On Acoustic Signal Compression for Ultrasonic Borehole Imaging

Abstract

This paper presents a novel approach for computationally efficient and robust compression for Ultrasonic Borehole Imaging. Although current methods achieve good compression versus accuracy tradeoffs, they inevitably employ iterative schemes, which for resource constrained downhole applications is computationally prohibitive. To alleviate this issue, we propose to model the waveforms as sum of exponentials (SOE) and use the matrix pencil (MP) algorithm for compression and recovery. This method is referred to as the SOE-MP method. We report that the SOE-MP method is able to compress the signal better than several existing methods in terms of accuracy, compression ratio, and speed. To achieve further gains in compression, we exploit the correlation across the waveforms and propose a novel method called angle-based adjacent basis grouping (ABBG). ABBG is an online method that exploits the correlation across successive acquisitions and avoids recomputing the MP solution for very similar waveforms. We report the tradeoffs among accuracy, compression, and running time for these methods on laboratory and field datasets, and show the nearly lossless imaging performance.