Combining DAS and DTS Measurements for Oil-Water Two-Phase Flow Profiling in Sucker Rod Pump Wells

Abstract Distributed temperature and acoustic sensing techniques (DTS and DAS) have been widely used in oil and gas wells of higher rates for flow profiling. However, current interpretation models usually cannot be directly applied to sucker rod pump (SRP) wells. Due to the existence of the sucker rod, the contact mode between the optical fiber and wellbore fluids is different from the pumpless wells. Furthermore, high water cut and pump noises also greatly increase the difficulty of DAS data analysis. This paper presented an improved theoretical model and interpretation method for oil-water two-phase profiling in SRP wells and a field case was used for illustration. The DTS data analysis was mainly based on a well-established numerical wellbore-reservoir coupled flow/thermal model that considers transient temperature behavior during production tests. Considering the different contact modes between optical fiber and wellbore fluids in SRP wells, a segmented function was adopted to describe the variation of heat transfer flux in different well sections. The DAS data were prefiltered to eliminate the pump noises based on the on-site test results. The possibility of determining the volume proportions of the oil and water phase in the mixed fluid through the utilization of the f-k plot was explored. The strength and energy of DAS data were used for preliminary flow profiling. The DAS flow profiles were used as the initial guess and the final interpretation results were inversed by combining DTS and DAS data. Levenberg-Marquardt algorithm was applied for the inverse procedure. Compared with pumpless wells, the wellbore temperature in the upper section of SRP wells was closer to the formation temperature, which was successfully characterized by this improved thermal model. The water-cut variation has a limited impact on temperature and it might be further obscured by the oscillation of temperature data to some extent. The flow profile calculated from DAS data served as the initial guesses in the DTS inverse modeling part, which greatly reduced the uncertainty of DTS data analysis and computation cost. The presented model and interpretation method have been applied to an SRP well in Liaohe oil field, China. The interpreted flow profiling by combining DTS and DAS data showed consistent results with that measured by production logging tools. Furthermore, the major oil-production zones were identified, and they are interestingly not the major liquid-production zones. An improved model and interpretation method to interpret the oil and water allocation in SRP wells was presented. The combining DAS and DTS measurements resulted in more accurate interpretation of oil and water allocation than using the DAS alone. In addition, this method may provide guidance for water plugging treatment in commingled wells.