Prasojo, Eka Wahyu (2019) Optimisasi Kondisi Operasi Biopolimer Microbial Enhanced Oil Recovery. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Salah satu cara dalam mengeksplorasi minyak menggunakan EOR yang saat ini dikembangkan yaitu menggunakan biothecnological yang biasa dikenal dengan Microbial Enhanced Oil Recovery (MEOR). Pada MEOR bakteri mengalami beberapa tahap siklus hidup dan fase eksponensial merupakan fase terpenting dalam memproduksi biopolimer sehingga dibutuhkan model kondisi operasi terbaik pada variabel desain yaitu laju aliran massa, tekanan, temperatur, konsentrasi bakteri dan konsentrasi nutrisi injeksi yang mampu memberikan hasil terbaik dalam memproduksi minyak. Begg’s-Brill digunakan untuk memodelkan pressure drop pada injection well dan production well yang menunjukkan rata-rata error 0.383% dan rata-rata error 2.437% untuk temperatur jika dibandingkan dengan software PIPESIM. Pada reservoir dengan menggunakan persamaan darcy didapatkan rata-rata error 0.782% untuk tekanan dan rata-rata error 0.115% untuk temperatur jika dibandingkan dengan software COMSOL Multiphysics. Berdasarkan hasil optimisasi menggunakan Stochastic Algorithms yang terdiri dari 2 jenis teknik optimisasi yaitu Duelist Algorithm (DA) dan Genetic Algorithm (GA) diperoleh hasil terbaik dari Genetic Algorithm dengan mengoptimalkan kondisi operasi hingga 88.6% dimana profit dapat dioptimisasi dari 23330.467 USD/hari menjadi 43998.396 USD/hari.
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One way to explore oil using EOR is currently being developed, namely using biotechnological, commonly known as Microbial Enhanced Oil Recovery (MEOR). in MEOR the bacteria undergo several life cycle stages and the exponential phase is the most important in producing biopolymer so that the best operating conditions model is needed on design variables, namely mass flow rate, pressure, temperature, bacterial concentration and concentration of injection nutrients that can provide the best results in producing oil. Begg’s-Brill is used to model pressure drop on injection well and production well which shows an average error of 0.383% and an average error of 2.437% for temperature when compared with PIPESIM software. In the reservoir using the Darcy equation, an average error of 0.115% was obtained for pressure and an average error of 0.782% for temperature when compared with COMSOL Multiphysics software. Based on the results of the optimization using Stochastic Algorithms which consists of two types of optimization techniques, namely Duelist Algorithm (DA) and Genetic Algorithm (GA), the best results from Genetic Algorithm are optimized by 88.6% where the profit can be optimized from 23330.467 USD to 43998.396 USD /day.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Biopolimer, Begg’s-Brill, Darcy, Stochastic Algorithms |
| Subjects: | T Technology > TN Mining engineering. Metallurgy T Technology > TN Mining engineering. Metallurgy > TN871.3 Offshore well drilling T Technology > TN Mining engineering. Metallurgy > TN879.5 Petroleum pipelines |
| Divisions: | Faculty of Industrial Technology > Physics Engineering > 30201-(S1) Undergraduate Thesis |
| Depositing User: | Eka Wahyu Prasojo |
| Date Deposited: | 13 Nov 2024 05:41 |
| Last Modified: | 13 Nov 2024 05:41 |
| URI: | http://repository.its.ac.id/id/eprint/68894 |
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