Processing multicomponent surfaceseismic data for converted modeimaging is geophysically demand-ing. The usual challenges confrontingconventional P-wave processing arecompounded by the problems ofdetermining a second (shear) veloc-ity field, asymmetric raypaths, muchstronger anisotropy effects, and oftenincreased attenuation.

In this paper we review ourmethodology to build and calibrate ananisotropic (VTI), anelastic model at awell and discuss how this model isused to process multicomponent data.One benefit of our calibrated model-based approach is that the viability ofusing other propagation modes suchas PSs events can be easily assessed.Another benefit is that processing canhappen directly in depth, although amore conventional time-based pro-cessing sequence is also enhanced witha simplified workflow that is consis-tent for moveout correction and CCPbinning.

Arguing for borehole data integra-tion. Standard time processing of con-verted waves requires determiningtwo effective velocity fields to move-out correct and stack the Pp and Psdata, assuming an initial value for ver-tical VP/VS. Once this is done, theprocessor often correlates geologicevents on the two sections or volumesto obtain an improved vertical VP/VSratio in order to properly bin the datainto common conversion point (CCP)gathers. CCP binning, in turn, affectsthe Ps velocity analysis, so some iter-ation is needed. Alternatively, tech-niques now exist to scan the data forthe necessary VP/VS ratios for CCP bin-ning. Either procedure is interpretiveand time consuming.

In deepwater OBC cases, the prob-lem of CCP binning is exacerbated bythe further asymmetry introduced bythe water layer itself. This must bedealt with both for the Ps waves andthe Pp waves. Although full 3-D reda-tuming is desirable, in practice it is notoften applied. In such cases the effectof the water layer on binning must beaddressed.

There are situations where deter-mining either the P or Ps velocity field

is not possible without external infor-mation. In gas clouds, for example,compressional waves can be soseverely attenuated as to make veloc-ity picking impossible. Likewise,strong multimodes (PSs, PSps, etc.)and/or multiples can make it difficultto identify primary converted (Ps)events and hence determine a reliableconverted wave velocity field.

The problem of determininganisotropic velocity fields is of partic-ular importance, because moveout cor-rection is impacted and so also is theshift from midpoint of the CCP loca-tion. Clearly, converted mode pro-cessing presents a variety of uniqueproblems. Many problems would beobviated if an anisotropic velocitymodel were available in depth at anearly stage in processing. But how tobuild such a model? Even if effective

P and S velocity fields can be reliablydetermined, a single, consistentanisotropic velocity model in depthcannot be determined from surfacedata alone.

Enter the borehole. VSP measure-ments provide, among other things,the absolute time-depth relationship atwells, essential to anisotropic depth-based processing. Borehole data alsoprovide the log measurements neces-sary for accurate simulations and, ifavailable, walkaway VSPs allow forrelatively painless estimation ofanisotropy and Q. In some cases prop-erly designed and processed boreholesurveys may be the only source of reli-able velocity information.

Required borehole data. Borehole-cal-ibrated processing requires a suffi-ciently rich borehole data set to begin

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Borehole-integrated anisotropic processing ofconverted modes

SCOTT LEANEY, RICHARD BALE, MARK WHEELER, and SERGEI TCHERKASHNEV, Schlumberger, Gatwick,England, U.K.

Figure 1. Recommended borehole geophysical surveys for calibratedconverted mode processing. Dipole sonic logging, vertical incidence, offsetand walkaway VSPs are shown for (a) vertical and (b) deviated wells.

a)

b)

with, so it is useful to review whatdata are needed and how they areused. The archetypal borehole data setfor converted mode calibrationincludes dipole sonic logs, vertical inci-dence and offset VSP, and walkawayVSP. Recommended survey geome-tries are shown schematically in Figure1 for vertical and deviated wells.

The dipole sonic data provide com-pressional and shear velocities at highvertical resolution for accurate simu-lations (including pore fluid substitu-tion) and can also provide useful datafor overburden trends and empiricalrelations if logging is done shallowenough. Vertically incident VSP dataare required as usual for the vertical Pvelocity and sonic calibration. The off-set VSP data provide seismic scale

shear velocity information, a convertedwave corridor stack, mode conversionidentification, multimode (e.g. PSs)identification, and the best data for Qshear estimation. However, the offsetVSP provides converted mode propa-gation information for only one offset,so the offset must be selected with carethrough survey design.

Multioffset or walkaway VSP datashould be acquired to sufficiently longoffset to record a turning ray or max-imum direct arrival angle (foranisotropy estimation). Symmetriclines extending either side of the wellare recommended to enable dip cor-rection. The receiver array should beclamped just above the target reflec-tor(s) and preferably at another inter-mediate depth. Of course, longer array

tools or multilevel walkaways provideeven greater control for depth depen-dent medium properties.

The walkaway direct arrival timesprovide essential information to con-strain anisotropy models; effective Qvalues can be determined from thedowngoing waveforms and, after trueamplitude processing, measurementsof Pp and Ps AVO are possible. AVOmeasurements are important to vali-date the anisotropic elastic model, thisbeing done by matching simulationsto measurements. Different well tra-jectories call for different operations.

If the well is deviated, the offsetVSP is supplied by a source fixed at therig. The vertical incidence survey isthen supplied by the “walkabove” sur-vey with the source moving to stayvertically over the receiver as it ispulled up the well. In either case,acquisition is efficiently carried outsimultaneously with flip-flop shoot-ing. Offshore, because a source boat isrequired for the offset or walkaboveshooting anyway, walkaway lines canbe acquired at comparatively smallincremental cost.

This summarizes the recom-mended borehole surveys for cali-brated converted mode processing ifthe geology is predominantly strati-graphic in nature. The multicompo-nent processing results in this paperhave all benefited from borehole sur-veys as described above. Other projectswith different objectives may requireother surveys. For example, azimuthalanisotropy processing can benefitgreatly from crossed dipole sonic andmultiazimuthal walkaway data; depthimaging to determine complex struc-tures can benefit greatly from 3-D VSPdata. Benefits, costs, and geophysicalobjectives can only be balancedthrough presurvey design.

Given the availability of a suffi-ciently rich borehole data set, con-struction of a calibrated anisotropicmodel may begin. We follow amethodology to build and calibrate a1-D anisotropic, anelastic model usingall available borehole data and OBCdata near the well. The workflow hasfour main steps: (1) initial model build-ing, (2) vertical velocity calibration, (3)VTI calibration, and (4) Q calibration.

Building the initial model.As always,careful data preparation is of para-mount importance. Optimum, dis-persive sonic waveform processing,density log editing, and depth match-ing are some essential steps in log datapreparation. The initial compressionalslowness (DTc) model is built byextending the sonic through the over-

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Figure 2. Empirical relations used to build initial shear velocity model. (a)Calibrated mudrock line approach. (b) Compaction trend in logged VP/VSwith an optional constraint at the seabed.

Figure 3. Overburden vertical shear velocity calibration. Near-offset shallowPS reflections observed on radial component OBC common receiver data areflattened using ray-trace NMO correction. (a) Initial model (too fast) and (b)updated model.

a) b)

a) b)

burden using a compaction trend,regional check-shot informationand/or surface seismic Dix velocities.This extended P velocity model is thencalibrated using small offset VSP times.For simulations a density model isneeded, and this comes from theedited density log together with a cal-ibrated empirical (Gardner’s) relationfor the overburden. Over critical zonesa full density log reconstruction maybe necessary. Given the calibrated ver-tical compressional velocity and den-sity, we now seek the vertical shearvelocity model.

The initial shear model comes fromthe shear sonic, validated against seis-mic shear velocities picked from theprocessed horizontal components ofthe VSP and/or offset VSP. On land ashear source VSP may be available tocalibrate the shear sonic slownessesbut otherwise the procedure is moreone of “validation” than “calibration.”In vertical wells, we have found littledifference between dipole shear veloc-ities and picked VSP shear velocities,

probably due to the lower frequencyof the dipole shear sonic measurement;but in deviated wells polar anisotropycan cause the logged VS to be signifi-cantly elevated, necessitating someshear sonic adjustment. Above theshallowest VSP receiver the initialshear velocities could come from theoverburden VP using an empirical rela-tion like the mudrock line, but we havealso found it useful to extrapolate acompaction trend in VP/VS, con-strained to pass through some valueat the seabed. Seabed velocities maycome from geotechnical surveys andif the water depth is shallow enough,shear velocities can come from Scholtewave analysis. These can be used tobuild the initial model or to constrainthe empirical relations. Figure 2 illus-trates two empirical approaches toobtaining an initial overburden verti-cal shear velocity model.

Vertical shear calibration. In theabsence of a shear source at the seabed,and because one cannot always iden-

tify a sea bottom mode conversion onVSP data with certainty, no reliabledirect measurement of the overbur-den shear velocity is available. We cal-ibrate overburden vertical VS using thenear-offset moveout of shallow Psreflections on the OBC radial compo-nent. Ray-based moveout correctionis used to remove near-offset reflec-tion moveout by interactively varyingthe sea bed constraint on VP/VS or,equivalently, the individual layer over-burden shear velocities. A few itera-tions provide the overburden verticalVS macro model (Figure 3). Furtherfine-tuning of the vertical shear veloc-ities is carried out using the processedVSP Ps corridor stack or a Ps synthetic.Through small adjustments to over-burden VS, marker events are matchedwith either the NMO-corrected OBCcommon receiver gather or a radialcomponent brute stack (Figure 4).

The final step in building the cali-brated elastic model is to zone or blockthe compressional, shear, and densitylogs into layers. This is done with an

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Figure 4. Fine tuning of overburden vertical shear veloc-ity. The offset VSP PS corridor stack and/or convertedwave synthetic are shifted to match a marker event onthe converted-wave brute stack. The shift isimplemented by adjusting the vertical shear velocity.

Figure 5. The piecewise gradient anisotropy model usedfor VTI traveltime calibration. Anisotropy parametersare assumed to increase (or decrease) linearly with depthsubject to a shaliness threshold so that reservoir sandsmay be made isotropic (or weakly anisotropic throughBackus averaging if log data are available).

Figure 6. Direct walkaway traveltime residuals (dataminus model times) for five receivers at two depth set-tings. The isotropic (calibrated vertical velocity) modelproduces times that are too long by about 60 ms at maxi-mum offset.

Figure 7. The calibrated VTI model showing VP, VS, den-sity, ellipticity, and anellipticity parameters. Walkawaytimes at two depths have been used to determine amodel with piecewise gradient VTI parameter variation.

automatic algorithm followed by inter-active editing to ensure that majorlithologic boundaries have beenincluded. Slowness averaging is donewithin layers to produce the calibrated1-D elastic model.

Polar anisotropy (VTI) calibration.The above workflow leaves us with thevertical (isotropic) elastic velocitymodel. At this point we could attemptto determine polar anisotropy by min-imizing the residual long offset move-out of Pp and Ps reflections on OBCdata, or, as we have done here, we canuse the direct arrival times recorded bythe walkaway VSP. Walkaway VTI cal-ibration is done through a simple two-parameter traveltime inversion, whereSchoenberg’s ellipticity and anellip-ticity parameters vary linearly withdepth, starting at 0 at the seabed. AVP/VS shaliness threshold below whichanisotropy is turned off is a usefuloption to model reservoir sands, whichare probably isotropic or weaklyanisotropic. Figure 5 shows schemat-ically our piecewise gradient VTIanisotropy model. By minimizing themisfit between modeled and mea-sured direct P times, each layer in themodel is made VTI. If walkaways have

been acquired at multiple depths, apiecewise gradient model inanisotropy parameters can be deter-mined.

Figure 6 shows data and modeledwalkaway direct arrival time residu-als (measured minus modeled) for fivereceiver arrays at two different arraydepths. Zero-offset times are repro-duced with either the isotropic oranisotropic model, but the isotropicmodel predicts times that are too longwith offset. The difference between

isotropic and anisotropic residuals is60 ms at maximum offset. This actu-ally corresponds to rather mildanisotropy. The piecewise gradient VTImodel parameters are shown in Figure7: maximum ellipticity is .12 and max-imum anellipticity is .15. This layeredVTI model is valid for converted SVmodes because, given correct verticalP and S velocities, long offset P-wavemoveout is sufficient to estimate theVTI parameters governing SV propa-gation. We usually retain at least twomodels—one with fewer layers forprocessing and one with more layersfor simulations.

The impact of anisotropy. The impactof anisotropy on converted wave prop-agation is well documented but it isnonetheless interesting to look at someof the effects using our calibrated VTImodel. The first check is to validate theborehole-calibrated model against theOBC data. Figure 8 shows the rawradial component at the well withisotropic ray-trace and VTI ray-traceNMO correction. Figure 9 illustratesthe well-known effect of conversionpoint shift. The effect of polaranisotropy is to move the conversionpoint toward the midpoint. In this case

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Walkaway array levels

Figure 8. Ray-trace converted-wave moveout correction applied to a common receiver radial component gather near thewell. (a) Isotropic (vertical velocity) model. (b) Calibrated VTI model. The equivalent two-way times of the walkawayreceiver control points are indicated.

a) b)

Figure 9. Isotropic and anisotropicconverted-wave (PS) raypaths in thecalibrated model. The effect of polaranisotropy is to shift the reflectionpoint toward the midpoint, in thiscase by more than 200 m.Anisotropy is comparatively mild.

the shift is 200 m at 60° incident Pangle. The same phenomenon can beseen in the cross-spread fold plot inFigure 10. The effect of polar aniso-

tropy is to increase coverage atreduced fold.

Given the large impact of polaranisotropy on shear waves it is rea-

sonable to assume that there wouldbe a large impact on converted waveAVO as well. Figure 11 shows this tobe true. The impact of polar anisotropyis two fold. First, the anisotropic over-burden alters the offset-to-angle (rayparameter) mapping such that phaseangles are smaller for the same offset.Second, there is an impact on the reflec-tion coefficient due to the contrast inanisotropy across the interface. Thecombination of these two effects leadsto the dramatic differences in Figure11. Clearly any hope of quantitativeconverted wave AVO requires theinclusion of polar anisotropy.

Calibration for Q. VSP data can yieldaccurate estimates of anelastic attenu-ation or Q. Walkaway direct arrivalsare ideal for estimating effective Qbecause the geometry is essentially oneof a common depth point gather, so Qvalues thus determined should beideal to use in surface processing.

The shallowest walkaway yieldseffective Qp to surface; then intervalestimates are taken from the VSP andoffset VSP data. High-amplitude trans-mitted mode conversions on the off-set VSP are used to estimate Qs. Whenwe have confidence in the measure-ment, we usually find that Qs isslightly higher than Qp, and that Qpis indeed very low in gas clouds. Qsis undoubtedly very low very shallow,but we do not yet have any measure-ments of this. Figure 12 shows a walk-away VSP Qp estimation from deepwater West Africa.

Model-based processing. The cali-brated VTI model including Qp andQs can be used in a variety of ways andto great advantage in multicomponentprocessing. While we have shown theconstruction of a 1-D VTI model, thismay be too restrictive for many geo-logic settings. If multiple wells areavailable, VTI model construction canbe carried out at more control pointsand the model interpolated for use inprocessing. Alternatively the VTImodel in depth may be converted toan effective model in time and theneffective parameters determined fromthe multicomponent data movingaway from the well. As with prestacktime processing, the underlying veloc-ities must be slowly varying.

The steps where model-based pro-cessing is used to advantage are geo-metrical spreading and Q compen-sation, NMO correction, CCP binning,angle-based mute design and offset-to-angle transform for AVO analysis. Noredatuming is necessary because the

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Figure 10. Converted-wave fold map for (a) isotropic and (b) anisotropic mod-els computed using ray-tracing. The effect of polar anisotropy is to increasecoverage at reduced fold.

Figure 11. Primaries-only converted-wave synthetics after NMO correctionwith phase angle overlays. (a) Isotropic and (b) anisotropic.

Figure 12. Coherency Q inversion of walkaway VSP data. Downgoing scalarwaveforms are aligned based on direct arrival times. Waveforms and ampli-tude spectra are shown (a) before and (b) after inverse Q filtering with thebest effective Q value. Note the strong forward-scattered diffractions.

a) b)

a) b)

a) b)

receiver depth is explicitly input at theseabed. We have also used the local 1-D VTI model in a very simple depthimaging + AVO sequence.

We illustrate the flexibility of thisapproach with a subchalk imaging

example from the North Sea. Asalluded earlier, one advantage of amodel-based approach is the oppor-tunity to assess the imaging potentialof other modes. In the vicinity of thewell, Pp imaging of the subchalk tar-

get was poor. It was also known thatthe P-impedance reflectivity was lowso a 2-D OBC line was acquired toinvestigate the possibility of using con-verted waves. Several attempts at con-verted wave processing also yieldeddisappointing images, thought now tobe because of strong near-offset mul-tiples and multimode propagation.Encouraged by observations in the off-set VSP, we simulated a PSs mode withtransmitted mode conversion occur-ring at the top chalk interface. It hadstrong amplitudes but at longer offsets.Ray-trace moveout correction usingour calibrated VTI model and theselected PSs mode flattened events atthe same offsets where simulationspredicted they should be. Meanwhilemodel-based Ps NMO produced nocoherent flat events (Figure 13).

When the reflection does not coin-cide with a mode conversion, it is nolonger correct to refer to it as CCP bin-ning but CRP (common reflectionpoint) binning. We did this for the PSsmode followed by a model-basedangle-band mute before stack. Wefound that the image was improved byincluding a stack of small angle datawith flipped polarity, as predicted bysimulations. The PSs stack was thenconverted to depth using the model.The result is shown in Figure 14 alongwith the shear impedance model atthe well. In spite of the presence ofsome regional dip, a laterally invari-ant model produced the best subchalkimage to date at this part of the line.

The previous study illustrated theflexibility of the borehole-calibratedmodel-based approach to processing.It can also greatly simplify the pro-cessing sequence when depth migra-

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Figure 13. Ray-trace VTI NMO correction for (a) Ps and (b) PSs modes(where PS transmitted mode conversion occurs at the top chalk interface).

Figure 14. CRP binning and stacking for the PSs mode together with theshear impedance log at the well.

a) b)

Figure 16. (a) Shear-wave reflectivity and (b) density reflectivity sections froma depth migration plus AVO analysis using the calibrated 1-D VTI model.

Figure 15. Calibrated model-basedmulticomponent AVO processingflow.

a)

b)

tion is used in place of NMO, CCP,DMO, migration, and depth conver-sion. We have used the borehole-cali-brated model for both Pp and Ps depthmigration followed by AVO analysis.The result is a simple and efficient pro-cessing sequence for slowly varyingvelocity fields. This simple processingworkflow is shown in Figure 15. Figure16 shows S impedance and densityreflectivity converted wave AVOattributes from a depth migration +AVO sequence.

Conclusions. Borehole-calibratedanisotropic velocity models in depthhelp obviate many problems in con-verted mode processing and can beused to improve survey design andinterpretation/validation. We haveshown the benefits of borehole dataintegration in the processing of con-verted modes because it has so manydifficult problems that borehole datacan help address, but conventionalprocessing and interpretation can ben-efit greatly too. We have shown resultsusing a locally 1-D VTI model but thebenefits to 3-D structural imaging areno less important.

The value of knowing somethingat only a few locations should not beunderestimated if it is known with cer-tainty. This is the case when diverseborehole data are turned into ananisotropic, anelastic model for seismicsimulation and processing. The bene-fits of integrating borehole data into aseismic project early on will be reapedthroughout the life of the project. Onlyif full use is made of a sufficiently richborehole data set will maximum valuebe harvested from the combined dataset.

Suggested reading. “Walkaway Qinversion” by Leaney (SEG 1999Expanded Abstracts). “Borehole-inte-grated surface seismic processing” byLeaney et. al. (PETEX 2000 Proceedings).“Approximate dispersion relations forqP-qSV waves in transversely isotropicmedia” by Schoenberg and de Hoop(GEOPHYSICS, 2000). “Converted-wavereflection seismology over inhomoge-neous, anisotropic media” by Thomsen(GEOPHYSICS, 1999). LE

Acknowledgments: We gratefully acknowledgeAmerada Hess, Chevron, TotalFinaElf, andUnocal for permission to show the data exam-ples. We would also like to thank our many col-leagues in the multicomponent and VSPsoftware development teams in WesternGecoand Schlumberger.

Corresponding author: leaney@slb.com

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