Method to predict coal seam's thickness and fine fault using RS and NN

Abstract

This paper puts forward a new method of Rough Sets (RS) and Neural Network (NN) which is used to detect fine faults and coal seam thickness by analyzing 3D seismic data. This method uses RS to reduce seismic data containing noise, and after reduction, low noise seismic data can be hold. Then input those reduced data to NN, a predicting model which can detect fine faults and predict coal seam's thickness can be achieved after NN training. After this step, this model was used to detect fine fault of 3D seismic data. We find that this method has a higher precision.