Wavefield separation by 3-D filtering in crosshole seismic reflection processing

Geophysics ◽  
1994 ◽  
Vol 59 (7) ◽  
pp. 1065-1071 ◽  
Author(s):  
Peter S. Rowbotham ◽  
Neil R. Goulty
Keyword(s):  
Seismic Reflection ◽  
Primary Energy ◽  
P Wave ◽  
Head Wave ◽  
Common Source ◽  
S Wave ◽  
Coherent Noise ◽  
Data Set ◽  
Seismic Reflection Data ◽  
Wavefield Separation

In processing crosshole seismic reflection data, it is necessary to separate the upgoing and downgoing primary reflections from each other, from the direct waves, and from other wave types in the data. We have implemented a 3-D f-k-k filter for wavefield separation that is applied in a single pass. The complete data set is treated as a data volume, with each sample defined by the three coordinates of source depth, receiver depth, and time. The filter works well because upgoing primaries, downgoing primaries, and direct waves lie in different quadrants in f-k-k space. The strongest multiples, including mode‐converted multiples, lie in the same quadrants in f-k-k space as the direct waves, so they are readily rejected together. Tube waves and mode‐converted primaries are also suppressed as most of the energy in these wave types lies outside the pass volume for P‐wave primaries. Some head wave and S‐wave primary energy will be passed by the filter; however, these waves tend to have low amplitudes and late arrival times, respectively, and will be smeared out on imaging with the P‐wave velocity field. We have processed a real crosshole data set using two different methods of wavefield separation: applying 2-D f-k filtering to common source gathers and applying a 3-D f-k-k filter to the whole data set. The migrated image produced after 3-D f-k-k filtering contains less coherent noise and consequently shows improved continuity of reflectors.

Separation of signal and coherent noise by migration filtering

Geophysics ◽  
2000 ◽  
Vol 65 (2) ◽  
pp. 574-583 ◽  
Author(s):  
Tamas Nemeth ◽  
Hongchuan Sun ◽  
Gerard T. Schuster
Keyword(s):  
Forward Modeling ◽  
P Wave ◽  
Wave Reflections ◽  
S Wave ◽  
Coherent Noise ◽  
Signal Model ◽  
Model Estimate ◽  
Wavefield Separation ◽  
Order Of Magnitude ◽  
Magnitude Increase

A key issue in wavefield separation is to find a domain where the signal and coherent noise are well separated from one another. A new wavefield separation algorithm, called migration filtering, separates data arrivals according to their path of propagation and their actual moveout characteristics. This is accomplished by using forward modeling operators to compute the signal and the coherent noise arrivals. A linearized least‐squares inversion scheme yields model estimates for both components; the predicted signal component is constructed by forward modeling the signal model estimate. Synthetic and field data examples demonstrate that migration filtering improves separation of P-wave reflections and surface waves, P-wave reflections and tube waves, P-wave diffractions, and S-wave diffractions. The main benefits of the migration filtering method compared to conventional filtering methods are better wavefield separation capability, the capability of mixing any two conventional transforms for wavefield separation under a general inversion framework, and the capability of mitigating the signal and coherent noise crosstalk by using regularization. The limitations of the method may include more than an order of magnitude increase in computation costs compared to conventional transforms and the difficulty of selecting the proper modeling operators for some wave modes.

A strategy for nonlinear elastic inversion of seismic reflection data

Geophysics ◽  
1986 ◽  
Vol 51 (10) ◽  
pp. 1893-1903 ◽  
Author(s):  
Albert Tarantola
Keyword(s):  
Wave Velocity ◽  
Seismic Reflection ◽  
Wave Impedance ◽  
P Wave ◽  
S Wave ◽  
Seismic Reflection Data ◽  
S Waves ◽  
Wave Velocities ◽  
Reflection Data ◽  
P Wave Velocity

The problem of interpretation of seismic reflection data can be posed with sufficient generality using the concepts of inverse theory. In its roughest formulation, the inverse problem consists of obtaining the Earth model for which the predicted data best fit the observed data. If an adequate forward model is used, this best model will give the best images of the Earth’s interior. Three parameters are needed for describing a perfectly elastic, isotropic, Earth: the density ρ(x) and the Lamé parameters λ(x) and μ(x), or the density ρ(x) and the P-wave and S-wave velocities α(x) and β(x). The choice of parameters is not neutral, in the sense that although theoretically equivalent, if they are not adequately chosen the numerical algorithms in the inversion can be inefficient. In the long (spatial) wavelengths of the model, adequate parameters are the P-wave and S-wave velocities, while in the short (spatial) wavelengths, P-wave impedance, S-wave impedance, and density are adequate. The problem of inversion of waveforms is highly nonlinear for the long wavelengths of the velocities, while it is reasonably linear for the short wavelengths of the impedances and density. Furthermore, this parameterization defines a highly hierarchical problem: the long wavelengths of the P-wave velocity and short wavelengths of the P-wave impedance are much more important parameters than their counterparts for S-waves (in terms of interpreting observed amplitudes), and the latter are much more important than the density. This suggests solving the general inverse problem (which must involve all the parameters) by first optimizing for the P-wave velocity and impedance, then optimizing for the S-wave velocity and impedance, and finally optimizing for density. The first part of the problem of obtaining the long wavelengths of the P-wave velocity and the short wavelengths of the P-wave impedance is similar to the problem solved by present industrial practice (for accurate data interpretation through velocity analysis and “prestack migration”). In fact, the method proposed here produces (as a byproduct) a generalization to the elastic case of the equations of “prestack acoustic migration.” Once an adequate model of the long wavelengths of the P-wave velocity and of the short wavelengths of the P-wave impedance has been obtained, the data residuals should essentially contain information on S-waves (essentially P-S and S-P converted waves). Once the corresponding model of S-wave velocity (long wavelengths) and S-wave impedance (short wavelengths) has been obtained, and if the remaining residuals still contain information, an optimization for density should be performed (the short wavelengths of impedances do not give independent information on density and velocity independently). Because the problem is nonlinear, the whole process should be iterated to convergence; however, the information from each parameter should be independent enough for an interesting first solution.

Shear‐wave velocity and density estimation from PS-wave AVO analysis: Application to an OBS dataset from the North Sea

Geophysics ◽  
2000 ◽  
Vol 65 (5) ◽  
pp. 1446-1454 ◽  
Author(s):  
Side Jin ◽  
G. Cambois ◽  
C. Vuillermoz
Keyword(s):  
Wave Velocity ◽  
North Sea ◽  
Random Noise ◽  
P Wave ◽  
S Wave ◽  
Data Set ◽  
Avo Analysis ◽  
The North ◽  
Avo Inversion ◽  
The North Sea

S-wave velocity and density information is crucial for hydrocarbon detection, because they help in the discrimination of pore filling fluids. Unfortunately, these two parameters cannot be accurately resolved from conventional P-wave marine data. Recent developments in ocean‐bottom seismic (OBS) technology make it possible to acquire high quality S-wave data in marine environments. The use of (S)-waves for amplitude variation with offset (AVO) analysis can give better estimates of S-wave velocity and density contrasts. Like P-wave AVO, S-wave AVO is sensitive to various types of noise. We investigate numerically and analytically the sensitivity of AVO inversion to random noise and errors in angles of incidence. Synthetic examples show that random noise and angle errors can strongly bias the parameter estimation. The use of singular value decomposition offers a simple stabilization scheme to solve for the elastic parameters. The AVO inversion is applied to an OBS data set from the North Sea. Special prestack processing techniques are required for the success of S-wave AVO inversion. The derived S-wave velocity and density contrasts help in detecting the fluid contacts and delineating the extent of the reservoir sand.

Shallow seismic reflection study of a glaciated valley

Geophysics ◽  
1998 ◽  
Vol 63 (4) ◽  
pp. 1395-1407 ◽  
Author(s):  
Frank Büker ◽  
Alan G. Green ◽  
Heinrich Horstmeyer
Keyword(s):  
Seismic Reflection ◽  
High Amplitude ◽  
Data Sets ◽  
Seismic Section ◽  
Data Set ◽  
Seismic Reflection Data ◽  
Northern Switzerland ◽  
Reflection Data ◽  
Shallow Seismic ◽  
Glaciated Valley

Shallow seismic reflection data were recorded along two long (>1.6 km) intersecting profiles in the glaciated Suhre Valley of northern Switzerland. Appropriate choice of source and receiver parameters resulted in a high‐fold (36–48) data set with common midpoints every 1.25 m. As for many shallow seismic reflection data sets, upper portions of the shot gathers were contaminated with high‐amplitude, source‐generated noise (e.g., direct, refracted, guided, surface, and airwaves). Spectral balancing was effective in significantly increasing the strength of the reflected signals relative to the source‐generated noise, and application of carefully selected top mutes ensured guided phases were not misprocessed and misinterpreted as reflections. Resultant processed sections were characterized by distributions of distinct seismic reflection patterns or facies that were bounded by quasi‐continuous reflection zones. The uppermost reflection zone at 20 to 50 ms (∼15 to ∼40 m depth) originated from a boundary between glaciolacustrine clays/silts and underlying glacial sands/gravels (till) deposits. Of particular importance was the discovery that the deepest part of the valley floor appeared on the seismic section at traveltimes >180 ms (∼200 m), approximately twice as deep as expected. Constrained by information from boreholes adjacent to the profiles, the various seismic units were interpreted in terms of unconsolidated glacial, glaciofluvial, and glaciolacustrine sediments deposited during two principal phases of glaciation (Riss at >100 000 and Würm at ∼18 000 years before present).

The 1998 Valhall microseismic data set: An integrated study of relocated sources, seismic multiplets, and S-wave splitting

Geophysics ◽  
2009 ◽  
Vol 74 (5) ◽  
pp. B183-B195 ◽  
Author(s):  
K. De Meersman ◽  
J.-M. Kendall ◽  
M. van der Baan
Keyword(s):  
Seismic Anisotropy ◽  
Amplitude Ratio ◽  
Temporal Variations ◽  
Oil Field ◽  
P Wave ◽  
Wave Form ◽  
S Wave ◽  
Data Set ◽  
Wave Splitting ◽  
Source Mechanisms

We relocate 303 microseismic events recorded in 1998 by sensors in a single borehole in the North Sea Valhall oil field. A semiautomated array analysis method repicks the P- and S-wave arrival times and P-wave polarizations, which are needed to locate these events. The relocated sources are confined predominantly to a [Formula: see text]-thick zone just above the reservoir, and location uncertainties are half those of previous efforts. Multiplet analysis identifies 40 multiplet groups, which include 208 of the 303 events. The largest group contains 24 events, and five groups contain 10 or more events. Within each multiplet group, we further improve arrival-time picking through crosscorrelation, which enhances the relative accuracy of the relocated events and reveals that more than 99% of the seismic activity lies spatially in three distinct clusters. The spatial distribution of events and wave-form similarities reveal two faultlike structures that match well with north-northwest–south-southeast-trending fault planes interpreted from 3D surface seismic data. Most waveform differences between multiplet groups located on these faults can be attributed to S-wave phase content and polarity or P-to-S amplitude ratio. The range in P-to-S amplitude ratios observed on the faults is explained best in terms of varying source mechanisms. We also find a correlation between multiplet groups and temporal variations in seismic anisotropy, as revealed by S-wave splitting analysis. We explain these findings in the context of a cyclic recharge and dissipation of cap-rock stresses in response to production-driven compaction of the underlying oil reservoir. The cyclic nature of this mechanism drives the short-term variations in seismic anisotropy and the reactivation of microseismic source mechanisms over time.

Migration with reduced artifacts from internal multiple reflections

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. A25-A29
Author(s):  
Lele Zhang
Keyword(s):  
Seismic Reflection ◽  
Computational Cost ◽  
Data Sets ◽  
Square Root ◽  
Multiple Reflections ◽  
Data Set ◽  
Seismic Reflection Data ◽  
Reflection Data ◽  
Recent Developments ◽  
Multiple Elimination

Migration of seismic reflection data leads to artifacts due to the presence of internal multiple reflections. Recent developments have shown that these artifacts can be avoided using Marchenko redatuming or Marchenko multiple elimination. These are powerful concepts, but their implementation comes at a considerable computational cost. We have derived a scheme to image the subsurface of the medium with significantly reduced computational cost and artifacts. This scheme is based on the projected Marchenko equations. The measured reflection response is required as input, and a data set with primary reflections and nonphysical primary reflections is created. Original and retrieved data sets are migrated, and the migration images are multiplied with each other, after which the square root is taken to give the artifact-reduced image. We showed the underlying theory and introduced the effectiveness of this scheme with a 2D numerical example.

Direct vector-field method to obtain angle-domain common-image gathers from isotropic acoustic and elastic reverse time migration

Geophysics ◽  
2011 ◽  
Vol 76 (5) ◽  
pp. WB135-WB149 ◽  
Author(s):  
Qunshan Zhang ◽  
George A. McMechan
Keyword(s):  
Direct Method ◽  
Incident Angle ◽  
Field Method ◽  
Propagation Direction ◽  
P Wave ◽  
Common Source ◽  
Spatial Gradient ◽  
Reverse Time ◽  
S Wave ◽  
Time Migration

We have developed an alternative (new) method to produce common-image gathers in the incident-angle domain by calculating wavenumbers directly from the P-wave polarization rather than using the dominant wavenumber as the normal to the source wavefront. In isotropic acoustic media, the wave propagation direction can be directly calculated as the spatial gradient direction of the acoustic wavefield, which is parallel to the wavenumber direction (the normal to the wavefront). Instantaneous wavenumber, obtained via a novel Hilbert transform approach, is used to calculate the local normal to the reflectors in the migrated image. The local incident angle is produced as the difference between the propagation direction and the normal to the reflector. By reordering the migrated images (over all common-source gathers) with incident angle, common-image gathers are produced in the incident-angle domain. Instantaneous wavenumber takes the place of the normal to the reflector in the migrated image. P- and S-wave separations allow both PP and PS common-image gathers to be calculated in the angle domain. Unlike the space-shift image condition for calculating the common-image gather in angle domain, we use the crosscorrelation image condition, which is substantially more efficient. This is a direct method, and is less dependent on the data quality than the space-shift method. The concepts were successfully implemented and tested with 2D synthetic acoustic and elastic examples, including a complicated (Marmousi2) model that illustrates effects of multipathing in angle-domain common-image gathers.

A multioffset, three‐component VSP study in the Sudbury Basin

Geophysics ◽  
1995 ◽  
Vol 60 (2) ◽  
pp. 341-353 ◽  
Author(s):  
Xiao‐Gui Miao ◽  
Wooil M. Moon ◽  
B. Milkereit
Keyword(s):  
Data Processing ◽  
Seismic Reflection ◽  
Velocity Structure ◽  
Least Square ◽  
Seismic Reflection Data ◽  
S Waves ◽  
Velocity Models ◽  
Reflection Data ◽  
Wavefield Separation ◽  
Vsp Data

A multioffset, three‐component vertical seismic profiling (VSP) experiment was carried out in the Sudbury Basin, Ontario, as a part of the LITHOPROBE Sudbury Transect. The main objectives were determination of the shallow velocity structure in the middle of the Sudbury Basin, development of an effective VSP data processing flow, correlation of the VSP survey results with the surface seismic reflection data, and demonstration of the usefulness of the VSP method in a crystalline rock environment. The VSP data processing steps included rotation of the horizontal component data, traveltime inversion for velocity analysis, Radon transform for wavefield separation, and preliminary analysis of shear‐wave data. After wavefield separation, the flattened upgoing wavefields for both P‐waves and S‐waves display consistent reflection events from three depth levels. The VSP-CDP transformed section and corridor stacked section correlate well with the high‐resolution surface reflection data. In addition to obtaining realistic velocity models for both P‐ and S‐waves through least‐square inversion and synthetic seismic modeling for the Chelmsford area, the VSP experiment provided an independent estimation for the reflector dip using three component hodogram analysis, which indicates that the dip of the contact between the Chelmsford and Onwatin formations, at an approximate depth of 380 m in the Chelmsford borehole, is approximately 10.5° southeast. This study demonstrates that multioffset, three‐component VSP experiments can provide important constraints and auxiliary information for shallow crustal seismic studies in crystalline terrain. Thus, the VSP technique bridges the gap between the surface seismic‐reflection technique and well‐log surveys.

Low‐cost geophysical investigations of a paleochannel aquifer in the Eastern Goldfields, Western Australia

Geophysics ◽  
2002 ◽  
Vol 67 (3) ◽  
pp. 690-700 ◽  
Author(s):  
Josef Holzschuh
Keyword(s):  
Water Table ◽  
Western Australia ◽  
Seismic Reflection ◽  
Wave Reflection ◽  
Gravity Data ◽  
P Wave ◽  
Gravity Modeling ◽  
S Wave ◽  
Sand And Gravel ◽  
Gravel Aquifer

Compressional (P) wave and shear (S) wave seismic reflection techniques were used to delineate the sand and gravel aquifer within a highly saline clay‐filled paleochannel in the Eastern Goldfields of Western Australia. The seismic refraction and gravity methods were also used to investigate the paleochannel. The unsaturated loose fine‐grained sand up to 10 m in depth at the surface is a major factor in degrading subsurface imaging. The seismic processing needed to be precise, with accurate static corrections and normal moveout corrections. Deconvolution enhanced the aquifer and other paleochannel reflectors. P‐wave reflection and refraction layer depths had good correlation and showed a total of six boundaries: (1) water table, (2) change in velocity (compaction) in the paleochannel sediments, (3) sand and gravel aquifer, (4) red‐brown saprolite and green saprolite boundary, (5) weathered bedrock, and (6) unweathered bedrock. P‐wave explosive and hammer sources were found to have similar signal characteristics, and the aquifer and bedrock were both imaged using the hammer source. The deep shots below the water table have the most broadband frequency response for reflections, but stacking clear reflections was difficult. The S‐wave reflection results showed high lateral and vertical resolution of the basal saprolite clay, the sand and gravel aquifer, and very shallow clays above the aquifer. The S‐wave reflection stacking velocities were 10–20% of the P‐waves, increasing the resolution of the S‐wave section. The gravity data were modelled to fit the known drilling and P‐wave seismic reflection depths. The refraction results did not identify the top of bedrock, so refraction depths were not used for the gravity modeling in this highly weathered environment. The final gravity model mapped the bedrock topography beyond the lateral extent of the seismic and drilling data.

Near-surface scattering phenomena and implications for tunnel detection

2015 ◽  
Vol 3 (1) ◽  
pp. SF43-SF54 ◽  
Author(s):  
Shelby L. Peterie ◽  
Richard D. Miller
Keyword(s):  
Synthetic Data ◽  
P Wave ◽  
S Wave ◽  
Seismic Line ◽  
Data Set ◽  
Near Surface ◽  
Tunnel Detection ◽  
Impedance Contrast ◽  
Diffraction Imaging ◽  
Imaging Algorithms

Tunnel locations are accurately interpreted from diffraction sections of focused mode converted P- to S-wave diffractions from a perpendicular tunnel and P-wave diffractions from a nonperpendicular (oblique) tunnel. Near-surface tunnels are ideal candidates for diffraction imaging due to their small size relative to the seismic wavelength and large acoustic impedance contrast at the tunnel interface. Diffraction imaging algorithms generally assume that the velocities of the primary wave and the diffracted wave are approximately equal, and that the diffraction apex is recorded directly above the scatterpoint. Scattering phenomena from shallow tunnels with kinematic properties that violate these assumptions were observed in one field data set and one synthetic data set. We developed the traveltime equations for mode-converted and oblique diffractions and demonstrated a diffraction imaging algorithm designed for the roll-along style of acquisition. Potential processing and interpretation pitfalls specific to these diffraction types were identified. Based on our observations, recommendations were made to recognize and image mode-converted and oblique diffractions and accurately interpret tunnel depth, horizontal location, and azimuth with respect to the seismic line.

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