توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱Screening of Iranian Carbonate Oil Reservoirs for CO2 Injection
نویسنده(ها): ، ، ،
اطلاعات انتشار: دوازدهمین کنگره ملی مهندسی شیمی ایران، سال
تعداد صفحات: ۱۰
Enhanced Oil Recovery (EOR) is referred to the methods for recovering more oil from depleted reservoirs. Increasing trend of oil price attracts more attention to EOR projects. In order to select the proper EOR method both technically and economically, it is of great importance to make a full field and pilot study. EOR screening criteria are useful tools to predict the results of an EOR project before any expensive pilot test or economic evaluations. In this study, the data pertaining 10 Iranian southwest reservoirs are gathered and compared to standard screening criteria. The results show that, among different EOR techniques, CO2 flooding is the best method. Besides the characteristics, data of all CO2 injection projects in the United States are compared with the Iranian oil reservoirs. which shows promising agreement. According to this study, considering the reservoir characteristics, excluding the economic restrictions, CO2 flooding is considered as the most efficient EOR method for the Iranian carbonate reservoirs under this study.<\div>

۲EOR screening using artificial intelligence Bayesian network
نویسنده(ها): ، ، ،
اطلاعات انتشار: چهاردهمین همایش بین المللی نفت، گاز و پتروشیمی، سال
تعداد صفحات: ۹
oil – production form enhanced oil recovery (EOR) projects continues supply an increasing in percentage of the world s oil. Therefore , the importance of choosing the best recovery method becomes increasingly important to petroleum engineers . In recent years computer technology has improved the application of screening criteria through the use of artificial intelligence techniques but the value of these programs depends on the accuracy of the input data used. bayesian network analysis is a powerful tool, which is already applied in some oil industry field. in this work we present screening criteria using bayesian network based on a combination of the reservoir and oil characteristics of successful projects plus generated data by taber table. we provide screening criteria for the six methods that are either the most important or still have some promise . the purpose is to develop software capable of combining the data extracted from different sources either experimental or modeling into a unified expert system in order to select the most proper technique for the situation. the efficiency is also checked with another set of data the accuracy of which in inside the acceptability margins.<\div>
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