EAGE EXTRA: Machine Learning-based Rock Type Classification

Date: June 14, 2017 Published by

  • Alongside waveform neural network classification, Paradigm 17 introduces a machine learning-based technology known as rock type classification based on Democratic Neural Network Association (DNNA).
  • On the other hand, the probabilities associated with each facies are directly input to simulate different scenarios of facies distribution.
  • It predicts not only the most likely facies distribution and associated maximum probability but the probability relative to each facies.
  • This method optimizes the use of prestack and post-stack seismic data along with well data using an innovative supervised process.
  • It delivers a calibrated and upscaled facies distribution that can be used directly in any reservoir characterization and modeling workflow.