A Robust Neural Network Model for Pattern Recognition of Pressure Transient Test Data

Abstract

Abstract A modified approach for pattern recognition from derivative plots by using neural network methodology is proposed. Instead of training only one single comprehensive neural net to recognize all possible patterns, multiple neural nets are employed in which each neural net is trained to recognize patterns for a specific conceptual reservoir model. This improves the full representation for each model. At the same time the proposed approach assists in recognition of various models with similar responses. A hybrid approach is suggested where the output from the proposed neural network can be cross correlated with models suggested from other data sources.