Aziz, Sarah Alya (2021) Optimisasi Operasi CO2 Enhanced Gas Recovery Pada Batuan Karbonat Depleted Gas Reservoir Menggunakan Algoritma Genetika. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Peningkatan emisi CO2 adalah ancaman terpenting bagi perubahan lingkungan yang merupakan kecemasan berkelanjutan yang paling penting untuk berbagai negara. Berbagai negara kini telah berkomitmen untuk mengurangi dampak emisi CO2 yang timbul. Salah satunya adalah dengan menerapkan kebijakan yang relevan, termasuk rencana aksi pengurangan emisi Gas Rumah Kaca (GRK) seperti penelitian dalam teknologi Carbon Capture dan Sequestration sebagai salah satu cara signifikan untuk mengurangi laju peningkatan konsentrasi CO2 pada atmosfer. Salah satunya pemanfaatannya adalah untuk produksi gas dengan Enhanced Gas Recovery (EGR). Pada penelitian ini, CO2 EGR dan Carbon Sequestration dimodelkan pada injection well, reservoir, dan production well.Penurunan tekanan pada injection well dan production well dimodelkan dengan persamaan Beggs-Brill, sedangkan pada reservoir menggunakan persamaan Darcy. Gradien temperatur untuk setiap bagian dimodelkan dengan persamaan heat transfer. Pemodelan kemudian divalidasi dengan software PIPESIM dan COMSOL. Pada pemodelan tekanan dan temperatur di injection well, dihasilkan deviasi rata-rata masing-masing sebesar 0,55% dan 0,82%, sedangkan di production well masing-masing sebesar 1,1% dan 0,93%. Sedangkan validasi pemodelan tekanan dan temperatur pada reservoir dihasilkan deviasi rata-rata masing-masing sebesar 0,75% dan 0,05%. Validasi menunjukkan bahwa hasil pemodelan sudah mendekati data riil. Adanya deviasi antara kedua hasil pemodelan disebabkan oleh adanya perbedaan kapasitas pencacahan pada software dengan perhitungan manual. Selain itu, pada COMSOL dan PIPESIM digunakan mode aliran distributed sedangkan pada perhitungan manual menggunakan jenis aliran laminar. Setelah dilakukan optimisasi menggunakan Algoritma Genetika (GA), dihasilkan nilai-nilai variabel optimal untuk kondisi operasi CO2 EGR yaitu pada tekanan injeksi 1071 psia, temperatur injeksi 40°C, dan laju aliran massa injeksi 0,6261 kg/s. Kondisi operasi tersebut berhasil meningkatkan laju produksi natural gas dan gas kondensat sehingga meningkatkan profit ketika gas tersebut dijual. Volume natural gas dan gas kondensat yang dapat diproduksi dalam satu hari tanpa adanya optimisasi adalah masing-masing sebesar 0,92 MMBtu/hari dan 71,26 bbl/hari. Setelah dilakukan optimisasi, volume natural gas dan gas kondensat yang dapat diproduksi dalam satu hari menjadi 2,49 MMBtu/hari dan 192,19 bbl/hari. Maka dari itu, terjadi peningkatan profit yang semula 3099,667 USD/hari menjadi 9588,88 USD/hari, atau dalam kata lain berhasil meningkatkan profit harian CO2 EGR sebesar 209,35%. Sedangkan jumlah CO2 storage yang semulanya 20,11 ton/hari menjadi 41,388 ton/hari, atau meningkat sebanyak 105,84% dibandingkan dengan sebelum dilakukan optimisasi.
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The increasing CO2 emissions are the most important threat to environmental change for most countries. Various countries are now committed to reducing the impact of the CO2 emission, and one of them is to implement relevant policies, including action plans to reduce Greenhouse Gas (GHG) emissions such as research in Carbon Capture and Sequestration technology as one significant way to reduce the rate of increased CO2 concentrations in the atmosphere. One of its utilization is for gas production with Enhanced Gas Recovery (EGR). In this study, CO2 EGR and Carbon Sequestration were modeled in 3 parts, namely injection well, reservoir, and production well. Pressure drop in the injection well and production well is modeled with the Beggs-Brill equation while in the reservoir using the Darcy equation. The temperature gradient for each section is modeled with a heat transfer equation. The model is then validated using PIPESIM and COMSOL as the software. The model of pressure and temperature in the injection well resulted in deviation by 0,55% and 0.82%, while in production well respectively by 1.1% and 0.93%. While validation of pressure drop and temperature gradient model in the reservoir resulted deviation of 0.75% and 0.05% respectively. It can be concluded that the model result is very close to the real data. The deviation between the two modeling results is due to differences in enumeration capacity in software with manual calculations. In addition, distributed flow mode is used in the simulation while in manual calculations laminar flow type is applied. After being optimized using Genetic Algorithm (GA), the optimal variable values for EGR CO2 operating conditions are at injection pressure 1071 psia, injection temperature 40°C, and injection mass flow rate 0.6261 kg/s. The operating conditions succeeded in increasing the rate of natural gas and condensate gas production, thus increasing profit of the gas sales. The volume of natural gas and condensate gas that can be produced in one day without optimization is 0.92 MMBtu/day and 71.26 bbl/day, respectively. After being optimized, the volume of natural gas and condensate gas that can be produced in one day becomes 2.49 MMBtu/day and 192.19 bbl/day. An increase in profit occurred from originally 3099,667 USD/day to 9588.88 USD/day, or in other words, this process managed to increase CO2 EGR's daily profit by 209.35%. The amount of CO2 that can be stored was initially 20,1 ton/day. After being optimized the CO2 Storage increases to 41,388 tons/day or increased by 105.84% compared to before the optimization was done.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Carbon Sequestration, Enhanced Gas Recovery, Genetic Algorithm, Optimization, Algoritma Genetika, Carbon Sequestration, Enhanced Gas Recovery, Optimisasi |
| Subjects: | Q Science Q Science > QA Mathematics > QA274.2 Stochastic analysis Q Science > QA Mathematics > QA402.5 Genetic algorithms. Interior-point methods. T Technology > TN Mining engineering. Metallurgy > TN880.5 Natural gas pipelines T Technology > TP Chemical technology > TP692.5 Oil and gasoline handling and storage |
| Divisions: | Faculty of Industrial Technology > Physics Engineering > 30201-(S1) Undergraduate Thesis |
| Depositing User: | Sarah Alya Aziz |
| Date Deposited: | 20 Aug 2021 06:13 |
| Last Modified: | 20 Aug 2021 06:13 |
| URI: | http://repository.its.ac.id/id/eprint/88026 |
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