Analysis of carbon dioxide reservoir performance and optimization strategies: a case study of a carbon dioxide plant

被引:0
|
作者
Emmanuel Monge [1 ]
Baraka Kichonge [2 ]
机构
[1] University of Dar Es Salaam (UDSM),College of Engineering and Technology (CoET)
[2] School of Materials Energy Water and Environmental Sciences (MEWES),Mechanical Engineering Department
[3] The Nelson Mandela African Institution of Science and Technology (NM-AIST),undefined
[4] Arusha Technical College,undefined
关键词
Carbon dioxide reservoir; Reservoir performance prediction; Resource recovery; Production optimization; Decline curve analysis;
D O I
10.1186/s40807-025-00146-2
中图分类号
学科分类号
摘要
This study aimed at developing an empirical model for estimating and analyzing CO2 reservoir performance. This was achieved by using decline curve analysis (DCA) to determine an accurate empirical decline model for reservoir performance prediction and optimal producing, i.e., time at which the plant recovery build-up (RBU) efficiency has declined to an approximate value of 44.5%. MATLAB R2013b was used for calculating raw gas density whereas Ms Excel 2007 was used in plotting and performing all calculations. Through an examination of real production data, a harmonic decline model with an Arps’ decline constant (d) of 1.0 and a nominal decline rate of approximately 0.035572337/year was identified as the most suitable for characterizing reservoir performance. The study identifies the year 2048 as an optimal opportunity for implementing production optimization strategies to maximize returns while ensuring efficient resource recovery. Acknowledging the limitations of DCA, the study recommends exploring alternative forecasting models such as type curve analysis (TCA), material balance equation (MBE), and well simulation techniques to mitigate uncertainties in reservoir performance prediction. In addition, the study proposes a 5-year model verification and improvement program to refine reservoir descriptions and enhance data acquisition practices, aiming to optimize production efficiency and minimize uncertainties in CO2 reservoir operations.
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