DTS data process method for horizontal well profile monitoring

Distributed temperature sensing (DTS) has been widely used for monitoring the downhole conditions in horizontal wells, enabling the determination of water inflow positions, identification of fluid types, and quantitative interpretation of reservoir production profiles. In unconventional horizontal wells, the accuracy of temperature measurements is highly sensitive and crucial for the precision of production logging inversion results based on temperature. Temperature measurement errors cannot be eliminated through simple averaging. In this study, we investigate a processing technique for distributed temperature sensing that enhances the signal-to-noise ratio of the temperature field and enables the recovery of the true temperature distribution in horizontal wells.