Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-03-17T19:32:33Z No. of bitstreams: 1 JoseEdenilsonOliveiraReges_TESE.pdf: 5841325 bytes, checksum: 2ead9ffcd013a5ed21850074ab97c30f (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-03-18T00:04:04Z (GMT) No. of bitstreams: 1 JoseEdenilsonOliveiraReges_TESE.pdf: 5841325 bytes, checksum: 2ead9ffcd013a5ed21850074ab97c30f (MD5) / Made available in DSpace on 2017-03-18T00:04:04Z (GMT). No. of bitstreams: 1 JoseEdenilsonOliveiraReges_TESE.pdf: 5841325 bytes, checksum: 2ead9ffcd013a5ed21850074ab97c30f (MD5) Previous issue date: 2016-11-18 / Esta Tese ? uma contribui??o ao desenvolvimento de sensores de vaz?o na ind?stria de petr?leo e g?s. O objetivo geral do trabalho ? apresentar uma metodologia para medir as vaz?es em po?os injetores de ?gua multizonas a partir de perfis de temperatura do fluido e estimar a incerteza da medi??o. Inicialmente, foi apresentada a equa??o cl?ssica de Ramey descrevendo a temperatura do fluido como uma fun??o da vaz?o ao longo do po?o. Ent?o, foram descritos tr?s m?todos de c?lculo das vaz?es a partir do perfil de temperatura e o sensor de vaz?o foi modelado computacionalmente. Em seguida, foram calculadas as vaz?es em quatro po?os injetores multizonas, localizados no Rio Grande do Norte, a partir de perfis de temperatura medidos experimentalmente. As vaz?es calculadas foram comparadas ?s vaz?es medidas no campo. Os resultados preliminares obtidos nos Po?os 1 e 2 foram satisfat?rios. Nestes po?os, os erros m?ximos observados foram de 28,55% (Po?o 1) e 15,72% (Po?o 2). Entretanto, desvios significativos entre as vaz?es calculadas e medidas foram encontrados nos Po?os 3 e 4. Nestes po?os, os erros m?ximos observados foram de 536,84% (Po?o 3) e 335,54% (Po?o 4). Utilizando a expans?o em S?rie de Taylor da equa??o exponencial de Ramey, foi obtida uma fun??o expl?cita, linear, entre a vaz?o ao longo do po?o e a temperatura do fluido, sendo realizada uma an?lise quantitativa da incerteza de medi??o. A partir desta an?lise, foi observado que, devido ? baixa resolu??o nas medi??es de temperatura, a incerteza de medi??o expandida pode atingir cerca de 155,04% da vaz?o calculada. Foi ent?o apresentado um m?todo de c?lculo estoc?stico das vaz?es a partir das distribui??es de probabilidade das temperaturas medidas, atrav?s da Simula??o de Monte Carlo. As novas vaz?es calculadas apresentaram erros m?ximos de 3,67% (Po?o 1), 14,45% (Po?o 2), 14,62% (Po?o 3) e 22,29% (Po?o 4). Logo, a abordagem probabil?stica permitiu que as vaz?es injetadas fossem satisfatoriamente estimadas mesmo nos casos em que a resolu??o do sensor de temperatura era inadequada ? detec??o de pequenas varia??es na temperatura do fluido. Portanto, a metodologia de c?lculo das vaz?es injetadas a partir do perfil de temperatura do fluido foi validada com sucesso. / 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 multiple-zone injection-wells, located in Rio Grande do Norte, were calculated from temperature profiles experimentally measured. The calculated flow rates were compared to the measured flow rates. The preliminary results, obtained from Wells 1 and 2, were satisfactory. In these wells, the maximum errors were equals to 28,55% (Well 1) and 15,72% (Well 2). However, significant deviations between the calculated and the measured flow rates were found at Wells 3 and 4. In these wells, the maximum errors were equals to 536,84% (Well 3) and 335,54% (Well 4). The Ramey equation was expanded in Taylor Series and linearized to obtain an explicit, linear, function between the flow and the fluid temperature. Then, a quantitative uncertainty analysis was performed. From this analysis, it was observed, due the temperature sensor resolution, the expanded measurement uncertainty may achieve about 155,04% of the calculated flow rate. Then, the injected flow rates were stochastically recalculated from the probability distributions of the measured temperatures, through a Monte Carlo simulation. The new calculated flow rates presented maximum errors of 3,67% (Well 1), 14,45% (Well 2), 14,62% (Well 3) and 22,29% (Well 4). This probabilistic approach allowed injected flow rates to be estimated even in the cases where the temperature sensor resolution was inadequate to detection of small variations into the fluid temperature. Therefore, the methodology to calculate the injected flow rates from the fluid temperature profile was successfully validated.