Incorporating FWI velocities in Simulated Annealing based acoustic impedance inversion

Transcription

1 Incorporating FWI velocities in Simulated Annealing based acoustic impedance inversion Date: 27 September 2018 Authors: Nasser Bani Hassan, Sean McQuaid

2 Deterministic vs Stochastic Inversion Deterministic Inversion Stochastic Inversion Coloured Inversion Relatively inexpensive and fast Single case Captures uncertainty Higher frequency nature Facies classification Useful in vertically complex areas 2

3 Amplitude Low Frequency Model LFC Seismic bandwidth Frequency A simple average Well data Processing velocities Neural Network Statistical Inversion Full waveform Inversion Param1 Param2 Param3 3

4 Amplitude mapping in RAI and AAI Relative Acoustic Impedance Absolute Acoustic Impedance 4

5 Full Waveform Inversion 5

6 Velocity Analysis Advances Exxonmobil.com 6

7 FWI How it works Field Data You only know this From Start Model From Final FWI Model Courtesy & Nvidia 7

8 FWI Benefits Optimised Seismic Processing Highest confidence in the depth structure Most accurate Gross Rock Volume Optimal use of seismic to define lithology and fluid 0-20 Hz from velocity inversion Optimised gain compensation Optimised de-multiple Optimised diffraction collapse Optimised stacking Optimised denoise algorithms Optimised phase control Optimised imaging Optimised seismic structural interpretation Minimised uncertainty away from well control Best structural definition Best velocity with least error away from wells Narrowest range in GRV Most accurate P50 Optimised real amplitude processing Optimised signal to noise Optimised phase stability Optimised offset to angle conversion Seismically derived low frequency component 8

9 XWI Algorithms Inverts turning waves FWI AWI XWI ATV Fixes the cycle-skipping Allows geology to constrain the inversion RWI Inverts reflected waves. Taking us 1km deeper in accuracy than FWI 9

10 XWI True Model Starting Model XWI Inversion 10

11 Simulated Annealing Inversion 11

12 Cost function Simulated Annealing - Cost Function All moves Accepted moves Temperature Steps Converged Iterations n f = W 1 i S obs i S mod m + W 2 i P pri i P mod i=1 i=1 i S obs Observed Seismic i P pri Priori Low Frequency Impedance i S mod Synthetic Seismic data i P mod Modelled Impedance W Weights 12

13 Simulated Annealing Inversion Process Seismic Trace Estimated Estimated Reflection Synthetic Impedance Wavelet Error Coefficient Trace (Colour represents the temperature) 13

14 Normalised Misfit Cost Function Minimisation Process Normalised Misfit vs Iterations Seismic Trace Synthetic Trace Residual Iterations Iterations 14

15 TWT (ms) Inversion Results Jansz-3 Seismic Synthetic Residual Upper and lower bounds in which impedance can move. Inversion AI Log Acoustic Impedance This plot shows the well based inversion. This is not the basis of this exercise and it is only for demonstration of the concept. 15

16 Jansz Field Acoustic Impedance Inversion 16

17 Jansz-IO Field Water depth: m WA-36L WA-40L Jansz-3 WA-39L Io-1 Carnarvon Basin Mesozoic stratigraphy Jenkins et.al km A U S T R A L I A 17

18 depth (m) Start model km Vp (m/s) 18

19 depth (m) XWI Model 5Hz km Vp (m/s) 19

20 depth (m) XWI Model 11Hz km Vp (m/s) 20

21 depth (m) XWI Model 22Hz km Vp (m/s) 21

22 depth (m) PSDM overlay km Vp (m/s) 22

23 Residual Synthetic Seismic Input Seismic Jansz SA Inversion Results - QC 23

24 Rev. Gardner s Gardner s Jansz-3 seismic-well tie 24

25 Sonic Log BP: Hz AI Log BP: Hz Inversion vs Well Logs Jansz-3 IO-1 Velocity AI Velocity AI Sonic Log Inversion Sonic Log Inversion FWI Velocity AI Log FWI Velocity AI Log Rev Gardner s 25

26 TWT (ms) Seismic (reflectivity) phase rotated -90 deg SW 7km NE

27 TWT (ms) Coloured Inversion SW 7km NE

28 TWT (ms) XWI Velocity Model Frequency Filtered Sonic Log SW 7km NE

29 TWT (ms) Simulated Annealing - Absolute AI Frequency Filtered AI Log SW 7km NE

30 Summary Extended Waveform Inversion (XWI) is a modern technique that gives one of the most accurate velocity models that can be used as a low frequency model. Simulated Annealing is an efficient and advanced method in calculating deterministic inversion. Combined the two will provide a very good deterministic absolute impedance inversion, and can be used for estimating reservoir properties.