the hydrocarbon (oil) reserve is predicted about  with 22.6% porosity and 70.7% water saturation. 

ADVANCES IN 3-D SEISMIC DATA PROCESSING TECHNIQUES

1992 ◽  
Vol 32 (1) ◽  
pp. 276
Author(s):  
T.J. Allen ◽  
P. Whiting
Keyword(s):  
Data Processing ◽  
Seismic Data ◽  
Three Dimensional ◽  
Velocity Model ◽  
Migration Velocity ◽  
Seismic Data Processing ◽  
Data Set ◽  
Migration Velocity Analysis ◽  
Processing Techniques ◽  
Made In

Several recent advances made in 3-D seismic data processing are discussed in this paper.Development of a time-variant FK dip-moveout algorithm allows application of the correct three-dimensional operator. Coupled with a high-dip one-pass 3-D migration algorithm, this provides improved resolution and response at all azimuths. The use of dilation operators extends the capability of the process to include an economical and accurate (within well-defined limits) 3-D depth migration.Accuracy of the migration velocity model may be improved by the use of migration velocity analysis: of the two approaches considered, the data-subsetting technique gives more reliable and interpretable results.Conflicts in recording azimuth and bin dimensions of overlapping 3-D surveys may be resolved by the use of a 3-D interpolation algorithm applied post 3-D stack and which allows the combined surveys to be 3-D migrated as one data set.

Deconvolutive Radon transform

Geophysics ◽  
2017 ◽  
Vol 82 (2) ◽  
pp. V117-V125 ◽  
Author(s):  
Ali Gholami
Keyword(s):  
Data Processing ◽  
Temporal Resolution ◽  
Radon Transform ◽  
Seismic Data ◽  
Model Building ◽  
Random Noise ◽  
Velocity Model ◽  
Seismic Events ◽  
Seismic Data Processing ◽  
Band Limited

The Radon transform (RT) plays an important role in seismic data processing for its ability to focus seismic events in the transform domain. The band-limited nature of seismic events due to the blurring effects of the source wavelet, however, causes a decrease in the temporal resolution of the transform. We have developed the deconvolutive RT (DecRT) as a generalization of conventional RT and to increase the temporal resolution. Unlike the conventional counterpart, the new basis functions can take an arbitrary shape in the time direction. This method is thus proposed to adaptively infer the temporal wave shape from the input data while finding a sparse representation of it. The new transform significantly improves the sparsity and thus the temporal resolution of the resulting seismic data. The applicability of the hyperbolic DecRT in seismic data processing is demonstrated for random noise attenuation, primary and multiple separation, high-quality stacking, and automatic velocity model building. The results obtained on synthetic and field data sets confirm the effectiveness of the method in improving the time and slowness/curvature resolutions compared with conventional transforms, which leads to improved seismic processing results in the deconvolutive Radon domains.

scholarly journals Elastic Full-Waveform Inversion Using Migration-Based Depth Reflector Representation in the Data Domain

Geosciences ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 76
Author(s):  
Vladimir Tcheverda ◽  
Kirill Gadylshin
Keyword(s):  
Data Processing ◽  
Seismic Data ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Critical Element ◽  
Full Waveform Inversion ◽  
Seismic Data Processing ◽  
Velocity Models ◽  
Data Space ◽  
Full Waveform

The depth velocity model is a critical element for providing seismic data processing success, as it is responsible for the times of waves’ propagation and, therefore, prescribes the location of geological objects in the resulting seismic images. Constructing a deep velocity model is the most time-consuming part of the entire seismic data processing, which usually requires interactive human intervention. This article introduces the consistently numerical method for reconstructing a depth velocity model based on the modified version of the elastic Full Waveform Inversion (FWI). The specific feature of this approach to FWI is the decomposition of the space of admissible velocity models into subspaces of propagator (macro velocity) and reflector components. In turn, the latter transforms to the data space reflectivity on the base of migration transformation. Finally, we perform minimisation in two different spaces: (1) Macro velocity as a smooth spatial function; (2) Migration transforms data space reflectivity to the spatial reflectivity. We present numerical experiments confirming less sensitiveness of the modified version of FWI to the lack of the low time frequencies in the data acquired. In our computations, we use synthetic data with valuable time frequencies from 5 Hz.

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