F006 Ultra High-density Full Wide-azimuth Processing … · Ultra High-density Full Wide-azimuth Processing Using Digital Array Forming ... data processing ... and well log data.

73rd EAGE Conference & Exhibition incorporating SPE EUROPEC 2011 Vienna, Austria, 23-26 May 2011

F006Ultra High-density Full Wide-azimuth ProcessingUsing Digital Array Forming - Dukhan Field, QatarS. Seeni (Qatar Petroleum), H. Zaki (Qatar Petroleum), K. Setiyono* (QatarPetroleum), J. Snow (Qatar Petroleum), A. Leveque (CGGVeritas), M.Guerroudj (CGGVeritas) & S. Sampanthan (Jaguar Exploration)

SUMMARYThis paper presents a case history of the pilot 3D seismic processing of the ultra high-density and fullwide-azimuth 3D seismic survey across the Dukhan field for Qatar Petroleum (QP). The acquisition of thesurvey commenced in early in 2009 and took 2 years to complete. The pilot processing was carried out inparallel over a small 85 sq km area as a test to parameterize the 860 sq km production processing. Thepilot test was completed in early in 2011. The VSP and uphole data processing and analysis has beeninitiated. The production surface seismic processing is expected to be completed by mid-2012. This paperfocuses on the pilot test processing.


Introduction

The Dukhan field is a major oil field in the State of Qatar. It was discovered in 1939 and contains more than 800 wells, producing from 4 major reservoirs. The existing fully processed 3D seismic data is about 20 years old, and lacks full-field seismic data coverage, vertical & spatial resolution, and quantitative attributes needed for enhanced reservoir characterization. QP’s expectation from this new state-of-art 3D seismic (Seeni et al., 2009) is for much improved data quality that allows for small fault imaging to locate bypassed oil in isolated fault blocks, fracture identification to delineate areas of enhanced productivity especially in tighter intervals, reservoir characterization to predict the distribution of reservoir properties and quality away from wells using seismic attributes, and improved structural definition of deeper reservoirs. Therefore, data processing is expected to maintain geophysical characteristics such as high signal preservation and Signal-to-Noise (S/N) ratio, high vertical & lateral resolution (~6 to 100 Hz or more) and negligible acquisition footprint. In this paper, we illustrate how a combination of high-end dense point-source point-receiver wide-azimuth acquisition with advanced processing and imaging solutions have allowed a major improvement in seismic data to meet QP’s objectives and expectations. The pilot test processing and results, completed in early 2011 is the subject of this paper. Seismic Acquisition Design The new acquisition consists of orthogonal cross spreads with source lines densely sampled by point sources spaced every 7.5 m and receiver lines densely sampled by point receivers spaced every 7.5 m as well (Figure 1a). Such a dense sampling was chosen to allow for de-aliased sampling of the surface waves and for signal preservation through suppression of ground roll and industrial noise. For each source point, the back reflected/scattered signals were recorded over 36 receiver lines of 5,000 m long and 120 m apart, which represents a 21 km2 wide patch with an aspect ratio of 0.84, close to a perfect Wide Azimuth (WAZ) acquisition with in-line offsets of +/- 2500 m and cross-line offsets of +/- 2100 m (Figure 1b). Such a wide patch was selected to ensure a significant increase in the S/N ratio at imaging stage when reflection data are back projected and re-focused onto their reflection point. The Source Line Increment (SLI) and the Receiver Line Increment (RLI) between two consecutive cross spreads were chosen to be 90 m and 120 m respectively. The small SLI and RLI distances allowed splitting of the pre-stack data volume into approximately 500 Common Offset Vector (COV) cubes. Each of the COV cubes can be imaged independently for a detailed analysis of subsurface properties (reflectivity, velocity) as a function of the acquisition offset and azimuth. With the surface seismic acquisition, 3D and zero offset VSP data were recorded in 8 wells. The VSP measurements, together with prior checkshot, well log, and reservoir data were used to guide and calibrate the processing and imaging of the surface seismic data. Q factors and interval velocities derived from VSP’s where used to corrected surface seismic data from frequency attenuation and for the initial migration of the surface seismic data prior to velocity model update. Zero Offset VSP’s and well log synthetics were keys to select the surface consistent deconvolution parameters.

Seismic Processing Challenges The survey area consists of land, sabkha, and Transition Zone (TZ) (0-16 m water depth), presented significant challenges in multi-source and multi-receiver modes generating a large dataset of 3.5 terabytes of data per day. Additionally, the ultra high-density full wide-azimuth point-source (HFVS)


point-receiver acquisition presents a formidable task in data management (bin size 3.75x3.75 m; fold 500). For optimum processing results, it was also critical to QC each of the processing steps in the migrated domain to ensure signal preservation as well as good agreement with auxiliary data (VSPs, check shots, well logs). Refraction statics, Surface consistent processing, Ground Roll attenuation All of the above cited processing steps were done on the individual source receiver pairs prior to any array forming. The picking of the First Breaks required careful data pre-conditioning to help auto picking tools deal with the highly noisy elementary traces. Similar pre-conditioning was needed for surface consistent deconvolution to ensure spectra to be signal driven and not noise driven. One of the main benefits of the fine source and receiver sampling is to be able to safely remove surface waves without causing any damage to the signal over the frequency range of interest (6Hz-110Hz). This is achieved on a cross-spread basis in order to benefit from the finest sampling rate and the most continuous trace to trace offset and azimuth variations (Figure 1c). The solution, a data driven approach to perform a very accurate Ground Roll attenuation even with an irregular offset distribution (Le Meur et al., 2010), has been applied. Digital Array Forming Processing When all short wavelength surface waves are safely removed, as well as other short wavelength distortions such as statics, amplitude, and phase variations, remaining data exhibit higher propagation velocities, which correspond to longer spatial wavelengths. Such waves do not need to be finely sampled. Therefore, one would have the possibility to down-scale the seismic field without significant loss of information, after application of a broadband Digital Array Forming (DAF) process. The objective of DAF is to retain signal wavelengths of interest. It is applied in the cross-spread domain with the following steps:

• Intra Array Static correction (Gulunay et al., 2009) • Cross-spread regularization (Poole et al., 2007) • Wave field de-aliasing at a sampling rate of interest (Poole et al., 2009)

After applying the broadband DAF, source and receiver density was scaled down from 7.5 m to 30 m, which corresponds to a 15x15 m2 bin size instead of 3.75x3.75 m2. The DAF procedure reduced the data size by 16 times, while maintaining most of the benefits of the original acquisition effort. The main reason for conducting DAF has to do with current industry limitation to process at 3.75x3.75 m2 bin. Wide Azimuth Processing and Imaging Processing of wide azimuth dataset needs a special handling. Once all the preprocessing was performed in the cross-spread domain such as DAF and 3D predictive deconvolution (Hugonnet et al., 2010), data were split into COV cubes to be migrated independently (Figure 1d). One of the benefits of the COV building is that they have minimum azimuth and offset dispersion and they are single fold. Therefore, each COV can be migrated independently and there is no need for azimuth sectoring. After migration, each of the migrated COV cubes was then re-sorted into 3D offset vector Common Image Gather for subsequent 3D parabolic Radon filtering (Hugonnet et al, 2009) and azimuthal velocity model update (Lecerf et al., 2009). All these correspond to a true one-pass WAZ processing and imaging workflow. As a result of combining all novel WAZ processing solutions, the signal integrity was preserved to deliver the expected imaging uplift from the wide-azimuth ultra dense acquisition. This is illustrated on the Figures 2 and 3, which compare the legacy 1998 data and the new 2010 data. The integration of the all available geophysical data in the decision for the selection of


the appropriate processing parameters such as deconvolution and multiple attenuation has allowed proper convergence of surface seismic, zero offset VSP, and well log data.

Conclusions

The ultra dense full wide-azimuth Dukhan 3D seismic survey generated a voluminous point-source point-receiver data set that required highly specialized and powerful data management schemes, hardware, and processing workflow. From this project, we have learned that proper sampling of surface noise provides significant improvement in signal preservation. This was confirmed, at each processing step, with a systematic QC process in the migrated domain. When all undesirable short wavelength distortions introduced by the near surface were corrected, a broadband DAF solution proved to be an efficient way to reduce data volume while preserving all benefits from the original dense acquisition. The use of a one-pass true WAZ imaging solution has also proven to be an effective way to preserve signal for post imaging processing steps and azimuthal-dependent velocity analysis that reconcile data over all offset and azimuth ranges involved. Acknowledgements

The authors would like to thank the management of Qatar Petroleum for granting permission to publish this work. We also thank our colleagues at Qatar Petroleum, Ardiseis, CGGVeritas, VSFusion and Jaguar Exploration for their contributions and insightful discussions during the course of this work.

References

Gulunay N., Khalil, A., Leveque, A., Seeni, S.R. and Robinson, S. W., 2009. Intra array statics derived in the cross-spread domain for a high density, high resolution, wide azimuth 3D land data currently being acquired in Qatar. A Global Theatre International Showcase presentation, 79th Ann. Intnl. Meeting of Soc. Expl. Geophy., Houston, TX, USA. Hugonnet P., Boelle J.L., Mihoub M., Herrmann P., 2009. 3D high resolution parabolic Radon filtering. 71st EAGE conf. Amsterdam, Expanded Abstracts. Hugonnet P., Boelle J.L., Herrmann P., Prat F., Navion S., 2010. 3D predictive deconvolution for wide-azimuth gathers. 72nd EAGE conf. Barcelona, Expanded Abstracts. Lecerf D., Navion S., Boelle J-L., 2009. Azimuthal residual velocity analysis in offset vector for WAZ imaging. 71st EAGE Conf. Amsterdam, Expanded Abstracts. Le Meur, D., Benjamin, N., Twigger, L., Garceran, K., Delmas, L., Poulain, G., 2010. Adaptive attenuation of surface-wave noise. First Break, volume 28, 83-88. Poole, G., Herrmann, P., Angerer, E., and Perrier, S., 2009. A regularization workflow for the processing of cross-spread data. EAGE conference and exhibition. Poole, G. and Herrmann, P., 2007. Multi-dimensional data regularization for modern acquisition geometries. 69th EAGE Conference & Exhibition, Expanded Abstracts, P143. Seeni, S.R., Robinson, S., Denis, M., Sauzedde, P., 2009. Dukhan 3D: an ultra high density, full azimuth seismic survey for the future, IPTC-13616-PP. Seeni, S.R., Robinson, S., Denis, M., Sauzedde, P., Taylor, R., 2010. Future-proof seismic: high-density full-azimuth. First Break, volume 28, 41-50.


Figure 1: a) Source and receiver sampling rates; b) 3D shot gather geometry; c) cross-spread data cube; d) COV definition from cross-spread parameters.

Figure 2: Inline final time-migration processing comparison between legacy 1998 data and new 2010 data and bandwidth comparison (blue 1998; red 2010).

Figure 3: Migrated time-slice processing comparison between legacy 1998 data and new 2010 data.

F006 Ultra High-density Full Wide-azimuth Processing … · Ultra High-density Full Wide-azimuth Processing Using Digital Array Forming ... data processing ... and well log data.

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