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. AFE in Petrel Edge Enhancement Seismic Conditioning Edge Detection
Median
Filter
Dip
Deviation
Variance
Original
Seismic
Structural
Smoothing
Gaussian
Spatial filter
Ant -
Track
Fault
Volume
Example Processes
Thinning
Chaos
Bandpass
filtering
Edge Enhancement
Seismic Conditioning
Edge Detection
Edit Extracted Faults
Auto-track Interpretation
Fault Interpretation
(Visual Filtering)
Post Conditioning
Spatial Filtering
Manual Interpretation
Patches

15. Insight Earth

16. Geometric attributes: tools for 3D seismic stratigraphy
1. Introduction
0.0
1.5
t (s)
convergent
divergent
Geometric attributes: tools for 3D seismic stratigraphy
divergent
convergent
Calculation of reflector convergence and divergence is the first step toward 3D computer-aided seismic stratigraphy. In these images, positive convergence is shown as blue, and negative convergence (divergence) is shown as yellow. Like dip and azimuth, reflector convergence is a vector. Here, we display the component of convergence/divergence in the inline direction. After Barnes (2000b).
(Barnes, 2002)

17. Towards computer-assisted seismic stratigraphy
1. Introduction
Towards computer-assisted seismic stratigraphy
moderate amplitude continuous
high amplitude continuous
low amplitude continuous
moderate amplitude semicontinuous
high amplitude semicontinuous
low amplitude semicontinuous
transparent
A typical seismic facies classification using an interpreter-trained probabilistic neural network, in which multiple facies classes have been identified. The seismic classification scheme on the right consists of high-amplitude (HA), moderate-amplitude (MA), low-amplitude (LA), continuous (C), and semicontinuous (SC) seismic facies. After West et al. (2002).
4. Generate a seismic facies map
2. Choose attributes that differentiate these zones
3. Train a neural network to imitate an interpreter
Select zones of geologic interest for training
(West et al., 2002)

18. Towards computer-assisted 3D seismic stratigraphy
1. Introduction
Towards computer-assisted 3D seismic stratigraphy
coherence
3D seismic facies
Geologic Interpretation
(a) A coherence slice highlighting the lateral edges of a channel (red lines), a broad, older sinuous element (1), and a narrower, younger sinuous element (2). (b) A seismic facies slice, showing that sinuous element (1) is composed of high-amplitude-continuous (HAC) to moderate-amplitude semicontinuous (MASC) seismic facies, whereas sinuous element 2 is composed primarily of HAC seismic facies. Because the texture-analysis seismic-facies classification is a volume, this type of analysis can be applied at different stratigraphic levels within an interval of interest, whether or not the interval is bounded by mapped horizons. (c) Considering the conceptual relationships between seismic facies and their potential associated geologic fill, the net-to-gross environment can be understood and 3D regions can delineate differing depositional and geologic properties. After West et al. (2002).
(West et al., 2002)

19. Unsupervised learning (clustering)
1.8 N
2D histogram
5 km
Time (s)
SOM latent axis 2
2.1
Similarity
0.3 1
100%
Opacity
(b)
1.7
(a)
SOM latent axis 1
Time (s)
2D colorbar
(b)
2.0
SOM latent axis 2
(d)
1.7
Amplitude − +
100%
Opacity
(c)
Time (s)
SOM latent axis 1
(c)
2.0
1.8
(e)
(d)
(f)
Time (s)
Because seismic is the only data we have, we want to look for evidence for the previous interpretation on vertical seismic amplitude sections. Section A shows the northern channel complex. We use red line to outline the channels. In this vertical section, Horizon A is at the middle of the SOM facies window. We can find channels are mapped in cyan to purple colors, while the surrounding overbank complex deposits mapped in yellow to brown colors. In section B, we can see the lateral migration of this channel complex. Here are at least four channel stories migrating from northeast to southwest. We can also see the oldest story is mapped as lime green, while the younger channels are cyan. This suggests a change in grain size during deposition. The oldest story is sand-filled, and the younger stories are mud-filled. The more distal part of this channel is more spread out, forming a lobe mixed with the other main channel. We also see an oxbow-like feature in the older deposits. At last, for the two twisted channels, we can clearly see the red channel cutting through the older sand-filled channel in lime green. Similar to the northern main channel, we see the width of these two channels has expanded dramatically from proximal to distal, merging into a lobate feature.
Inline
2.1
Z-scale=1:5
Crossline
(e)
(f)
1.7
1.7
Time (s)
Time (s)
2.0
Horizon A
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…