| Summary: | A method for interpreting the water injection profile based on Distributed Temperature Sensing (DTS) is proposed to address the technical challenges of diagnosing the water injection volume of each injection layer of water injection wells. Firstly, a temperature profile prediction model for water injection wells is established with considering the micro thermal effects. The influence of seven factors including water injection rate, water injection time, formation thermal conductivity etc. on the temperature profile is simulated and analyzed. Through orthogonal experiment analysis, it demonstrates that the sensitivity of temperature profile on different factors from strong to weak is water injection temperature, water injection time, water injection rate, wellbore radius, formation thermal conductivity, wellbore trajectory, formation permeability. Water injection temperature, water injection time, and water injection rate are the dominant parameters impacting the temperature profile of water injection wells. A simulated annealing (SA) algorithm is used to establish a DTS data inversion model for water injection wells. Using the inversion model, the DTS data of a field water injection well has been inverted and accurate water injection profile is obtained. The maximum inversion error of water absorption percentage of each layer is 14.25% and the average inversion error of water absorption percentage for all layers is 11.09% that validates the reliability of the inversion method in this paper. It can be seen that quantitative interpretation of water injection profiles can be achieved through DTS data inversion. It provides a direct basis for evaluating water injection effectiveness.
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