Reconstructing Sparse Images of Drill Cuttings using a Convergent POCS Method on a Raspberry Pi
Yimin Sun, M. Al Ibrahim · 2024
Summary Real-time data analysis on drill cuttings images can greatly improve the efficiency of drilling operations. A low-power computation platform is preferred for this task because it is a challenge to provide reliable and stable power supplies directly in the field. Raspberry Pi is a popular edge-computing platform. Due to its low-power consumption and versatile computation capabilities, it has powered plenty of realistic real-time edge-computing applications. However, its low I/O throughput is a grand challenge for acquiring high-resolution drill cuttings images efficiently. One solution to effectively increase its I/O throughput is to only acquire a sparse portion of the original drill cuttings image and reconstruct it at a later stage when it is no longer time sensitive. We demonstrate the feasibility of using a Convergent POCS (CP) method running on a Raspberry Pi 4B device for reconstructing sparse images of drill cuttings. Our work paves the way to further exploit high-performance edge-computing solutions for automatically analyzing drill cuttings in real time.