随钻声波测井数据压缩的小波神经网络法
Wavelet Neural Network Method for Acoustic Logging-While-Drilling Waveform Data Compression
-
摘要: 针对当前石油工程声波随钻测井中大量测井数据需要在井下实时压缩存储的迫切要求,结合声波测井数据的特点,提出了一种基于小波神经网络的数据压缩算法,并利用共轭梯度法优化网络参数。实验结果表明,该算法具有参数收敛速度快、数据压缩比高的特点,能够满足随钻声波数据高速实时处理的需要。Abstract: A large of logging data must be stored in downhole imminently in the acoustic logging-while-drilling of petroleum engineering. In this paper, an efficient data compression algorithm based on wavelet networks for acoustic wave data is presented. The experiment result shows the features of algorithm such as fast parameter approximation rate and high compression ratio. It can meet the need of the high-speed real-time processing in petroleum engineering.