Reaching new frontiers within seismic interpretation and analysis by utilizing deep learning computer vision technology. VAP4U has worked for a long period how to utilize this technology on normal standard seismic data (SEG/Y or other vendor formats) and propose how to use it through the software s AI s. Convolutional Neural Networks (CNN) and other machine learning algorithms and methods enables us to make the computer to identify and learn to identify more features in the seismic data than previously done. Training the computer with the help of some initial input which is done once. Then let the algorithms within limitations and boundaries set by the experts do its work identifying features of interest within the data. Looking for playmodels, lead types or prospects, then let the computer take the grunt of the workload and spend time on more important analysis such as risk and ranking of plays.

1. S AI S
S EIS M IC ARTIFICIAL INTELLIGENCE S YS TEM
A machine Learning software for use on
seismic data and raster data in general.

2. A PARADIGM SHIFT IN SEISMIC ANALYSIS

3. LET US MAKE A GUIDED TOUR OF SAIS

4. START A PROJECT IN SAIS

5. A BRAND NEW PROJECT IN SAIS
WITH TRAINING DATA AND FEATURE MODEL

6. LET’S GRAB SOME SOURCE DATA IN SAIS

7. WE HAVE MULTIPLE CHOICES OF DATA
TYPES WITHIN SAIS

8. WE IMPORT 2D SEG-Y DATA FOR NOW

9. TRAIN THE COMPUTER FOR SOME
SERIOUS ACTION LATER

10. A FEATURE MODEL IS REQUIRED FOR THE
MACHINE LEARNING TO DO IT’S JOB
FIRST WE USE AN EXISTING MODEL IN SYSTEM

11. A FEATURE MODEL IS REQUIRED FOR THE
MACHINE LEARNING TO DO IT’S JOB
NOW WE CREATE A NEW NEURAL MODEL

12. BUILDING THE NEURAL NETWORK MODEL
REQUIRE SEVERAL INPUT PARAMETERS

13. HOW DO WE WANT TO SEE THE
WINDOWS?

14. LET US TILE THE WINDOWS

15. WE CAN NOW SEE THE IMPORTED DATA
IN THE SEISMIC DATA WINDOW

16. THE COMPUTER IS READY TO START IT’S
WORK AND LEARNING –
IT IS IMAGE PROCESSING TIME!
W E US E A CLO UD B A S E D S E RVICE TO H A RVE ST CO M P UTER P OW E R

17. THE SYSTEM TAGS FEATURES WHICH IT WANT YOUR
INPUT ON TO ENSURE IT’S LEARNING WHAT TO DO
NEXT TIME IT SEES THE SAME FEATURE

18. IT ASKS FOR MORE CONFIRMATIONS AND
ALSO ASKS FOR WHAT FEATURE IT SEES
HERE.

19. S A I S H A S CRE ATE D A S UM M A RY O F F E ATURES A N D H OW M A N Y P LACE S
I T H A S F O UN D I T I N TH E S E I S MIC DATA . N OW YO U CA N VE RI F Y TH E S E
B Y S E LE CTING LI N E S A N D LO CATI O NS I T F O UN D TH E SE

20. LET US VERIFY FEATURE – AND SEE IF S AI S
HAS LEARNED CORRECT AND REMEMBERS
IT CORRECTLY.

21. YOU HAVE NOW WITNESSED MACHINE
LEARNING THROUGH IMAGE PROCESSING
USING NEURAL NETWORK MODEL

23. WHO ARE WE?
TheVAP4U team and our consultants are always ready to help you with the challenges you may have as
an individual or company.We have experience in many differenteducation,improvementand strategy
work:We also work in cognitive areas.
The companystarted in 2002 with focus on consulting in the energy sector in Scandinavia,and has since
developed into other sectors, such as manufacturing and service industries.
The latest service area in the company'sportfolio is facilitation in strategy,education and the sports
sector
Stig-Arne Kristoffersen
Entrepreneur, Certified facilitator and
experienced cognitive instructor and
football coach. Worked on opinion
formation for different companies and
authorities.
Tetyana Kristoffersen
Owner Civil Law firm, mathematics
and IT teacher and certified civil law
lawyer.
Experienced facilitator.
www.vap4u.eu