It is now almost a year since the Go computer program
AlphaGo, constructed by DeepMind, beat
the world Go champion, Lee Sedol .
As I understand it, a key success factor for DeepMind
was that Go is a rule-based game; and machine learning from DeepMind ‘loves’
rule-driven analyses and being fed
thousands of historic completed games from which to learn.
I have pointed out that geology is a rules-driven
science and that machine learning could be applied to seismic (perhaps
especially 3D seismic) interpretation, there being thousands of completed
interpretations available for ‘learning’.
Perhaps this is a half-baked idea? I do not yet see
any evidence of such disruptive transformation of seismic interpretation.
Approaching this with an inappropriate sense of humour,
I suggest this leaves us in the position of ‘Art can only be done with paint
brushes’ or ‘Presentations can only be done with transparencies and an OHP”!*
Perhaps this is the best analogue of the serried ranks
of seismic interpreters working in our industry…..
and inclined to travel to work in one of these:

Putting my
serious hat back on, it seems to me that the current combination of humans and
(interpretation) workstations is both too high cost, in an era of lower oil and
gas prices, and not as effective as we need, given that there are plenty of
examples of mis-interpretation – incorrect correlations, incorrect
chronostratigraphy, implausible structural geology, unlikely reservoir
distributions…….
Our report card would read: “Must do better! Can do
better!!”
* to the first person who can 100% prove to me that
they made a presentation using transparencies and an OHP in 2016, I will award
a prize of a lino-cut picture, based on a scene from the petroleum industry!