This thesis is a contribution to the development of flow sensors in oil and gas industry. The main objective of this work is presenting a methodology to measure the flow rates into multiple-zone water-injection wells from fluid temperature profiles and estimate the measurement uncertainty. First, the classical Ramey equation describing the fluid temperature as a function of flow was presented. Then, three methods to calculate the flow rates from temperature profile were described and the flow sensor was computationally modeled. Next, the flow rates into four injection-wells, located in Rio Grande do Norte, were calculated from temperature profiles experimentally measured. The Ramey equation was expanded in Taylor Series and linearized to obtain an explicit, linear, function between the flow rates and the fluid temperature. Then, a quantitative uncertainty analysis was performed. The flow rates calculated were compared to the flow rates measured in field and the preliminary results, obtained from Wells 1 and 2, were satisfactory. However, due temperature sensor resolution, significant deviations between the calculated and measured flow rates were found at Wells 3 and 4.  In these cases, the injected flow rates were stochastically recalculated from the probability distributions of the measured temperatures, through a Monte Carlo simulation. The recalculated flow rates were very close to the measured values and, therefore, the proposed methodology was successfully validated.