Optimization of Mud Injection Pressure in Oil Drilling Using Duelist Algorithm

Biyanto, Totok R.; Gharyta, Kukuh; Dienanta, Gabriella P.; Tama, Nanda E.; Abdillah, Arfiq I.; Matradji,; Cordova, Hendra; Anggrea, Tita Oxa; Irawan, Sonny

doi:10.1007/978-981-10-8450-8_8

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“…The operating condition variables are pressure, mass flow rate and temperature of CO 2 injection. The recent stochastic algorithms have been utilized, i.e., Killer Whale Algorithm (KWA) (Biyanto et al 2017a(Biyanto et al , b, 2018a, duelist algorithm (DA) (Biyanto et al 2016a(Biyanto et al , 2017c(Biyanto et al , 2018b, particle swarm optimization (PSO) (Biyanto and Dina 2016),…”

Section: Optimization Techniquesmentioning

confidence: 99%

Optimization of operating conditions of CO2-enhanced gas recovery and carbon sequestration

Biyanto

Febriansyah

Abdillah

et al. 2019

J Petrol Explor Prod Technol

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Currently, the climate changes are the big issue due to increasing in amount of CO 2 foot print over the time. One of the most effective solutions to reduce CO 2 emissions is to inject CO 2 into the earth as known as carbon sequestration. CO 2 injection has two advantages for CO 2 gas storage and increases gas production in depleted reservoir or known as enhanced gas recovery (EGR). Although many studies of EGR model and characterization have been done and the results show that the application of EGR has potentially increased gas production and CO 2 storage; however, EGR has not been applied in the field. The obstacle remaining in application of EGR is the significant cost related to EGR technology starting from CO 2 procurement cost, transportation and operational cost. The operational costs of CO 2 injection depend on the operating conditions of CO 2 injection which is mass flow rate, pressure and temperature of CO 2 injection. In this research, CO 2 EGR and carbon sequestration processes were modeled by dividing into three parts, i.e., injection well, reservoir and production well. Pressure gradient in injection and production well was modeled using Beggs-Brill, while in reservoir by using Darcy equation. Temperature gradient for each part was modeled using mass and energy balances equations. The fluid properties were predicted using Peng-Robinson vapor-liquid equilibrium under commercial software HYSYS. Validation of injection and production well models was compared with PIPESIM, and the average mean deviations are 1.919% and 1.578%, respectively. Meanwhile, the validation of pressure and temperature gradient model compared to COMSOL Multiphysics software simulation in reservoir shows the average mean deviation of 0.2003% and 0.0002%, respectively. Based on the sensitivity analysis of the model, the profit will increase proportionally if mass flow rate and temperature increase; otherwise, it will decrease if CO 2 injection pressure increases. Before optimization, the presence of CO 2 injection in depleted gas reservoir with normal operating conditions can produce gas recovery of about 90.09% in which the profit generated is 6175.6 USD/ day. EGR optimization has been performed using several recent stochastic algorithms, and the best optimization result was obtained by using Killer Whale Algorithm, duelist algorithm and Rain Water Algorithm. The optimization results show an increase in profit from 4453.8 USD/day to 12,331.9 USD/day or about 276.9% higher than the initial condition of the injection or without optimization. By using injection parameters that have been optimized, the CO 2 that can be stored is 1486.01 tons.

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