Enhanced Temperature Measurement Performance: Fusing DTS and DAS Results

Abstract

This paper presents the fusion of temperature measurements from different fiber sensing technologies. The method benefits from the absolute temperature accuracy of Raman-Distributed Temperature Sensing (DTS), but also the low noise properties, fast response, and high sensitivity to temperature gradients of coherent Rayleigh backscatter based Distributed Acoustic Sensing (DAS), which is processed to Distributed Temperature Gradient Sensing (DTGS) signals. The specific properties of the technologies allow two fundamental concepts, which are outlined in this paper. The concept having a DTS-like behavior, called enhanced-DTS (eDTS), is implemented using Kalman filters, where the fused temperature result yields an improvement of more than factor 3 in temperature resolution compared to DTS only. This allows more accurate absolute temperature results and faster response to temperature events especially at long distances.