This paper presents a new approach to borehole resistivity and acoustic imaging data compression. The method is based on the discrete wavelet transform (DWT) combined with the set partitioning in the hierarchical trees (SPIHT) coding method. The primary advantages of the DWT + SPIHT method are its superior compression performance, simple implementation, and constant compression and transmission rate control. This new approach generally performs better than the traditional discrete cosine transform (DCT) followed by Huffman coding methods such as JPEG, particularly for target compression ratios greater than 50:1. Image block size plays a key role in using this method. To achieve the best compression performance, the image block size needs to be selected appropriately. In general, large image block sizes and more DWT decomposition levels result in higher compression ratios and/or fewer reconstruction errors. Whenever possible, image block sizes that allow the maximum levels of dyadic DWT decomposition should be used. When insufficient data samples are available in either depth or azimuthal direction, a small number of extra data samples can be added without sacrificing the overall compression performance. The DWT + SPIHT method also shows good fidelity in representing major features in borehole images such as fractures and sinusoids.

You do not currently have access to this article.