Estudo da água produzida em diferentes zonas de produção de petróleo, utilizando a hidroquímica e a análise estatística de parâmetros químicos
Over exploitation of oil deposits on land onshore or offshore, there is simultaneous generation of waste water, known as produced water, which represents the largest waste stream in the production of crude oil. The relationship between the chemical composition of oil and water production and the con...
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| Định dạng: | Dissertação |
| Ngôn ngữ: | por |
| Được phát hành: |
Universidade Federal do Rio Grande do Norte
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| Những chủ đề: | |
| Truy cập trực tuyến: | https://repositorio.ufrn.br/jspui/handle/123456789/17620 |
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| Tóm tắt: | Over exploitation of oil deposits on land onshore or offshore, there is simultaneous generation of waste water, known as produced water, which represents the largest waste stream in the production of crude oil. The relationship between the chemical composition of oil and water production and the conditions in which this process occurs or is favored are still poorly studied. The area chosen for the study has an important oil reserve and an important aquifer saturated with freshwater meteoric. The aim of this work is to study some chemical parameters in water produced for each reservoir zone of production in mature oil fields of Açu Formation, using the
hydrochemical and statistical analysis to serve as a reference and be used as tools against the indicator ranges water producers in oil producing wells. Samples were collected from different wells in 6 different areas of production and were measured 50 parameters, which can be classified into three groups: anions, cations and physicochemical properties (considering only the parameters that generated values
above detection limits in all samples). Through the characterization hydrochemistry observed an area of water and chlorinated sodium, chlorinated calcium or magnesium (mixed) in well water in different areas of Açu, by applying a statistical treatment, we obtained a discriminant function that distinguishes chemically production areas. Thus, it was possible to calculate the rate of correct classification of the function was 76.3%. To validate this model the accuracy rate was 86% |
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