Quick
Search: 
 
advanced search
 GSW Home    GeoRef Home    My GSW Alerts    Contact GSW    About GSW    Journals List    Help 
The Leading Edge Signup for GSW Email News
JOURNAL HOME HELP CONTACT PUBLISHER SUBSCRIBE ARCHIVE SEARCH TABLE OF CONTENTS

The Leading Edge; 2005; v. 24; no. Supplement; p. S46-S71; DOI: 10.1190/1.2112392
© 2005 Society of Exploration Geophysicists
This Article
Right arrow Abstract
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Dragoset, B.
Right arrow Search for Related Content
GeoRef
Right arrow GeoRef Citation

A historical reflection on reflections

Bill Dragoset

WesternGeco, Houston, USA



View larger version (38K):

[in a new window]
 
Figure 1. Schematic diagram of the seismograph used to detect and record seismic reflections in the 1921 Vines Branch experiment. "TRANS" refers to amplifier circuits, and the seismic sensors are labeled "microphones" (Schriever, GEOPHYSICS 1952).

 


View larger version (32K):

[in a new window]
 
Figure 2. Data from three of the shots recorded during the Vines Branch experiment. The tuning fork signal appears at the top of each shot record. Below that are signals detected by the two sensors shown in Figure 1. Each signal recording is called a seismic trace.

 


View larger version (19K):

[in a new window]
 
Figure 3. Sketch of the 1921 Vines Branch experiment. (a) The very first seismic reflection profile identified a dipping reflecting boundary between two rock layers, the Sylvan shale and the Viola limestone. (b) A plan view of the Vines Branch experiment shows the positions of the shots and receivers and an overhead view of the reflection raypath for the fifth shot in the survey.

 


View larger version (170K):

[in a new window]
 
Figure 4. A Gulf of Mexico marine seismic profile from the late 1990s. This vertical profile was extracted from a 3D volume migrated with a 3D prestack wave-equation-based depth migration algorithm. Compare the imaging here to that in Figure 30 (WesternGeco).

 


View larger version (61K):

[in a new window]
 
Box 1. Seismic wave propagation

P- and S-waves are represented by the dark blue and dark pink shading, respectively. The horizontal black line represents the site of an acoustic impedance change (O. Barkved, et al., Schlumberger Oilfield Review 2004).

There are several modes of seismic wave propagation in solid materials. Pressure waves (also called compressional waves, acoustic waves, and P-waves) are characterized by particle motion in the material that is in the same direction as the wave travels. P-waves in fluids such as air and water are also called sound waves. Shear waves (S-waves), on the other hand, have particle motion that is transverse to the propagation direction. S-waves travel at a velocity (VS) that is about half the velocity (VP) of P-waves. The acoustic impedance of a material is defined as the product of its density and P-wave velocity. Because S-waves have different velocities than P-waves, shear-wave impedance is different than acoustic impedance.

Several phenomena occur when a P-wave encounters an impedance contrast. As shown in the diagram, some of the seismic energy is reflected as a P-wave. This is the wave detected in most reflection seismology experiments. Another portion of the energy is transmitted as a P-wave through the impedance discontinuity, but travels onwards in a different direction. We say that this wave has been refracted. Finally, if an incident P-wave travels in a direction that is not normal to the impedance boundary, then a final portion of the initial energy is converted into reflected and refracted S-waves.

The angle between the direction of travel of a reflected P-wave and the normal to the reflecting boundary is the same as the angle between the incident P-wave and the normal. That is not the case for a converted S-wave reflection.

 


View larger version (10K):

[in a new window]
 
Box 2. Dynamic range

Effects of absorption on a seismic impulse. Absorption changes the shape of an ideal seismic shot pulse as distance from the shot increases. The sketches represent particle displacement and particle velocity for a P-wave (After Ricker, GEOPHYSICS 1953).

The dynamic range of a seismic recording system is the ratio of the largest to smallest signals that it can faithfully detect and record. Seismic reflections have a wide range of amplitudes. The large-amplitude part is not hard to understand—anything that begins with a dynamite blast is obviously pretty loud—but what about the small-amplitude part? There are three phenomena that attenuate seismic reflections: spherical spreading, transmission loss, and intrinsic absorption. Together these effects mean that a seismic recording system needs a dynamic range of 100 decibels (dB) or more.

Spherical spreading. The seismic wave from a localized impulsive source spreads out equally in all directions. After it has traveled some distance, r, the energy in the original impulse is spread out over a spherical area of radius r. Since energy is conserved and the area of a sphere is proportional to r2, the energy per unit area must be proportional to 1/r2. The amplitude of a seismic wave is proportional to the square root of its energy. Thus, the amplitude of a seismic reflection is inversely proportional to the distance it has traveled.

Transmission loss. As explained in Box 1, a pressure wave that encounters an impedance contrast has its incident energy partitioned into several events. Only one of these is a P-wave that continues onward. Since the signal from a deep reflector may traverse many impedance contrasts on its way down to the reflector and back up to the surface, even a small energy loss per contrast can quickly add up to a significant effect.

Intrinsic absorption. As a seismic wave travels through a material, the particles that make up the material vibrate, generating heat. The energy that goes into that heat—intrinsic absorption—is supplied by the seismic wave. Intrinsic absorption attenuates higher frequencies more rapidly than lower frequencies, thereby changing the shape of the seismic pulse. The rate of intrinsic absorption varies greatly from one type of material to another.

 


View larger version (122K):

[in a new window]
 
Box 3. Noise in seismic data

A single-sensor seismic land record without any filtering applied. As done here, seismic records are usually displayed so that the vertical axis is time and the horizontal axis is offset (source-to-receiver distance). Facility and vehicle noise are ambient noises. The other noises are caused by the shot. Air blast noise is random. The other noises are coherent. The noise identified as surface waves is known as ground roll. Compare to Figure 18 (WesternGeco).

Noise in seismic data is ubiquitous. It comes from many different sources and in several categories. The figure identifies some noises that occur commonly in land shot records.

Ambient noise is always present, even when a shot has not been fired. There are two subcategories of ambient noise. Environmental noise, such as wind and traffic noise, is present independently of the seismic experiment. Intrinsic noise, such as the electronic noise in an amplifier or the swell noise in a seismic streamer, is inherently part of a data acquisition system. Shot-generated noise refers to the part of a seismic signal, such as multiple reverberations and ground roll, that are considered undesirable because they can obscure reflections. Unlike ambient noise, this type of noise is present only when a shot has been fired.

Noise can be categorized in another way. Noise that is completely unpredictable from one time or position to another is called random or incoherent noise. Noise that has a recognizable spatial or temporal pattern is called coherent noise.

The quality of a seismic signal is often expressed by its signal-to-noise ratio (SNR), which is the ratio of the amplitude of the desirable reflection signal to that of the noise. The amplitude of ambient noise typically does not vary with time in a seismic shot record, while the amplitude of seismic reflections decreases rapidly with time (Box 2). Thus, a seismic shot record has a much higher SNR at early times than it does at later times. Often seismic reflections late in a record are invisible among the noise.

 


View larger version (11K):

[in a new window]
 
Box 4. Seismic wavelets

Signatures for two types of marine seismic sources. The wavelets in this figure are about 350 ms long. (a) A signature produced by an underwater dynamite blast. (b) A signature of a tuned air-gun array. The large positive peak is a ghost reflection caused by sound that reflected from the ocean surface (Western Geophysical).

A seismic wavelet is the signal that would appear in a seismic trace if there was only one reflecting interface. It has several components: The source wavelet (also called the source signature) is the shape of the pressure pulse created by the source. That wavelet is modified by near-surface effects and the response of the receiver and recording equipment to produce the acquisition wavelet. Intrinsic absorption (Box 2) filters the acquisition wavelet in a time-varying manner to produce the seismic wavelet.

For most applications the ideal seismic wavelet is characterized as having a broad, flat spectrum in the frequency domain. In the time domain this means that the wavelet is a single impulse, or spike, which produces seismic profiles with the best possible resolution. In practice, intrinsic absorption limits the usefulness of high frequencies because they are attenuated rapidly in the subsurface. The usefulness of very low frequencies is also limited because noise tends to dominate at that end of the spectrum and near-surface effects, called ghost reflections, attenuate those frequencies. Thus, a typical bandwidth for a seismic wavelet is about 5–80 Hz for shallow reflections, and about to 5–20 Hz for deep reflections.

Source signatures have a major influence on the seismic wavelet. In marine acquisition a tuned air-gun array is considered a superior source to a dynamite charge because its signature is much closer to an ideal impulse.

 


View larger version (24K):

[in a new window]
 
Figure 5. Vibroseis correlation. The reference signal represents the shape of a pressure wave sent into the ground by a vibrator. The recorded composite signal contains three seismic events. They cannot be identified readily because each one is stretched out within the composite signal over a time span equal to the duration of the reference signal. After the correlation process (far right), the three events become visible, as if the vibrator had been an impulsive source (Crawford, et al., GEOPHYSICS 1960).

 


View larger version (192K):

[in a new window]
 
Figure 6. A comparison between records from an early vibrator and dynamite shots. Both data sets were acquired in the same area of southeast Montana. (a) The correlated vibrator records. (b) The dynamite shot records. Note the improved SNR in the vibrator records indicated by the clearly visible reflections annotated A, B, and C (Conoco).

 


View larger version (59K):

[in a new window]
 
Figure 7. The small white vehicle is a "swinging weight vibrator" of the late 1950s and early 1960s. The large vehicle on the right is a buggy-mounted, hydraulically-driven vibrator used in the late 1970s and early 1980s. When sweeping, the metal vibrating plate seen between the buggy's tires was lowered to the ground and held in place by the weight of the vehicle (Conoco).

 


View larger version (51K):

[in a new window]
 
Figure 8. PAR model 6600 air gun. The left-hand section of the gun is a compressed air reservoir. The small, light-colored rectangles in the center portion of the gun are ports through which the air escapes when the gun is fired. A compressed air hose and a cable that provides the firing signal are connected at the right (Courtesy Bolt Technologies).

 


View larger version (31K):

[in a new window]
 
Figure 9. Tuned air-gun array concept. (a) Signatures from individual airguns have bubble periods that depend on the gun volumes (listed in cubic inches on the left). (b) If the six guns are placed in an array and fired simultaneously, they produce a signature in which the bubble pulses are suppressed. (Dragoset, TLE 2000).

 


View larger version (25K):

[in a new window]
 
Figure 10. Plan view of tuned air-gun array. The numbers below the gun stations (green circles) are gun volumes (in3). The 155x3 notation indicates three 155-in3 guns that are so close together that their air bubbles coalesce after the guns fire. Such so-called "cluster guns" produce sound more efficiently than does a single large gun (Dragoset, TLE 2000).

 


View larger version (87K):

[in a new window]
 
Figure 11. Three vintages of geophones. W.C. Edwards is holding a geophone used in 1965. Next to him is a geophone from the 1930s. A clean-room technician inspects a microchip that contains the sensing element of a MEMS geophone from the 2000s. A cutaway view of an electromagnetic geophone shows the spring-mounted coil (GSI; Input/Output.)

 


View larger version (16K):

[in a new window]
 
Figure 12. Conceptual drawing of an acceleration-canceling hydrophone. The yellow shapes represent piezoelectric crystals. The orange shape is a support structure. The blue lines are electrical connections. (a) Acceleration bends both crystals in the same direction. No signal is generated because the voltages cancel. (b) Pressure bends the two crystals in opposite directions. A signal is produced because the voltages no longer cancel.

 


View larger version (79K):

[in a new window]
 
Figure 13. An early digital streamer from the 1980s. (a) A closeup view of an LRS-16 KILOSEIS streamer wound on a cable reel. A digital electronics module is visible in the center of the picture. (b) A disassembled LRS-16 electronics module showing its three circuit boards. Each module digitized the signals from 12 geophone arrays and transmitted them to the recording system on the seismic ship. When assembled, the electronics module was about 3 inches in diameter (Western Geophysical).

 


View larger version (19K):

[in a new window]
 
Figure 14. Common reflection point acquisition. The vertical dashed lines represent the locations of two reflection points during a sequence of shots. After each shot, the shot location (triangle) moves one unit to the left and the receiver spread (circles) moves one unit to the right. After 12 shots, the two reflection points as well as the area between them have each been recorded 12 times. At each reflection point, each of the 12 recordings is at a different source-to-receiver offset. (For clarity, the shots are shown offset from one another in the vertical direction. In practice, all shots and receivers are positioned along a single line on the surface.) (Mayne, GEOPHYSICS 1962).

 


View larger version (90K):

[in a new window]
 
Figure 15. A seismic ship shooting a 3D marine survey in 1991. The four streamers under tow create the wake patterns seen at the edges of the photo. Immediately to either side of the ship's wake is an air-gun array. Each array contains four strings of air guns. With the two sources firing in an alternating pattern, eight lines of seismic data were acquired at once (Western Geophysical).

 


View larger version (105K):

[in a new window]
 
Figure 16. The final product from a 3D seismic survey is a 3D image of the subsurface. Using interpretive workstation software, image planes in any direction through the volume can be displayed (shown at stockholder's meeting of Texas Instruments in 1984).

 


View larger version (60K):

[in a new window]
 
Figure 17. How time and spatial sampling intervals affect seismic data. These profiles from offshore Louisiana were recorded in the early 1980s with a 480-channel digital streamer. (a) Processing single-channel data at a 1-ms sampling interval produced a high-resolution result with traces spaced every 3 m. (b) The same data that produced the result in (a) were reprocessed at a 4-ms sampling interval with the single-channel data summed to simulate 60-m long hydrophone arrays found in conventional streamers of that time (Western Geophysical).

 


View larger version (146K):

[in a new window]
 
Figure 18. The same record as shown in Box 3 after noise was removed by the digital group forming process. Reflections appear after the noise removal (Shabrawi, et al., First Break 2005).

 


View larger version (74K):

[in a new window]
 
Figure 19. Comparison between images from single-sensor and conventional seismic data acquisition. (a) The final image from single-sensor acquisition has higher fidelity than that of the conventional data. (b) Image from conventional acquisition in the same area as shown in (a) (WesternGeco).

 


View larger version (99K):

[in a new window]
 
Figure 20. Control panel from a subunit of a 1950s seismic data recording system. The subunit contained an analog filter and an AGC amplifier that were applied to the signal from a geophone array prior to recording it. The entire recording system contained 24 identical control panels of this type (Conoco).

 


View larger version (172K):

[in a new window]
 
Figure 21. In the mid-1950s Carroll Murff uses a mechanical drafting tool called the "Gaebe Plotter" to produce a migrated seismic profile (Conoco).

 


View larger version (144K):

[in a new window]
 
Figure 22. The TIAC 827 digital computer installed in GSI's Calgary seismic data processing center in 1964 (Texas Instruments).

 


View larger version (116K):

[in a new window]
 
Figure 23. A small portion of a 2005 seismic data processing computer system. The entire massively-parallel system contains tens of thousands of linked CPU nodes and has a compute capacity of 60 teraflops (WesternGeco).

 


View larger version (120K):

[in a new window]
 
Figure 24. CMP stacked profiles without (a) and with (b) deconvolution applied to the prestack data. Note how deconvolution sharpens the reflection at about 1.3 s and the dipping reflections below 2.0 s on the left (Yilmaz, Seismic Data Analysis).

 


View larger version (94K):

[in a new window]
 
Figure 25. (a) A CMP stacked profile without application of refraction or residual statics corrections; (b) the same profile as in (a), but with refraction statics corrections applied prior to the stack. Note removal of the spurious structural high seen in (a); (c) the same profile as in (a), but with both refraction and residual statics corrections applied prior to the stack. Note the improved continuity of the reflection events compared to those in (b) (Yilmaz, Seismic Data Analysis).

 


View larger version (119K):

[in a new window]
 
Figure 26. A CMP gather (left) and its velocity spectrum obtained by coherence analysis. The small dark areas outlined in yellow correspond to velocity values (horizontal axis) that produce moveout curves matching those seen in the gather (Yilmaz, Seismic Data Analysis).

 


View larger version (25K):

[in a new window]
 
Figure 27. Primary and multiple reflections. The blue-green area represents the water layer. The red and yellow dots indicate the positions of seismic sources and receivers, respectively. The white lines are raypaths of the reflections. For the sake of simplicity in the figure, the raypaths do not refract as they cross reflecting horizons. (a) A primary reflection; (b) a first-order free-surface multiple; (c) a second-order free-surface multiple; (d) a first-order internal multiple; (e) a second-order internal multiple; (f) hybrid event 1–3 is a free-surface multiple that includes an internal multiple, subevent 1–2.

 


View larger version (174K):

[in a new window]
 
Figure 28. Three CMP gathers with strong multiple reflections before and after NMO correction. (a) Before NMO correction, both primary and multiple reflections have hyperbolic moveout trajectories. (b) NMO correction with the velocity of the primary reflections flattens the primary events. When the traces are stacked, the primary reflections will add together coherently. Because the multiple reflections still have moveout, they will not stack coherently. The success of CMP stacking in attenuating multiples depends on the degree of difference between the velocities of primaries and multiples (after Yilmaz, Seismic Data Analysis).

 


View larger version (150K):

[in a new window]
 
Figure 29. Attenuating multiples using the Radon transform. (a) A CMP gather from a deep-water area. In the Radon domain (not shown) the primary and multiple reflections are localized within separate regions. Thus, they can be separated by muting the undesirable region. (b) The primary reflections recovered by an inverse Radon transform after the multiples were muted. (c) The multiple reflections recovered by an inverse Radon transform after the primaries were muted. (d) The multiples from (c) are subtracted from the original data (a). The result is multiple-free primary reflections (Yilmaz, Seismic Data Analysis).

 


View larger version (166K):

[in a new window]
 
Figure 30. A Gulf of Mexico marine seismic profile from the late 1990s. This vertical profile was extracted from a 3D volume migrated with a 3D poststack Kirchhoff time migration algorithm. Because of the limitations of poststack and time migration, the base of the salt body in the center of the profile and the sediments below the salt are poorly imaged. Compare to Figure 4 (WesternGeco).

 


View larger version (46K):

[in a new window]
 
Figure 31. A seismic data processing flow designed to accomplish 3D imaging in a geologically complicated area containing a salt body. Note the iterative tomography to determine the sediment velocity model followed by iterative migration to build the salt model. The acronym KPSDM stands for Kirchhoff prestack depth migration (WesternGeco).

 


View larger version (127K):

[in a new window]
 
Figure 32. Concept behind dual-sensor ocean-bottom cable acquisition. If seismic sensors are placed on the sea floor, reflections from the sea surface interfere with the primary reflections. The interference may be constructive or destructive as shown by the peaks and troughs in the amplitude spectra at the right. Because surface reflections are recorded with opposite polarity by a hydrophone and geophone, they are eliminated by balancing and summing the two types of traces, as shown by the bottom trace and its spectrum (Fred Barr, Oil & Gas Journal, 1994).

 


View larger version (77K):

[in a new window]
 
Figure 33. Results from a multicomponent survey. A reservoir sand channel is visible on a P-S converted wave profile but not on a P-wave profile. The well-log velocity curves on the left indicate that the difference in the two sections is due to differences in the impedance contrasts for P- and S-waves. (J. Gaiser and A. Strudley, First Break 2005).

 


View larger version (69K):

[in a new window]
 
Figure 34. Time-lapse measurements. The image on the left was acquired over a producing reservoir in 2003. The middle image shows the difference between the 2003 image and an older image acquired in 1992. There is no clear indication of reservoir changes. The right-hand image shows the difference between the 2003 image and a newer image acquired in 2001. Because of improvements in the repeatability of seismic data acquisition and processing, reservoir changes are seen clearly. The red circle shows an area where water injection has increased reservoir pressure. The differences in the blue oval are caused by changes in velocity in the reservoir above. The green oval is an area where production may have reduced gas saturation (H. A. Aronsen, et al., Schlumberger Oilfield Review 2004).

 





JOURNAL HOME HELP CONTACT PUBLISHER SUBSCRIBE ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 2008 by Society of Exploration Geophysicists