Application of 3C/3D converted mode reflections, King County, Texas

Michael V. DeAngelo1 and Bob A. Hardage1

Abstract

We used a 3C/3D seismic reflection data set from King County, Texas, to investigate the utility of multi-component seismic data for improving reservoir characterization. We evaluated a new seismic processing/interpretation option, based on direct-S modes generated by a vertical-force source. This new seismic mode,SV-P, may allow legacy 3D P-wave data to be reprocessed to create converted-wave data without the need foradditional data acquisition costs associated with multicomponent surveys. Using traveltime and amplitudeanalysis, P-P, P-SV, and SV-P reflectivity was compared to determine which seismic mode might give a clearerpicture of the subsurface and subsequently reduce exploration risk.

IntroductionWe used a 3D multicomponent (3C/3D) seismic sur-

vey in King County, Texas, to evaluate potential pro-spective oil and gas reservoirs. In addition, a newconverted-wave mode (SV-P), based on direct-S modesgenerated by vertical-force sources, was used for com-parison with the more familiar P-SV converted-wavemode. There appear to be only two discussions (Frasierand Winterstein, 1990; Guy, 2004) in geophysical liter-ature that consider the SV-P mode as a means of imag-ing geology. Both of these investigations use horizontalvibrators, not vertical vibrators, to generate SV-P data.The objective of this study was to determine how SV-Pdata produced by a vertical vibrator compared to P-SVdata generated by the same source and to evaluate ifthis novel SV-P data processing approach could addvalue to reservoir characterization. The generation ofSV-P data was based on the theory of a downgoingSV-wave created by a standard P-wave source, in addi-tion to the standard downgoing compressional wave. Ata reflection point, this downgoing SV-wave converts toan upgoing compressional wave, and the upgoingP-wave is recorded by a traditional vertical geophone.

Geology and stratigraphyThe Pennsylvanian lithostratigraphic units of the

study area are the Cisco, Canyon, Strawn, and BendGroups in descending order of depth (Figure 1). Withinthe 3C/3D seismic survey measured, unit-top depthsaverage 1106.42, 1423.42, 1612.39, and 1746.50 m(3630, 4670, 5290, and 5730 ft), respectively. Brown(1962) extensively maps the Cisco Group from outcropsand characterizes the Lower Cisco unit as channel sand-

stones. He describes the shales in the Cisco Group asrich in marine organic content. Limestones are de-scribed as thin, but the zone overlying the Lower Ciscosandstone shows some local thickening. Although theCisco sandstone has minimal oil accumulations (e.g.,the adjacent Johnson oil field), it has produced eco-nomic quantities of gas (Brister et al., 2002). The Can-yon and Strawn sandstones are described as lenticular,indicating a different deposition environment. Thelower Bend Group, known locally as the Bend Con-glomerate, is described as generally dominated by sili-ciclastics interpreted to be of fluvial and deltaic origin(Lahti and Huber, 1982; Maharaj and Wood, 2009). TheBend Conglomerate has historically been a major pro-ducer of hydrocarbons in the area (Hentz et al., 2012).

MethodsData acquisition

Several 3C/3D seismic acquisition designs wereproposed for this study. Figure 2 shows the (a) finalacquisition design and (b) resulting actual (postplot)source deployment. The study area covered 12.51 km2

(4.83 mi2) with receiver line intervals of 251 m (825 ft),receiver group intervals of 50 m (165 ft), source line in-tervals of 251 m (825 ft), and source station intervals of50 m (165 ft), respectively. Vertical vibrators were usedas seismic sources, and the receiver (recording) patchwas 18 lines with 90 stations of single multicomponent(3C) geophones. In addition, a conventional P-wave(P-P) 2D seismic profile was incorporated to permit anearby calibration well with sonic logs to be used forsynthetic seismogram matching with the 3C/3D seismicdata.

1The University of Texas at Austin, John A. and Katherine G. Jackson School of Geosciences, Bureau of Economic Geology, Austin, Texas, USA.E-mail: mike.deangelo@beg.utexas.edu; bob.hardage@beg.utexas.edu.

Manuscript received by the Editor 18 November 2013; revised manuscript received 14 January 2014; published online 22 April 2014. This paperappears in Interpretation, Vol. 2, No. 2 (May 2014); p. SE39–SE45, 10 FIGS.

http://dx.doi.org/10.1190/INT-2013-0181.1. © 2014 Society of Exploration Geophysicists and American Association of Petroleum Geologists. All rights reserved.

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Special section: Multicomponent seismic interpretation

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Data processingThe P-P data processing was completed to a final

migrated stack before P-SV/SV-P data processing wasinitiated. Conventional P-P data processing methods,

using common midpoint (CMP) binning, provided im-portant static corrections and stacking velocities thatwere subsequently incorporated into the P-SV/SV-P dataprocessing flows. As Figure 3 may suggest, CMP bin-ning will not work for P-SV data imaging. Instead, theconverted-wave data relied on asymptotic conversionpoint (ACP) binning as outlined in Hardage (2012).An ACP is a P-SV image coordinate when data from sev-eral source-receiver combinations are binned to imagethe subsurface point where the trend of common-conversion-point (CCP) image coordinates for eachbinned source-receiver pair becomes quasivertical.

Figure 3 illustrates the particle displacement vectorsassociated with each raypath of P-SV and SV-P used inACP binning. For a given offset, the ACP position forthe P-SV raypath (ACP1) is closer to the receiver loca-tion than to the source station. In contrast, the ACP po-sition for the SV-P raypath (ACP2) is closer to thesource. Note that the SV-P data are recorded by avertical geophone because the upgoing raypath is aP-wave. Compare this sensor requirement with P-SVdata recording, which requires 3C geophones becauseSV displacement vectors are perpendicular to upgoingSV raypaths. This use of SV-P data allows older vintagesingle-component P-P data (e.g., conventional 2D/3Dseismic surveys) to be reprocessed to extract valuablemulticomponent mode data for additional analysis,without the need to acquire a multicomponent survey.

In this study, SV-P data processing was based on tra-ditional converted-wave (P-SV) processing parameters.SV-P binning was done by inverting the VP∕VS velocityratio used in P-SV binning. If a VP∕VS ratio of 2 is usedto bin P-SV data, the ratio is inverted to 0.5 to bin SV-Pdata. A VP∕VS ratio less than 1.0 is physically unreason-able but is valid for seismic binning purposes. By apply-ing P-SV velocities and statics and running oneadditional pass of surface-consistent statics, a SV-P datavolume was generated that was similar to the P-SV dataset. A strong reflection event at 500 ms (P-P final stack)was used to register/tie the data between the P-P waveand P-SV data, and a P-P event at approximately1000 ms was used as a secondary event for registration.For simplicity, the P-SV wave data were binned using aVP∕VS of 1.6 because that ratio gave the best stack re-sponse at the zone of interest (Lower Cisco sandstone),even though there was evidence that a variable VP∕VSfunction could have been used.

Spectral analysisSpectral analyses of the three time-domain volumes

(Figure 4) reveal that the frequency content of the P-Pand P-SV data volumes are broadband in nature. The P-P frequency spectrum between 10 and 85 Hz showed adominant frequency at 48 Hz, with a secondary peak at40 Hz. The conventional converted-wave (P-SV) had afrequency spectrum from approximately 18 to 40 Hz,a bandwidth spanning only 2 octaves. The SV-P data vol-ume had a broader spectrum range of 10–55 Hz, a band-width of approximately 2.5 octaves. The SV-P spectrum

Figure 1. Generalized stratigraphic column of the study area(Brister et al., 2002).

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was reasonably flat but exhibited an amplitude spikeat 15 Hz (dominant frequency). No effort was madeto suppress this spike and achieve a smooth, whiteSV-P spectrum. We can only speculate as to the causeof the frequency effects in the SV-P data. One possibilityis that the downgoing shear wave has a dominant 15 Hzcomponent, which causes the reflected compressionalwave to also have a dominating 15 Hz component. Inaddition, reduced energy at higher frequencies maybe due to not having correct velocity constraints and/or static corrections.

Correlation methodsThe greatest problem posed to the interpreter of con-

verted-wave data is correlating events with P-wave data(DeAngelo et al., 2003). In this study, we have an addi-tional converted-mode (SV-P) to integrate into the inter-pretation and evaluation of potential reservoirs. Adipole sonic log was recorded in a well outside the3C/3D survey area. In addition, a previously recorded2D seismic line that intersected this well (Figure 2)extended into the 3C/3D area, making it possible todo a robust correlation between the P-P wave 2D lineand 3D P-P data volume with minimal time shifting(Figure 5).

The 3C/3D study had no VSP data or shallow sonic(dipole) logs within the 3D image space, making a ro-bust correlation between P-wave and converted-wavedata sets difficult. As a result, the main method of cor-relating P-P reflectors to P-SV and SV-P data was to useinterpreter judgment to correlate events between thedifferent data modes in section view. These data hadno geometric features such as structural (faulting) orstratigraphic (lap-outs) terminations that could providea correlation “nail” point. However, comparing seismicreflector packages that have similar cycles of strongand weak reflections permitted us to achieve an appar-ent good correlation between P-wave and converted-wave data sets. The importance of a robust correlationcannot be overemphasized. An incorrect correlationwill lead to erroneous seismic-based attributes (root-mean-square [rms] amplitude ratio, VP∕VS ratio, etc.)that cannot be analyzed with a high degree of confi-dence or accuracy.

Figure 3. Comparison of P-SV and SV-P raypaths (modifiedfrom Hardage, 2012).

Figure 4. Comparison of P-P, P-SV, and SV-P frequency spec-tra extracted from each processed 3D seismic volume.

Figure 2. The 3C/3D seismic acquisition de-sign (a) before deployment with seismicsource stations (red) and geophone stations(blue) and (b) actual source station deploy-ment (black). Note the position of the ancillary2D P-P seismic line and calibration well.

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DiscussionFigure 6 shows cross-section views of the P-P, P-SV,

and SV-P seismic data along the same profile side byside for comparison. Time scales differ between theP mode and P-SV/SV-P modes; S-mode time axes havebeen compressed to roughly match reflectors on thethree sections. We use this method as a first-passapproximation to determine which reflectivity eventsmight represent the same stratigraphic interval in eachmode.

From a cursory first look, the Lower Cisco Sand-stones interval is imaged on all three data modes. Thisallowed robust horizon mapping in all three datamodes. There is a marked zone of signal attenuation,

starting at 1 s, in the SV-P data in the lower portionsof the seismic data volume, making any analysis ofthe more prolific Bend Conglomerate difficult. Conse-quently, any structural or attribute analysis below thislevel was not attempted. Given these characteristics,we conclude that the Lower Cisco sandstones wouldbe a good candidate for comparison of seismic attributeexpressions of P-P, P-SV, and SV-P data.

Historically, P-wave data have set the gold standardfor structural and stratigraphic interpretation in 3D seis-mic exploration. There have been substantial efforts toimprove processing algorithms in P-wave data that havenot yet been matched in the S-wave data arena. Conse-quently, interpreters will initially rely on P-wave data

Figure 5. P-P seismic 2D to 3D correlationwith interpreted horizons. Yellow arrows de-pict the Lower Cisco Sandstone interval, andblack arrows depict the Strawn interval. Col-ored lines are interpreted horizons.

Figure 6. Representative inline comparisonof P-P, P-SV, and SV-P seismic data. The LowerCisco Sandstone interval is indicated by theyellow arrow.

Figure 7. Comparison of P-P, P-SV, and SV-P seismic two-way time structure of the Top Lower Cisco Sandstone interval.

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results and use the S-wave data sets in an ancillarycapacity. Here, we used the P-P two-way time struc-tures as a control when comparing P-P data with P-SV and SV-P data. In addition, we wished to determineif P-SV and SV-P have similar characteristics when com-pared to each other. A favorable comparison would val-idate that the SV-P mode is as reliable as the P-SV mode.Figure 7 shows the results of two-way time structuremapping the top of the Lower Cisco Sandstone forthe P-P, P-SV, and SV-P data volumes, respectively.

The P-P data show a modest structural high of ap-proximately 6 ms in the southwestern corner of thestudy area that is associated with an interpreted carbon-ate buildup. The P-SV and SV-P maps, however, do notmatch the P-P time structure. The P-SV image shows noclosed structure at all. The SV-P data indicate a closedstructure but position the structure north of the struc-ture shown by the P-P data. The amount of SV-P closureis 8–10 ms, which would yield approximately the samevertical depth closure as indicated by the P-P data. Thislatter observation is based on using a VP∕VS velocityratio of 1.6, which results in a factor of 1.3 to equateP-P reflection time to SV-P reflection time (Chapter5, Hardage et al., 2011).

These variations in structure may be attributed toseveral things. Inaccurate S-wave receiver statics couldhave impacted the reliability of the processing. Fig-ure 2a gives an idea about the variation of the topogra-

phy within the study area. The variability (laterally andvertically) of the near surface has consistently plaguedthe S-wave processing community. Another possibilitywould be an erroneous VP∕VS ratio that would impactthe alignment of seismic reflectors, as explained inFrasier and Winterstein (1990). They show that varyingthe VP∕VS ratio during the processing of converted-wave data from 2.4 to 3.0 had a significant impact onthe lateral positioning of structural features (fault intheir case). Such lateral movements apply to all seismicreflectors including stratigraphic features, which woulddirectly impact any seismic attribute analysis. Figure 8illustrates this phenomenon and clearly highlights theimportance of robust VP and VS velocity analysis.

Seismic attributesSeismic attributes were extracted from a time inter-

val constrained between the interpreted top and bottomLower Cisco Sandstone horizons, which were mappedin all three data volumes. Figure 9 shows the rms am-plitudes calculated over their respective intervals (P-P,P-SV, and SV-P). The calculated amplitudes from allthree modes have different results. This is not a majorconcern when comparing attributes extracted from P-Pand P-SV or SV-P seismic data. In fact, we would expectthat the seismic attributes would be marginally differentif in situ fluids are present throughout the porous rocks(possible large in the presence of gas) or if there is

Figure 8. Imaging effects from using differentprocessing VP∕VS ratios on reflectors in theconverted-wave mode (modified from Frasierand Winterstein, 1990).

Figure 9. Comparison of P-P, P-SV, and SV-Pseismic rms amplitudes extracted from theLower Cisco Sand interval.

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significant anisotropy or shale variation within a studyarea. However, we expect similar attribute manifesta-tions between P-SV and SV-P modes. Observing suchsimilarity would help validate the concept of P-SVand SV-P mode equivalence we have introduced here.Unfortunately, such a correspondence did not happenwith these data. There are numerous possible reasonsfor such a discrepancy, but a few seem to be of firstorder: for example, the static estimations and velocityratio errors mentioned earlier when comparing the timestructure variations. In addition, perhaps poor velocitypicking resulted in spatial misalignment in the CCP bin-ning process. Any of these factors are possible. Regard-less, there are obvious concerns about the reliabilityof both the P-SV and SV-P mode data. Further investi-gations and trial and error will be needed to get theS-mode data sets up to a standard that allows the inter-preter to have confidence that what they are seeing rep-resents true subsurface geology.

An additional method of integrating multicomponentdata is to highlight the differences between P-P and P-SV/SV-P attributes. This can be achieved by calculatingratios of the respective attributes for a given interval ofinterest. Figure 10 is the result of dividing the P-P rmsamplitude by the SV-P and P-SV rms amplitudes, respec-tively. When comparing the images, there is a markeddifference in the final result. This was no surprise due tothe differences between the SV-P and P-SV rms ampli-tude responses.

ConclusionsThis study compared 3C/3D seismic images from P-

waves and two different converted waves. The ability toobtain a converted-wave seismic section from down-going S-wave generated by a vertical-force source(SV-P) opens up the possibility that legacy 3D P-waveseismic surveys could be reprocessed for converted-wave data. This would eliminate the need to acquiremulticomponent data from the field.

The converted-wave seismic volumes manifestedsome unexpected characteristics that were of concern.

First, time-structure interpretation var-ied significantly between the P-waveand converted-wave data. Both the P-SV and SV-P deviated from the P-P topLower Cisco sandstone control surface.The SV-P time structure did, however,compare more favorably to the P-P con-trol relative to the P-SV time structure.

Second, attributes generated fromcorrelated reservoir intervals in all threeseismic data sets varied significantly aswell. In this case, we hoped that the P-SV and SV-P attributes would be similar.That would validate the concept thatwe could extract converted-wave infor-mation generated from a vertical sourcerecorded into vertical geophones (con-

ventional 3D survey), avoiding the need for the moreexpensive 3C/3D seismic acquisition program. Regard-less, both converted-wave data sets needed additionalseismic processing to refine the final results.

Although our study had mixed results, this shouldnot discourage others from applying the same methodsin different geological settings or using more resourcesto ultimately improve this exciting concept.

AcknowledgmentsSupport for this work was provided in part by the

John A. and Katherine G. Jackson School of Geosci-ences and the Geology Foundation at The Universityof Texas at Austin. As an industry partner, BuckWheat Resources provided the 3C/3D seismic data;FairfieldNodal processed the digital data; and IHS,Inc., provided software for the basic 3C/3D seismic in-terpretation via the IHS Kingdom University Grant Pro-gram. Some of the illustrations were prepared with theassistance of J. Robinson and the BEG Graphics Sec-tion. Publication was authorized by the director ofthe Bureau of Economic Geology, The University ofTexas at Austin.

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Figure 10. Comparison of P-P/SV-P and P-P/P-SV rms amplitude ratios of theLower Cisco Sand interval.

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