Neural Network Smoothing of Geonavigation Data on the Basis of Multilevel Regularization Algorithm

The problem of increasing the accuracy of geonavigation data being used for the control of the drilling oil-gas well trajectory is considered. The approach to solving the problem based on the distortion and measurement noise filtration with the use of the smoothing neural network is proposed. The generalized algorithm of the smoothing neural network design on the basis of the multilevel regularization is discussed. The peculiarities of the algorithm realization with the use of the offered vector regularization criterion of network parameters ranking is considered. The example of smoothing the geonavigation data on the basis of designed RBF network is considered.