Interactive Deep Learning for Interpreting Seismic Expression of Injectites

  • Deep Learning
  • >
  • Interactive Deep Learning for Interpreting Seismic Expression of Injectites

Bluware’s Chief Geologist, Erik Holtar, is featured in EAGE First Break to demonstrate deep learning’s potential for interpreting the seismic expression of injectites.

The geometry and reservoir properties of injectites have always challenged seismic interpreters. The breakthroughs in understanding injection, formation, and impact from fluid migration, coupled with 3D seismic data in the early 2000’s, have given geoscientists more ways to assess lithology and seismic fluid effects.

Even with decent imaging of the injectite geometry, manual interpretation is difficult and time consuming using traditional interpretation tools.

The use of interactive deep learning for interpreting the 3D seismic geometry of injectites can have significant potential for injectite reservoir identification and risk analysis. Furthermore, AI-assisted interpretation enables the use of multiple seismic datasets, such as angle stacks and different survey vintages covering the same area. This supports generation of several alternative predictions of injectite geometry, giving the interpreter a better basis for critical data analysis.

Download Case Study

Notify of
Inline Feedbacks
View all comments

Sign up for updates.