An Experimental Investigation of WAG Injection in a Carbonate Reservoir and Prediction of the Recovery Factor Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{wojnicki:2022:Energies,

• author = "Miroslaw Wojnicki and Jan Lubas and Mateusz Gawronski and Slawomir Szuflita and Jerzy Kusnierczyk and Marcin Warnecki",
• title = "An Experimental Investigation of {WAG} Injection in a Carbonate Reservoir and Prediction of the Recovery Factor Using Genetic Programming",
• journal = "Energies",
• year = "2022",
• volume = "15",
• number = "6",
• pages = "Article No. 2127",
• keywords = "genetic algorithms, genetic programming",
• ISSN = "1996-1073",
• URL = "https://www.mdpi.com/1996-1073/15/6/2127",
• DOI = "doi:10.3390/en15062127",
• abstract = "Production from mature oil fields is gradually declining, and new discoveries are not sufficient to meet the growing demand for oil products. Hence, enhanced oil recovery is emerging as an essential link in the global oil industry. This paper aims to recognise the possibility of increasing oil recovery from Polish carbonate reservoirs by the water alternating gas injection process (WAG) using various types of gases, including CO2, acid gas (a mixture of CO2 and H2S of 70/30percent vol/vol) and high-nitrogen natural gases occurring in the Polish Lowlands. A series of 17 core flooding experiments were performed under the temperature of 126 °C, and at pressures of 270 and 170 bar on composite carbonate cores consisting of four dolomite core plugs. Original reservoir rock and fluids were used. A set of slim tube tests was conducted to determine the miscibility conditions of the injected fluids with reservoir oil. The WAG process was compared to continuous gas injection (CGI) and continuous water injection (CWI) and was proven to be more effective. CO2 WAG injection resulted in a recovery factor (RF) of up to 82percent, where the high nitrogen natural gas WAG injection was less effective with the highest recovery of 70percent. Based on the core flooding results and through implementing a genetic programming algorithm, a mathematical model was developed to estimate recovery factors using variables specific to a given WAG scheme.",
• notes = "also known as \cite{en15062127}",

}

Genetic Programming entries for Miroslaw Wojnicki Jan Lubas Mateusz Gawronski Slawomir Szuflita Jerzy Kusnierczyk Marcin Warnecki

Citations