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Intelligent Interpretation: From Here to Where?

Explore the future of seismic interpretation and the advancements in automatic horizon picking and fault extraction. Learn about the potential of computer-assisted seismic stratigraphy and the role of geologists in interpretation.

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Intelligent Interpretation: From Here to Where?

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  1. Intelligent Interpretation: From Here to Where? Dr. Bradley Wallet

  2. What is the Future for Seismic Interpreters? Dr. Bradley Wallet

  3. Is it this?

  4. Is it this? Belay that order!

  5. Or, is it this?

  6. Automatic horizon picking • Widely accepted and available • Relatively stable and mature technology • Works with supervision

  7. Automatic horizon picking +

  8. Automatic horizon tracking

  9. Automatic horizon picking

  10. Significant steps forward • Consistent dip (Petrel) – Provides consistent paths for horizon tracking using dip • Sequence Stratigraphy Interpretation System (Opendtect) – Offers a fully automatic option for horizon tracking in a volume

  11. Paleoscan

  12. Paleoscan

  13. Automatic fault extraction • Wide spread availability • Not widely used • Reliability is highly variable • Requires careful attribute tuning • Requires careful qc • Adding missing faults • Removing spurious faults • Combining fault patches

  14. Example Processes Median Filter Structural SeismicConditioning Smoothing Original Gaussian Seismic Spatial filter Bandpass filtering Chaos EdgeDetection Variance Dip Deviation EdgeEnhancement ManualInterpretation Ant - Track Fault Filter Volume SpatialFiltering Auto-trackInterpretation PostConditioning Thinning Fault Patches Edit Extracted Faults Fault Volume (Visual Filtering) Fault Interpretation AFE in Petrel

  15. Insight Earth

  16. 0.0 divergent divergent convergent t (s) convergent 1.5 Geometric attributes: tools for 3D seismic stratigraphy (Barnes, 2002)

  17. high amplitude continuous high amplitude semicontinuous moderate amplitude continuous moderate amplitude semicontinuous low amplitude continuous low amplitude semicontinuous transparent Towards computer-assisted seismic stratigraphy • Select zones of geologic interest for training 2. Choose attributes that differentiate these zones 3. Train a neural network to imitate an interpreter 4. Generate a seismic facies map (West et al., 2002)

  18. Towards computer-assisted 3D seismic stratigraphy coherence 3D seismic facies Geologic Interpretation (West et al., 2002)

  19. Amplitude Similarity + 1 Unsupervised learning (clustering) Opacity Opacity (a) 2D histogram N 1.8 0 5 km − 0.3 100% 100% Time (s) SOM latent axis 2 2.1 (b) 1.7 (a) SOM latent axis 1 Time (s) 2D colorbar (b) 2.0 SOM latent axis 2 (d) 1.7 0 (c) Time (s) SOM latent axis 1 (c) 1.8 2.0 (e) (d) (f) Time (s) Inline 2.1 Z-scale=1:5 Crossline (f) (e) 1.7 1.7 Time (s) Time (s) Horizon A 2.0 2.0

  20. Where are we? • Focused on individual data sets • Crafted and user intensive • Extends the efficiency of the interpreter • Dependent upon the skill of the interpreter • Allows the interpreter to quickly interpret in 3D

  21. How far can we go? • Multi-data set learning is possible • Object based learning is on the horizon • Completely map the facies in the data set

  22. What’s probably too far? • Computer can interpret the seismic • Human will still need to interpret the interpretation

  23. Let us hope Belay that order!

  24. But… We are increasingly removing the geophysics from interpretation of seismic. At this point, will a geologist be more qualified to do the interpretation than a geophysicist?

  25. This could be possible…

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