Reduce subsurface uncertainty in seismic reservoir characterization studies by predicting rock properties in 3D using machine learning. Our AI algorithms use ensemble learning and neural network technology to predict acoustic, elastic, and petrophysical properties from seismic data.
Geoscience Solutions
High-Def 3D
Log Prediction
Sonic and shear sonic measurements must be available at all wells to be used in mapping the lateral extent of a reservoir. Machine Learning can be used to help reduce the cost of a characterization campaign by eliminating the need to acquire these logs at every well.
Classification
Using well data and 3D rock properties, a spatial distribution of facies can be estimated using classification algorithms backed by artificial intelligence.
Seismic Data Conditioning
The quality of migrated gathers is central to seismic inversion. The objective of seismic conditioning is to ensure amplitude preservation while eliminating the post-processing residual effects of noise and multiples.
Seismic Interpretation
To properly calibrate a well into the time domain and build a prior model for inversion, horizon interpretation must be carried out.
Courses
Multi-Physics provides technical and practical training and professional development services for the E&P industry (http://www.nexttraining.net). The delivery method can be either as a traditional course or a more hands-on approach.