Compressional and shear‐wave logging in open and cased holes using a multipole tool

Geophysics ◽  
1991 ◽  
Vol 56 (4) ◽  
pp. 550-557 ◽  
Author(s):  
S. T. Chen ◽  
E. A. Eriksen
Keyword(s):  
P Wave ◽  
Log P ◽  
S Wave ◽  
S Waves ◽  
System P ◽  
Receiver System ◽  
Wide Range ◽  
Before And After ◽  
Sonic Logging ◽  
Logging Tool

We have found in field observations that the multipole sonic logging tool can effectively measure formation P‐wave and S‐wave data in a cased hole. The multipole tool, containing both monopole and quadrupole source‐receiver systems, was originally designed to log P‐ and S‐waves directly, in all lithologies, for an open borehole. The monopole source‐receiver system (P‐wave) operates at 7–10 kHz, as compared with 15–25 kHz for a conventional sonic tool, while the quadrupole source‐receiver system (S‐wave) operates at 3–7 kHz. These lower operating frequencies enable the signals to penetrate the well casing and cement more effectively than signals from a conventional sonic tool. As a result, the formation P‐ and S‐waves recorded by the multipole tool are generally much stronger than the unwanted waves which travel along the well casing and cement. Formation arrivals can be easily identified and separated from the casing arrivals for a wide range of lithologies. Logs run before and after the wells were cased show remarkable agreement even in severely washed out zones.

Numerical simulation of azimuthal acoustic logging in a borehole penetrating a rock formation boundary

Geophysics ◽  
2016 ◽  
Vol 81 (3) ◽  
pp. D283-D291 ◽  
Author(s):  
Peng Liu ◽  
Wenxiao Qiao ◽  
Xiaohua Che ◽  
Xiaodong Ju ◽  
Junqiang Lu ◽  
...  
Keyword(s):  
Domain Model ◽  
P Wave ◽  
S Wave ◽  
Angle Variation ◽  
P Waves ◽  
Acoustic Logging ◽  
S Waves ◽  
Rock Formation ◽  
Logging Tool ◽  
Difference Time

We have developed a new 3D acoustic logging tool (3DAC). To examine the azimuthal resolution of 3DAC, we have evaluated a 3D finite-difference time-domain model to simulate a case in which the borehole penetrated a rock formation boundary when the tool worked at the azimuthal-transmitting-azimuthal-receiving mode. The results indicated that there were two types of P-waves with different slowness in waveforms: the P-wave of the harder rock (P1) and the P-wave of the softer rock (P2). The P1-wave can be observed in each azimuthal receiver, but the P2-wave appears only in the azimuthal receivers toward the softer rock. When these two types of rock are both fast formations, two types of S-waves also exist, and they have better azimuthal sensitivity compared with P-waves. The S-wave of the harder rock (S1) appears only in receivers toward the harder rock, and the S-wave of the softer rock (S2) appears only in receivers toward the softer rock. A model was simulated in which the boundary between shale and sand penetrated the borehole but not the borehole axis. The P-wave of shale and the S-wave of sand are azimuthally sensitive to the azimuth angle variation of two formations. In addition, waveforms obtained from 3DAC working at the monopole-transmitting-azimuthal-receiving mode indicate that the corresponding P-waves and S-waves are azimuthally sensitive, too. Finally, we have developed a field example of 3DAC to support our simulation results: The azimuthal variation of the P-wave slowness was observed and can thus be used to reflect the azimuthal heterogeneity of formations.

The effect of the invaded zone on full wavetrain acoustic logging

Geophysics ◽  
1984 ◽  
Vol 49 (6) ◽  
pp. 796-809 ◽  
Author(s):  
L. J. Baker
Keyword(s):  
The Body ◽  
P Wave ◽  
Physical Parameters ◽  
S Wave ◽  
Acoustic Logging ◽  
S Waves ◽  
Sophisticated Model ◽  
Invaded Zone ◽  
Logging Tool ◽  
Depth Of Investigation

Most theoretical studies of acoustic borehole logging have employed the simple model of a fluid borehole in an infinite solid. This work attempts to account for the invaded zone using a more sophisticated model that additionally includes finite concentric shells surrounding the borehole. By appropriately choosing the physical parameters of these cylindrical shells, one can study the effect of the invaded zone, mudcake, or a cased hole on acoustic wavetrain components. The model accounts for geometric attenuation, but it assumes the formation is perfectly elastic. A key consideration is the distance that the acoustic log “sees” into the formation. The body of this report is devoted to studying the effect of the invaded zone, mudcake, or steel casing on the components of the full wavetrain (P-wave, S-wave, reflected modes, and Stoneley mode). I conclude that a sonic logging tool has a very shallow depth of investigation. This depth, for P- and S-waves, depends upon the spacing between the source and receiver. An approximate rule of thumb is that if the source‐to‐receiver separation is n feet, the logging tool sees n inches into the formation. Thus, a conventional logging tool sees less than 6 inches into the surrounding formation. Since attenuation of the P- and S-wave arrivals places a practical constraint on realistic source‐to‐receiver separations, the depth of investigation is limited to a maximum of about 2 ft. Therefore, an acoustic logging tool is usually capable of measuring properties of the invaded zone only. For the reader interested in the mathematical details of this work, the method of computation is described in Appendix A.

A method for correcting acoustic finite-difference amplitudes for elastic effects

Geophysics ◽  
2014 ◽  
Vol 79 (4) ◽  
pp. T243-T255 ◽  
Author(s):  
James W. D. Hobro ◽  
Chris H. Chapman ◽  
Johan O. A. Robertsson
Keyword(s):  
Wave Equation ◽  
Finite Difference ◽  
Effective Means ◽  
Cost Effective ◽  
P Wave ◽  
S Waves ◽  
Velocity Models ◽  
Acoustic Simulation ◽  
Wide Range ◽  
Elastic Simulation

We present a new method for correcting the amplitudes of arrivals in an acoustic finite-difference simulation for elastic effects. In this method, we selectively compute an estimate of the error incurred when the acoustic wave equation is used to approximate the behavior of the elastic wave equation. This error estimate is used to generate an effective source field in a second acoustic simulation. The result of this second simulation is then applied as a correction to the original acoustic simulation. The overall cost is approximately twice that of an acoustic simulation but substantially less than the cost of an elastic simulation. Because both simulations are acoustic, no S-waves are generated, so dispersed converted waves are avoided. We tested the characteristics of the method on a simple synthetic model designed to simulate propagation through a strong acoustic impedance contrast representative of sedimentary geology. It corrected amplitudes to high accuracy for reflected arrivals over a wide range of incidence angles. We also evaluated results from simulations on more complex models that demonstrated that the method was applicable in realistic sedimentary models containing a wide range of seismic contrasts. However, its accuracy was reduced for wide-angle reflections from very high impedance contrasts such as a shallow top-salt interface. We examined the influence of modeling at coarse grid resolutions, in which converted S-waves in the equivalent elastic simulation are dispersed. These results provide some validation for the accuracy of the method when applied using finite-difference grids designed for acoustic modeling. The method appears to offer a cost-effective means of modeling elastic amplitudes for P-wave arrivals in a useful range of velocity models. It has several potential applications in imaging and inversion.

scholarly journals Research on prediction method of S-wave velocity based on deep learning

2021 ◽  
Vol 2083 (4) ◽  
pp. 042065
Author(s):  
Guojie Yang ◽  
Shuhua Wang
Keyword(s):  
Deep Learning ◽  
Wave Velocity ◽  
Prediction Method ◽  
P Wave ◽  
Learning Technology ◽  
S Wave ◽  
Advantages And Disadvantages ◽  
Wave Prediction ◽  
Wide Range ◽  
Velocity Prediction

Abstract Aiming at the s-wave velocity prediction problem, based on the analysis of the advantages and disadvantages of the empirical formula method and the rock physics modeling method, combined with the s-wave velocity prediction principle, the deep learning method is introduced, and a deep learning-based logging s-wave velocity prediction method is proposed. This method uses a deep neural network algorithm to establish a nonlinear mapping relationship between reservoir parameters (acoustic time difference, density, neutron porosity, shale content, porosity) and s-wave velocity, and then applies it to the s-wave velocity prediction at the well point. Starting from the relationship between p-wave and s-wave velocity, the study explained the feasibility of applying deep learning technology to s-wave prediction and the principle of sample selection, and finally established a reliable s-wave prediction model. The model was applied to s-wave velocity prediction in different research areas, and the results show that the s-wave velocity prediction technology based on deep learning can effectively improve the accuracy and efficiency of s-wave velocity prediction, and has the characteristics of a wide range of applications. It can provide reliable s-wave data for pre-stack AVO analysis and pre-stack inversion, so it has high practical application value and certain promotion significance.

scholarly journals Determination of vp/vs on Bali Province: Case of Bali Earthquake March 22, 2017

2018 ◽  
Vol 19 (2) ◽  
pp. 73
Author(s):  
Febi Niswatul Auliyah ◽  
Komang Ngurah Suarbawa ◽  
Indira Indira
Keyword(s):  
Case Studies ◽  
Wave Velocity ◽  
P Wave ◽  
S Wave ◽  
Diagram Method ◽  
P Wave Velocity ◽  
Before And After ◽  
Earthquake Data

P-wave velocity and S-wave velocity have been investigated in the Bali Province by using earthquake case studies on March 22, 2017. The study was focused on finding out whether there were anomalies in the values of vp/vs before and after the earthquake. Earthquake data was obtained from the Meteorology, Climatology and Geophysics Agency (BMKG) Region III Denpasar, which consisted of the main earthquake on March 22, 2017 and earthquake data in August 2016 to May 2017. Data was processed using the wadati diagram method, obtained that the vp/vs on SRBI, IGBI, DNP and RTBI stations are shifted from 1.5062 to 1.8261. Before the earthquake occurred the anomaly of the value of vp/vs was found on the four stations, at the SRBI station at 10.35%, at the IGBI station at 16.16%, at DNP station at 12.27% and at RTBI station at 4.62%.

Green's function of the Lord–Shulman thermo-poroelasticity theory

2020 ◽  
Vol 221 (3) ◽  
pp. 1765-1776 ◽  
Author(s):  
Jia Wei ◽  
Li-Yun Fu ◽  
Zhi-Wei Wang ◽  
Jing Ba ◽  
José M Carcione
Keyword(s):  
Plane Wave ◽  
Green’S Function ◽  
Green's Function ◽  
Heterogeneous Media ◽  
Numerical Algorithms ◽  
Heat Diffusion ◽  
P Wave ◽  
Wave Analysis ◽  
S Wave ◽  
S Waves

SUMMARY The Lord–Shulman thermoelasticity theory combined with Biot equations of poroelasticity, describes wave dissipation due to fluid and heat flow. This theory avoids an unphysical behaviour of the thermoelastic waves present in the classical theory based on a parabolic heat equation, that is infinite velocity. A plane-wave analysis predicts four propagation modes: the classical P and S waves and two slow waves, namely, the Biot and thermal modes. We obtain the frequency-domain Green's function in homogeneous media as the displacements-temperature solution of the thermo-poroelasticity equations. The numerical examples validate the presence of the wave modes predicted by the plane-wave analysis. The S wave is not affected by heat diffusion, whereas the P wave shows an anelastic behaviour, and the slow modes present a diffusive behaviour depending on the viscosity, frequency and thermoelasticity properties. In heterogeneous media, the P wave undergoes mesoscopic attenuation through energy conversion to the slow modes. The Green's function is useful to study the physics in thermoelastic media and test numerical algorithms.

Scalar reverse‐time depth migration of prestack elastic seismic data

Geophysics ◽  
2001 ◽  
Vol 66 (5) ◽  
pp. 1519-1527 ◽  
Author(s):  
Robert Sun ◽  
George A. McMechan
Keyword(s):  
Seismic Waves ◽  
Velocity Model ◽  
P Wave ◽  
Common Source ◽  
Reverse Time ◽  
S Wave ◽  
Wave Source ◽  
Reflected Waves ◽  
S Waves ◽  
Elastic Data

Reflected P‐to‐P and P‐to‐S converted seismic waves in a two‐component elastic common‐source gather generated with a P‐wave source in a two‐dimensional model can be imaged by two independent scalar reverse‐time depth migrations. The inputs to migration are pure P‐ and S‐waves that are extracted by divergence and curl calculations during (shallow) extrapolation of the elastic data recorded at the earth’s surface. For both P‐to‐P and P‐to‐S converted reflected waves, the imaging time at each point is the P‐wave traveltime from the source to that point. The extracted P‐wave is reverse‐time extrapolated and imaged with a P‐velocity model, using a finite difference solution of the scalar wave equation. The extracted S‐wave is reverse‐time extrapolated and imaged similarly, but with an S‐velocity model. Converted S‐wave data requires a polarity correction prior to migration to ensure constructive interference between data from adjacent sources. Synthetic examples show that the algorithm gives satisfactory results for laterally inhomogeneous models.

Ground Motion From A Magnitude 3.5 Earthquake Near Massena, New York: Evidence For Poor Resolution of Corner Frequency For Small Events

1989 ◽  
Vol 60 (3) ◽  
pp. 95-100 ◽  
Author(s):  
S.E. Hough ◽  
K. Jacob ◽  
R. Busby ◽  
P.A. Friberg
Keyword(s):  
Earthquake Engineering ◽  
Epicentral Distance ◽  
Wave Spectrum ◽  
P Wave ◽  
Corner Frequency ◽  
Source Spectrum ◽  
Wave Spectra ◽  
S Wave ◽  
High Quality ◽  
Wide Range

Abstract We present analysis of a magnitude 3.5 event which occurred at 9 km epicentral distance from a digital strong motion instrument operated by the National Center for Earthquake Engineering Research. Although the size of this isolated event is such that it can scarcely be considered to be a significant earthquake, a careful analysis of this high quality recording does yield several interesting results: 1) the S-wave spectra can be interpreted in terms of a simple omega-squared source spectrum and frequency-independent attenuation, 2) there is the suggestion of a poorly-resolved resonance in the P-wave spectrum, and perhaps most importantly, 3) the apparently simple S-wave spectra can be fit almost equally well with a surprisingly wide range of seismic corner frequencies, from roughly 5 to 25 Hz. This uncertainty in corner frequency translates into uncertainties in inferred Q values of almost an order of magnitude, and into uncertainties in stress drop of two orders of magnitude. Given the high quality of the data and the short epicentral distance to the station, we consider it likely that resolution of spectral decay and corner frequency will be at least as poor for any other recording of earthquakes with comparable or smaller magnitudes.

scholarly journals A new acoustic assumption for orthorhombic media

2020 ◽  
Vol 223 (2) ◽  
pp. 1118-1129
Author(s):  
Mohammad Mahdi Abedi ◽  
Alexey Stovas
Keyword(s):  
Wave Propagation ◽  
Conventional Approach ◽  
P Wave ◽  
Model Parameters ◽  
Governing Equations ◽  
S Wave ◽  
S Waves ◽  
Exploration Seismology ◽  
And Inversion ◽  
Approximate Equations

SUMMARY In exploration seismology, the acquisition, processing and inversion of P-wave data is a routine. However, in orthorhombic anisotropic media, the governing equations that describe the P-wave propagation are coupled with two S waves that are considered as redundant noise. The main approach to free the P-wave signal from the S-wave noise is the acoustic assumption on the wave propagation. The conventional acoustic assumption for orthorhombic media zeros out the S-wave velocities along three orthogonal axes, but leaves significant S-wave artefacts in all other directions. The new acoustic assumption that we propose mitigates the S-wave artefacts by zeroing out their velocities along the three orthogonal symmetry planes of orthorhombic media. Similar to the conventional approach, our method reduces the number of required model parameters from nine to six. As numerical experiments on multiple orthorhombic models show, the accuracy of the new acoustic assumption also compares well to the conventional approach. On the other hand, while the conventional acoustic assumption simplifies the governing equations, the new acoustic assumption further complicates them—an issue that emphasizes the necessity of simple approximate equations. Accordingly, we also propose simpler rational approximate phase-velocity and eikonal equations for the new acoustic orthorhombic media. We show a simple ray tracing example and find out that the proposed approximate equations are still highly accurate.

Comparison of P‐ and S‐wave velocities and Q’S from VSP and sonic log data

Geophysics ◽  
1994 ◽  
Vol 59 (10) ◽  
pp. 1512-1529 ◽  
Author(s):  
Gopa S. De ◽  
Donald F. Winterstein ◽  
Mark A. Meadows
Keyword(s):  
Velocity Dispersion ◽  
P Wave ◽  
S Wave ◽  
S Waves ◽  
Wave Velocities ◽  
Sonic Log ◽  
Transit Times ◽  
Wave Slope ◽  
Northern Alberta ◽  
Q Values

We compared P‐ and S‐wave velocities and quality factors (Q’S) from vertical seismic profiling (VSP) and sonic log measurements in five wells, three from the southwest San Joaquin Basin of California, one from near Laredo, Texas, and one from northern Alberta. Our purpose was to investigate the bias between sonic log and VSP velocities and to examine to what degree this bias might be a consequence of dispersion. VSPs and sonic logs were recorded in the same well in every case. Subsurface formations were predominantly clastic. The bias found was that VSP transit times were greater than sonic log times, consistent with normal dispersion. For the San Joaquin wells, differences in S‐wave transit times averaged 1–2 percent, while differences in P‐wave transit times averaged 6–7 percent. For the Alberta well, the situation was reversed, with differences in S‐wave transit times being about 6 percent, while those for P‐waves were 2.5 percent. For the Texas well, the differences averaged about 4 percent for both P‐ and S‐waves. Drift‐curve slopes for S‐waves tended to be low where the P‐wave slopes were high and vice versa. S‐wave drift‐curve slopes in the shallow California wells were 5–10 μs/ft (16–33 μs/m) and the P‐wave slopes were 15–30 μs/ft (49–98 μs/m). The S‐wave slope in sandstones in the northern Alberta well was up to 50 μs/ft (164 μs/m), while the P‐wave slope was about 5 μs/ft (16 μs/m). In the northern Alberta well the slopes for both P‐ and S‐waves flattened in the carbonate. In the Texas well, both P‐ and S‐wave drifts were comparable. We calculated (Q’s) from a velocity dispersion formula and from spectral ratios. When the two Q’s agreed, we concluded that velocity dispersion resulted solely from absorption. These Q estimation methods were reliable only for Q values smaller than 20. We found that, even with data of generally outstanding quality, Q values determined by standard methods can have large uncertainties, and negative Q’s may be common.

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