Seismic monitoring of fluid fronts: An experimental study

Geophysics ◽  
2002 ◽  
Vol 67 (1) ◽  
pp. 221-229 ◽  
Author(s):  
Angelika‐M. Wulff ◽  
Svein Mjaaland
Keyword(s):  
Seismic Data ◽  
Seismic Monitoring ◽  
S Wave ◽  
Velocity Amplitude ◽  
S Waves ◽  
Transmitted Waves ◽  
Porous Sandstone ◽  
Grain Surface ◽  
Local Fluid Flow ◽  
Transmission And Reflection

Seismic signatures of time‐dependent reservoir processes, necessary for the interpretation of 4‐D seismic data, are still insufficiently described. This experiment was designed to monitor fluid‐front movements and saturation changes and to identify the related seismic signatures. Ultrasonic P‐ and S‐wave transmission and reflection measurements were used to monitor the waterflooding of a porous sandstone. The sandstone was flooded in steps by filling a tank in which the room‐dry cubic (50‐cm side) block of rock was placed. Waterflooding caused the velocity, amplitude, and frequency of the transmitted waves to diminish significantly; however, the changes were reversible by drying. The maximum reduction of the velocities was 7% and 12% for P‐ and S‐waves, respectively. The velocity and amplitude behavior can be explained by the Biot‐Gassmann's theory, local fluid flow, and grain‐surface effects. The correct interpretation of seismic signatures of fluid processes in reservoirs thus involves a knowledge of rock physical relations and attenuation mechanisms. Even at small saturations, reflections from the block bottom were strongly attenuated, but those from the upgoing water front could be monitored. The latter reflections were best observed in differential seismic traces, confirming that seismic monitoring can observe moving fronts directly.

The present state of seismic data acquisition: One view

Geophysics ◽  
1985 ◽  
Vol 50 (12) ◽  
pp. 2443-2451 ◽  
Author(s):  
Stanley J. Laster
Keyword(s):  
Data Acquisition ◽  
Seismic Data ◽  
Three Dimensional ◽  
Artificial Satellites ◽  
S Wave ◽  
Positioning Systems ◽  
S Waves ◽  
Exploration And Production ◽  
Seismic Data Acquisition ◽  
Marine Applications

Seismic data acquisition in the mid‐1980s is briefly reviewed. In terms of hardware, the trend has been toward an increased number of data channels in both land and marine applications. This has led to the development of digital telemetry systems. Positioning systems, particularly for marine work, have made use of artificial satellites. The perceived need for S‐wave information has led to development of S‐wave sources such as the horizontal vibrator. S‐waves in a few cases have been used to validate hydrocarbon indicators on seismic records. There has been a distinct trend toward three‐dimensional (3-D) seismic recording, both on land and at sea, and for both exploration and production applications.

Prestack multicomponent migration

Geophysics ◽  
1997 ◽  
Vol 62 (2) ◽  
pp. 598-613 ◽  
Author(s):  
Jingping Zhe ◽  
Stewart A. Greenhalgh
Keyword(s):  
Seismic Data ◽  
Numerical Test ◽  
Computer Time ◽  
Complex Structures ◽  
Test Results ◽  
S Wave ◽  
Displacement Potential ◽  
S Waves ◽  
And Function ◽  
Wavefield Extrapolation

Prestack elastic migration by displacement potential extrapolation is a mixed, systematic, and function‐blocked vector wavefield migration algorithm. A new wavefield extrapolation method for inhomogeneous media is introduced here according to the following sequence: displacements ← potentials ← extrapolation of the potentials ← displacements, which is relatively accurate and not computer‐time intensive. Traveltimes of both direct downgoing P‐ and S‐waves, which are necessary in elastic migration, are calculated with a modified convolutional acoustic forward modeling program applicable to complex structures. A new image condition based on the time consistent principle is developed. It involves first obtaining an image condition section. Then two images (P P and S S) are obtained from the product of the extrapolated and decomposed P P‐ and S S‐wave displacement amplitudes and the image condition section. All P P‐, P S‐, S P‐ and S S‐waves are considered when the image condition section is calculated. The image condition section minimizes cross‐talk between modes. Compared to previous treatments, the newly developed image condition formula is superior since it allows migration of multicomponent seismic data produced using a combined P and S source. Numerical test results are very encouraging and clearly demonstrate the robustness of the technique. Further work is continuing so as to overcome ray angle and polarity problems in the image condition.

Prestack scalar reverse-time depth migration of 3D elastic seismic data

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. S199-S207 ◽  
Author(s):  
Robert Sun ◽  
George A. McMechan ◽  
Chen-Shao Lee ◽  
Jinder Chow ◽  
Chen-Hong Chen
Keyword(s):  
Wave Equation ◽  
Finite Difference ◽  
Seismic Data ◽  
P Wave ◽  
Scalar Wave ◽  
Reverse Time ◽  
S Wave ◽  
Absolute Value ◽  
S Waves ◽  
Finite Difference Solution

Using two independent, 3D scalar reverse-time depth migrations, we migrate the reflected P- and S-waves in a prestack 3D, three-component (3-C), elastic seismic data volume generated with a P-wave source in a 3D model and recorded at the top of the model. Reflected P- and S-waves are extracted by divergence (a scalar) and curl (a 3-C vector) calculations, respectively, during shallow downward extrapolation of the elastic seismic data. The imaging time for the migrations of both the reflected P- and P-S converted waves at each point is the one-way P-wave traveltime from the source to that point.The divergence (the extracted P-waves) is reverse-time extrapolated using a finite-difference solution of the 3D scalar wave equation in a 3D P-velocity modeland is imaged to obtain the migrated P-image. The curl (the extracted S-waves) is first converted into a scalar S-wavefield by taking the curl’s absolute value as the absolute value of the scalar S-wavefield and assigning a positive sign if the curl is counterclockwise relative to the source or a negative sign otherwise. This scalar S-wavefield is then reverse-time extrapolated using a finite-difference solution of the 3D scalar wave equation in a 3D S-velocity model, and it is imaged with the same one-way P-wave traveltime imaging condition as that used for the P-wave. This achieves S-wave polarity uniformity and ensures constructive S-wave interference between data from adjacent sources. The algorithm gives satisfactory results on synthetic examples for 3D laterally inhomogeneous models.

Real data results of Kirchhoff elastic wave migration

Geophysics ◽  
1986 ◽  
Vol 51 (4) ◽  
pp. 1006-1011 ◽  
Author(s):  
Ting‐Fan Dai ◽  
John T. Kuo
Keyword(s):  
Seismic Data ◽  
Real Data ◽  
Horizontal Layer ◽  
S Wave ◽  
P Waves ◽  
S Waves ◽  
Surface Data ◽  
And Migration ◽  
Wave Migration ◽  
Kirchhoff Integral

Although Kirchhoff integral migration has attracted considerable attention for seismic data processing since the early 1970s, it, like all other seismic migration methods, is only applicable to compressional (P) waves. Because of a recent surge of interest in shear (S) waves, Kuo and Dai (1984) developed the Kirchhoff elastic (P and S) wave migration (KEWM) formulation and migration principle for the case of source and receiver noncoincidence. They obtained encouraging results using two‐dimensional (2-D) synthetic surface data from various geometric elastic models, including a dipping layer, a composite dipping and horizontal layer, and two layers over a half‐space.

scholarly journals Three-component amplitude versus offset analysis

1989 ◽  
Vol 20 (2) ◽  
pp. 257
Author(s):  
D.R. Miles ◽  
G. Gassaway ◽  
L. Bennett ◽  
R. Brown
Keyword(s):  
Seismic Data ◽  
P Wave ◽  
S Wave ◽  
Converted Wave ◽  
P Waves ◽  
S Waves ◽  
Avo Analysis ◽  
Avo Inversion ◽  
Amplitude Versus Offset ◽  
Converted Waves

Three-component (3-C) amplitude versus offset (AVO) inversion is the AVO analysis of the three major energies in the seismic data, P-waves, S-waves and converted waves. For each type of energy the reflection coefficients at the boundary are a function of the contrast across the boundary in velocity, density and Poisson's ratio, and of the angle of incidence of the incoming wave. 3-C AVO analysis exploits these relationships to analyse the AVO changes in the P, S, and converted waves. 3-C AVO analysis is generally done on P, S, and converted wave data collected from a single source on 3-C geophones. Since most seismic sources generate both P and S-waves, it follows that most 3-C seismic data may be used in 3-C AVO inversion. Processing of the P-wave, S-wave and converted wave gathers is nearly the same as for single-component P-wave gathers. In split-spread shooting, the P-wave and S-wave energy on the radial component is one polarity on the forward shot and the opposite polarity on the back shot. Therefore to use both sides of the shot, the back shot must be rotated 180 degrees before it can be stacked with the forward shot. The amplitude of the returning energy is a function of all three components, not just the vertical or radial, so all three components must be stacked for P-waves, then for S-waves, and finally for converted waves. After the gathers are processed, reflectors are picked and the amplitudes are corrected for free-surface effects, spherical divergence and the shot and geophone array geometries. Next the P and S-wave interval velocities are calculated from the P and S-wave moveouts. Then the amplitude response of the P and S-wave reflections are analysed to give Poisson's ratio. The two solutions are then compared and adjusted until they match each other and the data. Three-component AVO inversion not only yields information about the lithologies and pore-fluids at a specific location; it also provides the interpreter with good correlations between the P-waves and the S-waves, and between the P and converted waves, thus greatly expanding the value of 3-C seismic data.

Vector-wave-based elastic reverse time migration of ocean-bottom 4C seismic data

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. S333-S343 ◽  
Author(s):  
Pengfei Yu ◽  
Jianhua Geng ◽  
Jiqiang Ma
Keyword(s):  
Seismic Data ◽  
Ocean Bottom ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
S Wave ◽  
Vector Wave ◽  
S Waves ◽  
Time Migration ◽  
Multicomponent Seismic ◽  
Wavefield Extrapolation

The acoustic-elastic coupled equation (AECE) has several advantages when compared with conventional scalar-wave-based elastic reverse time migration (ERTM) methods used to image ocean-bottom multicomponent seismic data. In particular, vector-wave-based ERTM requires vectorial P- and S-waves on the source and receiver sides, but these cannot be directly obtained from wavefield extrapolation using AECE. Therefore, we have developed a P- and S-wave vector decomposition (VD) approach within AECE; this approach enables the deduction of a novel VD-based AECE, from which vectorial P- and S-waves can be obtained directly via wavefield extrapolation. We are also able to derive a new formulation suitable for vector-wave-based ERTM of ocean-bottom multicomponent seismic data that can generate a phase-preserved PS-image. Three synthetic examples illustrate the validity and effectiveness of our new method.

scholarly journals Responses of dipole-source reflected shear waves in acoustically slow formations

2019 ◽  
Author(s):  
Hao Wang ◽  
Ning Li ◽  
Caizhi Wang ◽  
Hongliang Wu ◽  
Peng Liu ◽  
...  
Keyword(s):  
Finite Difference Time Domain ◽  
Dipole Source ◽  
Sh Wave ◽  
S Wave ◽  
High Fracture ◽  
S Waves ◽  
Angle Fracture ◽  
Dip Angle ◽  
Difference Time

Abstract In the process of dipole-source acoustic far-detection logging, the azimuth of the fracture outside the borehole can be determined with the assumption that the SH–SH wave is stronger than the SV–SV wave. However, in slow formations, the considerable borehole modulation highly complicates the dipole-source radiation of SH and SV waves. A 3D finite-difference time-domain method is used to investigate the responses of the dipole-source reflected shear wave (S–S) in slow formations and explain the relationships between the azimuth characteristics of the S–S wave and the source–receiver offset and the dip angle of the fracture outside the borehole. Results indicate that the SH–SH and SV–SV waves cannot be effectively distinguished by amplitude at some offset ranges under low- and high-fracture dip angle conditions, and the offset ranges are related to formation properties and fracture dip angle. In these cases, the fracture azimuth determined by the amplitude of the S–S wave not only has a $180^\circ $ uncertainty but may also have a $90^\circ $ difference from the actual value. Under these situations, the P–P, S–P and S–S waves can be combined to solve the problem of the $90^\circ $ difference in the azimuth determination of fractures outside the borehole, especially for a low-dip-angle fracture.

Geometrical spreading in a layered transversely isotropic medium with vertical symmetry axis

Geophysics ◽  
2003 ◽  
Vol 68 (6) ◽  
pp. 2082-2091 ◽  
Author(s):  
Bjørn Ursin ◽  
Ketil Hokstad
Keyword(s):  
Ray Tracing ◽  
Seismic Data ◽  
Symmetry Axis ◽  
Transversely Isotropic ◽  
Analytical Approximation ◽  
Geometrical Spreading ◽  
S Wave ◽  
Weak Anisotropy ◽  
P Waves ◽  
Amplitude Versus

Compensation for geometrical spreading is important in prestack Kirchhoff migration and in amplitude versus offset/amplitude versus angle (AVO/AVA) analysis of seismic data. We present equations for the relative geometrical spreading of reflected and transmitted P‐ and S‐wave in horizontally layered transversely isotropic media with vertical symmetry axis (VTI). We show that relatively simple expressions are obtained when the geometrical spreading is expressed in terms of group velocities. In weakly anisotropic media, we obtain simple expressions also in terms of phase velocities. Also, we derive analytical equations for geometrical spreading based on the nonhyperbolic traveltime formula of Tsvankin and Thomsen, such that the geometrical spreading can be expressed in terms of the parameters used in time processing of seismic data. Comparison with numerical ray tracing demonstrates that the weak anisotropy approximation to geometrical spreading is accurate for P‐waves. It is less accurate for SV‐waves, but has qualitatively the correct form. For P waves, the nonhyperbolic equation for geometrical spreading compares favorably with ray‐tracing results for offset‐depth ratios less than five. For SV‐waves, the analytical approximation is accurate only at small offsets, and breaks down at offset‐depth ratios less than unity. The numerical results are in agreement with the range of validity for the nonhyperbolic traveltime equations.

Estimates of Q in central Asia as a function of frequency and depth using the coda of locally recorded earthquakes

1982 ◽  
Vol 72 (1) ◽  
pp. 129-149
Author(s):  
S. W. Roecker ◽  
B. Tucker ◽  
J. King ◽  
D. Hatzfeld
Keyword(s):  
Frequency Dependence ◽  
Central Asia ◽  
Wide Frequency Range ◽  
S Wave ◽  
Uppermost Mantle ◽  
Regional Heterogeneity ◽  
S Waves ◽  
Tectonic Processes ◽  
Hindu Kush ◽  
Attenuation Mechanism

abstract Digital recordings of microearthquake codas from shallow and intermediate depth earthquakes in the Hindu Kush region of Afghanistan were used to determine the attenuation factors of the S-wave coda (Qc) and primary S waves (Qβ). An anomalously rapid decay of the coda shortly after the S-wave arrival, observed also in a study of coda in central Asia by Rautian and Khalturin (1978), seems to be due primarily to depth-dependent variations in Qc. In particular, we deduce the average Qc in the crust and uppermost mantle (<100-km depth) is approximately four times lower than the deeper mantle (<400-km depth) over a wide frequency range (0.4 to 24 Hz). Further, while Qc generally increases with frequency at any depth, the degree of frequency dependence of Qc depends on depth. Except at the highest frequency studied here (∼48 Hz), the magnitude of Qc at a particular frequency increases with depth while its frequency dependence decreases. For similar depths, determinations of Qβ and Qc agree, suggesting a common wave composition and attenuation mechanism for S waves and codas. Comparison of these determinations of Qc in Afghanistan with those in other parts of the world shows that the degree of frequency dependence of Qc correlates with the expected regional heterogeneity. Such a correlation supports the prejudice that Qc is primarily influenced by scattering and suggests that tectonic processes such as folding and faulting are instrumental in creating scattering environments.

Automatic phase identification of earthquake based on the UBDN deep network

2021 ◽  
pp. 1-10
Author(s):  
Jianxian Cai ◽  
Xun Dai ◽  
Zhitao Gao ◽  
Yan Shi
Keyword(s):  
Seismic Data ◽  
Short Term Memory ◽  
Long Term Memory ◽  
Phase Identification ◽  
S Wave ◽  
Traditional Methods ◽  
Term Memory ◽  
Seismic Stations ◽  
2008 Wenchuan Earthquake ◽  
Deep Network

Seismic data obtained from seismic stations are the major source of the information used to forecast earthquakes. With the growth in the number of seismic stations, the size of the dataset has also increased. Traditionally, STA/LTA and AIC method have been applied to process seismic data. However, the enormous size of the dataset reduces accuracy and increases the rate of missed detection of the P and S wave phase when using these traditional methods. To tackle these issues, we introduce the novel U-net-Bidirectional Long-Term Memory Deep Network (UBDN) which can automatically and accurately identify the P and S wave phases from seismic data. The U-net based UBDN strongly maintains the U-net’s high accuracy in edge detection for extracting seismic phase features. Meanwhile, it also reduces the missed detection rate by applying the Bidirectional Long Short-Term Memory (Bi-LSTM) mode that processes timing signals to establish the relationship between seismic phase features. Experimental results using the Stanford University seismic dataset and data from the 2008 Wenchuan earthquake aftershock confirm that the proposed UBDN method is very accurate and has a lower rate of missed phase detection, outperforming solutions that adapt traditional methods by an order of magnitude in terms of error percentage.

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