Journal of Sustainable Energy Development

Carbon Capture Utilization (CCU) sebagai Generator Energi Listrik menggunakan Allam Cycle sebagai Upaya Dekarbonisasi Industri Migas

Fifi Izzati, Pijar Fitrah Ababil, Hadziqul Abror — Tue, 30 May 2023 00:00:00 +0700

Along with the development and progress of human civilization, the need for electrical energy continues to increase. For this reason, new energy sources are needed so that energy needs can be met. Carbon dioxide (CO₂) can be a new energy source obtained from industrial waste energy processing. CO₂ is a type of emission that can cause the formation of greenhouse gas (GHG) emissions and contributes to global climate change. A 6% increase in emissions from 2020 results in emissions of 36.3 giga tons (Gt). One utilization of CO₂ emissions that can be done is to convert CO₂ emissions into electricity. The data analysis method is done by comparing the technical and economic parameters between the rankine power cycle using H₂O as the working fluid and the Allam power cycle using CO₂ as the working fluid. The results obtained are that the natural gas-fired Allam cycle has a net HHV and LHV efficiency of 53.17% and 58.90%, respectively. For the coal-fired Allam cycle, the net HHV and LHV efficiencies obtained were 48.88% and 51.44%, respectively. The economic analysis conducted is LCOE, IRR, and NPV. The economic analysis shows that the project is feasible in terms of electricity cost.

EKSTRAKSI LITIUM PADA AIR FORMASI PANAS BUMI DENGAN METODE ADSORPSI (STUDI KASUS PADA PLTP DIENG)

Tue, 30 May 2023 00:00:00 +0700

Geothermal energy is produced due to the tectonic and volcanic activity of a hydrothermal system in the earth. Geothermal potential in Indonesia is 28,170 MW, but only 1728 MW or 4% of the geothermal potential is utilized as a source of Geothermal Power Plant (GPP). The development of GPP requires a very large investment and is not comparable to the selling price of electricity. The principle of GPP is to use hot steam from the reservoir to generate electricity through a generator. The produced fluid consists of steam and brine water which will later be discharged/reinjected. Brine water comes from meteoric water that settles around the reservoir rocks. This precipitation process will dissolve minerals in the reservoir rock, one of which is lithium which is the raw material for batteries. There are various methods to extract lithium from brine water, including precipitation, ion-exchange, extraction with ion-in-liquids (ILs), and adsorption. The lithium extraction process begins with brine that is adsorbed using Li-ion-sieves and will be eluted with dilute HCl and then precipitated with Na2CO3 to become LiCO3 which will be marketed as battery raw material. The brine at Dieng GPP has a lithium content of 50.11 to 99.4 mg/L in the brine, if the flow rate is 70 tons/hour, 1.89 tons/month of LiCO3 will be obtained.

Tinjauan Komprehensif Evaluasi Potensi Penerapan Enhanced Geothermal System Lanjutan: Fracking dan Hydroshearing

Adam Dwi Putra, Putri Rizkika Ramadhanti Pedraza, Riska Laksmita Sari — Tue, 30 May 2023 00:00:00 +0700

Indonesia merupakan negara dengan potensi panas bumi yang besar, dengan posisi negara yang terletak di cincin vulkanik menjadi Indonesia sebagai negara yang memiliki banyak tempat sumber panas bumi. Sumber panas bumi merupakan energi terbarukan yang dapat dikelola menjadi energi listrik, akan tetapi dalam proses produksinya masih banyak tantangan dan kendala dalam pengembangan energi panas bumi ini. Pada pengembangannya dibutuhkan metode yang efektif dalam menangani masalah yang ada dan mengoptimalkan produksi energi panas bumi. Penelitian ini ditujukan untuk membahas dan mereview salah satu metode peningkatan produksi energi panas bumi yaitu metode enhanced geothermal system (EGS). Metode stimulasi EGS dapat mengatasi beberapa kendala seperti permeabilitas kecil dan dapat memproduksi energi panas bumi pada hot dry rock (HDR). Pada EGS diterapkan fracking untuk memperbesar permeabilitas, hydroshearing juga dapat diterapkan pada EGS. Penelitian ini dilakukan dengan metode studi literatur dan mengumpulkan data dari beberapa artikel penelitian terdahulu yang berhubungan dengan EGS. Berdasarkan studi literatur, metode EGS sudah banyak diterapkan di beberapa negara di dunia. Indonesia juga sudah mulai melakukan penelitian mengenai penerapan metode EGS ini yang dilakukan di lapangan Kamojang dan Dieng.

Keywords: Enhanced Geothermal System, EGS, Fracking, Hydroshearing

Analisis Mutu Briket Berbahan Baku Campuran Ampas Teh dan Sekam Padi Menggunakan Perekat Molase Menggunakan Metode Pirolisis

Zeni Ulma, Nur Faizin, Reynadi Febri Afiandi — Tue, 30 May 2023 00:00:00 +0700

This study aims to anayze the effect of molasses adhesive composition on the quaity of briquettes made from tea dregs and rice husks and to determine the characteristics of tea dregs and rice husk briquettes using molasses adhesive. The research was carried out through severa stages, namely the preparation of raw materias, drying of raw materias, pyrolysis of rice husks and tea dregs, raw materias mashed with a 40 mesh sieve, mixing of molasses adhesive, printing, drying and testing the characteristics of briquettes. The pyrolysis process takes 1 hour for the preparation of rice husks and 1.5 hours for the preparation of tea dregs with no or little air. The results showed that the best composition was TSM2 with a ratio of 30% tea dregs and 70% rice husks. The results of the study with the best composition, namely TSM2, caorific vaue 3771 ca/g, moisture content 9.28%, ash content 6.92%, density 1.16 g/cm3, kamba density 0.49 g/cm3, combustion rate 0.031 g/ s. TSM1 10% tea dregs charcoa and 90% rice husk charcoa caorific vaue 3399 ca/g, moisture content 8.94%, ash content 8.02%, density 1.51 g/cm3, kamba density 0.53 g/cm3, burning rate of 0.049 g/s and TSM3 50% tea dregs charcoa and 50% rice husk charcoa caorific vaue 4192 ca/g, moisture content 9.98%, ash content 6.85%, density 0.86 g/cm3, kamba density 0.43 g/cm3, the combustion rate is 0.025 g/s.

Analisis Potensi Sumur dan Peramalan Keadaan Sumur Dimasa Depan Dengan Menggunakan Metode Wiggins pada Sumur FS-09ST Lapangan Sukowati

Faroucki Seven Mahendra, Hadziqul Abror — Tue, 30 May 2023 00:00:00 +0700

Production of the FS-09ST well began on January 17^th, 2009 with oil production is 401 BOPD and peak production on May 13^th, 2011 with oil production is 3254 BOPD. Over time, production has decreased until the well was shut-in on October 9^th, 2020 with oil production is 11 BOPD due to the high watercut which reached 99.55%. The location of this research is administratively located in Campurejo Village, Bojonegoro District, Bojonegoro Regency. Analysis of well potential and well forecasting was carried out using the Wiggins method based on well test data conducted on November 10^th, 2020. This method is used because the FS-09ST well has three-phase fluid and a high water cut. The results of the analysis show that the maximum flowrate is 3899.44 BFPD, the optimum flowrate is 2340 BFPD, and a recommended production flowrate is 2340 BFPD at flowing bottom hole pressure (Pwf) is 1240 Psi to avoid water coning. Based on forecasting future IPR, it is known that the economic limit rate of this well is when the reservoir pressure is 1965 Psi with a oil flowrate of 10.08 BOPD.

Analisa Model Machine Learning dalam Memprediksi Laju Produksi Sumur Migas 15/9-F-14H

Devy Ayu Rhamadhani, Eriska Eklezia Dwi Saputra — Tue, 30 May 2023 00:00:00 +0700

AI algorithm learns various data streams from various sources sensors and engines to extract the analytics resulting in sound advice smart based on business needs. This deep insight makes it possible for oil and gas companies to have better visibility of the whole process and operations, thereby enabling them to make strategic decisions better. This of course leads to increased operating efficiency, cost reduction, and even reduce the risk of failure. Application of artificial intelligence using machine learning to production of oil and gas wells needs to be done to get predictive results perfect. With the support of existing field data so obtained simulation results that provide an overview of the prediction of production wells can optimizing the implementation of production performance for wells that have same production history. The simulation is carried out using the development of machine learning models, Support Vector Regression (SVR), Elastic Net, dan Linear Regression. The data which contains informations about the well production will be divided into two parts, 70% for training and 30% for testing. Of the three models will be seen which one is the best in predicting the production rate of the well 15/9-F-14H based on the RMSE and R² score. SVR is the best model for predicting oil by producing RMSE 5.48 and R² 0.88 when testing. Elastic-Net is the best model for predicting gas by producing RMSE 966.82 and R² 0.85 when testing. There is no model that fits to predict the water production.