A lossless compression method for logging data while drilling

Abstract

Mud pulse transmission technology is widely used in logging while drilling (LWD), while its low data transmission efficiency has restricted the development of LWD technology for a long time. In order to improve the equivalent data transmission efficiency of LWD system, a data compression method, namely, Frame Prediction Huffman Coding (FPHC) with a group of frames, is proposed in this paper. Several factors including the data accuracy, the need for real-time transmission, and the existence of transmission errors are comprehensively considered in the proposed method. Through the probability statistical analysis of LWD data, it is proved that the data have a relatively stable probability distribution after predictive coding. In addition, the Huffman code table generated from predictive coding is universally applicable to other LWD data. Through data compression experiments on logging data, it is verified that the proposed method has higher compression efficiency compared with Huffman coding, Lempel-Ziv-Welch algorithm, adaptive Huffman coding and adaptive arithmetic coding. This lossless compression method will have a good application prospect because of its ability to prevent error diffusion, simple implementation and easy to be embedded in down-hole equipment.

A Data Compression Method for Wellbore Stability Monitoring Based on Deep Autoencoder

“…Due to the input dimension of the proposed method and deepAE method, the shape of the X inc_test and X azi_test data was reset to (18,088). In addition to the deepAE method, the quantization data bits of the proposed method, DPCM method, and DPCM-I method were set to 4, 5, 6, 7, and 8 to verify the error reduction performance under different quantization data bits.…”

“…Huffman coding, a classic lossless compression method, allows for complete restoration of original data from the compressed data, albeit with relatively low compression rates. For instance, Song et al [ 18 ] employed Frame Prediction Huffman Coding (FPHC) in their 2021 study to compress various logging data, achieving a compression ratio of only 1.41. Although this ratio surpasses that of traditional Huffman and arithmetic coding, its impact on enhancing data transmission efficiency remains limited.…”