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1 High-resolution model building and imaging workflow using multimeasurement towed streamer data: North Sea case study Shruti Gupta*, Chris Cunnell, Alex Cooke, Alexander Zarkhidze, Schlumberger Summary This paper discusses the workflow for high-resolution model building and imaging of a broadband multimeasurement towed streamer survey over the Mariner field in the North Sea. The model-building strategy combines the complementary techniques of full waveform inversion (FWI) and reflection tomography to generate an accurate, high resolution and geologically consistent velocity model, using both refraction and reflection energy. The 3D deghosted and reconstructed wavefield generated by the generalized matching pursuit (GMP) algorithm is densely sampled in all directions, and provides the ideal input for imaging techniques such as Kirchhoff prestack depth migration (KDM) and high-frequency reverse time migration (RTM). The combination of such a high resolution earth model and broadband, densely sampled input data provides the significant benefits for both overburden and reservoir characterization in this setting. Introduction Discovered in 1981, Mariner is a shallow heavy oil development field located in the East Shetland platform of the UK sector of the North Sea. It contains two main targets: the Heimdal sands within the Lista Shale formation and Maureen sandstone. Houbiers et al. (2012) and Østmo et al. (2014) describe a number of challenges for seismic imaging over the Mariner field, including: The presence of high-velocity shallow channels with very small spatial scales, causing significant distortion and pull-ups of the underlying events. Mapping of the Heimdal sands, which consists of a complex, disrupted channel system of remobilized unconsolidated and uncemented sand and injectites. These sands are hard to image due to the low acoustic impedance contrast with the surrounding shale. The impact of these features is highlighted on legacy towed streamer marine data sets, including a 2008 vintage shallow-tow survey. In addition, a small ocean bottom cable (OBC) survey was acquired in 2008 over a subset of the field. With the application of FWI, the OBC survey was able to map the high-velocity shallow channels (Houbiers et al., 2012). However, successful imaging of the Heimdal sands remained challenging due to the limited seismic resolution of this data set. To address these challenges, a 220 km 2 survey was acquired in August 2012 using a broadband, multimeasurement towed streamer system. The acquisition design comprised 8 streamers at 75 m separation, 3 km maximum offset, towed at a constant 18 m depth across the full offset range. The multimeasurement streamer technology records densely spaced, single-sensor accelerometer measurements orientated in the vertical and crossline horizontal directions, in addition to conventional hydrophone pressure measurements. The measurements are processed through a joint interpolation and 3D deghosting workflow described by Özbek et al. (2010), which reconstructs the upgoing pressure wavefield on a dense surface grid of 6.25 x 6.25 m for each shot, ready for subsequent processing. The receiver-side deghosting of this technique is complemented by a broadband multi-level source array. Results of a prestack time-migration workflow demonstrated improved imaging of the Heimdal formation versus legacy data sets, as described by Østmo et al. (2014). This case study presents an extension to the initial results into depth imaging. Here, FWI is used to build a high-resolution shallow velocity model. The model is well suited for combination with the densely sampled upgoing wavefield for accurate prestack depth migrations, such as KDM and high-frequency RTM, to assess the impact of imaging throughout the overburden and at the target level. Velocity model building workflow Numerous examples exist that demonstrate the effectiveness of FWI in solving shallow, small-scale features, and where reflection-based tomography techniques struggle due to the limited sampling of angles/offsets in the shallow overburden. FWI utilizes refractions and other early arrival energy to overcome these limitations. Figure 1 summarizes the model building workflow used in this study. The success of the FWI process is dependent on the starting velocity model. A fit-for-purpose initial velocity model was derived using a simple horizon-based well-driven model using sonic logs, followed by one iteration of large scale length common image point (CIP) tomography (Woodward et al., 2008) to compensate for any interpolation inaccuracies between the well locations. A key objective in SEG New Orleans Annual Meeting Page 1049

The seismic anisotropy used was compaction-based with very small values of maximum 2% epsilon and 1% delta in the Lista shale formation. Figure 1: Velocity model building workflow.

2 the experiment was to assess the ability of FWI to reliably delineate shallow channel velocity anomalies. To assess this, one of the shallow channels was manually inserted as a high velocity geobody in the initial model, whilst all other channels were ignored. The seismic anisotropy used was compaction-based with very small values of maximum 2% epsilon and 1% delta in the Lista shale formation. Figure 1: Velocity model building workflow. The input to FWI was minimally-processed hydrophoneonly measurements, which are appropriate given the generally low range of frequencies used in FWI. The hydrophone measurements further benefited from a narrower zero-frequency notch and improved signal to noise ratio of low frequencies due to the deep tow across all offsets. The FWI process iteratively updates the velocity model by minimizing the misfit between recorded data and synthesized waveforms. The inversion proceeds with a multiscale approach from low to high frequencies so that a global instead of local minimum can be achieved (Vigh et al., 2009). Both refraction and reflection energy was used during the FWI updates. Due to the rich low frequency content, the first FWI band operated across the 1.5 to 7 Hz range, expanding to higher frequencies for subsequent bands. The maximum effective depth for the FWI velocity updates was restricted to the overburden above the Lista shale formation due to the 3 km maximum offset imposed by acquisition. Hence, an additional step of CIP tomography was incorporated into the workflow to refine the velocity model in the deeper section. One pass of multiparameter FWI was included in the workflow to refine the anisotropic model parameters, followed by a final band of FWI for velocity resolution enhancement. This is performed sequentially to minimize possible crosstalk between inverted parameters velocity and epsilon (Cheng et al., 2014). Input to seismic imaging The data used for imaging was 3D deghosted and wavefield reconstructed using a generalized matching pursuit algorithm at a dense subsurface grid of 6.25 m by 6.25 m. The upgoing wavefield was input to deterministic waterlayer demultiple which was followed by general surface multiple prediction. All the processes were applied at the fine sampling in both inline and crossline direction to be consistent with 3D high-resolution imaging using the detailed model from FWI. Results Preliminary results from the early FWI band updates already show significant uplift in the imaging of the shallow channels, simplifying the pull ups and distortions created due to the high-velocity channel as shown in the Figure 2. Figure 2a and Figure 2b show the KDM stack with an overlay of initial and FWI band 2 velocity model respectively. Figure 3 shows overlays of velocity on the migrated depth slices. Note that the FWI updates have captured the high-velocity channels both at the control location (manually inserted geobody) as well as the other channels that were not included in the initial model. A variety of QC attributes, in addition to migrated images, depth slices, and gather flatness, were generated to validate the accuracy of the global updates from FWI: Figure 4 shows a crosscorrelation coefficient map between the measured and the modeled data over the survey area at the inversion frequency bandwidth. Figure 5 shows a crosscorrelation time shift map between the measured and modeled data. The presence of any structural information in the maps indicates the incorrect velocity for that particular event. Figure 6a shows a KDM image of the heritage OBC data with its FWI velocity overlaid. Figure 6b shows a nearby KDM image of the multimeasurement towed streamer data with the band 2 FWI model overlaid. Although both methods are successfully inserting a high-velocity geobody in the model, we observe a significant uplift in the SEG New Orleans Annual Meeting Page 1050

$Conclusions The model building workflow presented takes advantage of different parts of the wavefield for the model-building process: refractions and reflections for FWI, and reflections for$ tomography in shallow-water environments.

tomography in shallow-water environments.

3 resolution of the densely sampled broadband towed streamer image as compared to the OBC dataset. Final velocity model updates and image comparisons are in progress. Conclusions The model building workflow presented takes advantage of different parts of the wavefield for the model-building process: refractions and reflections for FWI, and reflections for tomography in shallow-water environments. The workflow also uses the broadband nature of the multimeasurement towed streamer data to achieve a detailed earth velocity model which accurately resolves near-surface heterogeneity. This model will be used in conjunction with a dense receiver grid of broadband data for high-resolution imaging with KDM and high-frequency RTM to provide highly accurate images of the overburden and reservoir targets. Acknowledgements We thank Statoil U.K. Limited, JX Nippon Exploration and Production (U.K) Limited and Dyas UK Limited for permission to use the data, and Schlumberger for permission to publish these results. We would further like to thank Dave Clark and Lianping Zhang for their contribution to this study. Figure 2: KDM stacks with velocity overlays (a) Initial velocity model (b) FWI Band 2 velocity model Figure 3: KDM slices with velocity overlays (a) Initial velocity model (b) FWI Band 2 velocity model. SEG New Orleans Annual Meeting Page 1051

Figure 4: Crosscorrelation map between observed and modelled data for Initial and

Figure 5: Timeshift map between observed and modelled data for Initial and

update with peak frequency 10Hz) (b) Multimeasurement towed streamer data stack

4 Figure 4: Crosscorrelation map between observed and modelled data for Initial and FWI Band 2 velocity model. Figure 5: Timeshift map between observed and modelled data for Initial and FWI Band 2 velocity model. Figure 6: (a) Legacy OBC stack with vintage velocity overlays (FWI velocity update with peak frequency 10Hz) (b) Multimeasurement towed streamer data stack with FWI band 2 velocity overlay (FWI velocity update with peak frequency 5 Hz). SEG New Orleans Annual Meeting Page 1052

5 EDITED REFERENCES Note: This reference list is a copyedited version of the reference list submitted by the author. Reference lists for the 2015 SEG Technical Program Expanded Abstracts have been copyedited so that references provided with the online metadata for each paper will achieve a high degree of linking to cited sources that appear on the Web. REFERENCES Cheng, X., K. Jiao, D. Sun, and D. Vigh, 2014, Multiparameter full-waveform inversion for acoustic VTI medium with surface seismic data: 76th Annual International Conference and Exhibition, EAGE, Extended Abstracts, We E Houbiers, M., E. Wiarda, J. Mispel, D. Nikolenko, D. Vigh, B. Knudsen, M. Thompson, and D. Hill, 2012, 3D full-waveform inversion at Mariner A shallow north sea reservoir: 82nd Annual International Meeting, SEG, Expanded Abstracts, doi: /IST Østmo, S., P. McFadzean, S. Silcock, C. Spjuth, E. Sundvor, L. P. Letki, and D. Clark, 2014, Improved reservoir characterization by multisensor towed streamer seismic data at the Mariner Field: 76th Annual International Conference and Exhibition, EAGE, Extended Abstracts, We P Özbek, A., M. Vassallo, K. Özdemir, D.-J. van Manen, and K. Eggenberger, 2010, Crossline wavefied reconstruction from multicomponent streamer data: Part 2 Joint interpolation and 3D up/down separation by generalized matching pursuit: Geophysics, 75, no. 6, WB69 WB85. Vigh, D. V., W. E. S. Starr, and K. D. Dingwall, 2009, 3D prestack time domain full-waveform inversion: Presented at the 71st Annual International Conference and Exhibition, EAGE. Woodward, M. J., D. Nichols, O. Zdraveva, P. Whitfield, and T. Johns, 2008, A decade of tomography: Geophysics, 73, no. 5, VE5 VE11. SEG New Orleans Annual Meeting Page 1053

Th E Integrating FWI with Surface-wave Inversion to Enhance Near-surface Modelling in a Shallowwater Setting at Eldfisk

Th E Integrating FWI with Surface-wave Inversion to Enhance Near-surface Modelling in a Shallowwater Setting at Eldfisk Th E106 03 Integrating FWI with Surface-wave Inversion to Enhance Near-surface Modelling in a Shallowwater Setting at Eldfisk E.J. Wiarda* (Schlumberger), S.A. Shaw (ConocoPhillips), D. Boiero (Schlumberger),