Importance of drilling-related processes on the origin of borehole breakouts — Insights from LWD observations

Stricker, Kai Robin; Schimschal, Stefan; Müller, Birgit; Wessling, Stefan; Bender, Florian; Köhl, Thomas

doi:10.1016/j.gete.2023.100463

Cited by 3 publications

(1 citation statement)

References 27 publications

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“…At present, the primary method for monitoring wellbore health [ 1 , 3 ] involves the use of logging while drilling (LWD) tools to gather real-time data on the wellbore’s condition. The data are then evaluated using established rock mechanics principles and correlations with logging data.…”

Section: Introductionmentioning

confidence: 99%

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

Song,

Zhao,

Zhang

et al. 2024

Sensors

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The compression method for wellbore trajectory data is crucial for monitoring wellbore stability. However, classical methods like methods based on Huffman coding, compressed sensing, and Differential Pulse Code Modulation (DPCM) suffer from low real-time performance, low compression ratios, and large errors between the reconstructed data and the source data. To address these issues, a new compression method is proposed, leveraging a deep autoencoder for the first time to significantly improve the compression ratio. Additionally, the method reduces error by compressing and transmitting residual data from the feature extraction process using quantization coding and Huffman coding. Furthermore, a mean filter based on the optimal standard deviation threshold is applied to further minimize error. Experimental results show that the proposed method achieves an average compression ratio of 4.05 for inclination and azimuth data; compared to the DPCM method, it is improved by 118.54%. Meanwhile, the average mean square error of the proposed method is 76.88, which is decreased by 82.46% when compared to the DPCM method. Ablation studies confirm the effectiveness of the proposed improvements. These findings highlight the efficacy of the proposed method in enhancing wellbore stability monitoring performance.

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Section: Introductionmentioning

confidence: 99%