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`An introduction to common offset vector
`trace gathering
`Xinxiang Li
`CGGVeritas, Calgary, Alberta, Canada
`
`Summary
`This paper is an introductory review of the recently devel-
`oped concept of common offset vector (COV) trace gathering.
`The COV trace gathering is a 3D generalization of conven-
`tional 2D offset gathering. A COV gather is a similar but
`d i ff e rent re p resentation of a common-offset common-
`azimuth gather. For many types of acquisition geometry with
`regular sampling, a COV gather should be a single-fold trace
`gather with a survey-size continuous coverage. The COV
`gathering can also be described as a tile-connection scheme
`from the cross-spreads in a 3D geometry. The COV gathering
`parameters are determined by acquisition parameters. The
`COV gathers can be useful in many aspects of processing
`p restack 3D seismic data, especially for the analysis of
`azimuthally varying data attributes.
`
`Introduction: offset gathering of 2D data
`An offset gather refers to a group of prestack traces with a
`limited range of offsets. The term “common offset gather” is
`often used for such trace gathers, even though the offsets
`within a gather do not have to be the same. I call an offset
`gather “valid” if it has a continuous CDP coverage of the size
`of the whole survey, 2D or 3D. The word “continuous” is
`used in the sense that the pertinent data are sampled with the
`finest spatial rate of the survey, for example, the CDP bin size.
`The word “valid” is used in the sense that such a gather, by
`itself, provides a continuous full-range subsurface image.
`
`F i g u re 1. Stacking chart of a 2D regular geometry: 24 channels per shot and the
`shot interval is 4 times the receiver spacing. To guarantee at least one trace at each
`C D P, an offset range (offset bin-size) of two times the shot interval (including 8
`traces in this example) is re q u i re d .
`
`spreads. An offset range of at least two times the shot interval
`is required to ensure a valid offset gather. In fact, because of
`the geometry regularity, an offset gather has one and only
`one trace at each CDP when its offset range is two times the
`shot interval. Such single-fold valid offset gathers have the
`highest possible offset resolution, besides the highest CDP
`resolution. They are desirable for producing high quality
`migration results for migration velocity analysis and AVO
`analysis. The offset range of an offset gather is often called the
`bin-size of the offset gather.
`
`One-sided spread geometry describes conventional marine
`2D seismic data acquisition. However, typical land 2D
`surveys use two-sided spreads, where active receivers are
`located on both sides of each source. Offset gathers for two-
`sided spreads can be formed by using signed offsets or by
`using absolute values of the offsets. When negative offset and
`positive offsets are gathered separately, an offset bin-size of
`two times the shot interval is required to ensure a valid offset
`gather, as in the one-sided spread case. However, when the
`absolute offset values are considered, offset bin-size of only
`one shot interval is enough to produce valid offset gathers,
`since the negative and positive offsets compensate each other
`by covering alternate CDP ranges (see Figure 2). The total
`number of single-fold valid offset gathers (non-overlapping)
`is always equal to the nominal fold of the survey.
`
`The parameters to form 2D single-fold valid offset gathers are
`determined by the acquisition parameters: the sourc e
`interval, receiver group intervals and the total offset range.
`The same scheme can be directly applied to 3D surveys with
`very narrow azimuth ranges, such as conventional towed-
`streamer marine 3D surveys (with some ignorable difficulty
`at the very near offsets). However, things become more
`complicated with 3D
`land, wide azimuth surveys.
`Nowadays, prestack data processing for land 3D datasets has
`been mostly using conventional 2D approaches. The forma-
`tion of offset gathers mostly ignores the implications of the
`azimuth dimension. This approach has found itself in a diffi-
`cult situation when dealing with concerns regarding the
`number of offset gathers to form, the fold distributions of
`each offset gather, and azimuth variation within an offset
`gather. It is practically impossible, with this 2D approach, to
`form 3D offset gathers that are both single-fold and valid,
`even when the acquisition geometry is perfectly regular. This
`paper discusses the COV gathering scheme, which can form
`single-fold valid offset gathers (COV gathers) for regular
`wide azimuth surveys.
`
`Grouping seismic data into offset gathers has been a routine
`p ro c e d u re for velocity analysis, prestack imaging and
`prestack data interpretation, such as AVO analysis. This
`section reviews the routine calculations for forming offset
`gathers for 2D data. Figure 1 shows the stacking chart of a
`perfectly regular 2D acquisition geometry with one-sided
`
`Common offset vector
`The offset of a trace is defined as the distance between its
`source and its receiver. It ignores the directional property of a
`trace and becomes inappropriate when dealing with
`processing procedures such as the prestack migration and the
`
`Continued on Page 29
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`An introduction to common offset…
`Continued from Page 28
`interpretation of azimuthally varing attributes. A combination of
`offset and azimuth is commonly used to describe a 3D trace and
`has been successful in theoretical and practical aspects of 3D
`seismic data processing. This paper discusses a different repre-
`sentation of the directional distance between a trace’s source and
`receiver. A 3D survey geometry grid has an inline direction and
`
`a crossline direction (We assume that the inlines are parallel to
`the receiver lines). The source-receiver offset, as a vector, can be
`projected onto these two directions and represented by two
`scalar offset values, called inline offset and crossline offset. This
`pair of scalars represents an offset vector in Cartesian coordi-
`nates, in contrast to the offset-azimuth representation in polar
`
`Article Cont’d
`
`F i g u re 2. Stacking charts for 2D two-sided spread geometry. Left: negative and positive offsets are treated separately. Right: the sign of offsets is ignored. Note that the nega-
`tive and positive offsets compensate each other by covering alternate CDP ranges.
`
`Continued on Page 30
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`Article Cont’d
`An introduction to common offset…
`Continued from Page 29
`coordinates. It is intuitively advantageous to use the Cartesian
`representation because 3D data are acquired in rectangular
`(possibly skewed), not circular, spreads.
`
`The next few sections consider, if not otherwise indicated, a
`regular, perpendicular 3D survey as partly shown in Figure 3.
`This survey has equally spaced receiver lines and equally spaced
`source lines, and these two spacings can be different. The
`receivers on each receiver line are evenly spaced, and this
`spacing is the same for all the receiver lines. The sources on each
`source line are equally spaced and this spacing is the same for all
`the source lines. All receivers active for one source form a patch
`for the source. The regular geometry in consideration assumes a
`uniform patch size for all the sources. To be more specific, we
`assume that the patch size is 12 receiver line spacings wide and
`10 source line spacings long. Every source is always located
`closest to the geometric center of its patch.
`
`F i g u re 3. A part of a regular orthogonal 3D geometry. By “regular”, we mean:
`uniform receiver line spacing, uniform source line spacing, uniform re c e i v e r
`interval within each receiver line, uniform source interval within each source line,
`and uniform patch size for all sourc e s .
`
`F i g u re 4. One CDP line in a 3D survey and the possible locations of the sources, 1
`to 6, and receivers, A to F, of the traces on this CDP line. All traces with their
`s o u rces at location 1 (2, 3, .., 6 respectively) and their receivers on line A (B, C, …,
`F, respectively) have their midpoint fall on this CDP line, and ONLY on this CDP
`l i n e .
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`A 3D bin line as collection of 2D lines
`Let’s start with one CDP bin inline in the survey, shown in
`F i g u re 4 as a dotted line. The receiver and source locations of
`traces on this line are limited by the size of the source patches.
`If a trace belongs to a CDP on this line, its receiver has to be on
`the receiver lines A to F, and its source has to be one of the
`s o u rces whose lateral locations are indicated by the numbers 1
`to 6. More pre c i s e l y, if its source is one of the sources at lateral
`location 1, then its receiver must be from the receiver line
`marked by A. Similarly, if the source is at location 2, the re c e i v e r
`must be on receiver line B; the relations between 3 and C, 4 a n d
`D, 5 and E, 6 and F a re the same. All the traces on this CDP l i n e
`a re thus grouped into six 2D CDP lines that can be identified
`with fixed sourc e - receiver pairs, namely 1 A, 2 B, 3 C, 4 D, 5 E, and
`6 F, re s p e c t i v e l y.
`
`For traces on each of these 2D lines, their sources are along a line
`parallel to the receiver line, but possibly with a distance between
`them. This is to say that these traces have the same crossline
`offset. If we ignore the crossline offset, the traces’ inline-offsets
`and CDP locations construct a 2D regular stacking chart as
`shown in Figure 2. Note that the source spacing of these six 2D
`lines is the same, and it is the source line interval for the 3D
`geometry. Therefore, by using two times the source line spacing
`as the offset bin-size, each of the six 2D lines forms single-fold
`valid offset gathers. The combination of these 2D inline-offset
`gathers becomes a six-fold valid offset gather for the 3D CDP line
`in consideration. This obviously is not our ultimate result.
`However, by the definition of the inline-offset and crossline-
`offset, and the geometric reciprocity of the source and receiver
`we should be able to further the offset gathering process using
`crossline-offset variations.
`
`Now let’s consider a CDP bin crossline parallel to the source
`lines. This 3D bin line can also be decomposed into a number of
`2D lines. On each of these 2D lines, a number of 2D single-fold
`valid offset gathers can be formed using crossline offset values,
`and the offset bin-size should be twice the receiver line interval.
`
`Finally, by combining these two 2D offset gathering schemes, we
`can construct a 3D scheme, the COV scheme, to form 3D single-
`fold valid offset gathers. Any given trace in the geometry belongs
`to an inline and a crossline. It also has an inline offset and a
`crossline offset. As an inline trace, its inline offset, with other
`acquisition parameters, determines which single-fold valid
`i n l i n e-offset gather it belongs to; as a crossline trace, its crossline
`o ffset is used to determine which c ro s s l i n e- o ffset gather it
`belongs to. This is to say that a trace’s inline offset and crossline
`offset determine which single-fold valid offset vector gather it
`belongs to. Such a single-fold valid offset v e c t o r gather is called
`a COV gather. The total number of COV gathers is determined
`by the number of single-fold valid gathers in both inline and
`c rossline directions. The single-fold property and the full-
`coverage property of a COV gather come from these properties
`of the two 2D offset gathering schemes. The number of COVs for
`a 3D survey should equal the survey’s nominal fold.
`
`Continued on Page 31
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`Article Cont’d
`
`Practical complications
`
`Determination of the COV parameters
`
`From the discussions above, we can extract a practical approach
`to form COV gathers. For inline offsets, the offset bin-size of a
`COV should be twice the source-line spacing because it is equiv-
`alent to the source interval on a 2D line parallel to the receiver
`lines. Similarly, the offset bin-size for crossline offsets of a COV
`should be twice the receiver line spacing. The minimum and
`
`An introduction to common offset…
`Continued from Page 30
`COV gather as connected tiles from cross-spreads
`A COV gather can also be formed equivalently based on the
`concept of cross-spreads. A cross-spread is defined as all the
`traces with their sources on same source line and their receivers
`on same receiver line. A cross-spread in a fairly regular geometry
`is single-fold and it has continuous subsurface coverage (in the
`sense of minimum spatial sampling intervals in both directions
`of a survey grid). The CDP coverage of a cross-spread is practi-
`cally the same as the coverage of the center shot record (the
`source closest to the receiver line of
`the cro s s - s p read). In the pre s e n t
`example geometry, the size of the
`CDP coverage of a cross-spread can
`only extend up to three receiver lines
`on each side of the receiver line of the
`c ro s s - s p read and two and a half
`source line spacings on each side of
`the source line of the cross-spread, as
`shown in Figure 5.
`
`Besides numerous advantages, cross-
`spreads have some drawbacks. They
`have very limited coverage are a ,
`practically unlimited offset range
`(usually the maximum range in the
`survey), and unlimited azimuth
`range (usually full 360 degrees). The
`large offset range prevents them from
`being used for velocity analysis and
`AVO analysis. Their small coverage
`areas limit their application in migra-
`tion processes. The COV gathering
`was introduced here as a solution to
`c reate full-coverage, limited off s e t
`and limited azimuth gathers by
`“patching” together parts of different
`c ro s s - s p reads (Vermeer 1998). The
`region between two adjacent source
`lines and two adjacent receiver lines
`in a cross-spread is called a tile. As
`shown in Figure 5, a cross-spread can
`be sectioned into little areas and each
`of them has the size of a typical tile.
`These sections can cross the source
`line and the receiver line if necessary.
`We develop a systematic indexing
`scheme based on the sections’ rela-
`tive positions to the zero-offset loca-
`tion (center) of the cro s s - s p re a d
`(Figure 5). We apply the indexing to
`all the cross-spreads. It can be veri-
`fied that two sections from two
`neighbouring cross-spreads but with
`the same index number connect to
`each other without either overlap or
`gap. Therefore all the sections with
`the same index number form a
`single-fold
`full-coverage of
`the
`survey. Each one group of the same-
`numbered sections is a COV gather.
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`Continued on Page 32
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`Article Cont’d
`An introduction to common offset…
`Continued from Page 31
`maximum of signed inline offsets and crossline offsets can be
`determined by the size of the typical source patch of the survey.
`
`Let’s go through the COV gathering pro c e d u re with an example.
`F i g u re 6 shows a patch with inline dimension of 4800 meters
`and crossline dimension of 3200 meters. The source line spacing
`is 800 meters and the receiver line spacing is 400 meters. There
`a re 6 x 8 = 48 tiles in the patch. The fold of this 3D survey should
`be 12, and we should have 12 COV gathers formed. Since the
`s o u rce is located at the geometric center of its patch, the
`minimum inline offset is -2400 meters and the maximum inline
`o ffset is 2400 meters; the minimum and maximum cro s s l i n e
`o ffsets are -1600 meters and 1600 meters, re s p e c t i v e l y. Using
`i n l i n e - o ffset bin-size of 2 x 800 = 1600 meters and three center
`locations of -1600 m, 0 m, and 1600 m, the total range of -2400 to
`2400 meters is covered. Similarly, using cro s s l i n e - o ffset bin-size
`of 2 x 400 = 800 meters and four center locations of -1200 m, -400
`m, 400 m, and 1200 m, the range of -1600 to 1600 meters are
`c o v e red. The total number of centers will be 3 x 4 = 12. Figure 7
`shows the COV gathers with their corresponding rangs in inline
`o ffsets and crossline off s e t s .
`
`The offset range of a COV gather
`
`The offset ranges within each COV gather are remarkably larger
`than that we are usually familiar with. In the example in Figure
`7, the largest offset difference can be as large as 1750 meters at the
`corner COVs (from 1131 m to 2884 m). Such large offset range
`within a COV gather is not desirable, and is probably one of the
`reasons why the COV gathering has not been widely used in
`routine data processing. Let’s put this offset range issue into
`perspective. In more realistic cases, the fold coverage of land 3D
`surveys is much higher than 12, ranging from around 30 to
`several hundreds. Offset range within a COV is accordingly
`much smaller. Also, the COV gathering attempts to sample both
`the offset dimension and the azimuth dimension at the same
`time. The reduction of offset sampling density is expected to be
`compensated by denser sampling in azimuth dimension. In the
`example shown in Figure 7, the 12 COVs represent 10 different
`azimuth values within the 360 degree range. Furthermore, when
`source-receiver reciprocity is assumed, two COVs from two
`
`opposite direction and same offset range can be combined to
`c reate two new COVs with much smaller offset ranges.
`Herrmann et al (2007) discovered this combination method and
`they call these new COVs “high resolution (HR)” because of
`denser offset sampling. Vermeer (2007) also gives some discus-
`sion on this topic. In the present example, a corner COV, for
`example (IL: [800~2400], XL: [800~1600]), along with its opposite
`COV, (IL: [-2400~-800], XL: [-1600~-800]), produces two new HR
`COVs with offset range of about 1131~2530 meters and about
`1789~2884 meters respectively. This innovative application of the
`reciprocity is similar in principle to the offset coverage compen-
`sation in the 2D two-sided spread acquisition shown in Figure 2.
`
`Perpendicularity not essential
`
`All the discussions so far are dealing with perpendicular source
`lines and receiver lines, but the perpendicularity is not essential
`to the COV concept. If the source lines and receiver lines are not
`perpendicular to each other, the shape of the coverage of cross-
`spreads will be a parallelogram rather than the rectangular shape
`described above. A similar sectioning and numbering scheme
`can be applied to these parallelogram-shaped cross-spreads and
`COVs can thus be formed accordingly from these parallelogram-
`shaped tiles.
`
`Another option is to calculate the effective source distance
`parallel to the receiver lines and the effective source distance
`perpendicular to the receiver lines. The new source distances
`can then be used to form “rectangular” COVs. These eff e c t i v e
`
`F i g u re 6. A s o u rce patch of size of 4800 m by 3200 m. The source line spacing is
`800 m and receiver line spacing is 400 m. The source is at the geometric center of
`the patch.
`
`F i g u re 5. The coverage of a cro s s - s p read. A c ro s s - s p read is all the traces with their
`s o u rces on same source line and their receivers on same receiver line. The coverage
`of a cro s s - s p read is determined by the locations of the source line and the re c e i v e r
`line, and is limited by the size of the source patches. In fact, the CDP coverage size
`of a cro s s - s p read is about the same as the CDP coverage of the shot record of the
`center source of the cro s s - s p read. A c ro s s - s p read can be sectioned into tiles and the
`tiles can be systematically numbered.
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`F i g u re 7. COV gathers, identified with their ranges of inline and crossline offsets.
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`An introduction to common offset…
`Continued from Page 32
`s o u rce distances are not uncommon in 3D processing; geophysi-
`cists are using a similar concept when they calculate the CDP
`bin-size when constructing geometry bin grids (which are
`always rectangular). Conventional marine 3D geometry is an
`e x t reme case, where the source lines are parallel to the re c e i v e r
`lines. When the azimuth is so limited that it is often ignored in
`the processing sequence, the COV concept seems unnecessary.
`H o w e v e r, the inline offset and crossline offset concepts can still
`be useful. For example, when forming offset gathers, the
`c rossline offsets can be ignored and the channel numbers can be
`e ffectively used as inline offsets. Using channel numbers instead
`of sourc e - receiver offsets can put all near-gun channels from all
`the streamers into one offset gather. Even though the off s e t
`range of these near-gun gathers can be “too large”, the conti-
`nuity of the CDP coverage may improve the migration quality
`of near offset gathers.
`
`Geometry irregularity
`
`Acquisition geometry irregularity does not cause pro b l e m s
`specific to COV gathering. On the other hand, COV gathers can
`handle irregularity better than conventional offset gathering in
`many aspects. The conventional offset gathering method prac-
`tically ignores the acquisition geometry, whether it is regular or
`not. It is impossible to form offset gathers with even fold distri-
`bution by simply gathering traces using only the sourc e -
`receiver offsets, because the distribution of fold along offsets is
`always irregular for wide-azimuth 3D
`g e o m e t r i e s .
`
`Article Cont’d
`
`In many implementations of prestack migration of 3D land data
`the large trace density variation with offset becomes a concern.
`The number of traces in the middle offset range is many times
`more than the near offset and far offset ranges. By forcibly
`producing even-spaced offset sampling, middle offset traces
`have to be weighted down. However, once the even-spaced
`o ffset sampling re q u i rement is removed, more re a s o n a b l e
`approaches for prestack trace gathering are possible. Wilkinson
`(2007) uses flexed offset binning to prepare offset gathers for
`migration that is able to preserve the trace density variation after
`migration. Migration of individual COV gathers automatically
`p reserve both offset and azimuth information. The off s e t
`sampling is somewhat compromised due to better azimuth
`sampling. These approaches tend to give all input traces the
`same weight, at least with fairly regular geometries. This is intu-
`itively more desirable since it is difficult to find convincing
`reasons for preferring some traces over others. Especially since
`the preferred traces tend to be at the noisy near and far offsets.
`
`Conclusions
`The COV concept has been around for 10 years. It was first intro-
`duced by Vermeer (1998) and Cary (1999) from different view-
`points (under different names). This paper has reviewed the
`concept of COV gathering from both the 2D offset gathering
`concept (Cary, 1999) and the cross-spread concept (Vermeer,
`
`Any CDP binning grid has a certain
`size; a slight deviation from perfectly
`regular positioning usually does not
`move a trace from one CDP to another.
`This also means that slight mis-posi-
`tioning of a trace (source and receiver
`locations) does not cause any problem
`in producing single-fold valid off s e t
`gathers. When acquisition irregularities
`necessitate borrowing or interpolating
`traces for the missing locations, the
`COV gathers need less effort in such
`regularization processes.
`
`Possible applications
`
`The COV gathers can be very useful
`when both azimuth and offset informa-
`tion has to be kept after migration. The
`COV gathering couple the azimuth and
`o ffset binning naturally, and this is
`d i ff e rent
`from
`the
`conventional
`azimuth sectoring plus a separated
`o ffset gathering. The difficulties of
`creating offset gathers with even fold
`distributions will only be more serious
`after azimuth sectoring. A m p l i t u d e
`variation with offset and azimuth
`(AVAz) and velocity azimuthal varia-
`tion are
`two examples of such
`azimuthally variant attributes where
`COV gathering can provide help.
`
`Continued on Page 34
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`November 2008 CSEG RECORDER
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`Article Cont’d
`An introduction to common offset…
`Continued from Page 33
`1998). Direct application of conventional 2D offset gathering to
`3D cross-spread acquisition creates irregularities in offset gathers
`even when the acquisition geometry is perfectly regular. The
`COV gathering process clears up some confusing issues in
`forming single-fold, large coverage, limited offset, limited
`azimuth gathers. The acquisition parameters fully determine
`how the COV gathers are formed. The COV gathering is yet to be
`widely used in the industry. One reason is probably the large
`offset range within each COVs. Herrmann et al. (2007) has found
`a way to significantly improve the offset sampling of COV
`gathers using source-receiver reciprocity. I believe COV gath-
`ering is useful in many aspects of 3D wide-azimuth data
`processing. R
`
`Acknowledgements
`I thank my employer, CGGVeritas, for granting the permission to
`publish this paper. I also thank many of my colleagues who have
`given helpful suggestions and comments.
`
`References
`Cary, P.W., 1999, Common-offset-vector gathers: an alternative to cross-spreads for wide-
`azimuth 3-D surveys, 69th Ann. Internat. Mtg., Soc. Expl. Geophys., Expanded
`Abstracts, paper SPRO P1.6.
`Cary, P.W. and Li, X., 2001, Some basic imaging problems with regularly-sampled seismic
`data, 71st Ann. Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, pp. 981-984
`Cooper, J., Margrave, G., and Lawton, D., 2008, Simulations of Seismic Acquisition
`Footprint, Expanded Abstracts CSEG 2008 annual meeting, 160-164.
`Gesbert, S., 2002, From acquisition footprints to true amplitude, Geophysics, 67, 830-
`839.
`Herrmann, P., and Suaudeau, E., 2007, internal discussions.
`
`Padhi, T., and Holley, T.K., 1997, Wide azimuths, why not?, The Leading Edge, 16,
`175-177.
`Perz, M., and Zheng, Y., 2008, Common-offset and common offset-vector Migration of 3D
`Wide Azimuth Land Data: A Comparison of Two Approaches, Expanded Abstracts
`CSEG 2008 annual meeting, 167-171.
`Vermeer, Gijs J.O., 1998, Creating image gathers in the absence of proper common-offset
`gathers: Exploration Geophysics (ASEG Conference issue), 29, 636-642. (available at
`http://www.3dsymsam.nl/publicat.htm)
`Ve r m e e r, Gijs J.O., 2000, P rocessing with offset-vector-slot gathers: 70th A n n u a l
`Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, paper ACQ1.2.
`Vermeer, Gijs J.O., 2005, Processing orthogonal geometry – what is missing?: 75th
`Annual Internat. Mtg., Soc. Expl. Geophys., Expanded Abstracts, paper SPNA 2.9.
`Vermeer, Gijs J. O., 2007, Reciprocal offset vector tiles in various acquisition geometries,
`Expanded Abstracts, SEG Annual meeting, 61-65.
`Wilkinson, D., 2007, internal discussions.
`
`X i n x i a n g Li has a B.Sc. (1987) and a M.Sc.
`(1989) in mathematics. After working for
`the Chinese Academy of Sciences for six
`years, Xinxiang came to the University of
`Calgary in 1996 to pursuit a geophysics
`m a s t e r’s degree, which he obtained in
`1999. Since 1997, he has worked in
`Calgary as a pro c e s s o r, a developer and
`re s e a rc h e r, in Enertec, the CREWES Project at the University
`and Sensor Geophysical. He joined CGGVeritas at the begin-
`ning of 2006 and is currently working as a member of the
`R&D team. He is interested in many aspects of pro c e s s i n g
`and analysis of seismic reflection data, especially in pre s t a c k
`data signal enhancement, noise attenuation and imaging.
`
`Brian Russell awarded
`SEG Honorary Membership
`
`Dr. Brian Russell, vice president of Hampson-Russell software, is to be awarded
`SEG Honorary Membership at the SEG International Exposition and 78th
`Annual Meeting in Las Vegas, Nevada, 9–14 November 2008.
`
`Dr. Russell is receiving the SEG’s second highest honor for his distinguished
`contributions to the Society and to the SEG Foundation over the last two
`decades. He served as SEG second Vice President in 1993, as chairman of The Leading Edge edito-
`rial board in 1995, technical co-chairman of the 1996 SEG annual meeting in Denver and as
`President of SEG during 1998-99. He has been on the Board of Directors of the SEG Foundation
`since 2003. In 1996 he and Dan Hampson were jointly awarded the SEG Enterprise Award, and in
`2005 Brian received SEG Life Membership.
`
`Dr. Russell is an internationally recognized expert in seismic inversion, amplitude variations with
`offset (AVO) and seismic attribute analysis. He is the author of the SEG Course Notes publication
`entitled: “Introduction to Seismic Inversion Techniques”. In addition, he presents advanced
`training courses on inversion, AVO and seismic attributes to petroleum geophysicists throughout
`the world. He is also an Adjunct Professor in the Department of Geoscience at the University of
`Calgary and is Chairman of the Board of Directors of the Pacific Institute of the Mathematical
`Sciences (PIMS). R
`
`34
`
`CSEG RECORDER November 2008
`
`Ex. PGS 2012