Fiber Optic Strain and Temperature Sensing for Gas-Liquid Production Profiling

Abstract The analysis of gas-liquid ratio is critical for interpreting production profiles in tight gas reservoirs. This study investigates the sensitivity of different fiber optic sensors, including the outside casing cemented distributed strain sensor (DSS) and distributed temperature sensor (DTS), to the gas-liquid ratio during horizontal fractured gas well production tests. Through the integration of DSS and DTS data and by developing fluid-solid and thermal-fluid mathematical models, this study demonstrates a method to significantly reduce uncertainty in gas-liquid ratio analysis during shut-in and open-up well tests. The DSS strain model can be used for capturing the expansion or compression of fractures due to transient fluid refilling or releasing. The DTS temperature model accounts for the Joule-Thomson effect which is critical to distinguish gas and liquid. For the cases of single-phase fluid flow, results showed that DTS data was more sensitive to gas production due to the larger Joule-Thomson coefficient which leads to a more visible temperature drop in the near wellbore region, while DSS data had a better sensitivity to liquid production since the smaller compressibility and higher viscosity of liquid causes more significant strain changes. Further simulations were conducted to investigate gas-liquid two-phase flow into the wellbore through multiple fractures with varied fracture conductivities and stimulated reservoir volume (SRV). The DTS temperature signals and DSS strain signals showed good sensitivity to the gas-liquid ratio, fracture location, fracture conductivity and SRV. The amplitude and broad extent of the fiber optic data local variation were used to analysis the correlations for above mentioned factors. Finally, the Monte-Carlo Markov Chain inverse algorithm was applied to obtain the gas and liquid production profile in the monitored well. This study investigates the integration of DSS and DTS for gas-liquid ratio analysis in tight gas reservoirs. This method significantly enhances the precision of production profiling, addressing challenges such as premature water breakthrough and rapid production decline in unconventional reservoirs.