Analysis of conventional and converted mode reflections at Putah sink, California using three‐component data

Geophysics ◽  
1990 ◽  
Vol 55 (6) ◽  
pp. 646-659 ◽  
Author(s):  
C. Frasier ◽  
D. Winterstein
Keyword(s):  
Time Window ◽  
Structural Features ◽  
Low Noise ◽  
P Wave ◽  
Bright Spot ◽  
High Signal ◽  
Converted Wave ◽  
Gas Field ◽  
Seismic Line ◽  
S Waves

In 1980 Chevron recorded a three‐component seismic line using vertical (V) and transverse (T) motion vibrators over the Putah sink gas field near Davis, California. The purpose was to record the total vector motion of the various reflection types excited by the two sources, with emphasis on converted P‐S reflections. Analysis of the conventional reflection data agreed with results from the Conoco Shear Wave Group Shoot of 1977–1978. For example, the P‐P wave section had gas‐sand bright spots which were absent in the S‐S wave section. Shot profiles from the V vibrators showed strong P‐S converted wave events on the horizontal radial component (R) as expected. To our surprise, shot records from the T vibrators showed S‐P converted wave events on the V component, with low amplitudes but high signal‐to‐noise (S/N) ratios. These S‐P events were likely products of split S‐waves generated in anisotropic subsurface media. Components of these downgoing waves in the plane of incidence were converted to P‐waves on reflection and arrived at receivers in a low‐noise time window ahead of the S‐S waves. The two types of converted waves (P‐S and S‐P) were first stacked by common midpoint (CMP). The unexpected S‐P section was lower in true amplitude but much higher in S/N ratio than the P‐S section. The Winters gas‐sand bright spot was missing on the converted wave sections, mimicking the S‐S reflectivity as expected. CRP gathers were formed by rebinning data by a simple ray‐tracing formula based on the asymmetry of raypaths. CRP stacking improved P‐S and S‐P event resolution relative to CMP stacking and laterally aligned structural features with their counterparts on P and S sections. Thus, the unexpected S‐P data provided us with an extra check for our converted wave data processing.

Imaging beneath a high‐velocity layer using converted waves

Geophysics ◽  
1992 ◽  
Vol 57 (11) ◽  
pp. 1444-1452 ◽  
Author(s):  
Guy W. Purnell
Keyword(s):  
High Velocity ◽  
Energy Partitioning ◽  
P Wave ◽  
Converted Wave ◽  
P Waves ◽  
Lower Velocity ◽  
S Waves ◽  
High Velocity Layer ◽  
The Waves ◽  
Velocity Layer

High‐velocity layers (HVLs) often hinder seismic imaging of deeper reflectors using conventional techniques. A major factor is often the unusual energy partitioning of waves incident at an HVL boundary from lower‐velocity material. Using elastic physical modeling, I demonstrate that one effect of this factor is to limit the range of dips beneath an HVL that can be imaged using unconverted P‐wave arrivals. At the same time, however, partitioning may also result in P‐waves outside the HVL coupling efficiently with S‐waves inside. By exploiting some of the waves that convert upon transmission into and/or out of the physical‐model HVL, I am able to image a much broader range of underlying dips. This is accomplished by acoustic migration tailored (via the migration velocities used) for selected families of converted‐wave arrivals.

MULTI-COMPONENT SEISMIC—THE TOOL FOR ALL REASONS

2002 ◽  
Vol 42 (1) ◽  
pp. 587
Author(s):  
F.L. Engelmark
Keyword(s):  
Fractured Reservoirs ◽  
Time Lapse ◽  
P Wave ◽  
Converted Wave ◽  
S Waves ◽  
The North ◽  
Impedance Contrast ◽  
Seismic Sensors ◽  
Wave Imaging ◽  
Wave Modes

Marine multi-component seismic, known as 4C, is an emerging seismic technology providing improved and sometimes unique solutions to many common problems. In the marine environment the seismic sensors have to be placed on the sea-floor to capture converted or shear wave modes that cannot propagate through liquid media. Although this means increased acquisition cost, the improved information content makes it money well spent to better image and characterise reservoirs.The 4C solutions fall into two major groups of five. First there are the imaging solutions:Improved standard P-wave imaging. Improved converted wave (P-S) resolution in the shallow sediments. Converted wave imaging through gas clouds. Converted wave imaging of low impedance contrast reservoirs. Improved sub-salt and sub-basalt imaging with converted waves. The second group consists of the five characterisation solutions:Improved fracture characterisation by means of P-S waves. Qualitative 4D or time-lapse characterisation of fractured reservoirs with low intrinsic permeability. Improved lithology and fluid characterisation by combining the information in the two wave modes. Improved quantitative time-lapse evaluation of pressure and saturation changes. Improved characterisation of drilling hazards by combined evaluation of the two wave modes. So far the most popular 4C solutions are imaging through gas and improved P-wave imaging of Jurassic reservoirs in the North Sea, for example the Statfjord, Brent and Beryl fields. However, as the technology is developing and maturing, the characterisation solutions will probably be the most common applications of 4C in the near future.

Source characteristics of small to moderate earthquakes in the Kanto region, Japan: application of a new definition of the S-wave time window length

1996 ◽  
Vol 86 (5) ◽  
pp. 1284-1291
Author(s):  
Kazutoshi Watanabe ◽  
Haruo Sato ◽  
Shigeo Kinoshita ◽  
Masakazu Ohtake
Keyword(s):  
Wave Energy ◽  
Seismic Moment ◽  
Time Window ◽  
P Wave ◽  
Corner Frequency ◽  
Window Length ◽  
S Wave ◽  
S Waves ◽  
Source Characteristics ◽  
Kanto Region

Abstract The S wave from a local earthquake generally consists of several pulses, in contrast to a simple pulse of P wave. This results in a large uncertainty in the estimation of seismic moment and wave energy when the window length for S-wave analysis is not chosen properly. In this study, we propose a new method to define objectively an appropriate time window length of the S wave for estimation of source characteristics based on the S-wave to P-wave energy ratio for a point shear dislocation source. Analyzing waveform data of 97 local earthquakes in the Kanto region, Japan, whose magnitudes M range from 3.3 to 6.0, we obtained simple equations for predicting the time window length of the S-wave TS as a function of earthquake magnitude or pulse width of P-wave TP; we got TS ≈ 1.8 TP for the relation between TP and TS. Applying the S-wave window thus defined, we estimated seismic energy E, seismic moment M0, and corner frequency fc for both P and S waves. Regression analysis of those parameters revealed (1) our method to define TS is confirmed by the fact that the seismic moment determined from P and S waves are consistent; (2) in the range of 1014 < M0 < 1018 (N·m), M0 is almost proportional to f−3c both for P and S waves; (3) the value of E/M0 is 2.7 ∼ 4.0 × 10−5; and (4) breakdown of the scaling relation is seen at M ≦ 4.

Shear‐wave studies in glacial till

Geophysics ◽  
1998 ◽  
Vol 63 (4) ◽  
pp. 1273-1284 ◽  
Author(s):  
Bradley J. Carr ◽  
Zoltan Hajnal ◽  
Arnfinn Prugger
Keyword(s):  
Shear Wave ◽  
P Wave ◽  
Vertical Resolution ◽  
S Wave ◽  
Glacial Deposits ◽  
Seismic Line ◽  
S Waves ◽  
Additional Information ◽  
Vsp Data ◽  
Clay Percentage

Within a high‐resolution shallow reflection survey program in Saskatchewan, Canada, S-waves were produced using a single seismo‐electric blasting cap and were found to be distinguishable from surface wave phases. The local glacial deposits have average velocities of 450 m/s. [Formula: see text] ratios average 3.6 in these sequences, but they vary laterally, according to the velocity analyses done in two boreholes drilled along the seismic line. Vertical resolution for S-wave reflections are 0.75 m [in the vertical seismic profiling (VSP) data] and 1.5 m (in the CDP data). Yet, the S-wave CDP results are still better than corresponding P-wave data, which had a vertical resolution of 2.6 m. S-wave anisotropy is inferred in the glacial deposits on the basis of particle motion analysis and interpretations of S-wave splitting. However, the amount of observed splitting is small (∼2–6 ms over 5–10 m) and could go undetected for seismic surveys with larger sampling intervals. VSPs indicate that S-wave reflectivity is caused by both distinct and subtle lithologic changes (e.g., clay/sand contacts or changes in clay percentage within a particular till unit) and changes in bulk porosity. Migrated S-wave sections from line 1 and line 2 image reflections from sand layers within the tills as well as the first “bedrock” sequence (known as the Judith River Formation). Shear wave images are not only feasible in unconsolidated materials, but provide additional information about structural relationships within these till units.

Examining the processing differences between P and P-S waves in a Rocky Mountain Foothills model

2014 ◽  
Vol 54 (2) ◽  
pp. 504
Author(s):  
Sanjeev Rajput ◽  
Michael Ring
Keyword(s):  
Rocky Mountain ◽  
P Wave ◽  
S Wave ◽  
Converted Wave ◽  
Wave Source ◽  
Depth Migration ◽  
S Waves ◽  
Full Waveform ◽  
Fluid Saturation ◽  
Converted Waves

For the past two decades, most of the shear-wave (S-wave) or converted wave (P-S) acquisitions were performed with P-wave source by making the use of downgoing P-waves converting to upgoing S-waves at the mode conversion boundaries. The processing of converted waves requires studying asymmetric reflection at the conversion point, difference in geometries and conditions of source and receiver, and the partitioning of energy into orthogonally polarised components. Interpretation of P-S sections incorporates the identification of P-S waves, full waveform modeling, correlation with P-wave sections and depth migration. The main applications of P-S wave imaging are to obtain a measure of subsurface S-wave properties relating to rock type and fluid saturation (in addition to the P-wave values), imaging through gas clouds and shale diapers, and imaging interfaces with low P-wave contrast but significant S-wave changes. This study examines the major differences in processing of P and P-S wave surveys and the feasibility of identifying converted mode reflections by P-wave sources in anisotropic media. Two-dimensional synthetic seismograms for a realistic rocky mountain foothills model were studied. A Kirchhoff-based technique that includes anisotropic velocities is used for depth migration of converted waves. The results from depth imaging show that P-S section help in distinguishing amplitude associated with hydrocarbons from those caused by localised stratigraphic changes. In addition, the full waveform elastic modeling is useful in finding an appropriate balance between capturing high-quality P-wave data and P-S data challenges in a survey.

Examining the processing differences between P and P-S waves in a Rocky Mountain Foothills model

2014 ◽  
Vol 54 (2) ◽  
pp. 536
Author(s):  
Sanjeev Rajput ◽  
Michael Ring
Keyword(s):  
Rocky Mountain ◽  
P Wave ◽  
S Wave ◽  
Converted Wave ◽  
Wave Source ◽  
Depth Migration ◽  
S Waves ◽  
Full Waveform ◽  
Fluid Saturation ◽  
Converted Waves

For the past two decades, most of the shear-wave (S-wave) or converted wave (P-S) acquisitions were performed with P-wave source by making the use of downgoing P-waves converting to upgoing S-waves at the mode conversion boundaries. The processing of converted waves requires studying asymmetric reflection at the conversion point, difference in geometries and conditions of source and receiver, and the partitioning of energy into orthogonally polarised components. Interpretation of P-S sections incorporates the identification of P-S waves, full waveform modeling, correlation with P-wave sections and depth migration. The main applications of P-S wave imaging are to obtain a measure of subsurface S-wave properties relating to rock type and fluid saturation (in addition to the P-wave values), imaging through gas clouds and shale diapers, and imaging interfaces with low P-wave contrast but significant S-wave changes. This study examines the major differences in processing of P and P-S wave surveys and the feasibility of identifying converted mode reflections by P-wave sources in anisotropic media. Two-dimensional synthetic seismograms for a realistic rocky mountain foothills model were studied. A Kirchhoff-based technique that includes anisotropic velocities is used for depth migration of converted waves. The results from depth imaging show that P-S section help in distinguishing amplitude associated with hydrocarbons from those caused by localised stratigraphic changes. In addition, the full waveform elastic modeling is useful in finding an appropriate balance between capturing high-quality P-wave data and P-S data challenges in a survey.

A simple method for resolving large converted‐wave (P-SV) statics

Geophysics ◽  
1993 ◽  
Vol 58 (3) ◽  
pp. 429-433 ◽  
Author(s):  
Peter W. Cary ◽  
David W. S. Eaton
Keyword(s):  
P Wave ◽  
S Wave ◽  
Converted Wave ◽  
P Waves ◽  
Simple Method ◽  
Near Surface ◽  
S Waves ◽  
Static Solutions ◽  
Surface Fluctuations

The processing of converted‐wave (P-SV) seismic data requires certain special considerations, such as commonconversion‐point (CCP) binning techniques (Tessmer and Behle, 1988) and a modified normal moveout formula (Slotboom, 1990), that makes it different for processing conventional P-P data. However, from the processor’s perspective, the most problematic step is often the determination of residual S‐wave statics, which are commonly two to ten times greater than the P‐wave statics for the same location (Tatham and McCormack, 1991). Conventional residualstatics algorithms often produce numerous cycle skips when attempting to resolve very large statics. Unlike P‐waves, the velocity of S‐waves is virtually unaffected by near‐surface fluctuations in the water table (Figure 1). Hence, the P‐wave and S‐wave static solutions are largely unrelated to each other, so it is generally not feasible to approximate the S‐wave statics by simply scaling the known P‐wave static values (Anno, 1986).

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.

Geophysical case history of the Two Hills Colony gas field of Alberta

Geophysics ◽  
1985 ◽  
Vol 50 (7) ◽  
pp. 1061-1076 ◽  
Author(s):  
G. W. Focht ◽  
F. E. Baker
Keyword(s):  
Colony Formation ◽  
Oil And Gas ◽  
Direct Detection ◽  
Waveform Analysis ◽  
Bright Spot ◽  
Low Velocity ◽  
Gas Field ◽  
Seismic Line ◽  
Seismic Waveform ◽  
Bright Spots

Seismic waveform changes, which in their most obvious form are known as “bright spots,” have been known for some years to give direct indications of hydrocarbons. An example of successful application of waveform analysis and direct detection of gas in a shallow Lower Cretaceous formation of east‐central Alberta, Canada, is detailed. At a depth of approximately 1 800 ft, the Colony formation typically consists of only thin (10 ft) blanket sands interbedded with shale. However, in 1976, Hudson’s Bay Oil and Gas Company Ltd., encountered a 100 ft thick occurrence of channel sand (with substantial gas pay) in this formation. After some hit and miss attempts at extending the channel trend through geologic interpretation, seismic methods were applied. A seismic line over the channel well revealed a classic bright spot. Several other lines also showed bright spots in the Colony zone. The conclusions from seismic modeling are as follows. Gas within the Colony sand is seismically detectable. The relatively low velocity of the gas sand, combined with the lateral consistency of the sediments above the Colony formation, permits detection. However, the inconsistency and complexity of sediments underlying the Colony resulted in interference patterns that prevented exact quantitative analysis of gas pays. Furthermore, other geologic phenomena provided waveform changes similar to that of gas sand. Through detailed examination of the geology and evaluation of the alternative explanations of the waveform changes, successful interpretation was accomplished. Estimations of net gas pay were generally accurate within 20 percent. In some areas, very subtle anomalies in wave character representing gas pays as thin as 5 ft can now be interpreted with confidence. Several examples are given of successful detection and prediction of gas. To date (October, 1979) seismic waveform analysis has led to the drilling of 86 wells; 67 of these are commercial gas wells in the Colony formation, representing a success ratio of 78 percent. Total reserves discovered geophysically (by Hudson’s Bay Oil and Gas Co. Ltd.) to date in the Colony formation are estimated at 110 Bcf.

Data-driven, target-oriented, kinematic prediction and subtraction of multiples from pure and mode-converted multicomponent data

Geophysics ◽  
2011 ◽  
Vol 76 (6) ◽  
pp. V105-V114 ◽  
Author(s):  
Juanjuan Cao ◽  
George A. McMechan
Keyword(s):  
Time Window ◽  
P Wave ◽  
Data Driven ◽  
Propagation Path ◽  
Common Source ◽  
Converted Wave ◽  
Before And After ◽  
Explicit Consideration ◽  
Data Adaptive ◽  
Polarity Correction

Most multiple removal algorithms focus on multiples of primary P-wave reflections; removal of multiples of converted reflections have not received comparable attention, so explicit consideration is overdue. A target-oriented algorithm predicts converted wave multiples by coupling apparent slownesses, and then subtracts them from elastic common-source data in a data-adaptive window. Prediction is based on matching apparent slownesses in common-source and common-receiver gathers at all source and receiver locations along the propagation path. Predictions use only offset and traveltime, of the primary pure and converted waves that produce the multiples, picked from common-source gathers, and the slownesses calculated from them. Higher-order multiples can be predicted by repeating this process to match slownesses at a sequence of alternating source and receiver locations in turn. Primary reflections (e.g., SS, SP, and PS) that are considered to be noise, can also be subtracted. The predictions are data-driven and require no velocities, angles, reflector orientations or free-surface topography. Any single component (usually vertical) may be used to identify and pick the traveltimes. The resulting predictions are also valid for all other components. The subtraction involves flattening the predicted time trajectory of the multiple, followed by trace averaging to estimate the local wavelet at each location in a moving trace and time window that contains the wavelet of the multiple. The subtraction is data-adaptive, and implicitly involves amplitude and phase information, so separate or prior estimation of the source time or directivity functions is not required. Two synthetic examples showed that the slowness-based algorithm is successful in predicting and reducing converted wave multiples in an elastic medium. Migrated P-wave subsurface images are generated before and after multiple removal to evaluate the performance. Polarity correction of the horizontal component (either before or after subtraction) ensures coherent stacking.

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