Borehole Image Compression for Low-Bandwidth LWD Telemetry
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Solution Overview
Problem
Existing LWD borehole image transmission technologies face challenges due to limited telemetry speed and bandwidth, leading to inefficient compression and transmission of images, particularly in deeper wells, where the mud pulse signal is weak, and existing JPEG-style compression algorithms are not adaptable to varying data quality requirements or drilling conditions.
Innovation Solution
A Fourier-transform-based lossy compression method is employed, using a data compressor with components like a frequency domain coefficients generator, prioritizer, and encoder to compress 16-bin waveforms into 26 bits, allowing flexible update rates and eliminating bandwidth overhead for error correction, enabling efficient transmission of low-azimuth-resolution images using mud-pulse telemetry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If JPEG-style 2D compression is used for borehole image transmission, then image data can be compressed, but the compression efficiency is low and bandwidth is wasted due to fixed block transmission requirements
Solution Approach 1:
The patent segments the borehole image data into individual scan lines (1D data sequences) rather than processing 2D image blocks. Each scan line is compressed independently using 1D DCT, allowing flexible transmission of any number of scan lines without requiring fixed block structures. This eliminates the bandwidth waste from hand-shaking signals and gaps between compression blocks while maintaining compression efficiency.
2Loss of information
If existing JPEG compression algorithm is used, then image compression is achieved, but the information rate is low due to overhead for hand-shaking and error correction
Solution Approach 1:
The patent extracts and eliminates the hand-shaking overhead inherent in traditional JPEG compression. By using 1D DCT on individual scan lines and transmitting variable-length compressed data without requiring block-synchronized hand-shaking protocols, the system removes approximately 7 out of 18 DPOINTs (39% reduction) that were previously wasted on overhead, thereby increasing the information rate from 61% to significantly higher values.
3Adaptability or versatility
If multi-mode image compression is used, then compression flexibility is improved, but downhole tool computation resource consumption increases tremendously
Solution Approach 1:
The patent applies 1D DCT compression to individual scan lines (local data units) rather than requiring complex multi-mode processing of entire image blocks. This localized approach maintains compression flexibility by allowing selective transmission of scan lines based on bandwidth availability while significantly reducing computation resource requirements in the downhole environment, as 1D DCT is computationally simpler than 2D DCT with multiple modes.
4Stability of the object's composition
If fixed block transmission is used, then data transmission is structured, but gaps appear between compression blocks when transmission cannot catch up with image acquisition speed
Solution Approach 1:
The patent implements dynamic transmission by compressing and transmitting individual scan lines independently rather than requiring fixed block structures. The system can transmit any number of scan lines based on real-time bandwidth availability and drilling conditions, eliminating gaps between compression blocks. This dynamic approach maintains transmission structure through sequential scan line delivery while adapting flexibly to varying acquisition speeds and bandwidth conditions.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enhances image quality and usability by optimizing compression for available bandwidth and drilling conditions, improving the efficiency of borehole image transmission and reducing gaps between compression blocks, while maintaining image integrity even in low-bandwidth scenarios.
Implementation Method 1
A Fourier-transform-based lossy compression method is employed, using a data compressor with components like a frequency domain coefficients generator, prioritizer, and encoder to compress 16-bin waveforms into 26 bits
Data Source
AI summary
Data transmission from a bottom hole assembly (BHA) includes obtaining a scan from multiple scans forming a downhole data log of a borehole within a subterranean formation. The scan includes a sequence of data items from a sensor in the BHA located in the borehole. Each data item corresponds to an azimuth angle of the sensor. Further, compressed scan data is generated from the sequence of data items on a per-scan basis, and transmitted, using a pre-determined borehole telemetry, to a surface unit.