GEOPHYSICS, VOL. 71, NO. 2 (MARCH-APRIL 2006); P. E13–E23, 20 FIGS., 2 TABLES.10.1190/1.2187730

Annual Meeting Selection

HFVSTM: Enhanced data quality through technology integration

Christine E. Krohn1 and Marvin L. Johnson1

ABSTRACT

Known problems with vibroseis data include difficult-to-pick and inaccurate first-arrival times, poor well ties,correlation side lobes, harmonic ghosts, and couplingdifferences. Also, to reduce acquisition costs, variousmethods are used to record and then separate data fromdifferent source locations using vibrators sweeping si-multaneously, but these methods suffer from poor dataseparation and harmonic contamination. A novel com-bination of heritage Mobil High Fidelity Vibratory Seis-mic (HFVS) and heritage Exxon vibrator technologiessolves these problems with vibroseis data. The methodinvolves vibrator separation combined with vibrator sig-nature deconvolution in such a manner that the outputis minimum phase and matches impulsive data. Vibratorsignatures are calculated from the vibrator accelerome-ter measurements. The signatures from multiple vibra-tors and multiple sweeps are used to design a filter thatoptimally separates the data from each vibrator and re-places the signatures with a specially designed impulseresponse. Specific procedures are included to reduce theeffects of inversion noise, which can distort the phase.

HFVS recording can be used to increase productionrates and reduce acquisition costs or to increase spatialsampling and improve data quality. Data recorded frommultiple vibrators sweeping simultaneously can be sep-arated by at least 60 dB. After separation, the data fromeach vibrator can be processed as unique source points.Compared with traditional vibrator arrays, individuallyprocessing each source point can result in better dataquality by reducing intra-array effects and improvingthe mitigation of ground-roll noise.

Presented at the 73rd Annual International Meeting, Society of Exploration Geophysicists. Manuscript received by the Editor February 1, 2005;revised manuscript received June 17, 2005; published online March 6, 2006.

1ExxonMobil Upstream Research Company, P.O. Box 2189, Houston, Texas 77252-2189. E-mail: chris.e.krohn@exxonmobil.com; marvin.l.johnson@exxonmobil.com.c© 2006 Society of Exploration Geophysicists. All rights reserved.

INTRODUCTION

With the merger of Exxon and Mobil Corporations, theneed arose to integrate the two companies’ vibrator technolo-gies. Each technology solves different problems with conven-tional recording, so the integration is not as simple as usingboth together. Exxon processes for correlated data cannot beapplied directly to Mobil inversion filtering processes. The in-tegration of these technologies improves on both. In addition,the integration solves known problems with conventional vi-brator processing, such as the match to dynamite data andphase issues with spiking deconvolution, are well documentedin the literature (Gibson and Larner, 1984; Baeten and Zi-olkowski, 1990).

In this paper, we discuss the prior Exxon and Mobil vi-brator technologies. Then we focus on a single vibrator toillustrate the inversion process, wavelet shaping, and the de-sired minimum-phase output. The final sections discuss vibra-tor separation and the advantages of processing the data fromeach vibrator as unique source points.

Heritage Exxon shaped-sweep technology

Heritage Exxon technology (Trantham, 1994) incorporatesa nonlinear shaped sweep (Andersen, 1994) with an amplitudespectrum that, after correlation, results in a simple waveletwith side-lobe energy reduced by at least 40 dB. These spe-cially designed sweeps are loaded into the vibrator control sys-tem in the field. Autocorrelations of a linear 6–96-Hz sweepand a 36-Hz shaped sweep are shown in Figures 1a and 1b; theamplitude spectra are shown in Figure 1e. The autocorrela-tion of a shaped sweep is a Ricker wavelet (Trantham, 1993a).The field technique also includes phase rotation of the shapedsweep to suppress harmonics (Rietsch, 1981). Typically, foursweeps with phase rotations of 0◦, 90◦, 180◦, and 270◦ are uti-lized, followed by correlation and stack.

E13

E14 Krohn and Johnson

The second part of the technology is vibrator signature de-convolution (Trantham, 1993b), in which an operator is de-signed from the sweep and used to convert the data to min-imum phase after correlation (Figures 1c and 1d). With theshaped sweep, a correction is made only for phase, minimiz-ing problems with inversion noise; with the linear sweep, theamplitude is shaped as well. In addition, geophone data arerotated by 90◦, which applies a phase correction correspond-ing to a time derivative. As seen in Figures 1c and 1d, the de-convolved autocorrelation wavelets are causal with no energyrecorded before zero time. The time-derivative correction iswell known; both theory and experiments show that geophonedata should be in phase with the time derivative of the ground-force signals (Sallas, 1984; Baeten et al., 1987; Baeten andZiolkowski, 1990). A reasonable estimate of the ground-forcesignal, used in vibrator-control electronics, is a mass weightedsum of accelerations measured on the baseplate and reactionmass.

The use of shaped sweeps and vibrator signature deconvolu-tion results in clean, approximately minimum-phase waveletswith large first lobes. The data can be used to pick first-arrival times, which match those of dynamite data. In addi-tion, the phase is optimized for subsequent processing. Theuse of statistical spiking deconvolution can result in phase er-rors if the input is not minimum phase. Correlated vibratordata are mixed phase because the correlation process, whichis zero phase, is combined with the earth filter, which is mini-mum phase. The use of amplitude shaping in the field followedby a phase correction by vibrator signature deconvolution re-sults in approximately minimum-phase data. After statisticaldeconvolution and final processing, the data are converted tozero phase for interpretation.

Figure 1. Autocorrelation of (a) a linear sweep and (b) ashaped sweep as well as a vibrator signature deconvolution of(c) linear and (d) shaped sweeps. The side lobes for the shapedsweep are reduced much more than for the linear sweep. Af-ter deconvolution, the autocorrelation wavelets are minimumphase and casual. (e) Deconvolution includes shaping the am-plitude spectrum for the linear sweep but not for the shapedsweep.

Heritage Mobil HFVS technology

Heritage Mobil technology (see Allen et al., 1998) is re-ferred to as High Fidelity Vibratory Seismic (HFVSTM), a li-censed Exxon Mobil technology. Instead of correlating thedata with the pilot signal, which is only an approximation ofthe signal imparted into the ground, the data are inverted us-ing recordings made of the actual vibrator motion, such asthe vibrator weighted-sum signal. These recordings includeharmonics and vibrator nonlinearities, which are part of therecorded signal and are included as part of the signature ininversion.

HFVS technology also includes the capability to separateoptimally data from multiple vibrators operating simultane-ously (Sallas et al., 1998). Each vibrator is assumed to radiatea signature into the ground, and each signature is convolvedwith a different earth reflectivity sequence for the vibrator po-sition. The earth sequence can include reflectors, multiples,and near-surface effects. A trace d recorded at a geophone isa sum of the convolutions for all vibrators. The data trace di(t)recorded for sweep i as a function of time t is

di(t) =N∑

j=1

sij (t) ⊗ ej (t), (1)

where sij (t) is sweep i from vibrator j, ej (t) is earth reflectivityseen by vibrator j, and ⊗ denotes the convolution operator. Inthe frequency domain, this becomes

di(f ) =N∑

j=1

sij (f )ej (f ). (2)

In the rest of this paper, all variables are in the frequency do-main. In matrix form for M sweeps and N vibrators, equation 2is

s11 s12 · · · s1N

s21 s22 · · · s2N

s31 s32 · · · s3N

s41 s42 · · · s4N

......

......

sM1 sM2 · · · sMN

e1

e2...

eN

d1

d2

d3

d4...

dM

(3)

or

Se = d. (4)

If the number of sweeps is equal to the number of vibrators,this system of simultaneous equations can be solved for e:

e = Fd, (5)

where

F = (S)−1. (6)

The term F is the filter or operator that, when applied to thedata, separates it into individual vibrator records.

If there are more sweeps than vibrators, then the solution isdetermined by least squares. The normal equations are

S∗Se = S∗d, (7)

HFVS: Enhanced Data Quality E15

where S∗ is the conjugate transpose of S. Solving for the earthresponses gives

e = (S∗S)−1S∗d. (8)

A separation-and-inversion filter can be designed from all ofthe vibrator signatures. The filter is of the form

F = (S∗S)−1S∗. (9)

The filter is applied then to the data, resulting in separaterecords for each vibrator position.

To prevent the matrix (S∗S) from being singular, HFVSrecording includes phase encoding for each sweep. For exam-ple, it is sufficient to have one vibrator sweeping 90◦ out ofphase of the other vibrators for each sweep (Table 1). Afterseparation and inversion, subsequent processing steps includeminimum-phase bandpass filtering followed by statistical spik-ing deconvolution. The spiking deconvolution is used to esti-mate any differences between the true vibrator signature andthe measured vibrator motions. In addition, a model trace canbe processed with the data so that phase errors can be cor-rected.

TECHNOLOGY INTEGRATION

The goal of integrating these technologies is to obtain trueminimum-phase data with good S/N quality after separationand inversion without the need for a model trace. Our unpub-lished tests show that while shaped sweeps can be used withHFVS, a different strategy is needed to integrate the technolo-gies fully. Heritage Exxon techniques designed for correlateddata cannot be applied directly to inversion.

Inversion

The process of HFVS inversion can be understood from thefollowing equations. We assume the recorded data for a singlevibrator in the frequency domain d(f ) are given by

d(f ) = [(i2πf )s(f )]e(f )g(f ), (10)

where s( f ) is the ground-force signal, g( f ) is the geophone re-sponse, and e( f ) is the earth response. The factor (i2πf ) rep-resents the time derivative. If we apply a filter equal to 1/s(f ),we get(

1s(f )

)d(f ) =

([(i2πf )s(f )]

s(f )

)e(f )g(f ). (11)

Effectively, the filter removes the sweep function, and the re-mainder should be minimum phase because the derivative,

Table 1. Standard HFVS phase rotation for four vibratorsand four sweeps.

SweepVibrator

1 (◦)Vibrator

2 (◦)Vibrator

3(◦)Vibrator

4(◦)

1 0 0 0 902 0 0 90 03 0 90 0 04 90 0 0 0

earth response, and geophone response are minimum-phasefunctions.

A problem with inversion is that all frequencies are not rep-resented in the sweep. An inversion operator is shown in Fig-ure 2a for an 8–128-Hz linear sweep. The amplitudes at lowand high frequencies outside the sweep band are close to zero;thus, inversion applies a large gain at these frequencies. Theapplication of this inversion operator to vertical seismic profile(VSP) data is shown in Figures 2b and 2c. The inverted datain the time domain (Figure 2b) are obscured by low-frequencynoise, and the spectrum (Figure 2c) shows a 30-dB peak atthe lowest frequencies. Conventionally, prewhitening is per-formed by adding noise to the sweep to stabilize the inversionand prevent large gains. Adding 3% noise decreases the gain,but as shown in Figure 2a, an amplitude gain still exists at thelower frequencies, so bandpass filtering is needed.

The process of adding noise or prewhitening can distort thephase as can be referred from equation 11 and illustrated withmodeling results shown in Figure 3. Equation 11 becomes(

1s(f ) + noise

)d(f ) =

([(i2πf )s(f )]s(f ) + noise

)e(f )g(f ).

(12)

Figure 2. (a) HFVS inversion operator for a linear 8–128-Hzlinear sweep and (b, c) its application to VSP data. The opera-tor applies a large gain to any noise outside of the sweep band.Both the (b) time domain data and (c) frequency spectrumare dominated by amplified low-frequency noise. The opera-tor gain can be reduced by adding noise to the sweep beforeinversion (a).

E16 Krohn and Johnson

The process of adding noise makes an amplitude correctionto the data without the corresponding minimum-phase correc-tion. If the noise is large, the phase can be distorted. For HFVSdata, 3%–5% noise may be required, even when followed bymultiple bandpass filters.

Modeling results for a single-vibrator inversion are shownin Figure 3. The model includes attenuation and a geophoneresponse. The model response (Figure 3a) is minimum phaseand casual. The model is convolved with the derivative of ameasured ground force signal and inverted. Inversion with theground force (Figure 3b), as in the original HFVS method, re-sults in a wavelet that is close to minimum phase; however,the wavelet is ringy, even for noise-free model data. Invertingthe data by the ground force and doing a 90◦ phase rotation asin the shaped-sweep method (Figure 3c) does not yield thecorrect wavelet because the corresponding minimum-phaseamplitude correction is not made. Figure 3d shows the datainverted by the derivative of the ground force. Now thepulse matches that of the original. However, the addition ofprewhitening noise results in a small precursor. The data arenot rigorously minimum phase because the wavelet is notcausal.

Inversion with a vibrator signature that most closely match-es the signal put into the ground, such as the time derivativeof the weighted sum, results in cleaner pulses and requiresless prewhitening. If the added noise is large, however, phasedistortion is observed. Bandpass filtering also is required toreduce noise amplified by the inversion. The problem withadded noise in vibrator signature deconvolution is discussedin Bickel (1982) and in Gibson and Larner (1984).

Wavelet shaping

The integrated, improved solution replaces the inversionwith deterministic vibrator signature deconvolution using aspecially designed minimum-phase impulse response. Equa-tion 11 becomes(

w(f )[(i2πf )s(f )]

)d(f ) =

([(i2πf )s(f )][(i2πf )s(f )]

)w(f )e(f )g(f ),

(13)

Figure 3. Application of HFVS operators to model data show-ing (a) the original model, (b) inversion with the ground forceas with the original HFVS method, (c) phase rotation of 90◦as in the shape-sweep method followed by inversion with theground force, and (d) inversion with the derivative of theground force. Panel (d) shows the cleanest result and the bestmatch to the model, but a precursor related to the amount ofprewhitening noise is present.

where w(f ) is the impulse response or wavelet designed fromthe amplitude spectrum corresponding to a characteristic vi-brator signature. The amplitude of the impulse response ismade to be less than or equal to that of the vibrator signa-ture so that the resulting operator does not exceed 1.0 or 0 dB(Figure 4). The need for prewhitening is significantly reduced.The separation and inversion process now becomes a separa-tion and deconvolution process, and equation 9 becomes

F = (S∗S)−1S∗w. (14)

An impulse response is designed from the ground force orits derivative. Conventional linear sweeps can be used. The re-sulting wavelets are simple with large front lobes and can beoptimal in terms of bandwidth and pulse length (Trantham,1993b). Alternatively, the impulse response can be designedto generate broadband data, matching that achieved throughspiking deconvolution. Tests show that deconvolution with thederivative of the ground force removes the sweep from thedata and replaces it with the desired impulse response. Decon-volution with the ground force without the derivative removesthe sweep and replaces it with the derivative of the impulse re-sponse, as can be inferred from equation 13.

Figure 4. HFVS operator used to remove the vibrator signa-ture and replace it with the impulse response shown in (a) andits application to (Figure 2) VSP data (b and c). The operatoramplitudes are less than 0 dB, and no gain is applied to thedata outside of the sweep band.

HFVS: Enhanced Data Quality E17

Minimum-phase output

The goal of shaping is to obtain data that have first-arrivalswhich match those of impulsive sources and are minimumphase — optimal for subsequent processing. VSP first-arrivalsfor the integrated HFVS method match those for an impulsivesource as shown in Figure 5; precursors are smaller comparedto data correlated conventionally or inverted by the originalHFVS method.

In Figure 6a, we compare data recorded with a shapedsweep followed by correlation and conversion to minimumphase and data recorded with a linear sweep using the HFVStechnique and shaped to the same wavelet. The interleavedseismic traces (Figure 6b) show similar waveforms and compa-rable S/N quality. The main difference is in the first arrivals inthe gathers (Figures 6c and 6d). The HFVS data do not showthe precursor side lobes typically ob-served with vibrator data, and they aremore suitable for automatic first-breakpicking. Processing the data to stack alsoresults in data with similar phase and S/Nquality (Figure 7). In these tests the sameshaped wavelet is used for both tech-niques, but we have found that we canshape the HFVS data differently to im-prove resolution.

Finally in Figure 8, surface seismicHFVS data processed by these methodsand converted to zero phase after surface-consistent spiking deconvolution is shownwith a zero-phase VSP corridor stack. TheVSP corridor stack has been processedwith downwave deconvolution and shouldbe true zero phase. The VSP ties the seis-mic data with minimal need for time shiftsor phase rotations.

VIBRATOR SEPARATION

When multiple vibrators are used withHFVS, a filter can be designed usingequation 14 to provide separate outputrecords for each vibrator. The methodrequires that the number of sweeps begreater than or equal to the number of vi-brators. To ensure matrix solvability, dur-ing the sequence each of the vibratorsshould sweep, at least one time, differ-ently than the other vibrators. A phaserotation of 90◦ for each of the vibratorsduring one of the sweeps (Table 1) is suf-ficient for data separation and to keep thematrix S∗S in equation 14 from becomingsingular.

Harmonics are part of the vibrator sig-nature and become part of the signal in-stead of noise. However, we observe someresidual harmonics, which are not rep-resented in the measured ground-forcesignal and appear as harmonic ghosts inthe output. It is helpful to superimpose

Figure 5. Application of the different methods to VSP vibra-tor data compared to data recorded with an impulsive source.Shown are (a) the shaped-sweep method, (b) the originalHFVS method, (c) the integrated method, and (d) the resultsfrom an impulse. The impulse is generated by applying a pulseto the vibrator actuator. The integrated method has less pre-cursor and is the best match to the impulsive data.

Figure 6. (a) Shot records recorded with (left) a two-vibrator array and the in-tegrated HFVS method and (right) a four-vibrator array and the shaped-sweepmethod. The boxes correspond to zoomed images in (b) and (c). The traces matchwiggle by wiggle, seen in interwoven traces (b), in which the first trace in each pairis the HFVS method and the second is the correlated shaped sweep followed byvibrator signature deconvolution. (d) The first arrivals for the shaped sweep showthe side lobes normally associated with correlated vibrator data, but side lobes arenot visible with HFVS data (c). Ground roll is stronger on the HFVS data in thisexample because of the smaller source array.

E18 Krohn and Johnson

a phase rotation to suppress these residual harmonics Forexample, for four sweeps, phase rotations of 0◦, 90◦, 180◦,and 270◦ can be added to subsequent sweeps in Table 1 togenerate the phase rotations shown in Table 2. This phaserotation can give up to 20 dB suppression of the residual har-monic ghosts up to the fifth order (Rietsch, 1981).

Figure 7. Interwoven traces from stacks of HFVS data (firsttrace) and shaped-sweep data (second trace). There is an ex-cellent match of waveforms and S/N quality.

Figure 8. HFVS processed and stacked data converted to zerophase and compared to a VSP composite trace. The HFVSdata tie the VSP data without a time shift.

Offset VSP tests

As a first test, we compare two offset VSPs that were ac-quired individually and separately using HFVS. All recordingswere made with a downhole cemented array of 80 geophones.A vibrator was located at an offset of 300 m and was activatedto generate offset VSP data. A second vibrator was locatedat an offset of 450 m, and a second offset VSP was recorded.Then the two vibrators were operated simultaneously and therecords were separated using HFVS. Comparisons of the twoVSPs acquired with the two techniques are shown in Figure9. The data for each offset were subtracted; the amplitude ofthe subtracted record (the difference) is −40 dB, comparedwith the 0 dB amplitude of the first record. This differencecan be attributed partly to the difference from repeating the

Table 2. HFVS phase rotation plus rotation to suppressresidual harmonics.

SweepVibrator

1 (◦)Vibrator

2 (◦)Vibrator

3 (◦)Vibrator

4 (◦)

1 0 0 0 902 90 90 180 903 180 270 180 1804 0 270 270 270

Figure 9. Offset VSPs acquired individually and simultane-ously. Two vibrators were located at different offsets of (a)300 and (b) 450 m from the well and operated one at a time.Then they were operated simultaneously, and the recordswere HFVS separated. The amplitude of the difference in thetwo methods is less than −40 dB compared to that of therecords.

HFVS: Enhanced Data Quality E19

experiment. Even after removing the strong first arrivals andimaging the reflectors (Figure 10), there is little differencebetween separate or simultaneous acquisition of the vibratordata.

In a second test at a different site, we compare the resid-ual left on each record after separation from the other vibra-tors operating at the same time. This test was performed priorto recording a 3D VSP with four vibrators and an 80-levelreceiver tool. During the survey, HFVS was used to recordsimultaneously two vibrators centered at two different shot-points, reducing acquisition costs. To evaluate the separationeffectiveness, we located the four vibrators at offsets of 90,760, 1100, and 1500 m from the well and operated them simul-taneously. Separated HFVS data using eight sweeps are shownin Figure 11. The high-amplitude tube waves and first arrivalsvisible on the near-offset record (Figure 11a) are not visible inthe other records. P-wave and S-wave reflections are evidenton the far-offset data, but the tube waves corresponding to thenear-offset data cannot be located. The noise before the firstarrivals comes from a nearby gas plant. The process has sep-arated these events, showing no contamination of the recordsby the other vibrators operating simultaneously. We used f–kanalysis to search for linear tube waves on the far-offset datain a time window corresponding to the tube-wave arrivals on

Figure 10. Images made from the data shown in Figure 9 af-ter removing the first-arrivals and imaging the reflections us-ing VSP–common-depth-point transform for data acquired (a)separately and (b) simultaneously. The first image in eachpanel corresponds to a source offset of 300 m, and the sec-ond corresponds to a source offset of 450 m. There is littledifference between the images.

the near-offset data. They could not be observed and were be-low the background noise. Since the signal-to-ambient-noiseratio was approximately 60 dB, the data separation was at least60 dB in this example.

Surface seismic tests

Separation of surface seismic data is shown in Figure 12.Again, after separation the cross-contamination between vi-brator records is not evident and is below background noise.These data were recorded at the start of a 3D survey. The testinvolved locating four vibrators at the intersections of a re-ceiver line and different source lines. The vibrators were ap-proximately 130 m apart. When the data from a single sweepwere correlated, the records showed the superposition of datafrom the four vibrators (Figure 12a). After separation, thestrong first arrivals and ground roll from the different sourcescould not be located on the other records as in the separateddata for the second vibrator (Figure 12b). The separation ex-ceeds 60 dB (Figure 12c). One to two traces corresponding togeophones at the same stations as the vibrators are overdrivenand leave some noise on the separated traces.

Separation quality control for acquisition

It is important to monitor data quality during acquisition forall land operations. For HFVS acquisitional, standard vibratorattributes and the condition number from the matrix inversionin equation 14 can be used to monitor possible problems inthe separation process. The process is robust. In production3D surveys, we typically find only a few records that are noisyor show problems in separation. If a vibrator is not performingproperly and the ground-force signal becomes corrupted, thenfull separation may not be achieved, although the data stillmay be useable. In Figure 13, the first arrivals from the near-offset records are visible on the far-offset records. The vibra-tor signature (Figure 14) indicates that one vibrator has devel-oped a serious problem: The amplitudes in the middle of the

Figure 11. Data recorded using HFVS and four vibrators lo-cated (a) 90, (b) 760, (c) 1100, and (d) 1500 m away fromthe well and operated simultaneously. Strong direct arrivalsand tube waves visible from the near-offset vibrator record(a) cannot be located on the separated far-offset record (d).

E20 Krohn and Johnson

Figure 12. Surface seismic gathers recorded by four vibrators located 130 m apartalong one receiver line. (a) When the data from a single sweep are correlated, ar-rivals from all four vibrators are evident in the record. When the data are separatedusing HFVS, the first arrivals and ground roll from neighboring vibrators are notpresent in the record. Only the record for the second vibrator is shown in (b). (c)The HFVS data plotted on a decibel scale.

Figure 13. Separated data from two vibrators centered at anoffset of 90 m (a and b) and two vibrators centered at an offsetof 1500 m (c and d). In comparison to Figure 11, some of thefirst arrivals from the near-offset data are present on separateddata for the far offsets. Ground-force data are shown in Fig-ure 14.

sweep are half of the normal amplitudes,and the waveform shows a doublet. Evenso, the data are useable; reflections arereadily visible in the far-offset data.

With HFVS, it is important to trackthe geometry through the separation pro-cess because the number of records afterseparation can differ from those acquired.New SEGD file format standards, whichallow for multiple shotpoints per record,and recording systems in which vibratoraccelerometer and geophone records arerecorded together will facilitate HFVS ac-quisition and separation.

PROCESSING VIBRATORDATA AS UNIQUESOURCE POINTS

During conventional acquisition, datafrom vibrators operating simultaneouslyform a source array. There are advantages,however, in separating these data so thatunique records are obtained for each vi-brator. With HFVS, there is no increase insource effort and acquisition time. The costdifferential should be small and is associ-ated with recording vibrator motions andstoring data uncorrelated and unstacked.

Intra-array effects

CMP gathers of HFVS data after separa-tion can show a substantial intra-array ef-fect, especially in areas with large surfacerelief. Data from a sand dune and sabkhaarea with 60-m dunes are shown in Fig-ures 15–17. Prestack-migrated images (Fig-ure 15c) for HFVS are substantially betterwith improved reflector continuity and re-duced noise compared with those for con-ventional correlated data (Figure 15a). Part

of this improvement arises from the correction of intra-arrayeffects (Figure 15b). Data are shown for the negative offsetsof a CMP gather in Figure 16. There are several skips becausethe vibrators could not reach the top of the steepest dunes.The four traces close together are generated by separating therecords for the four vibrators at each source station. In con-ventional recording, the vibrators form an array, and therewould be a single trace. The vibrators are located bumper tobumper, and the pads are approximately 13 m apart. As canbe seen in Figure 16a, there are misalignments between eventsacross each set of four traces because of elevation changes anddifferential moveout between vibrator positions. In this exam-ple at an offset of 1.6 km, there is 12 ms of misalignment acrossthe 39-m array. Of this misalignment, 4 ms is caused by staticscorrections and elevation changes and 8 ms is caused by dif-ferential moveout. With conventional recording, these traceswould be summed by the array as shown in Figure 17a. WithHFVS, corrections can be made for intra-array statics (Fig-ure 16b) and NMO moveout (Figure 16c), resulting in better

HFVS: Enhanced Data Quality E21

alignment and more coherent reflections after the array sum(Figure 17b).

Figure 14. Vibrator signature data for the record in Figure 13,indicating a corrupted ground-force signal from vibrator fourfor (a) the waveforms and (b) the spectra.

Figure 15. Migrated images from a sand dune and sabkha en-vironment, comparing (a) conventional vibrator data with (band c) HFVS data. (b) Correction is made for intra-array ef-fects, an array sum is performed, and the data are prestack-migrated with 25-m CMP bins. (c) The fine trace spacing iscarried through migration. Correction is made for the intra-array effects, and the data are migrated with 6.25-m bins andoutput at 25 m. Correction of intra-array effects and migrationwith smaller bins both contribute to the imaging improvementover conventional data, especially noticeable between 1.8 and2.0 s.

Migration with greater spatial sampling

Further improvement for these data can be obtained by bin-ning the HFVS data at 6.25 m instead of the natural 25-mCMP bins. Kirchhoff prestack time migration was performedwith the smaller CMP bins (Figure 15c) and output with 25-mbins. This can be compared to Figure 15b, where corrections

Figure 16. Negative offsets for a CMP gather showing sub-stantial intra-array effects. The four neighboring traces arefrom data separated from four vibrators located 13 m apart.With conventional recording, these would be summed. Shownare the (a) raw data, (b) after static corrections, and (c) af-ter NMO. The data are better aligned for the array sum aftercorrections are applied.

E22 Krohn and Johnson

are made for the intra-array effects, array summed, and thenmigrated with 25-m bins. Gaps in the source coverage at thetop of the dunes result in poor noise attenuation by the stackafter migration. Migrating with the smaller bin size improvesnoise suppression in this example. Alternatively, the data canbe output with the smaller bin size.

Ground-roll suppression

HFVS recording with multiple vibrators at a small sourceinterval can be used to better sample and suppress strongground-roll noise. In the area shown in Figures 18–20, conven-tional recording is performed with four vibrators per station.Raw shot gathers after HFVS separation of the four vibratorsare shown in Figure 18. Ground roll is aliased by the receiverspacing for both the individual gathers (Figure 18a) and thearray sum (Figure 19a). If a supergather is constructed by sort-ing the separated data on station and offset, then the ground-

Figure 17. CMP gather from Figure 16 after the array sum.(a) The array sum is performed with the uncorrected datafrom Figure 16a followed by NMO and static correction. (b)after An array sum is made of the corrected data from Figure16c. Both positive and negative offsets are displaced withoutthe near-offset traces. The gather with intra-array correctionsmade before the array sum shows better reflector continuity.

roll noise is not aliased (Figure 18b) and can be suppressed. Aphase-match filter is used to remove ground roll, and then thefour records for each station are summed. Reflections are nowvisible under the ground roll cone (Figure 19b). Unmigrated

Figure 18. Shot gathers for separated HFVS data with fourvibrators per station. (a) The ground roll is aliased in the fourshot gathers. (b) If a supergather is constructed by sorting intostation and offset order, the ground roll is not aliased and canbe removed.

Figure 19. Array sums for the data in Figure 18, showing (a)the array sum followed by ground-roll suppression as in con-ventional recording and (b) ground-roll suppression using thesupergather followed by the array sum as can be done withHFVS. More ground roll can be removed, with the HFVS datashowing reflectors under the air blast.

HFVS: Enhanced Data Quality E23

Figure 20. Unmigrated stacks for an area with large ground-roll noise for (a) shaped-sweep data and (b) HFVS data.Ground roll can be removed better with the HFVS sampling(Figure 19), and the data also can be shaped to a greater band-width.

stacks show reduced noise and wider bandwidth from the useof HFVS (Figure 20).

CONCLUSIONS

Tests show that integrating heritage Exxon shaped-sweepand heritage Mobil HFVS technology improves data quality.The data after separation are minimum phase and matchthe data recorded with impulsive sources. Traveltimes can bepicked accurately for checkshot times, tomography, and staticcorrections. In addition, the phase is optimized for subsequentprocessing, and after conversion to zero phase it matches zero-phase VSP well data The S/N quality improves, and the needfor further bandpass filtering is reduced.

Optimal separation is achieved by HFVS through the designof a single separation filter based on all sweeps at a location.Separation is greater than 60 dB. This method gives the sur-vey designer increased flexibility. A survey can be designedtraditionally with three or four vibrators per source point, orit can be designed to have one vibrator per shotpoint witha decreased shot interval. Data quality can be improved bycorrecting for intra-array effects and improving noise suppres-sion. Alternatively, in good data areas single vibrators can belocated at each source point and the data collected simultane-ously, reducing costs.

This paper demonstrates the advantages of single-sourcerecording without arrays. There also should be advantages inreducing the size of receiver arrays. With larger channel-countrecording systems and with HFVS, the potential exists for fur-ther data-quality improvements with better sampling of bothsignal and noise.

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