4D elastic full-waveform inversion Making full use of the life of field seismic datasets

Transcription

1 Workshop on 4D seismic and history matching 4D elastic full-waveform inversion Making full use of the life of field seismic datasets Wiktor Weibull Associate professor Department of Petroleum Engineering Stavanger, April 28, / 19

2 Life of field seismic (LoFS) What is LoFS? Permanent reservoir monitoring (PRM) using seismic data 250 History of LoFS: First LoFS experiment was in Foinaven in 1995 Valhall installed in 2003 Clair installed in 2006 Ekofisk installed in 2010 Jubarte installed in 2012 Snorre installed in 2013 Grane installed in 2014 Coverage (sq. km) Foinaven Valhall Clair Ekofisk Jubarte Snorre Grane (Source: Eriksrud, 2014) 2 / 19

3 Life of field seismic Life of field seismic is still in its infancy High frequency of repetition (2 surveys per year) Repeatability is mainly controlled by diurnal and seasonal changes in water velocity Dynamic images show changes in seismic even in obscured areas Data are in many ways underutilized Data acquired consists of 4 components (Pressure and 3 orthogonal particle motions) Mostly the P component is currently being used for qualitative and quantitative 4D analysis Exploring the full potential of the data will help improve history matching 3 / 19

4 Surface seismic vs. Ocean bottom seismic (Modified from Ikelle and Amundsen, 2005) (Ikelle and Amundsen, 2005) 4 / 19

5 Elastic wavefields 5 / 19

6 PP and PS imaging I PP reflections consist of incident P-waves reflected as P-waves I PS reflections consist of incident P-waves reflected as S-waves I In contrast to P-waves, S-waves are largely insensitive to pore fluids I PS reflections help to illuminate areas that are obscure for PP reflections I The conventional independent processing of PP and PS leads to depth mismatch between the images (Modified from Ikelle and Amundsen, 2005) (Bertrand et al., 2013) 6 / 19

7 Full-waveform inversion (FWI) FWI is a classical non-linear least squares inverse problem The observed seismic data is fitted to a parameter model through a non-linear optimization procedure seeking to minimize the difference between observed and simulated seismic data Depending on the choice of the wave equation used to simulate the seismic data, physical phenomena such as P- to S-wave conversion, and anisotropy can be used in the inversion process (Sirgue et al., 2009) 7 / 19

8 Full-waveform inversion In FWI, the goal is to minimize the difference between waveforms Very non-linear because the waveforms are oscillatory Waveform equation u(x, t) = d 3 x G(x, t; x, 0) S(x, t) (Fichtner et al., 2009) 8 / 19

9 Full-waveform inversion Definition of the error (data misfit) S(m) = 1 2 u(x, t; x s) u obs (x, t; x s ) 2, where u is the simulated data and u obs is the recorded data. To mitigate the non-linearity, it is customary to add a regularization term (model misfit) S R = 1 2 m(x) m 0(x) 2, where m is the estimated model, and m 0 is the initial estimate. 9 / 19

10 Full-waveform inversion Solved using an iterative method m k+1 = m k α k g k, m k g k α k model at iteration k gradient of S(m) at iteration k step length at iteration k Gradient of S is normally computed using the adjoint state method (Chavent, 2009) 10 / 19

11 Application to ocean bottom data from Valhall (Sirgue et al., 2009) 11 / 19

12 Application to ocean bottom data from Tommeliten (Warner et al., 2013) 12 / 19

13 4D FWI Sequential strategy m 0 u base m 0 u mon Data difference strategy (Zheng et al., 2011) m 0 u base û mon = u n + (u mon u base ) FWI FWI FWI u n FWI m n m k m n m k 13 / 19

14 Example of 4D FWI using multi-component data (Raknes and Arntsen, 2015) 14 / 19

15 Example of 4D FWI using multi-component data (Raknes and Arntsen, 2015) Case 1: 1% and 5% 4D anomalies Case 2: 5% 4D anomali 500m 575m 15 / 19

16 Example of 4D FWI using multi-component data (Raknes and Arntsen, 2015) V p V s Sequential Data difference Sequential Data difference 1% 5% 16 / 19

17 Example of 4D FWI using multi-component data (Raknes and Arntsen, 2015) 500 m Vp 575 m Vs Vp Vs 17 / 19

18 Summary Full-waveform inversion(fwi) can be used to estimate changes in V p and V s from 4D multi-component ocean bottom data It is a technique well suited for LoFS data Can incorporate a large range of physical phenomena, including multiple reflections, P- and S-waves and anisotropy Minimal preprocessing of the data is necessary We still rely on conventional processing, such as reflection tomography and migration velocity analysis in order to create a decent initial model In 4D applications, given good repeatability, the data difference strategy can quantify changes in elastic parameters down to 1% of the background model The dependence of the method on the quality of the background model is also reduced 18 / 19

19 Plans for the future I have plans to start a group dedicated to imaging and inversion in the University of Stavanger The group will lead to the training of students in processing and interpretation of multi-component data We will focus on development of new methods to exploit all the information contained in this kind of data At the same time we will do our best to integrate geological knowledge, which is the strength of our group, in the processing and interpretation of the seismic data At some point, I hope to have some cooperation with the industry, as I believe that field data is essential for testing the developed methodologies 19 / 19

20 Bertrand, A., P. G. Folstad, B. Lyngnes, S. Buizard, H. Hoeber, N. Pham, S. de Pierrepont, J. Schultzen, and A. Grandi, 2014, Ekofisk life-of-field seismic: Operations and 4d processing: The Leading Edge, 33, Eriksrud, M., 2014, Seabed permanent reservoir monitoring (PRM) A valid 4D seismic technology for fields in the North Sea: First Break, 32, Fichtner, A., B. L. N. Kennett, H. Igel, and H.-P. Bunge, 2009, Full seismic waveform tomography for upper-mantle structure in the Australasian region using adjoint methods: Geophysical Journal International, 179, Ikelle, L. T., and L. Amundsen, 2005, Introduction to petroleum seismology: Society of exploration geophysicists. Raknes, E. B., and B. Arntsen, 2015, A numerical study of 3D elastic time-lapse full-waveform inversion using multicomponent seismic data: GEOPHYSICS, 80, R303 R315. Sirgue, L., O. Barkved, J. van Gestel, O. J. Askim, and J. H. Kommedal, 2009, 3D waveform inversion on Valhall Wide-azimuth OBC: Presented at the 71st Conference and Exhibition, EAGE, Expanded Abstracts, European Association of Geoscientists and Engineers. Warner, M., A. Ratcliffe, T. Nangoo, J. Morgan, A. Umpleby, N. Shah, V. Vinje, I. Štekl, L. Guasch, C. Win, G. Conroy, and A. Bertrand, 2013, Anisotropic 3D full-waveform inversion: GEOPHYSICS, 78, R59 R / 19