4

Hydrocarbon Detection With AVO

Edward ChiburisECGeoHouston, Texas, USA

Charles FranckRoyal Oil & Gas CorporationCorpus Christi, Texas, USA

Scott LeaneyJakarta, Indonesia

Steve McHugoOrpington, England

Chuck Skidmore Amoco Production CompanyHouston, Texas, USA

S E I S M I C S

Imagine a geophysical technique with the volumetric coverage of surface seismic that could delineate zones

of gas, oil and water. In many ways, that summarizes the potential of interpreting seismic reflection ampli-

tude variation with offset, or AVO.

nBright spots—froma gas sand, andfrom a high veloc-ity basalt. Numbersat top are shotpoints. (Courtesy of BillOstrander and ChevronCorporation, reference 5.)

Tim

e, s

ec

0

0.5

1.0

1.5

2.0

0170 150 130 110 90

150 130 110 90 70A

A

Gas

In the late 1920s, the seismic reflectiontechnique became a key tool for the oilindustry, revealing shapes of subsurfacestructures and indicating drilling targets.This has developed into a multibillion dollarbusiness that is still primarily concernedwith structural interpretation. But advancesin data acquisition, processing and interpre-tation now make it possible to use seismictraces to reveal more than just reflectorshape and position. Changes in the charac-ter of seismic pulses returning from a reflec-tor can be interpreted to ascertain the depo-sitional history of a basin, the rock type in alayer, and even the nature of the pore fluid.This last refinement, pore fluid identifica-tion, is the ultimate goal of AVO analysis.

Early practical evidence that fluids couldbe seen by seismic waves came from “brightspots”—streaks of unexpectedly high ampli-tude on seismic sections—often found to

2 Oilfield Review

For help in preparation of this article, thanks to JackCaldwell, Barry Donaldson and Jim Hovland, GECO-PRAKLA, Houston, Texas, USA; Al Frisillo, Amoco Pro-duction Company, Tulsa Research Center, Tulsa, Okla-homa, USA; Michael Mikulich, Chevron Corporation,San Francisco, California, USA; Bill Murphy and AndyReischer, Schlumberger-Doll Research, Ridgefield, Con-necticut, USA; Bill Ostrander, Benecia, California, USA.* In this article, DSI (Dipole Shear Sonic Imager) andELAN (Elemental Log Analysis) are marks of Schlumberger.1. An intermediate step called normal moveout correc-

tion is omitted here for brevity, but described in“Structural Imaging: Toward a Sharper SubsurfaceView,” page 28.

Tim

e, s

ec

0.5

1.0

1.5

2.0

Basalt-dry

nSingle-layeracquisition geome-try, associated syn-thetic traces show-ing AVO effect ofgas sand, and amultilayer geome-try. Synthetics showamplitude increas-ing with offset(deflections to theleft becoming morenegative). Althoughseismic coordinatesare based on offset,theory relatingchanges in ampli-tude with materialproperties of thereflector is basedon angle (θ).Because the reflec-tion point is mid-way betweensource and receiver,and common to alltraces, it is calledthe common mid-point (CMP). A col-lection of traces isknown as a gather,in this case a CMPgather. In simplecases (top) with lay-ers of uniform den-sity and velocity, adirect relationshipexists between off-set and angle ofincidence. But mostof the time (bottom),variations in den-sity and velocitybend rays, requir-ing ray-trace mod-eling to relateangle to offset. aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaOffset 4

Offset 3

Offset 2

Offset 1

S4 S3 S2 S1 R1 R2 R3 R4

Offset 4

Offset 3

Offset 2

Offset 1

Shale

Gas sandCommonmidpoint (CMP)

S1

Gas sand

Shale 1

Shale 2

CMP

Synthetic traces—CMP gather

Amplitude increases with offset

R1

θ1

θ2

Single-layer geometry—Direct relationship between θ and offset

Multilayer geometry— Complex relationship between θ and offset

signify gas. Bright spots were recognized inthe early 1970s as potential hydrocarbonindicators, but drillers soon learned thathydrocarbons are not the only generators ofbright spots. High amplitudes from tight orhard rocks look the same as high amplitudesfrom hydrocarbons, once seismic traceshave been processed conventionally (previouspage). Only AVO analysis, which requiresspecial handling of the data, can distinguishlithology changes from fluid changes.

An analogy for the physics of AVO is theskipping of a stone across a pond. Everyoneknows that if a stone is dropped or throwninto water from directly above, it sinksinstantly. But skimmed nearly horizontally, itbounces off the surface of the water. Theamplitude of the bounce, which was zero atvertical incidence, increases with the angleof incidence.

Now replace the water with rubber andrepeat the process. This time the verticalbounce is high, and the high-angle bounceis low. The amplitude of the bouncedecreases with angle of incidence, a dramat-ically different behavior from the water case.

Analogous concepts applied to seismicsform the basis for inferring formation prop-erties—density and compressional andshear velocities—from seismic reflectionamplitude variation with angle of incidence.And because formation density and velocitydepend on the fluid saturating the forma-tion, reflection amplitude variation also per-mits identification of pore fluid.

January 1993

Conventional treatment of seismic data,however, masks this fluid information. Theproblem lies with the way seismic traces aremanipulated in order to enhance reflectionvisibility. In a seismic survey, as changes aremade in the horizontal distance betweensource and receiver, called offset, the angleat which a seismic wave reflects at an inter-face also changes (above). Seismic traces—recordings of transmitted and reflectedsound—are sorted into pairs of source-receiver combinations that have differentoffsets but share a common reflection pointmidway between each source-receiver pair.This collection of traces is referred to as acommon midpoint (CMP) gather. In conven-tional seismic processing, in which the goalis to create a seismic section for structural or

stratigraphic interpretation, traces in agather are stacked—summed to produce asingle average trace.1

Stacking enhances signal at the expenseof noise, making reflections visible, andcompresses data volume. But it destroysinformation about amplitude variation withoffset. Consider two reflections in the sec-tion: one has amplitude increasing with off-set, such as in the case of the stone bounc-ing off the water, and the other hasamplitude decreasing with offset, similar tothe stone bouncing off rubber. Once thereflection traces are stacked, they may have

43

1. Green G: “On the Laws of Reflexion and Refraction of Light,” inTransactions of the Cambridge Philosophical Society 7 (1839):245. Reprinted in Mathematical Papers of the Late GeorgeGreen. London, England: Macmillan, 1871.

Kelvin WT: “Reflexion and Refraction of Light,” PhilosophicalMagazine, Fifth Series 26 (1888): 420-422.

2. In the 1620s, Snell observed that light refracts at different anglesthrough different materials. In 1657, Fermat postulated the cor-rect expression for its reflection and refraction.

Knott CG: “On the Reflexion and Refraction of Elastic Waves,With Seismological Applications,” Philosophical Magazine, FifthSeries 48 (1899): 64-97.

Zoeppritz K: “Über Erdbebenwellen, VIIB: Über Reflexion undDurchgang seismischer Wellen durch Unstetigkeitsflächen,”Nachrichten der Königlichen Gesellschaft der Wissenschften zuGöttingen, Mathmatisch-physikalische Klasse (1919): 57-84.

3. Macelwane JB and Sohon FW: Introduction to Theoretical Seis-mology. New York, New York, USA: John Wiley & Sons, Inc.(1936): 147-179.

4. Muskat and Meres published hand-calculated reflection coeffi-cients in 1940, assuming Poisson’s ratio was a constant 0.25across the interface. Koefoed, in 1955, and Bortfeld, in 1961,simplified the Zoeppritz expressions by assuming that changesin material properties across the interface are much smaller thanthe average value of the properties on each side and that theincident angle does not exceed 30°.

Muskat M and Meres MW: “Reflection and Transmission Coeffi-cients for Plane Waves in Elastic Media,” Geophysics 5 (1940):115-148.

Koefoed O: “On the Effect of Poisson’s Ratios of Rock Strata onthe Reflection Coefficients of Plane Waves,” Geophysical

identical amplitudes—they may even bebright spots—while their AVO signatures arecompletely different. AVO analysis can usu-ally distinguish fluid contrasts from lithologycontrasts, but it requires carefully processedgathers that have not been stacked.

A Little TheoryAttempts at practical application of AVObegan about 15 years ago, but the physicswas understood around the turn of the cen-tury (see “History,” below, right). The gen-eral expressions for the reflection of com-pressional and shear waves at a boundary asa function of the densities and velocities ofthe layers in contact at the boundary arecredited to Karl Zoeppritz.2 Zoeppritz foundthat amplitudes increase, decrease orremain constant with changing angle ofincidence, depending on the contrast indensity, compressional velocity, Vp , andshear velocity, Vs , across the boundary.

Conventional seismic surveys deal exclu-sively with the reflection of compressionalwaves. When a compressional seismicwave arrives vertically at a horizontal inter-face, the amplitude of the reflected wave isproportional to the amplitude of the incom-ing wave, according to the normal inci-dence reflection coefficient:3

in which ρ is density and 1 and 2 signify thetop and bottom layer, respectively. Whenthe seismic wave arrives obliquely, the situ-ation is more complicated. The compres-sional reflection coefficient is now a tortu-ous function of the angle of incidence, thedensities, and Vp and Vs of the two layers incontact. The simplest useful approximationsto the Zoeppritz theory comprise the normalincidence reflection coefficient writtenabove plus at least three other terms—func-tions of angle and contrasts in density andthe two velocities. Nevertheless, the depen-dence of reflectivity on density, Vp and Vsmakes it possible to deduce fluid and rocktype. Gas, oil and water have different den-sities and acoustic velocities. They insinuatethis difference on the rocks they saturate.

ρ2Vp2 - ρ1Vp1

ρ2Vp2 + ρ1Vp1 '

44

2. Zoeppritz K: “Über Erdbebenwellen, VIIB: ÜberReflexion und Durchgang seismischer Wellen durchUnstetigkeitsflächen,” Nachrichten der KöniglichenGesellschaft der Wissenschften zu Göttingen, Math-matisch-physikalische Klasse (1919): 57-84.

3. This is strictly true only if transmission effects, such asspherical spreading and attenuation, are neglected. Italso holds when the layers are not horizontal, as longas the angle between the wave and the interface is 90°.

Synthetic AVOs from LogsIn much the same way that a blindfoldedexpert can identify a wine and its vintage, oran X-ray diffraction lab technician can iden-tify mineral components in a rock sample,the key to using AVO for fluid identificationis comparison of real data with a stan-dard—in this case a synthetic seismogram (a“synthetic” for short). This is an artificialseismic trace manufactured by assumingthat some pulse travels through an earthmodel—rock layers of given thickness, den-sity and velocity—and returns to berecorded. The earth model that producedthe synthetic can be modified, sometimesrepeatedly, until the synthetic matches themeasured data, indicating the earth model isa reasonable approximation of the earth.

The densities and velocities of fluid-satu-rated rocks necessary for the creation ofsynthetic traces preferably come from logsor cores. Missing data can be estimated

using theoretical or empirical equations.The synthetic traces show the expectedAVO effect for each fluid type.

Take, for example, the AVO effect of gasin sandstone predicted from logs in a gasfield operated by Texas-based Royal Oil &Gas (next page, top). Here, acoustic veloci-ties were measured with the DSI DipoleShear Sonic Imager tool. The seismic eventof interest is the circled blue reflection cor-responding to the interface between anoverlying shale and the gas sand. The tracerecorded at zero offset—0° from vertical,directly above the reflecting point—beginswith a small negative amplitude (tracedeflects to the left). The amplitude becomesmore negative as offset increases. The AVOresponse to oil is the same (next page, mid-dle). But when hydrocarbons are replacedwith water, the AVO response changes (nextpage, bottom). Now polarity becomes posi-

Prospecting 3 (December 1955): 381-387.

Bortfeld R: “Approximation to the Reflection and TransmissionCoefficients of Plane Longitudinal and Transverse Waves,” Geo-physical Prospecting 9 (December 1961): 485-502.

5. Aki K and Richards PG: Quantitative Seismology, Theory andMethods Vol. 1. San Francisco, California, USA: WH Freemanand Co. (1980): 123-155.

Shuey RT: “A Simplification of the Zoeppritz Equations,” Geo-physics 50 (April 1985): 609-614.

Attempts at practical application of AVO began

about 15 years ago, but the physics draws on 19th

century advances in optics and electromagnetic

wave theory. In the 1800s, Green and Kelvin spec-

ulated about the similarity of the reflective

behavior of light and elastic waves.1 Using

Snell’s law, Knott in 1899, and Zoeppritz in 1919,

developed general expressions for the reflection

of compressional and shear waves at a boundary

as a function of the densities and velocities of the

layers in contact.2 Although Zoeppritz was not the

first to publish a solution, his name is associated

with the cumbersome set of formulas describing

the reflection and refraction of seismic waves at

an interface. In 1936, Macelwane and Sohon

recast the equations to gain insight into the

physics and facilitate calculations.3

Before computers were widespread, AVO

effects were incorporated into synthetic seismo-

grams and other calculations using approximated

Zoeppritz equations.4 Today, personal computers

can generate synthetics based on the full Zoep-

pritz formalism, but approximations are still used

to gain physical insight into the relative influence

of velocity and density changes on seismic ampli-

tudes, and in the attempt to back out lithology

and fluid type from AVO data.5

History

Oilfield Review

nSynthetic traces showing AVO effects ofgas, oil and water, and an ELAN Elemen-tal Log Analysis output. The negativepolarity event at the top of the gasbecomes more negative with increasingoffset, a signature of gas (top). In this idealcase, the synthetics are created from anearth model based on measured logs con-verted from depth to time. Velocities weremeasured using the DSI Dipole Shear SonicImager tool. In the less desirable but morecommon situation, all three log measure-ments are not available. Missing data arecreated using empirical relations. Mea-sured logs (middle) from an African oilsand at 0.97 sec, as identified by ELANcalculation, have an AVO effect similar togas, but in some cases, AVO can distin-guish the two. Water sands identified bythe ELAN log deeper in the section showno amplitude increase with offset. TheAVO signature of water is virtually alwaysdifferent from that of oil or gas, makingAVO a hydrocarbon indicator (bottom). Inthis example, water is substituted for gasin the sand of the top figure using empiri-cal and theoretical equations.

45January 1993

Tim

e, s

ec

1.0

1.1

Shale Boundwater Quartz

Calcite Oil Movedhydr

Tim

e, s

ecTi

me,

sec

1.0

1.1

1.5

1.6

Gas

Oil

Water

0

0

0 50001000

3280 6560

50001000

Offset (horizontal distancebetween source and receiver), ft

Vp Vs bρ

8 9 3 4 2 2.25kft/sec kft/sec g/cm3

Vp Vs bρ

8 9 3 4 2 2.25kft/sec kft/sec g/cm3

Offset, ft

Offset, ft

Matrix, %

Cal

cula

ted

Mea

sure

d

Cal

cula

ted

nThe measuredAVO gather fromRoyal Oil’s Texasgas well. Ampli-tude of the smallnegative (blue)reflection at the topof the gas becomesmore negative asoffset increases.The seismic datahave undergonetrue amplitude pro-cessing describedin “Processing forAVO Interpretation,”(page 48).

Offset, ft

Tim

e, s

ec

0 2200 4400 6600

1.3

1.03

0.8

0.55

tive (amplitude deflection to the right), andamplitude decreases with offset.4

The AVO effect at any interface can bequantified with the Zoeppritz formulas, andplotted as a curve (above). At the top of thegas sand in Royal Oil & Gas’ well, and formost gas sands, Zoeppritz calculations pre-dict an increasingly negative amplitude withoffset. In this case, the predicted negativeamplitude increases 100%. Also shown arethe Zoeppritz-predicted AVO effects for thegas-water contact deeper in the sand, andfor a nonfluid, lithologic contact higher inthe section.

These curves of amplitude versus angle ofincidence can be used to make quantitativecomparisons between synthetic predictionsand amplitudes from real data, once thedata have been processed for true ampli-tudes. This is made easier by plotting ampli-tude versus angle of incidence squared,which converts Zoeppritz curves to straightlines. AVO behavior can then be succinctlydescribed by the line’s gradient, G, and nor-mal incidence intercept, P.

For typical reservoir rocks, the reflectionat an interface between a water-bearinglayer and a hydrocarbon-bearing layer issuch that a negative polarity reflectionbecomes more negative—intercept and gra-dient both negative—or a positive polarityreflection becomes more positive—interceptand gradient both positive (above, right ).

0 1000 5000

1.0

1.1

Offset, ft

Angle, deg

Tim

e, s

ec

0 8 16 24 32

Am

plitu

de

0

-0.05

-0.1

-0.15

Angle, deg0 8 16 24 32

Am

plitu

de

0.15

0.1

0.05

0

Angle, deg0 8 16 24 32

Am

plitu

de

0

-0.05

-0.1

-0.15

Top gas sand

No fluid change

Bottom gas sand

nQuantitative Zoeppritz prediction of AVO effects for three reflections in the Texas gas field of Royal Oil & Gas. At top of gas sand (left),amplitude doubles, from slightly negative to very negative, as offset increases. At the gas-water contact near the bottom of the sand(lower right) amplitude increases 50%, from slightly positive to more positive. Most reflections that do not involve a fluid change (upperright) show negligible amplitude change.

46 Oilfield Review

Tim

e, s

ec

1.0

1.1

0 50001000

Offset, ft Gra

dien

t (G

)

Inte

rcep

t (P

)

Gx P

Gas

nSynthetic tracesfrom page 45, topand associatedAVO compositetraces—gradient,intercept and theirproduct (GxP). Wig-gles in the G trace,for example, haveamplitudes equal tothe best-fitting gra-dient computed forevery time level inthe gather. Reflec-tors emerge as neg-ative or positivewiggles, easily dis-tinguishable fromnoise, which staysaround zero. Posi-tive product indi-cates hydrocarbon,in this case gas.

ft0 5000

0.55

0.8

1.05

1.3

0.9

1.0

1.1

1.2

1.3

-2 0 2

Tim

e, s

ec

Tim

e, s

ec

Offset, ft0 2200 4400 6600

Am

plitu

de

Angle2

GxP Section

0 50 100 150 200CMP

nAVO data, gradient and interceptcalculation and product section for theTexas gas field. On the top, amplitudesare measured across data traces frompage 45, top. Amplitudes are fit to astraight line (middle)—by changingaxes in the original Zoeppritz predic-tion plot from amplitude vs. angle toamplitude vs. angle squared—with acorresponding gradient and intercept.Traces containing the values of thegradient, intercept, or the product ofthe two form a seismic section, in thiscase, a product section from the Texasgas field (bottom). The region betweenCMP 70 to 100 shows a positive AVOproduct (red), and corresponds to thegas-producing sand. A second well4400 ft to the left has confirmed thisgas extent.

nGathers from well locations in twobright spots seen on page 42, showingdifferent AVO signatures. At left is thegather from shot point 81 of top section.Negative amplitude becomes morenegative with offset in gas sand. On theright is a gather from shot point 127 ofbottom section. Amplitude decreaseswith offset, indicating no hydrocarbon. 47January 1993

The simplest indicator of hydrocarbons istherefore the product of gradient and inter-cept. A positive product most likely indi-cates oil or gas. A product trace for theRoyal Oil & Gas example clearly revealsgas. G traces, P traces or product traces canbe plotted next to each other to producesections, similar to stacked sections, forAVO interpretation.

Interpretation of Actual AVOsHow do real AVO gathers compare withsynthetics? The real gather (previous page,bottom) observed at the Texas gas well andcarefully processed by GECO-PRAKLA (see“Processing for AVO Interpretation,” nextpage) shows the same AVO signature as thesynthetic gather generated using log datafrom the well (page 45, top). Both gathersshow a small negative reflection at normalincidence that becomes more negative withoffset. This signals hydrocarbons, and sureenough, the well did produce gas. The gra-dient and intercept are both negative, andtheir product positive. A section composedof product traces from every gather in theseismic line shows a zone of positive prod-uct (right). A second well drilled in the zoneconfirmed the presence of gas.

Because the synthetic was built from logdata—density, compressional velocity andshear velocity—rather than estimated val-ues, it closely matches the observed gather.Often estimated is shear velocity, and thiscreates a common stumbling block to AVOmodeling. Dramatic AVO effects appear ingas sands where the shear velocity is oftentoo slow to be measured with conventionalsonic tools. Introduction of the DSI toolremoves this impediment.

Once the AVO signature of hydrocarbonsis known, seismic data can be examined forfluids. For example, what would AVO anal-ysis have revealed about the two brightspots—one from gas, the other frombasalt—described on pages 42-43? Theanswer was published in 1984 by BillOstrander, then at Chevron USA (below).5 Gas

shot point 81Basalt

shot point 127

4. Velocities and density for this example were com-puted using a technique described in “Taking Advan-tage of Shear Waves,” Oilfield Review 4, no. 3, (July1992): 52-54. For further reading see Murphy W, Reischer A andHsu K: “Modulus Decomposition of Compressionaland Shear Velocities in Sand Bodies,” Geophysics 58,no. 2, (February 1993): 227-239.

5. Ostrander WJ: “Plane-Wave Reflection Coefficientsfor Gas Sands at Nonnormal Angles of Incidence,”Geophysics 49 (October 1984): 1637-1648.

Basic Steps

True Amplitude Recovery (TAR)—compensates

for amplitude loss caused by wavefront spreading

and low transmission quality (Q) of the rock

through which the seismic wavefront travels.

Frequency wave number (F-K) filtering—is

required to attenuate coherent noise generated

by near-surface or seabed features such as rigs,

buildings and seabed channels. Ground roll, or

surface waves, common in land data, cannot usu-

ally be removed with this method. Correctly

designed receiver arrays can solve this problem.

Generalized Radon Transform (GRT) demultiple—

reduces amplitude of multiples (interbed or water

column reverberations) relative to primary

energy. Conventional demultiple techniques do

not preserve true amplitudes, nor do they elimi-

nate all multiples. The GRT demultiple separates

seismic arrivals by differences in their apparent

velocities, then suppresses multiples by an

inverse transform of only part of the data.1

Deconvolution—creates a new trace with wiggles

that indicate the location (in time) and the

strength of each reflector. Surface-consistentdeconvolution reduces pulse shape distortion

because the filter is the same for each shot and

receiver location.

Surface-consistent scaling and residual statics—

correct amplitudes and arrival times of raypaths

distorted by near-surface anomalies, such as

those caused by the unconsolidated (“weath-

ered”) zone on land or a rough ocean bottom.

Velocity analysis and Normal Moveout (NMO)—create and apply the velocity model that aligns

wiggles from all offsets. In conventional seismic

processing, velocity analyses are made every 2 to

3 km [1.2 to 1.8 miles]. Because most AVO

anomalies are caused by velocity variation,

closely spaced velocity analyses are required

every 0.25 km [0.15 mile].

Fine-Tuning Steps

CMP-consistent statics—sometimes called non-

surface consistent statics or trim statics, forces

alignment of selected events that have not been

properly aligned by standard processing, on a

CMP-by-CMP basis. This is a compromise, and

considered unscientific by purists.

Dephasing—attempts to restore each trace to

zero phase so reflection events can be tracked

and their amplitude changes quantified.

Mixing and median filtering—attenuate random

noise and reinforce signal. In median filtering,

traces within a small offset range are summed or

stacked. Mixing does the same kind of summing

over a small range of CMPs.

Bandpass filtering—removes high- and low-fre-

quency noise from traces.

Carefully processed gathers from the welllocations show the difference between theAVO signature of gas and that of high-veloc-ity basalt. Gas shows the now-familiarincrease of amplitude with offset, whilebasalt shows a decrease.

AVO effects may also be tracked across areservoir to delineate a fluid contact. A tech-nique developed by Ed Chiburis, while atSaudi Aramco, has had remarkable successdelineating Saudi Arabian oil reservoirs.6 In26 of 27 cases, the technique predicted thepresence or absence of oil, which was laterconfirmed by drilling (next page, bottom).

The technique identifies changes in AVObehavior along a seismic line, and associ-ates those changes with changes in fluidcomposition. Once a given fluid has beenidentified in a well, the AVO behavior of thegather at the well is defined as the standardto look for elsewhere in the section.

To overcome the lack of true amplitudeprocessing in most data, Chiburis developeda normalization technique using anotherreflection that shows consistent amplitudein the section as a reference. Peak ampli-tudes of the target reflection in each AVOgather are picked interactively on a worksta-tion and normalized trace by trace to thereference event. Use of a reference eventremoves or minimizes amplitude distortionassociated with flaws in acquisition andprocessing. The technique also circumventsthe need for synthetics. The measured AVOresponse at the well serves as the standard.The major limitation of this method is thatthe geology and stratigraphy must be well-known in order to associate changes inAVO with changes in fluid type.

Another clever AVO analysis techniquepracticed by Amoco is to display and com-pare seismic sections made up of partialstacks (next page, top). Here, AVO informa-tion—or fluid discrimination informa-tion—masked by a full stack, is retained in apartial stack of the far offsets. A partial stackis similar to a full stack, except that eachtrace is the average of traces in a smallrange of offsets rather than all offsets in theCMP gather.

48 Oilfield Review

Processing for AVO Interpretation

Any properly acquired seismic survey, new or old, can be processed for AVO analysis. The goal of

processing is to preserve reflected pulse shape and amplitude. Changes in pulse with offset can then

be interpreted in terms of lithology or fluid contrasts at the reflector. Data destined for stratigraphic

interpretation or lithostratigraphic inversion (see “Structural Imaging: Toward a Sharper Subsurface

View,” page 28) also benefit from true amplitude processing. Every seismic data set creates its own

processing problems, requiring a tailor-made processing sequence. Here is a typical AVO processing

sequence, one that works for the data sets described in this article.

6. Chiburis EF: “Studies of Amplitude Versus Offset inSaudi Arabia,” Expanded Abstracts , 57th SEG AnnualInternational Meeting and Exposition, New Orleans,Louisiana, USA (October 11-15, 1987): 614-616.

1. The GRT technique is described in Beylkin G, Miller D andOristaglio M: “The Generalized Radon Transform: A Break-through in Seismic Migration,” The Technical Review 35, no. 3(July 1987): 20-27.

I R A QI R A N

S A U D I A R A B I A

A R A B I A N G U L F

KUWAIT

QATARRiyadh

Known reservoirs

AVO locations

Dhahran

km

miles

Line

1

Line 2

Line 3

Line 4

Line 5

km

miles

Known extentof reservoir

0 200

0 125

0 10

0 6.2

nSaudi reservoirs, showingdelineation of spatialextent of a hydrocarbondiscovery using Chiburis’relative event AVO tech-nique. In the inset, the yel-low area under the curvesshows where AVO indicateshydrocarbon. Based onAVO analysis and the localgeology, the interpretationof the reservoir extent isshaded in dark green.

Where is AVO going?Some companies use AVO routinely in anattempt to reduce risk associated withpotential drilling locations. Others havetried the technique and found the process-ing too time-consuming or too difficult. Anincreasing number of practitioners is insist-ing on quantitative agreement between syn-thetic and observed data before they willuse the technique. Currently, most examplesof AVO interpretation are qualitative. In theRoyal Oil & Gas example (page 46, middleand bottom), the qualitative match betweenthe two is good, but quantitatively, the syn-thetics predict a 100% increase in ampli-tude with offset while the data show anincrease of more than 200%.

Eliminating the discrepancy betweenobserved and synthetic data is therefore afocus of AVO-related research, and toucheson five main topics—processing, syntheticmodeling, petrophysics, interpretation andinversion.

Researchers seek a true amplitude pro-cessing scheme to produce AVO data tracesthat can be compared quantitatively to com-puter-perfect synthetics. Conventional pro-cessing for structural imaging does not pre-serve amplitudes. Researchers are revisiting

nNow you see it, now you don’t—a far offset stack of 2D offshoredata reveals hydrocarbons masked in conventional full stack.Plotted in two-way time, brighter colors indicate higher reflectionamplitude. Red and yellow are positive polarity, green and bluenegative. Insets show offsets stacked to create each section. Bedsdipping to the right are the only structure visible in all but the far-offset case. A flat spot is circled (above, left), indicating a fluid-fluid contact cutting across the dipping layers. (Courtesy of Rod VanK-oughnet and Chuck Skidmore, Amoco Production Company.)

49January 1993

Far offset stack Near offset stack Full stack

1.5

1.9

Tim

e, S

ec

basic processing steps such as deconvolu-tion, velocity analysis and migration with aview to AVO applications.

Current research in synthetic modelingaddresses a wide range of topics. Syntheticsare only as good as what goes into them.How should logs sampled every 6 inches[15 cm] be “averaged,” or blocked, to pro-duce layered earth models? Different block-ing techniques produce different synthetics.What is the effect of layer thickness on AVOsynthetics? The right combination of layerthickness and seismic wavelength gives riseto reverberations in the layer that alterreflected amplitude. Can seismic energy bemodeled as simple rays, or is it better to useseismic wave theory? In the examples pre-sented above, ray theory was enough. Butwhen angles become large and velocityvariations complex, more computer-inten-sive wave theory is necessary. How doesvelocity anisotropy affect AVO? As angle ofincidence increases, differences betweenhorizontal and vertical velocities cannot beignored in earth models.

In general, petrophysics is the linkbetween earth models and any seismicinterpretation, but it is particularly importantin AVO interpretation. Changes in porosity,mineralogy, cementation, stress, com-paction or other properties that modify thevelocity or density of the rock, can give riseto AVO signatures that mask fluid effects.Changes in fluid saturation, on the otherhand, may exhibit no change in AVO signa-ture. For example, in shallow or unconsoli-

dated sands, or overpressured zones, theAVO response is about the same for all satu-rations. Drilling will confirm the presence ofgas, but it might be just “fizz water.” Labora-tory and field measurements on reservoirrocks, and especially nonreservoir rocks,under in-situ conditions, are crucial to theconstruction of a reliable earth model.Improved understanding of rock propertiesat core, log and seismic scales will lead tomore unambiguous AVO interpretation.

Standard AVO interpretation fits reflectionamplitudes to straight line approximationsof Zoeppritz prediction curves. More refinedinterpretations quantify goodness-of-fit orother statistical analyses of the fit. Work isunder way to abandon the straight-lineapproximation and fit the real curve.

A great deal of research is devoted toinversion, the attempt to derive a likelyearth model starting with real data—theinverse of synthetic modeling. To date,results indicate that knowledge of the Vp /Vsratio is required for stable inversion. Some-times Vp can be estimated from seismicstacking velocities, but Vs cannot. Full inver-sion of AVO data for material propertiescontinues to intrigue researchers, but it hasyet to be proven feasible.

What is the future in AVO? One hot topicis three-dimensional (3D) AVO. Many oper-ators have already successfully interpreted3D seismic data sets for AVO by assemblingtwo-dimensional (2D) AVO sections inseries. Few have tried real 3D AVO, that is,considering source-receiver paths in differ-ent azimuths. This requires knowing veloc-ity anisotropy in the horizontal plane.

Time-lapse AVO is another topic thatshows promise. As a reservoir is produced,fluid contacts will move. Seismic surveysshot at different times can be analyzed forfluid changes using AVO techniques. Infor-mation about drained and undrained vol-umes can affect development and produc-tion plans.

AVO can be a powerful tool for hydrocar-bon detection. Although experts may com-prehend the theory behind AVO interpreta-tion, unwary practitioners make mistakes.Progress has been made in modeling, pro-cessing and interpretation, but improve-ments need further joint efforts from the seis-mic, logging and petrophysics communities.

—LS

50 Oilfield Review