基于泰勒级数估计的油井数据无损压缩

为了实现油井数据的高效传输,提出一种新的无损压缩算法.利用泰勒级数分解拟合出油井数据曲线,进行后向估计,通过传输拟合值与实际值的估计误差,实现数据的无损压缩.实测油井数据仿真表明该算法压缩率可达25%~40%,其整体性能优于霍夫曼编码、LZW编码等无损压缩算法至少20%,并具有时间空间复杂度低的特点.通过大港油田数据远程传输系统验证,该算法可将传输网络数据负荷降低至45%. 

Oil Well Data Lossless Compression Based on Taylor Series Estimating

A lossless compression algorithm applied on the oil well data transmission was proposed in this paper. Taylor series expansion was used to fit the curve of the oil well data, then the backward estimation was used for data processing. The lossless compression was realized by transmitting the fitting estimation error and initial sequence. From the simulation results, data compression ratio is up to 25%~40% with a low time-space complexity. Compared with other typical coding, like Huffman coding and LZW coding and Delta coding, this compression ratio has 20% advanced. Based on the verification of the actual oilfield RTU, this design can significantly decrease the burden of the data-transmitting net to 45%.