scholarly journals Hydrocarbon identification by evaluating anisotropy parameters estimated from crosswell seismic data

2021 ◽  
Vol 1943 (1) ◽  
pp. 012030
Author(s):  
T Suroso ◽  
W Triyoso ◽  
A Priyono
Keyword(s):  
Seismic Data ◽  
Anisotropy Parameters

Traveltime approximation for converted waves in elastic orthorhombic media

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. C229-C237 ◽  
Author(s):  
Shibo Xu ◽  
Alexey Stovas
Keyword(s):  
Seismic Data ◽  
Real Data ◽  
Processing Parameters ◽  
Model Parameters ◽  
Seismic Data Processing ◽  
Converted Wave ◽  
Rational Form ◽  
Time Migration ◽  
Taylor Series Approximation ◽  
Anisotropy Parameters

The moveout approximations are commonly used in seismic data processing such as velocity analysis, modeling, and time migration. The anisotropic effect is very obvious for a converted wave when estimating the physical and processing parameters from the real data. To approximate the traveltime in an elastic orthorhombic (ORT) medium, we defined an explicit rational-form approximation for the traveltime of the converted [Formula: see text]-, [Formula: see text]-, and [Formula: see text]-waves. To obtain the expression of the coefficients, the Taylor-series approximation is applied in the corresponding vertical slowness for three pure-wave modes. By using the effective model parameters for [Formula: see text]-, [Formula: see text]-, and [Formula: see text]-waves, the coefficients in the converted-wave traveltime approximation can be represented by the anisotropy parameters defined in the elastic ORT model. The accuracy in the converted-wave traveltime for three ORT models is illustrated in numerical examples. One can see from the results that, for converted [Formula: see text]- and [Formula: see text]-waves, our rational-form approximation is very accurate regardless of the tested ORT model. For a converted [Formula: see text]-wave, due to the existence of cusps, triplications, and shear singularities, the error is relatively larger compared with PS-waves.

Borehole-Driven 3D Surface Seismic Data Processing Using DAS-VSP Data

2021 ◽  
Author(s):  
Gang Yu ◽  
Junjun Wu ◽  
Yuanzhong Chen ◽  
Ximing Wang
Keyword(s):  
Data Processing ◽  
Data Acquisition ◽  
Seismic Data ◽  
Field Data ◽  
Seismic Data Processing ◽  
3D Surface ◽  
Data Volume ◽  
Vsp Data ◽  
Seismic Data Acquisition ◽  
Anisotropy Parameters

Abstract A 3D surface seismic data acquisition project was conducted simultaneously with 3D DAS-VSP data acquisition in one well in Jilin Oilfield of Northen China. The 3D surface seismic data acquisition project covered an area of 75 km2, and one borehole (DS32-3) and an armoured optical cable with high temperature single mode fiber were used to acquire the 3D DAS-VSP data simultaneously when the crew was acquiring the 3D surface seismic data. The simultaneously acquired 3D DAS-VSP data were used to extract formation velocity, deconvolution operator, absorption, attenuation (Q value), anisotropy parameters (η, δ, ε) as wel as enhanced the surface seismic data processing including velocity model calibration and modification, static correction, deconvolution, demultiple processing, high frequency restoration, anisotropic migration, and Q-compensation or Q-migration. In this project, anisotropic migration, Q-migration was conducted with the anisotropy parameters (η, δ, ε) data volume and enhanced Q-field data volume obtained from the joint inversion of both the near surface 3D Q-field data volume from uphole data and the mid-deep layer Q-field data volume from all available VSP data in the 3D surface seismic surveey area. The anosotropic migration and Q-migration results show much sharper and focussed faults and and clearer subsutface structure.

Role of the inhomogeneity angle in anisotropic attenuation analysis

Geophysics ◽  
2009 ◽  
Vol 74 (5) ◽  
pp. WB177-WB191 ◽  
Author(s):  
Jyoti Behura ◽  
Ilya Tsvankin
Keyword(s):  
Attenuation Coefficient ◽  
Seismic Data ◽  
Spectral Ratio ◽  
Ratio Method ◽  
Attenuation Coefficients ◽  
Anisotropic Models ◽  
High Attenuation ◽  
Wide Range ◽  
Anisotropy Parameters ◽  
Attenuation Anisotropy

The inhomogeneity angle (the angle between the real and imaginary parts of the wave vector) is seldom taken into account in estimating attenuation coefficients from seismic data. Wave propagation through the subsurface, however, can result in relatively large inhomogeneity angles [Formula: see text], especially for models with significant attenuation contrasts across layer boundaries. Here we study the influence of the angle [Formula: see text] on phase and group attenuation in arbitrarily anisotropic media using the first-order perturbation theory verified by exact numerical modeling. Application of the spectral-ratio method to transmitted or reflected waves yields the normalized group attenuation coefficient [Formula: see text], which is responsible for amplitude decay along seismic rays. Our analytic solutions show that for a wide range of inhomogeneity angles, the coefficient [Formula: see text] is close to the normalized phase attenuation coefficient [Formula: see text] computed for [Formula: see text] [Formula: see text]. The coefficient[Formula: see text] can be inverted directly for the attenuation-anisotropy parameters, so no knowledge of the inhomogeneity angle is required for attenuation analysis of seismic data. This conclusion remains valid even for uncommonly high attenuation with the quality factor [Formula: see text] less than 10 and strong velocity and attenuation anisotropy. However, the relationship between group and phase attenuation coefficients becomes more complicated for relatively large inhomogeneity angles approaching so-called ‘‘forbidden directions.’’ We also demonstrate that the velocity function remains practically independent of attenuation for a wide range of small and moderate angles [Formula: see text]. In principle, estimation of the attenuation-anisotropy parameters from the coefficient [Formula: see text] requires computation of the phase angle, which depends on the anisotropic velocity field. For moderately anisotropic models, however, the difference between the phase and group directions should not significantly distort the results of attenuation analysis.

scholarly journals VSP polarization angles determination: Wysin-1 processing case study

2018 ◽  
Vol 66 (5) ◽  
pp. 1047-1062 ◽  
Author(s):  
Mateusz Zaręba ◽  
Tomasz Danek
Keyword(s):  
Seismic Data ◽  
Seismic Profile ◽  
Seismic Data Processing ◽  
Profile Data ◽  
Experiment Data ◽  
High Quality ◽  
Walkaway Vsp ◽  
Anisotropy Parameters ◽  
Borehole Seismic

Abstract In this paper, we present an analysis of borehole seismic data processing procedures required to obtain high-quality vertical stacks and polarization angles in the case of walkaway VSP (vertical seismic profile) data gathered in challenging conditions. As polarization angles are necessary for more advanced procedures like anisotropy parameters determination, their quality is critical for proper media description. Examined Wysin-1 VSP experiment data indicated that the best results can be obtained when rotation is performed for each shot on data after de-noising and vertical stacking of un-rotated data. Additionally, we proposed a procedure of signal matching that can substantially increase data quality.

Automatic early arrival traveltime tomography and its applications

Geophysics ◽  
2017 ◽  
Vol 82 (2) ◽  
pp. U1-U11 ◽  
Author(s):  
Chengbin (Chuck) Peng ◽  
Jun Tang
Keyword(s):  
Seismic Data ◽  
Field Data ◽  
Velocity Model ◽  
Accurate Estimation ◽  
Model Parameters ◽  
Data Set ◽  
Early Arrival ◽  
Head Waves ◽  
Synthetic Test ◽  
Anisotropy Parameters

We have developed a method of macrovelocity inversion that does not require explicit picking of either common-image point gathers or first breaks. The method uses head waves, diving waves, and wide-angle reflections in seismic data (collectively early arrival energies) for accurate estimation of velocity and anisotropy parameters. In this method, seismic data are first decomposed into Gaussian packets. Packets associated with early arrival energies are selected and used as input to a tomography solver. The outputs of the solver are velocity and Thomsen’s anisotropy parameters, or any of their combinations. Using information contained in the packets, we can correctly model the early arrival energies (first breaks and/or other refractions). The workflow is fully automatic and can be used in a batch processing environment with minimum human intervention. We have tested the method on synthetic and field data sets. In one synthetic test, we were able to reduce traveltime residuals of diving waves from 400 to 5 ms and recover anisotropic model parameters that are sensitive to early arrival traveltimes. In another synthetic test, we were able to recover a large shallow low-velocity anomaly with a very simple starting velocity model. The first field data set was for a shallow marine seismic data project. We were able to obtain a better shallow velocity model using our method than when using a legacy approach. In the second field data test, we applied our method on a deepwater data set from a dual-coil acquisition, with full-azimuth and long-offset coverage. Our method can correctly model early arrival energies recorded at long offsets and use them in the iterative inversion such that better estimation of velocities and anisotropy parameters in shallow sediments can be achieved. We have tested different starting models for the inversion. We are able to get very similar results, suggesting that our method is not sensitive to the accuracy of a starting model.

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