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1. QI technology Theory and application AVO, Seismic Geomechanics Workflows

2. AGENDA

3. What is Seismic Inversion? + = - Forward Inverse rock column acoustic impedance reflectivity input wavelet seismic traces = estimated wavelet reflectivity acoustic impedance rock column

4. What is inversion of reflection seismic data? Iterative updating of a sub-surface model in terms of elastic parameters, e.g. acoustic impedance until the object function is minimized, e.g. misfit between observed and synthetic seismic data 4

5. AVO Inversion Workflow Well data Interpretation data Seismic data Background model Inversion Property Builder Wavelet Estimation Simultaneous AVO inversion AI (Acoustic + Shear) Poisson’s Ratio Density

6. Seismic inversion techniques Inversion techniques can be divided into two main classes: Those using global optimization , ISIS Global Seismic Inversion. Those using local optimization , sparse-spike based methods. 6

7. 7 Global optimization ISIS SEISMIC INVERSION Global search covering all possible solutions Cost function Solutions • • • • • • • • • • ISIS 3D global optimization 3D multi-trace global optimization Based on simulated annealing Allows realistic statistical model for sub-surface prediction

8. AGENDA

9. AVO Inversion Workflow Well data Interpretation data Seismic data Background model Inversion Property Builder Wavelet Estimation Simultaneous AVO inversion AI (Acoustic + Shear) Poisson’s Ratio Density

10. Wavelet Extraction To estimate the embedded wavelet in the seismic data by matching the seismic reflectivity with the well log reflectivity, and tie the well to the seismic data Methods available in 2013: Extended Roy White ISIS Time Domain ISIS Frequency Domain Objective

11. ISIS Wavelet Estimation Methods Least squares Least squares constant phase Linear phase Minimum phase Maximum phase Estimated parabolic phase Estimated constant phase Least squares 1 st harmonic phase Least squares Least squares phase Linear phase Minimum phase Maximum phase Time domain * * * * preferred methods * Frequency domain

12. ISIS Frequency : Least squares phase Extended White Wavelet examples (real data) ISIS Time : Least squares constant phase ISIS Time : Least squares ISIS Frequency : Least squares Frequency Domain Time Domain

13. AGENDA

14. AVO Inversion Workflow Well data Interpretation data Seismic data Background model Inversion Property Builder Wavelet Estimation Simultaneous AVO inversion AI (Acoustic + Shear) Poisson’s Ratio Density

15. Introduction AVO seismic inversion to absolute acoustic and elastic properties requires low frequency data from outside the seismic bandwidth For this purpose a Low frequency model is required Seismic bandwidth Low frequency model

16. Inversion Property Builder - Prior Model workflow 16 Inversion Property Builder Wells and 3D Surfaces Properties 2D Elastic Properties Well Weight Maps Blind Well Test Wells and 2D horizons + Markers 3D Elastic Properties Scenario 3D Seismic Scenario 2D Seismic

17. Data and Parameter QC Blind well test: It generates. for every property and at every well location, the extrapolated trace from all other wells and compares it to the actual well log . The plot should highlight any log data/horizon inconsistence's. The Green curve is the well log, the red curve the model log

18. Data and Parameter QC A weight map for each well is generated in a folder in the data tree, the map may be viewed in the map window. Here the extent of influence of a given well may be QC’ed as the parameters for the well weight, inverse distance and cluster weighting are optimised weight plots

19. 2D Lines models outputs AI VPVS RHO

20. AGENDA

21. AVO Inversion Workflow Well data Interpretation data Seismic data Background model Inversion Property Builder Wavelet Estimation Simultaneous AVO inversion AI (Acoustic + Shear) Poisson’s Ratio Density

22. ISIS inversion objective function E = f(S/N)   (Si – di)² + f(1/  horizontal)   Ci.( Zi – Zi ± 1) ² + f(1/  prior)   ( Zi – Zprior ) ² + Rthreshold  # significant reflectors S/N : User-defined signal-to-noise ratio di : Seismic data at sample i . Si : Synthetic seismic at sample i . σhorizontal : User-defined horizontal standard deviation parameter Ci : Continuity at sample i . Zi : Property value at sample i Zi±1 : Property value at the four neighbouring samples (neighbours opt. determined by dip) σprior : User-defined deviation between the inversion result and the low frequency model Zprior : Property value of the prior model at sample i Rthreshold : User-defined threshold for significant reflectors # significant reflectors : The total number of significant reflectors 22

23. ISIS inversion parameters The four terms in the objective function are weighted by the user by: 1. Signal to noise ratio per seismic dataset 2. Continuity parameter - RALPHA 3. Deviation from prior model parameter -RSIGMA 4. Threshold for reflection coefficients - R1 23

24. ISIS inversion parameters 24 Signal to Noise Ratio Deviation From Prior Model Continuity Threshold For Reflector Coefficient

25. Simultaneous seismic inversion - Inversion case setup

26. Simultaneous seismic inversion - Inversion case setup optional – time variant wavelets- Frequency dependent attenuation

27. Simultaneous seismic inversion Once run the case may be opened and the run statistics reviewed. Rthreshold  # significant reflectors