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

We used a 3C/3D seismic reflection data set from King County, Texas, to investigate the utility of multicomponent 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 for additional data acquisition costs associated with multicomponent surveys. Using traveltime and amplitude analysis, P-P, P-SV, and SV-P reflectivity was compared to determine which seismic mode might give a clearer picture of the subsurface and subsequently reduce exploration risk. Introduction We used a 3D multicomponent (3C/3D) seismic survey in King County, Texas, to evaluate potential prospective oil and gas reservoirs. In addition, a new converted-wave mode (SV-P), based on direct-S modes generated by vertical-force sources, was used for comparison with the more familiar P-SV converted-wave mode. There appear to be only two discussions (Frasier and Winterstein, 1990; Guy, 2004) in geophysical literature that consider the SV-P mode as a means of imaging geology. Both of these investigations use horizontal vibrators, not vertical vibrators, to generate SV-P data. The objective of this study was to determine how SV-P data produced by a vertical vibrator compared to P-SV data generated by the same source and to evaluate if this novel SV-P data processing approach could add value to reservoir characterization. The generation of SV-P data was based on the theory of a downgoing SV-wave created by a standard P-wave source, in addition to the standard downgoing compressional wave. At a reflection point, this downgoing SV-wave converts to an upgoing compressional wave, and the upgoing P-wave is recorded by a traditional vertical geophone. Geology and stratigraphy The Pennsylvanian lithostratigraphic units of the study area are the Cisco, Canyon, Strawn, and Bend Groups in descending order of depth (Figure 1). Within the 3C/3D seismic survey measured, unit-top depths average 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 outcrops and characterizes the Lower Cisco unit as channel sandstones. He describes the shales in the Cisco Group as rich in marine organic content. Limestones are described as thin, but the zone overlying the Lower Cisco sandstone shows some local thickening. Although the Cisco sandstone has minimal oil accumulations (e.g., the adjacent Johnson oil field), it has produced economic quantities of gas (Brister et al., 2002). The Canyon and Strawn sandstones are described as lenticular, indicating a different deposition environment. The lower Bend Group, known locally as the Bend Conglomerate, is described as generally dominated by siliciclastics interpreted to be of fluvial and deltaic origin (Lahti and Huber, 1982; Maharaj and Wood, 2009). The Bend Conglomerate has historically been a major producer of hydrocarbons in the area (Hentz et al., 2012). Methods Data acquisition Several 3C/3D seismic acquisition designs were proposed for this study. Figure 2 shows the (a) final acquisition 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 intervals of 251 m (825 ft), and source station intervals of 50 m (165 ft), respectively. Vertical vibrators were used as seismic sources, and the receiver (recording) patch was 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 a nearby calibration well with sonic logs to be used for synthetic seismogram matching with the 3C/3D seismic data. The University of Texas at Austin, John A. and Katherine G. Jackson School of Geosciences, Bureau of Economic Geology, Austin, Texas, USA. E-mail: [email protected]; [email protected]. Manuscript received by the Editor 18 November 2013; revised manuscript received 14 January 2014; published online 22 April 2014. This paper appears 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. t Special section: Multicomponent seismic interpretation Interpretation / May 2014 SE39 D ow nl oa de d 04 /2 5/ 14 to 1 29 .1 16 .2 32 .2 33 . R ed is tr ib ut io n su bj ec t t o SE G li ce ns e or c op yr ig ht ; s ee T er m s of U se a t h ttp :// lib ra ry .s eg .o rg / Data processing The P-P data processing was completed to a final migrated stack before P-SV/SV-P data processing was initiated. Conventional P-P data processing methods, using common midpoint (CMP) binning, provided important static corrections and stacking velocities that were subsequently incorporated into the P-SV/SV-P data processing flows. As Figure 3 may suggest, CMP binning will not work for P-SV data imaging. Instead, the converted-wave data relied on asymptotic conversion point (ACP) binning as outlined in Hardage (2012). An ACP is a P-SV image coordinate when data from several source-receiver combinations are binned to image the subsurface point where the trend of commonconversion-point (CCP) image coordinates for each binned source-receiver pair becomes quasivertical. Figure 3 illustrates the particle displacement vectors associated with each raypath of P-SV and SV-P used in ACP binning. For a given offset, the ACP position for the P-SV raypath (ACP1) is closer to the receiver location than to the source station. In contrast, the ACP position for the SV-P raypath (ACP2) is closer to the source. Note that the SV-P data are recorded by a vertical geophone because the upgoing raypath is a P-wave. Compare this sensor requirement with P-SV data recording, which requires 3C geophones because SV displacement vectors are perpendicular to upgoing SV raypaths. This use of SV-P data allows older vintage single-component P-P data (e.g., conventional 2D/3D seismic surveys) to be reprocessed to extract valuable multicomponent mode data for additional analysis, without the need to acquire a multicomponent survey. In this study, SV-P data processing was based on traditional converted-wave (P-SV) processing parameters. SV-P binning was done by inverting the VP∕VS velocity ratio used in P-SV binning. If a VP∕VS ratio of 2 is used to bin P-SV data, the ratio is inverted to 0.5 to bin SV-P data. A VP∕VS ratio less than 1.0 is physically unreasonable but is valid for seismic binning purposes. By applying P-SV velocities and statics and running one additional pass of surface-consistent statics, a SV-P data volume was generated that was similar to the P-SV data set. A strong reflection event at 500 ms (P-P final stack) was used to register/tie the data between the P-P wave and P-SV data, and a P-P event at approximately 1000 ms was used as a secondary event for registration. For simplicity, the P-SV wave data were binned using a VP∕VS of 1.6 because that ratio gave the best stack response at the zone of interest (Lower Cisco sandstone), even though there was evidence that a variable VP∕VS function could have been used. Spectral analysis Spectral analyses of the three time-domain volumes (Figure 4) reveal that the frequency content of the P-P and P-SV data volumes are broadband in nature. The PP frequency spectrum between 10 and 85 Hz showed a dominant frequency at 48 Hz, with a secondary peak at 40 Hz. The conventional converted-wave (P-SV) had a frequency spectrum from approximately 18 to 40 Hz, a bandwidth spanning only 2 octaves. The SV-P data volume had a broader spectrum range of 10–55 Hz, a bandwidth of approximately 2.5 octaves. The SV-P spectrum Figure 1. Generalized stratigraphic column of the study area (Brister et al., 2002). SE40 Interpretation / May 2014 D ow nl oa de d 04 /2 5/ 14 to 1 29 .1 16 .2 32 .2 33 . R ed is tr ib ut io n su bj ec t t o SE G li ce ns e or c op yr ig ht ; s ee T er m s of U se a t h ttp :// lib ra ry .s eg .o rg / was reasonably flat but exhibited an amplitude spike at 15 Hz (dominant frequency). No effort was made to suppress this spike and achieve a smooth, white SV-P spectrum. We can only speculate as to the cause of the frequency effects in the SV-P data. One possibility is that the downgoing shear wave has a dominant 15 Hz component, which causes the reflected compressional wave to also have a dominating 15 Hz component. In addition, reduced energy at higher frequencies may be due to not having correct velocity constraints and/ or static corrections. Correlation methods The greatest problem posed to the interpreter of converted-wave data is correlating events with P-wave data (DeAngelo et al., 2003). In this study, we have an additional converted-mode (SV-P) to integrate into the interpretation and evaluation of potential reservoirs. A dipole sonic log was recorded in a well outside the 3C/3D survey area. In addition, a previously recorded 2D seismic line that intersected this well (Figure 2) extended into the 3C/3D area, making it possible to do a robust correlation between the P-P wave 2D line and 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 robust correlation between P-wave and converted-wave data sets difficult. As a result, the main method of correlating P-P reflectors to P-SV and SV-P data was to use interpreter judgment to correlate events between the different data modes in section view. These data had no geometric features such as structural (faulting) or stratigraphic (lap-outs) terminations that could provide a correlation “nail” point. However, comparing seismic reflector packages that have similar cycles of strong and weak reflections permitted us to achieve an apparent good correlation between P-wave and convertedwave data sets. The importance of a robust correlation cannot be overemphasized. An incorrect correlation will lead to erroneous seismic-based attributes (rootmean-square [rms] amplitude ratio, VP∕VS ratio, etc.) that cannot be analyzed with a high degree of confidence or accuracy. Figure 3. Comparison of P-SV and SV-P raypaths (modified from Hardage, 2012). Figure 4. Comparison of P-P, P-SV, and SV-P frequency spectra extracted from each processed 3D seismic volume. Figure 2. The 3C/3D seismic acquisition design (a) before deployment with seismic source stations (red) and geophone stations (blue) and (b) actual source station deployment (black). Note the position of the ancillary 2D P-P seismic line and calibration well. Interpretation / May 2014 SE41 D ow nl oa de d 04 /2 5/ 14 to 1 29 .1 16 .2 32 .2 33 . R ed is tr ib ut io n su bj ec t t o SE G li ce ns e or c op yr ig ht ; s ee T er m s of U se a t h ttp :// lib ra ry .s eg .o rg / Discussion Figure 6 shows cross-section views of the P-P, P-SV, and SV-P seismic data along the same profile side by side for comparison. Time scales differ between the P mode and P-SV/SV-P modes; S-mode time axes have been compressed to roughly match reflectors on the three sections. We use this method as a first-pass approximation to determine which reflectivity events might represent the same stratigraphic interval in each mode. From a cursory first look, the Lower Cisco Sandstones interval is imaged on all three data modes. This allowed robust horizon mapping in all three data modes. There is a marked zone of signal attenuation, starting at 1 s, in the SV-P data in the lower portions of the seismic data volume, making any analysis of the more prolific Bend Conglomerate difficult. Consequently, any structural or attribute analysis below this level was not attempted. Given these characteristics, we conclude that the Lower Cisco sandstones would be a good candidate for comparison of seismic attribute expressions of P-P, P-SV, and SV-P data. Historically, P-wave data have set the gold standard for structural and stratigraphic interpretation in 3D seismic exploration. There have been substantial efforts to improve processing algorithms in P-wave data that have not yet been matched in the S-wave data arena. Consequently, interpreters will initially rely on P-wave data Figure 5. P-P seismic 2D to 3D correlation with interpreted horizons. Yellow arrows depict the Lower Cisco Sandstone interval, and black arrows depict the Strawn interval. Colored lines are interpreted horizons. Figure 6. Representative inline comparison of P-P, P-SV, and SV-P seismic data. The Lower Cisco Sandstone interval is indicated by the yellow arrow. Figure 7. Comparison of P-P, P-SV, and SV-P seismic two-way time structure of the Top Lower Cisco Sandstone interval. SE42 Interpretation / May 2014 D ow nl oa de d 04 /2 5/ 14 to 1 29 .1 16 .2 32 .2 33 . R ed is tr ib ut io n su bj ec t t o SE G li ce ns e or c op yr ig ht ; s ee T er m s of U se a t h ttp :// lib ra ry .s eg .o rg / results and use the S-wave data sets in an ancillary capacity. Here, we used the P-P two-way time structures as a control when comparing P-P data with PSV and SV-P data. In addition, we wished to determine if P-SV and SV-P have similar characteristics when compared to each other. A favorable comparison would validate that the SV-P mode is as reliable as the P-SV mode. Figure 7 shows the results of two-way time structure mapping the top of the Lower Cisco Sandstone for the P-P, P-SV, and SV-P data volumes, respectively. The P-P data show a modest structural high of approximately 6 ms in the southwestern corner of the study area that is associated with an interpreted carbonate buildup. The P-SV and SV-P maps, however, do not match the P-P time structure. The P-SV image shows no closed structure at all. The SV-P data indicate a closed structure but position the structure north of the structure shown by the P-P data. The amount of SV-P closure is 8–10 ms, which would yield approximately the same vertical depth closure as indicated by the P-P data. This latter observation is based on using a VP∕VS velocity ratio of 1.6, which results in a factor of 1.3 to equate P-P reflection time to SV-P reflection time (Chapter 5, Hardage et al., 2011). These variations in structure may be attributed to several things. Inaccurate S-wave receiver statics could have impacted the reliability of the processing. Figure 2a gives an idea about the variation of the topography within the study area. The variability (laterally and vertically) of the near surface has consistently plagued the S-wave processing community. Another possibility would be an erroneous VP∕VS ratio that would impact the alignment of seismic reflectors, as explained in Frasier and Winterstein (1990). They show that varying the VP∕VS ratio during the processing of convertedwave data from 2.4 to 3.0 had a significant impact on the lateral positioning of structural features (fault in their case). Such lateral movements apply to all seismic reflectors including stratigraphic features, which would directly impact any seismic attribute analysis. Figure 8 illustrates this phenomenon and clearly highlights the importance of robust VP and VS velocity analysis. Seismic attributes Seismic attributes were extracted from a time interval constrained between the interpreted top and bottom Lower Cisco Sandstone horizons, which were mapped in all three data volumes. Figure 9 shows the rms amplitudes calculated over their respective intervals (P-P, P-SV, and SV-P). The calculated amplitudes from all three modes have different results. This is not a major concern when comparing attributes extracted from P-P and P-SV or SV-P seismic data. In fact, we would expect that the seismic attributes would be marginally different if 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 different processing VP∕VS ratios on reflectors in the converted-wave mode (modified from Frasier and Winterstein, 1990). Figure 9. Comparison of P-P, P-SV, and SV-P seismic rms amplitudes extracted from the Lower Cisco Sand interval. Interpretation / May 2014 SE43 D ow nl oa de d 04 /2 5/ 14 to 1 29 .1 16 .2 32 .2 33 . R ed is tr ib ut io n su bj ec t t o SE G li ce ns e or c op yr ig ht ; s ee T er m s of U se a t h ttp :// lib ra ry .s eg .o rg /