W011 Full Waveform Inversion for Detailed Velocity Model Building

Transcription

1 W011 Full Waveform Inversion for Detailed Velocity Model Building S. Kapoor* (WesternGeco, LLC), D. Vigh (WesternGeco), H. Li (WesternGeco) & D. Derharoutian (WesternGeco) SUMMARY An accurate earth model is key to any successful depth imaging effort. Full-waveform inversion (FWI) is an advanced velocity model building process that uses the full two-way wave equation. Existing methods use a ray-tracing approach to distribute velocity errors within the model. In this presentation, we will show examples of seismic data processed with the latest technology, including earth model building with fullwaveform inversion.

2 Introduction An accurate earth model is key to any successful depth imaging effort. Full-waveform inversion (FWI) is an advanced velocity model building process that uses the full two-way wave equation. Existing methods use a ray-tracing approach to distribute velocity errors within the model. In this presentation, we will show examples of seismic data processed with the latest technology, including earth model building with full-waveform inversion. The industry has moved to using two-way wave-equation migrations commonly known as reversetime migration (RTM), especially in areas of complex geology such as the salt bodies in the Gulf of Mexico, offshore West Africa, Brazil, and the Red Sea. The velocity model, including velocity anisotropy, is key to any depth migration effort. The natural next step is to use the two-way wave equation for velocity model building. One of the most advanced tools for velocity model building using the two-way wave equation is full-waveform inversion. Full-waveform inversion uses computer-intensive forward modeling of the seismic measurement combined with residual wavefield back propagation to iterate to a final velocity model, which can provide greater detail than tomographic ray-tracing approaches. Method and Theory Full-waveform inversion, based on the finite-difference approach, was originally introduced in the time space domain (Tarantola 1984; Pica et al. 1990; Sun and McMechan 1992). Inversion can also be implemented in the frequency domain (Pratt et al. 1998, 1999; Ben-Hadjali et al. 2008). Recently, 3D FWI has been applied on real data sets in marine (Plessix 2009; Sirgue et al. 2009; Vigh et al. 2009, 2010) and land (Plessix et al. 2010) environments. These works demonstrate that FWI can be used for velocity updates if the acquired data have enough low frequencies and long offsets. Particularly, the shallow part of the model could be significantly enhanced by use of FWI and can result in a more improved depth image over all. One of difficulties with FWI is the convergence to the local minima, which makes the technique very sensitive to the starting velocity model, especially when 3D is considered. To lessen the sensitivity of the initial velocity field, low frequencies and long offsets are required (Bunks et al. 1995; Pratt and Shipp 1999) enabling FWI to update the low-frequency component of the velocity model. We have implemented a time-domain acoustic version of full-waveform inversion using the two-way wave equation with an elastic correction factor to model seismic data using an initial best guess of the earth model. This can be a depth model from a previous processing effort and/or calibrated to well logs and any other seismic or non-seismic measurements. The modeled seismic data are compared to the real prestack seismic measurement, and errors are backwards propagated into the velocity model, iterating to a final detailed model (Figure 1).

3 Figure 1 Full-waveform inversion workflow. Results As with the deployment of any new data processing solution, FWI was initially applied and tested on synthetics. Encouraging results were obtained by performing FWI on the SEG Advanced Modeling (SEAM) Corporation model. Starting with a smoothed version of the SEAM velocity model, FWI was able to recover a significant amount of the true model detail (Figure 2). Figure 2 FWI is able to capture the thin layer of higher velocities just above the salt and the slowvelocity, over-pressured sediments below the salt. FWI has been performed to build velocity models on several real 3D projects in the Gulf of Mexico (GoM), North Sea, offshore Australia, and on an onshore near-surface project, and is currently being applied on a 30,000-km 2 reprocessing project in the GoM. In all cases, results are very encouraging. Figure 3 shows a comparison of RTM images produced with a tomography velocity model versus the FWI velocity mode.

4 Traditional model RTM FWI model RTM Figure 3 Comparison of RTM images using a velocity model produced with tomography (left) and FWI (right). The FWI image on the right improves the structural closure and enhances the detail in the sediments. The ability of FWI to delineate salt reflectivity, starting with a sediment velocity model derived from a conventional tomography approach, reduces the manual effort required in interpreting salt geometry. See comparison depth slices (Figure 4). Figure 4 Results from a FWI project with the starting model from tomography on the left and the FWI model on the right. Note the ability of FWI to add detail and delineate the reflectivity of the salt horizon. Observations and Conclusions Prestack full waveform inversion is a challenging and compute-intensive task, especially for 3D projects on real data (Vigh et al. 2009). However, with the availability of increased compute power and faster two-way wavefield propagation algorithms, it is now realistic to apply full-waveform inversion as part of the imaging effort. Applications to date have universally shown uplift, with more detail in the velocity model and better definition of complex structures.

5 Acknowledgements We thank the FWI team at WesternGeco, whose work led to the examples shown in this paper, and WesternGeco management for allowing us to present this paper. References Ben-Hadj-ali, Operto, H.S. and Vireux, J. [2008] Velocity model building by 3D frequency-domain, fullwaveform inversion of wide-aperture seismic data. Geophysics, 73, VE101 VE117. Bunks, C., Saleck, F.M., Zaleski, S. and Chavent, G. [1995] Multiscale seismic waveform inversion. Geophysics, 60, Pica, A., Diet, J.P. and Tarantola, A. [1990] Nonlinear inversion of seismic reflection data in laterally invariant medium. Geophysics, 55, Plessix, R.-E. [2009] Three-dimensional frequency-domain full-waveform inversion with an iterative Solver. Geophysics, 74, no.6, WCC149 WCC157. Plessix, R. E., Baeten, G., demaag, J.W., Klaasen, M., Rujie, Z. and Zhifei, T. [2010] Application of acoustic full waveform inversion to a low-frequency large-offset land data set. 80th SEG Annual International Meeting, Expanded Abstracts, Pratt, R. G., Shin, C. and Hicks, G.J. [1998] Gauss-Newton and full Newton methods in frequency space seismic waveform inversion. Geophysical Journal International 133, Pratt, R. G., and Shipp, R.M. [1999] Seismic waveform inversion in the frequency domain, Part 2: Fault delineation in sediments using crosshole data. Geophysics, 64, Sirgue, L., Barkel, O.I., van Gestel, J.P., Askim, O.J. and Kommendal, J.H. [2009] 3D waveform inversion in Valhall wide-azimuth OBC. 71st EAGE Conference and Exhibition, Extended Abstracts. Sun, R., and McMechan, G.A. [1992] 2D full-wavefield inversion for wide-aperture, elastic, seismic data. Geophysical Journal International, 111, Tarantola, A. [1984] Inversion of seismic reflection data in the acoustic approximation. Geophysics, 49, Vigh, D. V., Starr, W.E.S. and Dingwall, K.D. [2009] 3D prestack time domain full waveform inversion. 71st EAGE Conference and Exhibition, Extended Abstracts. Vigh, D., Starr, B., Kapoor, J. and Li, H. [2010] 3D full waveform inversion on a GOM data set. 80 th SEG Annual International Meeting, Expanded Abstracts,