DASPack: Controlled Data Compression for Distributed Acoustic Sensing [Dataset]

The study introduces DASPack, an open-source, high-performance compression tool specifically designed to address the growing storage challenges of Distributed Acoustic Sensing (DAS) data, which already reach hundreds of terabytes in large-scale deployments. Its objective is to provide both lossless and controlled lossy compression, allowing users to balance storage efficiency and signal fidelity, while remaining scalable and practical for real-world applications. DASPack combines wavelet transforms, linear predictive coding, and entropy coding to achieve up to 3× file size reduction in lossless mode and between 6× and 10× in lossy mode, depending on the acceptable level of signal degradation. The tool delivers high throughput, with single-thread speeds of 100–200 MB/s and up to 750 MB/s using eight threads, making it suitable for real-time deployment under high data rates. Its performance was validated on 15 datasets from diverse acquisition environments, demonstrating robustness, speed, and broad applicability. Overall, DASPack establishes a practical foundation for sustainable, long-term management of DAS data in large-scale monitoring networks