A blind interpretation of drill‐bit signals

Geophysics ◽  
2000 ◽  
Vol 65 (3) ◽  
pp. 970-978 ◽  
Author(s):  
Flavio Poletto
Keyword(s):  
Seismic Signal ◽  
Dominant Frequency ◽  
Drill Bit ◽  
Coherent Noise ◽  
Seismic Profiling ◽  
Vertical Seismic Profiling ◽  
Vsp Data ◽  
First Arrival

The role of kurtosis in evaluating the quality of vertical seismic profiling (VSP) drill‐bit data is investigated. The calculations show how kurtosis depends on the dominant frequency, bandwidth, and phase content of a seismic signal. This analysis is applied to synthetic and real common‐offset and common‐shot drill‐bit seismograms to evaluate the prominence and quality of the first arrival and other coherent events. High values of kurtosis correspond to an isolated first arrival or to a compressed coherent noise event, while low values are typical of low S/N (distributed) ratio traces. Kurtosis analysis applied to drill‐bit VSP data while drilling proved to be successful at identifying high‐quality traces with little interpretational input.

scholarly journals An extraction method of dispersion curve from vertical seismic profiling data

2020 ◽  
Author(s):  
Zhi Hu ◽  
Jinghuai Gao ◽  
Yanbin He ◽  
Guowei Zhang
Keyword(s):  
Dispersion Curve ◽  
Group Velocity ◽  
Body Wave ◽  
Seismic Signal ◽  
Time Frequency ◽  
Seismic Profiling ◽  
Vertical Seismic Profiling ◽  
Wave Data ◽  
Vsp Data ◽  
The Relationship

Abstract The dispersion curve describes the relationship between velocities and frequencies. The group velocity is a kind of dispersion, which presents the velocities of the energy with different frequencies. Although many studies have shown methods for estimating group velocity from a surface wave, the estimation of group velocity from body-wave data is still hard. In this paper, we propose a method to calculate the group velocity from vertical seismic profiling (VSP) data that is a kind of body-wave data. The generalised S-transform (GST) is used to map the seismic signal to the time-frequency (TF) domain and then the group delay (GD) can be extracted from the TF domain. The GD shows the travelling time of different frequency components. The group velocity can be calculated by the GD and the distance between receivers. Unfortunately, the GD is hard to measure accurately because of the noise. Inaccurate GD introduces errors in estimating the velocity. To reduce the errors, we make use of the multiple traces and the iterative least-squares fitting to extract the relationship line between GD and depths. The slope of the line is the reciprocal of the group velocity. Two numerical examples prove the effectiveness of the method. We also derive the formula of group velocity in diffusive-viscous media. In the field data example, the dispersion intensity at different depths and the geological layers can be well matched. These examples illustrate the proposed method is an alternative method for dispersion estimation from VSP.

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.

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.

Prediction ahead of the bit by using drill‐bit pilot signals and reverse vertical seismic profiling (RVSP)

Geophysics ◽  
2002 ◽  
Vol 67 (4) ◽  
pp. 1169-1176 ◽  
Author(s):  
Massimo Malusa ◽  
Flavio Poletto ◽  
Francesco Miranda
Keyword(s):  
Numerical Model ◽  
Low Cost ◽  
Drill Bit ◽  
Seismic Profiling ◽  
Vertical Seismic Profiling ◽  
Zero Offset

Surface drillstring axial pilot signals are used to predict reflections ahead of the drill bit. We show that part of the drill‐bit signal propagates downward in the formation, reflects upward by a seismic interface, and is then transmitted to the drillstring and the surface pilot sensors. These reflections are interpreted in drill‐bit pilot signals by means of a numerical model of the drillstring coupled to the formation at the bit–rock contact. The result is an additional, low‐cost, reverse VSP (RVSP) in the zero‐offset approximation. These while‐drilling results are integrated with conventional drill‐bit RVSP measurements and compared with other geophysical and well results.

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.

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