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

Size: px

Start display at page:

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

Dortha Wood
5 years ago
Views:

1 Th E 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), A. Gundersen (ConocoPhillips) & L.R. West (Schlumberger) SUMMARY Following a noise becomes signal philosophy, we have successfully integrated surface-wave inversion and early-arrival full-waveform inversion on a multicomponent ocean-bottom cable dataset, thus extracting more information from the recorded field data. In the near-surface above the Eldfisk Field, Norwegian North Sea, two perpendicular sets of Pleistocene subglacial tunnel valley systems have been resolved at two depth ranges between the seabed and 300m depth of the updated Vp model by this integrated inversion scheme. This indicates that the integrated near-surface Vp model is of high resolution both laterally and vertically and explains surface-waves and the early arrivals, diving waves, or both. We have demonstrated that surface-wave inversion complements full-waveform inversion by providing a nearsurface (0 150 m) Vp model in a depth range where full-waveform inversion techniques typically produce suboptimal results due to null-space issues, vertical resolution limitations and errors in source wavelet, density approximations, multiple modelling, and acoustic assumptions. The combined full-waveform inversion and surface-wave inversion Vp model update in the near-surface significantly flattens the common-image gather events between m and deeper. This confirms the validity of these nearsurface updates.

$In shallow-water environments, early-arrival full-waveform inversion (EA FWI) uses the near-critical near-seabed reflections, diving waves, refracted head-waves, and all other events arriving prior$

2 Introduction Increasingly, elements of the recorded wavefield that have conventionally been targeted as noise are now being exploited to characterize the near-surface and overburden. In shallow-water environments, early-arrival full-waveform inversion (EA FWI) uses the near-critical near-seabed reflections, diving waves, refracted head-waves, and all other events arriving prior to the seabed reflection on minimally processed gathers, to obtain a near-surface (0 400m depth) and shallow overburden velocity model (Figures 1a c). In this paper, the frequency cut-offs of the band-pass filters that define the FWI bandwidth are annotated as [0,4]Hz for a 4Hz high-cut filter (peak frequency is 2.5Hz). A shallow marine environment also supports surface waves in the form of P- waves guided in the water layer (Figure 1d). Guided waves are multi-modal dispersive events (Figure 1e) generated by reverberating P-wave reflections in the near surface that propagate as leaking modes horizontally from the source and are usually recognized in seismic gathers by a characteristic high-amplitude interference pattern often called shingling (Figure 1d). By inverting the guided-wave dispersion curves, the vertical distribution of the P-wave velocity (V P ) in the shallow near-seabed layers can be estimated, since their propagation properties depend directly upon the properties of the near-surface (Boiero et al., 2013). A key limitation of Surface-wave Inversion (SWI) is the maximum update depth, which is typically tens of meters below the seabed, depending on the water depth and nearsurface properties. Figure 1 a) [0,4]Hz observed FWI gather with EA inner mute annotated; b) Velocity update dv after [0,4]Hz FWI, the red box indicates the depth range affected by EA FWI; c) Forward-modelled gather after [0,4]Hz FWI, d) input data for surface-wave analysis, d) example of FK spectrum showing dispersive guide-wave modes; f) Near-seabed (0-150m) updated [0,4]Hz FWI model, input into SWI; g) SWI model (0-150m). In the near-surface (0 400 m depth range), conventional reflection tomography is typically compromised by a lack of traces that have recorded pre-critical reflections, and by multiple and noise contamination at near offsets. Obtaining an accurate and high-resolution FWI V P model can be difficult in the near-seabed depth range, down to m below the seabed. The key challenges in using FWI to update the near-seabed zone can be broadly classified as 1) null-space issues and acquisition footprint due to exclusion of near offsets, near-offset acquisition gaps and tight inner mutes, 2) vertical resolution limitations due to high-frequency cut-off and wavelet interference

between early arrivals, and 3) velocity model imprint of the errors in the source wavelet, density approximations, multiple modelling, and acoustic assumptions.

3 between early arrivals, and 3) velocity model imprint of the errors in the source wavelet, density approximations, multiple modelling, and acoustic assumptions. There is an abundance of m depth-slice overlays of updated FWI models on top of shallow pre-stack depth migration (PSDM) stack volumes from the North Sea, showing velocity anomalies representing shallow-channel systems that correlate well with the underlying seismic (Figure 2). The above mentioned FWI challenges could be the reason why there is a noticeable lack of shallower depth-slice overlays and vertical overlay sections in the near-surface, showing an equally convincing vertical correlation and vertical FWI model resolution. Figure 2 Side-by-side comparison of 295m depth slices of a) the 2007 legacy PSDM stack volume, and b) the [0,9]Hz EA FWI updated V P model. Interpretation of a set of shallow channels is used to show the correlation between the velocity model and the structures on the seismic. The red arrow annotates the same channel as in Figure 1f. Integrating EA FWI and SWI at Eldfisk OBC The 2012/2013 Eldfisk 3D/4C WAZ OBC survey, acquired in Norwegian North Sea Blocks 2/7 and 2/8, was acquired with an orthogonal geometry. Source line spacing was 300 m and source stations were 25 m apart. Receiver line spacing was 300 m over most of the survey, with 25 m receiver station spacing. The water depth is approximately 70 m. On average, the sail lines are 18 km in length. The maximum offset for the resulting dataset is m in both the inline and cross-line direction. The lowest usable frequency for these data is around 2.25Hz. One of the primary objectives is to perform FWI and reverse time migration (RTM) to significantly improve the imaging within a pair of seismically obscured areas at the Eldfisk reservoir level at about 3000 m depth. These are associated with thin gas-charged zones in the overburden from about 900 m downwards, directly overlaying the Eldfisk Field. A second objective is to enhance imaging in the overburden. In this case study, the FWI starting model is a legacy (2007) anisotropic VTI model resulting from reflection tomography applied on a smaller vintage (2001) OBC dataset (Knoth and Whitmore, 2008). An extensive FWI feasibility study prior to production revealed that the near-surface velocities in the 0-500m depth range of this starting model are consistently too slow. In order to mitigate cycleskipping issues due to this discrepancy, during the initial EA VTI FWI iterations, the starting frequency bandwidth was minimized to [0,4]Hz, with a peak frequency of 2.5Hz. Acoustic 3D VTI FWI was applied in the time domain after adapting a multiphase, multiscale workflow described by Houbiers et al. (2012). Two significant enhancements were incorporated into this shallow-water EA FWI flow. First, we adopted an approach based on the variable projection technique to estimate the source wavelet alongside model parameters during inversion, which is naturally embedded into each FWI iteration (Sun et al., 2013). This produced an updated source wavelet for each iteration within and across widening FWI frequency bands. Second, within each frequency-band set of cascaded iterations, EA FWI was followed by subsequent passes of widemute (WM) FWI in which significant reflection energy is included in addition to transmitted energy. This resulted in enhanced vertical and horizontal resolution of the updated FWI models, and an increase in FWI update depth from the maximum diving-wave penetration depth of 1200 m (onset of a velocity inversion) to below reservoir depth at 3000 m. The SWI approach involves analyzing the phase velocity of the different surface- and guided-waves modes. The inversion algorithm modifies S- and P-wave velocities to match the estimated phase

4 velocities with the secular function solutions. This misfit function allows dispersive modes to be inverted without needing to associate experimental data points to a specific mode, thereby avoiding mode-misidentification errors in the retrieved velocity profiles (Boiero et al., 2013). Figure 3 Velocity model at 110m depth; a) [0,4]Hz FWI updated model at receiver locations (shot lines parallel to cables), input into SWI; b) SWI updated model at receiver locations; c) SWI updated model at source locations (shot lines perpendicular to cables). To update the erroneously low velocities in the near-surface, we first ran [0,4]Hz FWI (Figure 1b). The increased velocities in the shallow overburden (0 500 m) of the resulting FWI model were expected to aid the merge between the SWI near-seabed V P model (0 150 m) with the underlying [0,4]Hz FWI model. The updated [0,4]Hz FWI V P model (Figure 3a) was then used as input to SWI (Figure 3b-c). The resulting 0 150m near-seabed V P model from SWI was then coblended with the [0,4]Hz FWI V P model, which served as the input model for [0,6.5]Hz FWI iterations. The aim of this approach is to produce a high-resolution and accurate near-seabed V P model early in the FWI flow that can be fixed between m depth and would benefit the subsequent higher-frequency [0,6.5]Hz and [0,9]Hz FWI iterations. Results Figure 1a shows an example of an observed common-receiver gather produced during [0,4]Hz FWI, with the EA inner mute annotated in red. As shown by the combined [0,4]Hz EA and WM FWI velocity update dv of Figure 1b, the overburden velocities are predominantly increased by [0,4]Hz FWI. Figure 1c shows an encouraging match of the resulting forward-modelled gathers after [0,4]Hz FWI when compared with the observed gathers. Note that the dv update resulting from [0,4]Hz EA FWI is limited by the maximum diving-wave penetration depth of 1200 m (red box in Figure 1b). Figure 1d shows the selected input data for SWI analysis, and the representative FK spectrum of Figure 1e exhibits the dispersive nature of the individual guided-wave modes of propagation. The m near-seabed section of the updated [0,4]Hz FWI model, which is the input model for SWI (Figure 1e), shows the FWI challenge of null-space leakage of the m deep channel (Figure 2b) into the near-seabed zone (red arrow). Overall, SWI has further increased V P in the near-seabed depth range (Figure 1f), which can also be observed in Figure 3 and the well log overlays of Figure 4c. In addition, Figure 3 demonstrates that SWI completely overwrites the velocity structures of the input [0,4]Hz FWI model and resolves a set of 3 E-W trending low-velocity channels of a Pleistocene subglacial tunnel valley system, each approximately m wide, m deep, and containing m/s V P anomalies (black arrows, also in Figure 1f). Figure 4 shows the very good improvement of common-imaging gather flatness associated with the V P increase in the m depth range due to [0,4]Hz FWI, and the additional increase in the m depth range, due to SWI. Note that the dominant gather flatness improvement is due to [0,4]Hz FWI, with a residual flatness enhancement after application of SWI.

Discussion and conclusions We have successfully integrated surface-wave inversion (SWI) and early-arrival full-waveform inversion (EA FWI) and thereby extracted more information from the recorded

5 Figure 4 Kirchhoff PSDM commonimage gathers a) for the FWI starting model; and b) for the integrated [0,4]Hz FWI+SWI model. Figure 4c shows overlays of shallow V P model updates onto a well log V P trend. Discussion and conclusions We have successfully integrated surface-wave inversion (SWI) and early-arrival full-waveform inversion (EA FWI) and thereby extracted more information from the recorded field data. Within 300 m of the near-surface above the Eldfisk Field, two perpendicular sets of Pleistocene subglacial tunnel valley systems have been resolved at two depth ranges of the updated V P model by this integrated inversion scheme. This indicates that this integrated near-surface V P model is high-resolution both laterally and vertically, and explains guided waves and the early arrivals, diving waves, or both. The combined FWI and SWI V P model update in the near-surface significantly flattens the commonimage gather events in the m depth range and deeper, whilst un-flattening suspect multiple events. This confirms the validity of these near-surface updates. Ideally, the shallow (0 500 m) part of this integrated model is of sufficiently high quality and resolution that subsequent passes of highresolution tomography can be focussed on updating the in situ V P model of deeper overburden and reservoir levels. Obviously, PSDM imaging quality of the reservoir targets is expected to benefit from the correct velocity modelling of small-scale and complex structural and stratigraphic features in the near surface. For shallow hazard assessment, the integrated near-surface model can be used directly as interpretation product, and would improve mirror migration of the downgoing wavefield. Acknowledgments The authors thank ConocoPhillips Skandinavia AS and the PL018 partners Total E&P Norge AS, ENI Norge AS, Statoil Petroleum AS and Petoro AS for permission to publish the data examples and Schlumberger for permission to publish this work. References Boiero, D., Wiarda, E., and Vermeer, P. [2013] Surface- and guided-wave inversion for near-surface modeling in land and shallow marine seismic data. The Leading Edge, 32, Knoth, O., and Whitmore, N.D. [2008] Depth Imaging beneath a Seismic Obscured Area (SOA) and Analyzing Its Character - Eldfisk Field Experience. 70 th Annual EAGE Conference and Exhibition. Houbiers, M., Wiarda, E., Mispel, J., Nikolenko, D., Vigh, D., Knudsen, B-E., Thompson, M., and Hill, D. [2012] 3D Full-waveform Inversion at Mariner a shallow North Sea reservoir. 82 th SEG Annual International Meeting. Sun, D., Jiao, K., Huang, W., Vigh, D., and Coates, R. [2013] Source wavelet estimation in full waveform inversion. 83 th SEG Annual International Meeting.

Downloaded 02/10/17 to Redistribution subject to SEG license or copyright; see Terms of Use at

Downloaded 02/10/17 to Redistribution subject to SEG license or copyright; see Terms of Use at 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