Geosciences Artificial Intelligence Applications

Patrick Stinson*, Frederic Joncour**, Sebastien Guillon**, Pierre Goutorbe**, Laurent Castanie***Total E&P Norge, Stavanger, Norway**Total E&P Research and Technology USA, Sunnyvale, CA

ConfidentialContract FR00009812

What is Gaia ?

Gaia Mission: To Give Back Time to the Geoscientists

Digital program to accelerate 2G part of the E&P workflow

GeosciencesArtificialIntelligenceApplication

Seismic acq. & imaging

Interpretation & geomodel

Reservoir simulation

Well design & planning

Well design & drilling

Production optimization

ConfidentialContract FR00009812

Ready to build?

ConfidentialContract FR00009812

Geoscience Artificial Intelligence Program

Semantic AI

Accelerate search for relevant information in documents from weeks to minutes.

Pattern Recognition AI

Automatic interpretation of 3D seismic images (faults, salt bodies, etc.).

What are the different sources used to build this report, do we have access to them?

What are the different PVT (pressure, volume, temperature) laws used in this field?

.

Tools to help geoscientists gain time during mundane and tedious tasks

ConfidentialContract FR00009812

5

Potential for significant time saving depending on data quality

Fault model prediction

• Result depends on seismic data quality

• Current effort on 3D prediction model and cleaning the output

ConfidentialContract FR00009812

Manual interpretation

AI Fault Attribute(ASL current product)

Fault Stick Extraction(Post-processing)

Fault Individualization(Post-processing)

2D workflow

Prediction quality estimated by comparing manual interpreted and prediction on one vertical section and slice for each evaluation set

Precision : accuracy of predictionRecall : Detected faults/all faults Human interpretation

Fault model prediction

ConfidentialContract FR00009812

Manual interpretation

AI Fault Attribute

StickExtraction

FaultIndividualization

~40% ~70%

Tim

e

(estimation based on a good seismic quality blind dataset)

ManualFault Interpretation

Fault stick assignation + manual editing

Productivity gain estimation

ConfidentialContract FR00009812

3D Fault interpretation

8

Current effort on 3D prediction model

Additional upside : improve post processing and better training datasets

2D Fault model

3D Fault model

ConfidentialContract FR00009812

Ongoing improvement Model 2D Model 3D

+

+Improve training datasets

1

2

3

Post Processing Upside

Fault Model Upside

ConfidentialContract FR00009812

Horizons interpretation• Direct segmentation is challenging

• Assisted workflow trained with a small amount of data gives promising results in 2D

• Capacity of extrapolation of the ML model to near-by data

Still in progress and will require significant effort on user interface

S NRaw Psdm section S NPsdm section with prediction

ConfidentialContract FR00009812

Lessons learnt: what does a ML project look like?

13

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Our ambition

14

Main challenges:

• Legal & confidentiality

• Data (gathering, quality)

• Maintenance of model

• Organizational changes

More time to think, more time to explore other ideas and to exchange

As for every technique, you will need to learn how to use it

Today

Highest added value geoscientists input

Reporting and presentationsCreativityInformation gatheringSeismic interpretationCollaboration

ConfidentialContract FR00009812

Our ambition

15

Main challenges:

• Legal & confidentiality

• Data (gathering, quality)

• Maintenance of model

• Organizational changes

More time to think, more time to explore other ideas and to exchange

As for every technique, you will need to learn how to use it

Today

Highest added value geoscientists input

Long term

Highest added value geoscientists input

Reporting and presentationsCreativityInformation gatheringSeismic interpretationCollaboration

ConfidentialContract FR00009812

Thank you

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ConfidentialContract FR00009812