Adaptive Wavelet Transform for Borehole Image Compression
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Solution Overview
Problem
The limited bandwidth of the logging while drilling telemetry system constrains the transmission of subsurface data from downhole data acquisition equipment, leading to distorted reconstruction of borehole images due to high pass coefficient truncation during data compression.
Innovation Solution
The method involves using a Discrete Wavelet Transform to encode borehole image blocks, modifying wavelet transform functions to match formation features, and transmitting encoded bit streams that include feature attributes and wavelet transform coefficients to preserve image quality while minimizing data rate usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If data compression is applied to borehole image data, then bandwidth utilization is improved, but image reconstruction quality deteriorates due to high pass coefficient truncation
Solution Approach 1:
The patent modifies the wavelet transform parameters by adapting the decomposition level and selection of wavelet basis functions based on the specific characteristics of borehole images. This allows optimal balance between compression ratio and reconstruction quality by changing transform parameters to suit the geological features being captured
Solution Approach 2:
The patent applies different compression strategies to different regions of the borehole image based on local feature importance. Critical formation features are preserved with higher fidelity while less important regions undergo more aggressive compression, achieving local optimization of reconstruction quality
2Productivity
If high pass coefficients are truncated during compression, then data rate is reduced, but formation feature accuracy deteriorates
Solution Approach 1:
The patent applies partial action by selectively retaining only the most significant high pass coefficients that correspond to actual formation features, rather than truncating all high pass coefficients. This selective retention maintains formation feature accuracy while still achieving data rate reduction through compression of less critical components
Solution Approach 2:
The patent employs feedback mechanisms where the compression algorithm analyzes the reconstructed image quality and adjusts the threshold for coefficient retention. This iterative feedback process ensures that formation feature accuracy is maintained by dynamically adjusting which high pass coefficients are preserved based on their contribution to geological feature fidelity
Data Source
AI summary
Image block transmission includes reading an image block from a downhole sensor. Based on the image block, a set of formation features attributes for the image block are detected. The set of formation features attributes describe a structural property of a subsurface formation. Based on the set of formation feature attributes, a wavelet transform function is modified to obtain a modified wavelet transform function. The modified wavelet transform function is applied to the image block to obtain a set of wavelet transform coefficients for the image block. The image block transmission further includes generating an encoded bit stream comprising the set of formation features attributes and the set of wavelet transform coefficients for the image block, and transmitting the encoded bit stream.