Intersection recognition of well logging curve based on discrete hopfield neural network
Luo Dai-sheng · Journal of Computer Applications · 2008
In the process of vector quantization of well logging curve, background grids and other forms of curve interference discontinue curve tracking and hardly to achieve automatic tracking, so manual direction judgment is needed. This article proposes a method for well log curves intersection recognition using Discrete Hopfield Neural Network (DHNN). This method presets 8 standard direction samples for network training. During curve tracking, entering recognition status if comes across intersection, the algorithm makes accurate prediction of curve direction through branch match of well-trained Hopfield network, in combination with width match. Theoretical analysis and experiment demonstrates that this method improves the precision of intersection recognition and has a good result of anti-interference.