Articles
<![CDATA[Rekonstruksi dan Validasi Data Permeabilitas Relatif Untuk Proses History Matching Dalam Simulasi Reservoir Pengembangan Lapangan X ]]>
<![CDATA[Novia Rita]]>;
<![CDATA[Tomi Erfando]]>
<![CDATA[ Journal of Earth Energy Engineering Vol. 4 No. 2 (2015): OCTOBER ]]>
Publisher : <![CDATA[Universitas Islam Riau (UIR) Press ]]>
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DOI: 10.22549/jeee.v4i2.637
<![CDATA[Sebelum suatu model reservoir digunakan, terlebih dahulu dilakukan history matching atau menyesuaikan kondisi model dengan dengan kondisi reservoir. Salah satu parameter yang perlu disesuaikan adalah permeabilitas relatif. Untuk melakukan rekonstruksi nilai permeabilitas relatifnya dibutuhkan data SCAL (Special Core Analysis) dari sampel core. Langkah awal rekonstruksi adalah dengan melakukan normalisasi data permeabilitas relatif (kr) dan saturasi air (Sw) dari data SCAL yang berasal dari tiga sampel core. Setelah dilakukan nomalisasi, dilakukan denormalisasi data permeabilitas relatif yang akan dikelompokkan berdasarkan jenis batuannya. Setelah dilakukan history matching menggunakan black oil simulator, data denormalisasi tersebut belum sesuai dengan kondisi aktual. Selanjutnya digunakan persamaan Corey untuk rekonstruksi kurva permeabilitas relatifnya. Hasil dari persamaan tersebut didapat bahwa nilai kro dan krw jenis batuan 1 sebesar 0,25 dan 0,09 kemudian nilai kro dan krw untuk jenis batuan 2 sebesar 0,4 dan 0,2. Nilai permeabilitas dari persamaan Corey digunakan untuk melakukan history matching, hasilnya didapat kecocokan (matching) dengan keadaan aktual. Berdasarkan hasil simulasi, nilai produksi minyak aktualnya adalah 1.465.650 bbl sedangkan produksi dari simulasi adalah 1.499.000 bbl. Artinya persentase perbandingan aktual dan simulasinya adalah 1,14% yang dapat dikatakan cocok karena persentase perbedaannya di bawah 5%.]]>
<![CDATA[Optimasi Laju Injeksi Pada Sumur Kandidat Convert to Injection (CTI) di Area X Lapangan Y ]]>
<![CDATA[Tomi Erfando]]>;
<![CDATA[Novia Rita]]>;
<![CDATA[Toety Marliaty]]>
<![CDATA[ Journal of Earth Energy Engineering Vol. 6 No. 2 (2017): OCTOBER ]]>
Publisher : <![CDATA[Universitas Islam Riau (UIR) Press ]]>
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DOI: 10.22549/jeee.v6i2.992
<![CDATA[Area X merupakan bagian dari lapangan Y saat ini mengalami dalam kurun waktu 16 tahun terakhir penurunan laju alir produksi sebesar 64.4%. Diperlukan upaya untuk meningkat laju alir produksi minyak dan recovery factor dari area tersebut, upaya yang akan dilakukan adalah injeksi air atau waterflood dengan mengubah salah satu sumur produksi menjadi sumur injeksi (convert to injection). Penentuan kandidat sumur convert to injection (CTI) berdasarkan kondisi laju alir produksi, jarak antara sumur kandidat dan sumur produksi, serta korelasi antar sumur. Untuk memperoleh hasil yang optimal akan dibuat beberapa skenario yang akan disimulasikan dengan parameter rate injeksi dan penambahan perforasi. Penentuan rate injeksi dilakukan dengan uji sensitivitas terlebih dahulu dan memperhatikan tekanan fracture dari tiap lapisan. Penambahan perforasi dengan melihat korelasi dari data log yang ada sehingga sumur CTI dapat memberikan peningkatan terhadap sumur produksi. Hasil simulasi yang paling optimal dari skenario yang direncanakan diperoleh penambahan produksi sebesar 800 MSTB dan recovery factor sebesar 12.9%.]]>
<![CDATA[Effects of Various Steam Flooding Injection Patterns and Steam Quality to Recovery Factor ]]>
<![CDATA[Indri Kusumastuti]]>;
<![CDATA[Tomi Erfando]]>;
<![CDATA[Fiki Hidayat]]>
<![CDATA[ Journal of Earth Energy Engineering Vol. 8 No. 1 (2019): APRIL ]]>
Publisher : <![CDATA[Universitas Islam Riau (UIR) Press ]]>
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DOI: 10.25299/jeee.2019.vol8(1).2909
<![CDATA[The main principle of steam flooding is to reduce the oil viscosity using hot steam that is injected into the reservoir. In the field implementation there are several injection patterns that can be applied for steam flooding. This research aims to determine the effect of several injection patterns and steam quality on oil recovery factor. Therefore, it can be known the injection pattern and steam quality are right to obtain the best recovery factor. Analysis was carried out on injection patterns including five-spots, inverted five-spots, seven-spots, inverted seven-spots, nine-spots, and inverted nine-spots. The variations in the steam quality used are 50%, 70% and 90%. The simulation model a 3-dimensional cartesian with grid block size 5x5x5 on CMG STARS. The parameters in this steam flooding scenario are temperature at 450° F, injection pressure of 500 psi, and injection rate of 1000 bbl /day. Of all the scenarios tested the best results were in the inverted seven spot pattern with steam quality 0.9, where recovery factor was 35,1% and total cumulative production was 269397 bbl.]]>
<![CDATA[Application of Pineapple Skin Waste as a Source of Biosolvent for Use as Wax Inhibitor ]]>
<![CDATA[Muhammad Khairul Afdhol]]>;
<![CDATA[Tomi Erfando]]>;
<![CDATA[Fiki Hidayat]]>;
<![CDATA[Rosdanelli Hasibuan]]>;
<![CDATA[Muhammad Yudatama Hasibuan]]>;
<![CDATA[Chalidah Pratiwi Siregar]]>
<![CDATA[ Journal of Earth Energy Engineering Vol. 9 No. 2 (2020): OCTOBER ]]>
Publisher : <![CDATA[Universitas Islam Riau (UIR) Press ]]>
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DOI: 10.25299/jeee.2020.3922
<![CDATA[Wax paraffin deposition is a problem faced in the pipeline for petroleum industries that they blockage the partial or full inside the pipe, which will decrease the production rate. One of the treatments is to use the preventive methods called wax inhibitors which are expected to inhibit the crystallization of paraffin wax, and bio-solvent is included. Hydrolysis and fermentation technique are used to produced bio-solvent. Hydrolysis aims to break lignin and hemicellulose, damage the crystal structure, and increase the porosity of the material. At the same time, the occurrence of pentose changes and some glucose into ethanol is present in the fermentation process. Then, purified by the distillation process to obtain bio solvent products that are applied with waxy crude oil can reduce the pour point value of crude oil. From the hydrolysis process with five variations of acid percentage, the amount of reducing sugars increase. By increasing temperature from 50 ° C to 100 ° C, the reducing sugars continues to increase until it reaches the optimal point of 18.2 ° Brix. The amount of inoculant also affects the level of bio-solvent where the optimum results using inoculants are 0.015 g/mL, which produces 6% levels of bioethanol. The high ethanol content of 2% had a density value of 0.979 g/mL. The best °API at 5% is 13.901, and the average value is about 13.0945, where the best viscosity values for ethanol content of 6% are 0.814. Bioethanol testing using waxy crude oil is carried out with the bioethanol content of 6%. The addition of the ethanol contents only decreased the pour point 2-3℃. At sample, #LGK19 experienced a 3°C drop in pour point from 45°C to 42°C. Therefore, it can be concluded that bioethanol used as a solvent can potentially inhibit paraffin deposition.]]>
<![CDATA[Identifikasi Potensi Jeruk Purut Sebagai Demulsifier Untuk Memisahkan Air Dari Emulsi Minyak di Lapangan Minyak Riau ]]>
<![CDATA[Tomi Erfando]]>
<![CDATA[ JURNAL KIMIA MULAWARMAN Vol 15 No 2 (2018) ]]>
Publisher : <![CDATA[Jurusan Kimia Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Mulawarman ]]>
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DOI: 10.30872/jkm.v15i2.604
<![CDATA[Emulsion stability is an indicator that needs to be controlled to prevent the degradation of petroleum quality. Emulsion breakdown is one of the mechanisms to separate the water phase from oil. It is transformed into a chemical compound that is expected to function as emulsion blocking or commonly known as a demulsifier. An organic demulsifier is one of the right ideas in preventing environmental pollution without diminishing its main function as an emulsion breaker. The bottle test method is one of the most commonly used methods in demulsification tests. Testing using this method is done by inserting the prepared emulsion into the bottle, then it will be placed into a waterbath under certain temperature conditions for several hours. This test will be done by looking at the demulsification that occurs every 30 minutes. From the testing of temperature, concentration, and effectiveness of the formulated formula, an optimal condition is obtained based on the highest demulsification efficiency. Based on the research, optimal condition of organic demulsifier formula is (3ml, 80˚C) with 7 ml demulsification efficiency. The results obtained from organic material formulations have not been able to increase the effectiveness of emulsion-breaking processes compared to commercial demulsifiers and basecase conditions (20 ml).]]>
<![CDATA[Evaluasi Kebijakan Program MBKM dalam Meningkatkan Capaian Pembelajaran Lulusan Perguruan Tinggi ]]>
<![CDATA[Kurnia Hastuti]]>;
<![CDATA[Heni Susanti]]>;
<![CDATA[Tomi Erfando]]>
<![CDATA[ EDUKATIF : JURNAL ILMU PENDIDIKAN Vol 4, No 6 (2022): December 2022 ]]>
Publisher : <![CDATA[Universitas Pahlawan Tuanku Tambusai ]]>
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DOI: 10.31004/edukatif.v4i6.4119
<![CDATA[Penelitian ini bertujuan untuk mengevaluasi impelementasi kebijakan MBKM di Indonesia. Pendekatan evaluasi dalam kajian ini menggunakan pendekatan kualitataif. Pastisipan dalam penelitian ini adalah seluruh stakeholder yang mengelola kegiatan MBKM yang terdiri dari Rektor, Wakil Rektor Bagian akademik, Direktorat Akademik yang berperan aktif dalam mengelola program MBKM di pada empat kampus di Indonesia yaitu Pekanbaru, Bandung, Pontianak, dan Makasar. Teknik pengumpulan data dalam kajian evaluasi ini adalah observasi dan wawancara mendalam untuk mendapatkan data tentang impelementasi kebijakan program MBKM yang ada di Indonesia. Teknik analisis data dalam penelitian menggunakan Creswell (2014): preparing and defining data, reading the data as a whole, encoding data, defining themes and creating descriptions, linking. Hasil penelitian menunjukkan bahwa kebijakan program MBKM yang diterapkan pada beberapa kampus di Indonesia belum berjalan dengan maksimal. Hal ini dikarenakan belum maksimalnya koordinasi antara pimpinan tertinggi di Kampus sampai dengan ketua prodi pada masing-masing jurusan. Hal yang paling sulit dirasakan oleh kampus adalah sulitnya mengkonversi kegiatan di luar kampus dengan mata kuliah yang disajikan dalam kurikulum yang dirancang oleh oleh universitas.]]>
<![CDATA[SOSIALISASI KURIKULUM PEMBINAAN SEPAKBOLA INDONESIA DI KABUPATEN SIAK ]]>
<![CDATA[Ricky Fernando]]>;
<![CDATA[Tomi Erfando]]>;
<![CDATA[Anggea Titania]]>;
<![CDATA[Ade Irma]]>
<![CDATA[ JURNAL PENGABDIAN MANDIRI Vol. 1 No. 11: November 2022 ]]>
Publisher : <![CDATA[Bajang Institute ]]>
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<![CDATA[The Indonesian football coaching curriculum aims to serve as a guide for teachers and coaches at an early age and young age on how to provide appropriate and appropriate stages of training according to age levels. To strengthen and develop the philosophy of Indonesian football, it takes a touch of Sports Science that is thick in Indonesian football culture. The Indonesian football coaching curriculum also describes the stages of coaching in which each stage has systematic and specific training methods according to the needs of the age level. The stages of coaching in the Indonesian football curriculum prepare players who are capable of playing football. compose a logical and simple football to make it easier for players to understand the game of football. The coach's understanding of the football coaching curriculum is the key in shaping the character and development of players from an early age and young age, in essence, all phases that are passed in football coaching are designed as a contribution to print players in elite pro clubs and professional players. strong and able to compete at international level.]]>
<![CDATA[Optimasi Volume Injeksi Pada Waterflooding Menggunakan Metode Artificial Neural Network ]]>
<![CDATA[Rizka Haswinda Putri]]>;
<![CDATA[Tomi Erfando]]>
<![CDATA[ Jurnal Serambi Engineering Vol 8, No 2 (2023): April 2023 ]]>
Publisher : <![CDATA[Fakultas Teknik ]]>
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DOI: 10.32672/jse.v8i2.5987
<![CDATA[Waterflooding adalah salah satu metode pemulihan sekunder yang bertujuan untuk mempertahakan tekanan reservoir. Volume air injeksi disesuaikan agar tidak terjadi penurunan oil recovery. Tujuan dari penelitian ini adalah untuk mengoptimalkan nilai Injection Volume dan Recovery Factor (RF) dengan menggunakan metode Artificial Neural Network (ANN). Parameter yang digunakan adalah porositas, permeabilitas horizontal, permeabilitas vertikal, saturasi minyak, saturasi air, kompresibilitas batuan. Software simulasi reservoir menggunakan Computer Modeling Group (CMG), kemudian optimasi menggunakan Machine Learning (ML). Pendekatan Machine Learning menggunakan rasio 0,7:0,3 untuk data pelatihan dan pengujian. kemudian dilakukan trial and error pada 10 node hidden layer. Hasil penelitian memiliki akurasi yang tinggi karena nilai R2 pada data training dan testing mendekati 1, sehingga nilai optimasi pada recovery factor sebesar 26.17%, meningkat sebesar 5.85% dari basecase dan volume injeksi sebesar 15387684 bbl atau 15.4 MMbbl.]]>
<![CDATA[Sensitivity Study of The Effect Polymer Flooding Parameters to Improve Oil Recovery Using X-Gradient Boosting Algorithm ]]>
<![CDATA[Tomi Erfando]]>;
<![CDATA[Rizqy Khariszma]]>
<![CDATA[ Journal of Applied Engineering and Technological Science (JAETS) Vol. 4 No. 2 (2023): Journal of Applied Engineering and Technological Science (JAETS) ]]>
Publisher : <![CDATA[Yayasan Riset dan Pengembangan Intelektual (YRPI) ]]>
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DOI: 10.37385/jaets.v4i2.1871
<![CDATA[Implementation of waterflooding sometimes cannot increase oil recovery effectively and requires additional methods to increase oil recovery. Polymer flooding is a common chemical EOR method that has been implemented in the last few decades and provides good effectiveness in increasing oil recovery and can reduce the amount of injection fluid injected into the reservoir. Seeing the success of polymer flooding in increasing oil recovery, it is necessary to know the parameters that influence the success of polymer flooding so that it can be evaluated and taken into consideration in creating a new scheme to increase oil recovery with polymer flooding. The parameters tested in this study include Injection Rate, Injection Time, Injection Pressure, Adsorption, Inaccessible Pore Volume, Residual Resistance Factor. This research uses the X-Gardient Boosting Algorithm to look at the most influential parameters in polymer flooding. The parameters that most influence the performance of polymer flooding on the value of oil recovery with the importance level of each parameter in this study are injection time of 0.452632, injection rate of 0.430075, injection pressure of 0.064662, Adsorption of 0.025564, RRF of 0.021053, IPV of 0.006014 and produce accurate predictive modeling using x-gradient boosting where with 3 variations of the comparison ratio of training and testing data obtained at a ratio of 0.7 : 0.3 obtained an R2 train of 0.9886 and an R2 test of 0.9645, a ratio of 0.8 : 0.2 obtained an R2 train of 0.9891 and an R2 test of 0.9579, and a ratio of 0.9: 0.1 obtained R2 train of 0.9890 and R2 test of 0.9660.]]>
<![CDATA[Optimasi Volume Injeksi Pada Waterflooding Menggunakan Metode Artificial Neural Network ]]>
<![CDATA[Rizka Haswinda Putri]]>;
<![CDATA[Tomi Erfando]]>
<![CDATA[ Jurnal Serambi Engineering Vol 8, No 2 (2023): April 2023 ]]>
Publisher : <![CDATA[Fakultas Teknik ]]>
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DOI: 10.32672/jse.v8i2.5987
<![CDATA[Waterflooding adalah salah satu metode pemulihan sekunder yang bertujuan untuk mempertahakan tekanan reservoir. Volume air injeksi disesuaikan agar tidak terjadi penurunan oil recovery. Tujuan dari penelitian ini adalah untuk mengoptimalkan nilai Injection Volume dan Recovery Factor (RF) dengan menggunakan metode Artificial Neural Network (ANN). Parameter yang digunakan adalah porositas, permeabilitas horizontal, permeabilitas vertikal, saturasi minyak, saturasi air, kompresibilitas batuan. Software simulasi reservoir menggunakan Computer Modeling Group (CMG), kemudian optimasi menggunakan Machine Learning (ML). Pendekatan Machine Learning menggunakan rasio 0,7:0,3 untuk data pelatihan dan pengujian. kemudian dilakukan trial and error pada 10 node hidden layer. Hasil penelitian memiliki akurasi yang tinggi karena nilai R2 pada data training dan testing mendekati 1, sehingga nilai optimasi pada recovery factor sebesar 26.17%, meningkat sebesar 5.85% dari basecase dan volume injeksi sebesar 15387684 bbl atau 15.4 MMbbl.]]>
