First-break vertical seismic profiling tomography for Vinton Salt Dome

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. U29-U36 ◽  
Author(s):  
Hua-wei Zhou
Keyword(s):  
A Priori ◽  
Salt Dome ◽  
Data Set ◽  
Velocity Anisotropy ◽  
Seismic Profiling ◽  
Velocity Models ◽  
Vertical Seismic Profiling ◽  
Vsp Data ◽  
Multiscale Inversion ◽  
Sonic Logs

Building laterally depth-varying velocity models for vertical seismic profiling (VSP) imaging is challenging because of the narrow ray-angle coverage of VSP data, especially if only first arrivals are used. This study explores the potential of a new deformable-layer tomography (DLT) for building velocity models with a VSP data set acquired over the Vinton salt dome in southwestern Louisiana. The DLT method uses first breaks to constrain the geometry of velocity interfaces from an initial model of flat, constant-velocity layers parameterized using a priori geologic and geophysical information. A progressive multiscale inversion loop gradually updates the interface geometry. The final solution model, containing 3D geometry, is well supported by resolution and reliability tests and closely matches the long-wavelength trends of area sonic logs. The presence of velocity anisotropy is also indicated.

Analysis and removal of multiply scattered tube waves

Geophysics ◽  
2000 ◽  
Vol 65 (3) ◽  
pp. 745-754 ◽  
Author(s):  
Gérard C. Herman ◽  
Paul A. Milligan ◽  
Qicheng Dong ◽  
James W. Rector
Keyword(s):  
Wave Field ◽  
Large Amplitude ◽  
Data Set ◽  
Impedance Function ◽  
Seismic Profiling ◽  
Vertical Seismic Profiling ◽  
Total Data ◽  
Vsp Data ◽  
Tube Wave

Because of irregularities in or near the borehole, vertical seismic profiling (VSP) or crosswell data can be contaminated with scattered tube waves. These can have a large amplitude and can interfere with weaker upcoming reflections, destroying their continuity. This type of organized noise cannot always be removed with filtering methods currently in use. We propose a method based on modeling the scattered tube‐wave field and then subtracting it from the total data set. We assume that the scattering occurs close to the borehole axis and therefore use a 1-D impedance function to characterize borehole irregularities. Estimation of this impedance function is one of the first steps. Our method also accounts for multiply scattered tube waves. We apply the method to an actual VSP data set and conclude that the continuity of reflected, upcoming events improves significantly in a washout zone.

Correlation between seismic diffractions extracted from vertical seismic profiling data and borehole logging in a carbonate environment

2015 ◽  
Vol 3 (2) ◽  
pp. T121-T129 ◽  
Author(s):  
Alexander Klokov ◽  
Damir Irkabaev ◽  
Osareni C. Ogiesoba ◽  
Nail Munasypov
Keyword(s):  
Joint Analysis ◽  
Seismic Attribute ◽  
Data Set ◽  
Borehole Logging ◽  
Seismic Profiling ◽  
Vertical Seismic Profiling ◽  
Fluid Saturation ◽  
Attribute Analysis ◽  
Vsp Data ◽  
Tectonic Dislocations

Seismic diffractions may play an important role in seismic interpretation because they characterize geologic objects that might not be visible for conventional seismic attribute analysis. Diffractivity may be caused by, and consequently may define, tectonic dislocations (faults and fractures), lithologic variations, and fluid saturation within rocks. We have tied seismic diffractions extracted from vertical seismic profiling (VSP) data and borehole logging, from which we recognized the reasons that were responsible for diffractivity of the strata. First, we processed a multisource multicomponent VSP data set to extract seismic diffractions and constructed diffraction images of the strata for all three of the VSP data components. Then, we performed joint analysis of well logs and diffractions to obtain petrophysical attributes associated with diffraction images. We divided the rock succession into several units, which have different diffraction properties. We identified compacted rock, alternating intervals, isolated fractured zones, and fluid-saturated layers.

A recursive method for the separation of upgoing and downgoing waves of vertical seismic profiling data

Geophysics ◽  
1986 ◽  
Vol 51 (12) ◽  
pp. 2206-2218 ◽  
Author(s):  
F. Aminzadeh
Keyword(s):  
Time Domain ◽  
Fourier Transforms ◽  
A Priori ◽  
Computational Time ◽  
Linear Filter ◽  
Seismic Profiling ◽  
Vertical Seismic Profiling ◽  
Starting Point ◽  
Vsp Data ◽  
The Time Domain

An important part of the processing of vertical seismic profiling (VSP) data is the separation of upgoing and downgoing waves. I introduce a new method for separation based on a time‐domain recursive linear filter. The separation method uses an approximation to an optimal, frequency‐domain, nonlinear filter solution as the starting point. The time‐domain recursive linear (approximate) filter converges to the optimal (exact) solution. Since the computation is in the time domain and since this filter is linear, some of the temporal aliasing and other problems resulting from the forward and inverse Fourier transforms are avoided. Specifically, instability for some frequencies (spectral singularities) is not experienced here. This method uses a priori information of the opposite stepouts of the upgoing and downgoing waves. Equal spacing between borehole measurement points is not required. Further, the computational time may be controlled according to the desired accuracy. An important feature of this method is that it locates the reflecting boundaries of the subsurface. Having located the homogeneous layers, it allows variable‐length windows of traces for separation, which eliminates the undesirable effects of smearing and extending wave fields beyond their origins. Also, knowledge of acoustic impedances for accurate implementation of the optimum filter is no longer required.

Comparison of seismic attenuation models using zero-offset vertical seismic profiling (VSP) data

Geophysics ◽  
2005 ◽  
Vol 70 (2) ◽  
pp. F17-F25 ◽  
Author(s):  
Tommy Toverud ◽  
Bjørn Ursin
Keyword(s):  
Model Fitting ◽  
Seismic Attenuation ◽  
Data Set ◽  
Seismic Profiling ◽  
Vertical Seismic Profiling ◽  
Vsp Data ◽  
Seismic Frequencies ◽  
Standard Linear Solid ◽  
Attenuation Models ◽  
Zero Offset

For seismic frequencies it is common to use an empirical equation to model attenuation. Usually the attenuation coefficient is modeled with linear frequency dependence, a model referred to as the Kolsky-Futterman model. Other models have been suggested in the geophysical literature. We compare eight of these models on a zero-offset vertical seismic profiling (VSP) data set: the Kolsky-Futterman, the power law, the Kjartansson, the Müller, the Azimi second, the Azimi third, the Cole-Cole, and the standard linear solid (SLS) models. For three separate depth zones we estimate velocities and Q-values for all eight models. A least-squares model-fitting algorithm gives almost the same normalized misfit for all models. Thus, none of the models can be preferred or rejected based on the given data set. Slightly better overall results are obtained for the Kolsky-Futterman model; for one depth zone, the SLS model gave the best result.

Migration moveout analysis and depth focusing

Geophysics ◽  
1993 ◽  
Vol 58 (1) ◽  
pp. 91-100 ◽  
Author(s):  
Claude F. Lafond ◽  
Alan R. Levander
Keyword(s):  
Heterogeneous Media ◽  
A Priori ◽  
Complex Structure ◽  
Tomographic Reconstruction ◽  
Synthetic Data ◽  
Real Data ◽  
Velocity Model ◽  
Velocity Analysis ◽  
Data Set ◽  
Velocity Models

Prestack depth migration still suffers from the problems associated with building appropriate velocity models. The two main after‐migration, before‐stack velocity analysis techniques currently used, depth focusing and residual moveout correction, have found good use in many applications but have also shown their limitations in the case of very complex structures. To address this issue, we have extended the residual moveout analysis technique to the general case of heterogeneous velocity fields and steep dips, while keeping the algorithm robust enough to be of practical use on real data. Our method is not based on analytic expressions for the moveouts and requires no a priori knowledge of the model, but instead uses geometrical ray tracing in heterogeneous media, layer‐stripping migration, and local wavefront analysis to compute residual velocity corrections. These corrections are back projected into the velocity model along raypaths in a way that is similar to tomographic reconstruction. While this approach is more general than existing migration velocity analysis implementations, it is also much more computer intensive and is best used locally around a particularly complex structure. We demonstrate the technique using synthetic data from a model with strong velocity gradients and then apply it to a marine data set to improve the positioning of a major fault.

Calculate Formation Velocity from Vertical Seismic Profiling Data

2014 ◽  
Vol 599-601 ◽  
pp. 639-642
Author(s):  
Jun Zhou ◽  
Chun Hui Xie ◽  
Peng Yang
Keyword(s):  
Random Errors ◽  
Seismic Profiling ◽  
Interval Velocity ◽  
Vertical Seismic Profiling ◽  
Long Offset ◽  
Vsp Data ◽  
Velocity Information

Extracting interval velocity is one of important applications of VSP data. Also, imaging of VSP data requires accurate velocity information. Two kinds of algorithms on the assumption of straight-ray and curve-ray are employed to calculate interval velocity respectively. Comparison of the extracted velocity from the two methods above with real velocity shows that both methods are suitable for VSP data recorded in the vicinity of well, while the algorithm derived from straight-ray fails in the long-offset. Moreover, the curve-ray is more reliable when there are some random errors due to the first arrivals picking.

How to twist and turn a fiber: Performance modeling for optimal DAS acquisitions

2019 ◽  
Vol 38 (3) ◽  
pp. 226-231 ◽  
Author(s):  
Andreas Wuestefeld ◽  
Matt Wilks
Keyword(s):  
Strain Energy ◽  
Performance Modeling ◽  
Design Parameters ◽  
Target Area ◽  
Complex Velocity ◽  
Detection Thresholds ◽  
Seismic Profiling ◽  
Velocity Models ◽  
Vertical Seismic Profiling ◽  
Distributed Acoustic Sensing

The success of a distributed acoustic sensing (DAS) survey depends on strain energy impeding at favorable angles at most sections of the fiber. Although constrained to the path of the wellbore, there are various design parameters that can influence the recorded DAS amplitude. We present here a method to model the performance of DAS installations. We use precise raypath modeling in complex velocity models to determine ray incidence angles and show variations between different wrapping angles and detection thresholds. We then propose a way to evaluate the performance of the DAS acquisition design, and how to optimize processing, based on the percentage of DAS channels above a chosen amplitude threshold. For microseismic studies, the best wrapping angle of the fiber can be determined, which may be defined as covering the target area most homogeneously. For vertical seismic profiling projects, surface shot positions can be evaluated for their predicted recorded energy.

On: “Vertical seismic profiling: Separation of upgoing and downgoing acoustic waves in a stratified medium” by B. Seeman and L. Horowicz (GEOPHYSICS, 48, 555–568, May 1983)

Geophysics ◽  
1986 ◽  
Vol 51 (5) ◽  
pp. 1148-1149
Author(s):  
S. D. Stainsby ◽  
M. H. Worthington
Keyword(s):  
Acoustic Waves ◽  
Sampling Interval ◽  
Stratified Medium ◽  
Time Shift ◽  
Reference Level ◽  
Seismic Profiling ◽  
Vertical Seismic Profiling ◽  
Cutoff Frequencies ◽  
The Earth ◽  
Vsp Data

Seeman and Horowicz devised an elegant procedure for the separation of upgoing and downgoing waves in VSP data. Their method is based upon a least‐squares solution of the frequency‐domain equations which relate the upgoing and downgoing signals at a reference level to the observed signals at other levels in the Earth. The coefficients of these equations are time‐shift operations. Unfortunately, for frequencies [Formula: see text] where δt is the vertical time sampling interval, the denominator of the solution equations is zero. For this reason the authors only applied the method over a passband: [Formula: see text] where the cutoff frequencies [Formula: see text] and [Formula: see text] are chosen to reflect the useful frequency band of the signal.

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