دورية أكاديمية

Using data analytics to quantify the impact of production test uncertainty on oil flow rate forecast

التفاصيل البيبلوغرافية
العنوان: Using data analytics to quantify the impact of production test uncertainty on oil flow rate forecast
المؤلفون: Monteiro Danielle D., Duque Maria Machado, Chaves Gabriela S., Ferreira Filho Virgílio M., Baioco Juliana S.
المصدر: Oil & Gas Science and Technology, Vol 75, p 7 (2020)
بيانات النشر: EDP Sciences, 2020.
سنة النشر: 2020
المجموعة: LCC:Chemical technology
مصطلحات موضوعية: Chemical technology, TP1-1185, Energy industries. Energy policy. Fuel trade, HD9502-9502.5
الوصف: In general, flow measurement systems in production units only report the daily total production rates. As there is no precise control of individual production of each well, the current well flow rates and their parameters are determined when production tests are conducted. Because production tests are performed periodically (e.g., once a month), information about the wells is limited and operational decisions are made using data that are not updated. Meanwhile, well properties and parameters from the production test are typically used in multiphase flow models to forecast the expected production. However, this is done deterministically without considering the different sources of uncertainties in the production tests. This study aims to introduce uncertainties in oil flow rate forecast. To do this, it is necessary to identify and quantify uncertainties from the data obtained in the production tests, consider them in production modeling, and propagate them by using multiphase flow simulation. This study comprises two main areas: data analytics and multiphase flow simulation. In data analytics, an algorithm is developed using R to analyze and treat the data from production tests. The most significant stochastic variables are identified and data deviation is adjusted to probability distributions with their respective parameters. Random values of the selected variables are then generated using Monte Carlo and Latin Hypercube Sampling (LHS) methods. In multiphase flow simulation, these possible values are used as input. By nodal analysis, the simulator output is a set of oil flow rate values, with their interval of occurrence probabilities. The methodology is applied, using a representative Brazilian offshore field as a case study. The results show the significance of the inclusion of uncertainties to achieve greater accuracy in the multiphase flow analysis of oil production.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
French
تدمد: 1294-4475
1953-8189
Relation: https://ogst.ifpenergiesnouvelles.fr/articles/ogst/full_html/2020/01/ogst190262/ogst190262.html; https://doaj.org/toc/1294-4475; https://doaj.org/toc/1953-8189
DOI: 10.2516/ogst/2019065
URL الوصول: https://doaj.org/article/8e875d890699445c982427c261fc881a
رقم الأكسشن: edsdoj.8e875d890699445c982427c261fc881a
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:12944475
19538189
DOI:10.2516/ogst/2019065