Integration of seismic data

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Integration of Seismic

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Integration of seismic data

  1. 1. Integration of Seismic Data and Uncertainties in the Facies Model P. Nivlet*, S. Ng, M.A. Hetle, K. Børset, A.B. Rustad (Statoil ASA), P. Dahle, R. Hauge & O. Kolbjørnsen (Norwegian Computing Center) 1- Classification: Internal 2010-06-10
  2. 2. Motivation: 3D reservoir modelling Reservoir simulations Production data 3D reservoir model 2- 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  3. 3. The Snorre field • Location: Blocks 34/4 and 34/7 in the Tampen area, in the northern part of the North Sea (191 km2) • Production start: 1992 • Production (2009): ~180,000 bbl/day 3- 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  4. 4. Motivations: Data integration seismic amplitudes (angle-stacks) Well log data 3D reservoir model Structure, stratigraphy 4- 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  5. 5. Challenges in integrating the data • Multi-scale issue 5- 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  6. 6. Challenges in integrating the data Shale 2.0 Vp/Vs Sand 1.7 6,000 10,000 AI (g/cm3.m/s) • Non-unique relationship between seismic amplitudes and geology • A multivariate problem 6- 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  7. 7. The data uncertainty challenge • Random noise • Acquisition / Processing footprint • Angle Misalignments • Imperfect physical model 7- 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  8. 8. Geological setting 1,000 m •Reservoir depth: 2-2.7 km 8- 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  9. 9. Traditional workflow Reservoir grid (depth) geometry Seismic attribute Well facies+extracted (depth) seismic attribute conditioning integration Facies model 9- 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  10. 10. Proposed workflow Reservoir grid (depth) geometry Seismic attribute (depth) Well facies+extracted seismic attribute conditioning integration Facies model 10 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  11. 11. Workflow from inversion to facies prediction Bayesian wavelet extraction Seismic modelling Vp Seismic facies analysis Vs Seismic (partial angle-stacks) Inversion ρ 34/4-1 34/4- m BCU = OWCLunde Increasing probability of shale SN ML SN LL Decreasing probability of shale Lomvi Fm m mBG mS mHF Facies probability 11 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  12. 12. Geostatistical seismic inversion • 1D modelling of seismic amplitudes (Aki&Richards’ model): linear in m=(log(vp), log(vs), log)) d  Gm  n • Normal distribution of elastic properties m mm|d = mBG+mG*(GmG* + e )-1(d - GmBG) m|d = m - mG*(GmG* + e )-1G m • Data (e) stationary uncertainties estimated from analysis of amplitudes • Prior (m) stationary uncertainties estimated from well log analysis 12 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  13. 13. Advantages/limitations of the technique Stationary uncertainty model: Lateral correlations - Global matrix - Different stratigraphy settings - Lateral correlations - Grid built from max. 2 horizons - Vertical correlations 13 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  14. 14. Inversion result: Elastic properties 14 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  15. 15. Impact on elastic parameter uncertainties Seismic bandwidth (Near) 0 10 20 30 AI 0 Vp Rho -50 SI Vs Vp/Vs 0 20 40 60 Frequency (Hz) Prior Posterior uncertainty Prior Posterior uncertainty variation (%) variation AI (%) 15 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  16. 16. Inversion results QC Band-pass filtered AI SI Rhob 100 ms Well Inversion Multivariate correlation (RV) between band- pass well-logs and inversion results  35% of wells RV > 0.8  33% of wells 0.8 > RV > 0.7  32% of wells RV < 0.7 16 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  17. 17. Workflow from inversion to facies prediction Bayesian wavelet extraction Seismic modelling Vp Seismic facies analysis Vs Seismic (partial angle-stacks) Inversion ρ 34/4-1 34/4- m BCU = OWCLunde Increasing probability of shale SN ML SN LL Decreasing probability of shale Lomvi Fm m mBG mS mHF Facies probability 17 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  18. 18. Supervised seismic facies analysis Kernel estimator p(m | Sand) p(Sand | m) 18 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  19. 19. Supervised seismic facies analysis Different resolution scales Raw Well logs Filtered well logs Inversion results at well position Inversion filtered well logs μ m|d = μm+(I- Σm/dΣm-1)(m – μm) + e* 19 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  20. 20. Cross plots: Inversion filtered well logs 1 2.0 2.0 Shale Vp/Vs Vp/Vs Sand 1.7 1.7 0 6,000 10,000 6,000 10,000 AI (g/cm3 m/s) AI (g/cm3 m/s) Inversion frequency filtered Predicted SAND probability 20 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  21. 21. Seismic facies analysis: Sand probability results Sand probability 21 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  22. 22. Inversion results QC: Finding optimal well position Confidence index (khi2): Vertical sand proportion from well 100 ms compared with seismic sand probability Seismic sand probability section 22 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  23. 23. Facies probability QC  31% of wells: Good confidence  61% of wells: Medium  8% of wells: Bad confidence 23 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  24. 24. Inversion results QC Potential factors impacting mismatch Stratigraphic level ++ Position with respect to OWC + Presence of faults + Average shale proportion + 24 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  25. 25. 3D confidence index • Measurement of prediction • Weighting function in facies modelling 1 Well Confidence Inversion result [0,1] 0 25 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  26. 26. Proposed workflow Reservoir grid (depth) geometry Well facies+extracted seismic attribute conditioning integration Facies model 26 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  27. 27. Snorre: Average proportion of channel Average map estimated from 8 realizations 1 1 0 0 27 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  28. 28. Concluding remarks • Integrated workflow from seismic inversion to consistent seismic constrained facies modelling • Fast geostatistical inversion approach and facies prediction • Consistent resolution between inversion results and facies probabilities gives realistic predictions and facies models 28 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  29. 29. Concluding remarks: Further work • How to refine the upscaling of elastic parameters from well log to seismic scales? How to have a more local approach? • Constraining observed 4D signals by using predicted facies sand probability (Ayzenberg and Theune, “Stratigraphically constrained seismic 4D inversion” M017, Room 127/128, Wednesday, 9h30) • Flow simulations of constrained facies models and history matching with 4D for more predictive production prognoses 29 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  30. 30. Acknowledgements Thanks to Statoil, Norwegian Computing Center and the Snorre partners Petoro, ExxonMobil Norge, Idemitsu Petroleum, RWE Dea Norge, Total E&P Norge and Amerada Hess Norge for discussions and permission to publish this work. 30 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010
  31. 31. Thank you Integration of Seismic Data and Uncertainties in the Facies Model Philippe Nivlet Principal Geophysicist –Petek Tyrihans pniv@statoil.com, tel: +47 958 16 589 www.statoil.com 31 - 72nd EAGE Conference and Exhibition – Barcelona, June 14th-17th 2010

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