Machine Learning Assisted Seismic Fault Interpretation
Fahad Khan, Schlumberger
The machine learning assisted fault interpretation workflow has been able to identify a higher proportion of the structures in the seismic survey within a given timeframe. Input seismic is optimised through ingestion in an OSDU compatible data ecosystem. The fault detection process is discussed that provides prediction cubes as well as segmentation and extraction of fault planes to be analysed by the interpreter for a subsequent construction of a fault framework and structural model. The process assists exploration scale seismic interpretation as well as in field appraisal and development through building of multiple structural scenarios that feed into the Agile Reservoir Modeling process where generation of multiple uncertainty realisations for various scenarios is enabled through parallel HPC processes.
About the Presenter:
Fahad Khan is a Senior Geoscientist with Schlumberger Software Integrated Solutions. He is based in Perth, with international experience in a wide variety depositional settings and field developments. He specialises in the development of geoscience workflows to optimise time spent on exploration and development workflows. He is a certified NExT Instructor, having previously delivered many Advanced Level courses.
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As on the last technical meeting, this talk includes a sit-down buffet lunch. Please let us know ahead of time if you have any dietary requirement.
People outside Perth, WA are invited to join through the webinar.
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|Retiree/Student (early bird, inc. GST)||$ 10.00|
|Webinar: FESAus Member (In Perth, WA, inc. GST)||$ 30.00|
|Webinar: FESAus Member (outside Perth, inc. GST)||$ 10.00|
|Webinar: Non-Member (inc. GST)||$ 40.00|
|Webinar: Retiree/Student||$ 0.00|