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All Journal Simetris IJOG : Indonesian Journal on Geoscience Jurnal Spektra JITEK (Jurnal Ilmiah Teknosains) Indonesian Journal on Geoscience Indonesian Journal on Geoscience Indonesian Journal of Physics (IJP) Aceh International Journal of Science and Technology Jurnal Polimesin
Arya Dwi Candra
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Evaluation of Tubing Diameter and Bean Size for Optimization of Well Production Rate Arya Dwi Candra; Muhammad Firmansyah Hafidzullah; Rakha Reswara; Paradongan Siahaan; Dies Elita Budiyanti; Zainal Abidin
Jurnal POLIMESIN Vol 21, No 1 (2023): February
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v21i1.3196

Abstract

Gas field development is a costly affair, thus it is essential that each component of the production system operates properly. The objective of field optimization is to discover the parameter range that maximizes productivity. In addition, the development of natural gas reserves for both fuel and petrochemical purposes is accelerating. Well X is an approximately 4-year-old natural-flow gas well with a gas flowrate of 7.7 MMSCF/D, condensate flowrate of 55 BCPD, and water flowrate of 2 BWPD. As fluid is generated from the reservoir to the surface, the production rate of the well decreases. This well's productivity was evaluated using nodal analysis in conjunction with a comparison of tubing size and bean size. aiming to satisfy gas demand without exceeding the critical limit. The nodal analysis approach is utilized to determine the well's optimal and efficient performance. Moreover, utilizing system analysis, which is a graphical plot between the tubing size and the resulting flow rate, as depicted in Figure 6, we can determine which tubing size delivers the highest or most efficient rate at a particular moment under constant wellhead pressure (node at the wellhead). If the demand grows by 14.4 MMSCF/D, the installed tube size can be changed to 40/64" for optimization purposes. This procedure is more cost-effective because it does not squander money and does not halt gas production at the well. To satisfy the increased gas demand of 14.4 MMSCF/D, the production operator can rotate the bean or choke from its initial 24/64" size to 40/64" size.
The Effect of Modular Portable Clamp on Electrical Heat Traces for Wellhead Icing Prevention Arya Dwi Candra; Pradini Rahalintar; Akba Gushari; Muhammad Aulia Fikri; Novlian Adonia Borolla; Zulfan Zulfan; Zainal Abidin
Jurnal POLIMESIN Vol 21, No 1 (2023): February
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jpl.v21i1.3193

Abstract

Gas wells have numerous safety devices installed at the wellhead, including pressure sensors with high-high (HH) and low-low (LL) parameter set points that can close the shut-down valve (SDV). A phenomenon of icing was discovered on the wellhead tube wings during open well X operations (after shut-in wells). This occurs when wells are shut down for longer than three days, such as during turnaround operations or emergency situations. The occurrence of ice blocks on the wellhead tube wings during wellbore startup disrupts gas flow to well X and has the potential to result in an annual loss of production opportunity (LPO) of $960 million. When there is a significant heat release phenomenon around the wing tube area, the absence of a heating facility around the wellhead area is one of the most important factors in this icing. To prevent icing and ice blockage, a portable, modular electric heat trace with clamp-on attachment is installed. Heat Trace cable is connected to a portable generator for power. This device is capable of converting electricity into heat up to 167 °F (75 °C). The heat generated by the instrument will mitigate the sudden release of heat when the gas begins to flow. Modular portable clamp-on heat tracing has been demonstrated to eliminate the possibility of icing at the wellhead due to a significant drop in temperature and maintain the gas field's production rate.
Comparison Of Facies Estimation Using Support Vector Machine (SVM) And K-Nearest Neighbor (KNN) Algorithm Based on Well Log Data Prabowo*, Urip Nurwijayanto; Ferdiyan, Akmal; Raharjo, Sukmaji Anom; Sehah, Sehah; Candra, Arya Dwi
Aceh International Journal of Science and Technology Vol 12, No 2 (2023): August 2023
Publisher : Graduate School of Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.12.2.28428

Abstract

Facies classification is the process of identifying rock lithology based on indirect measurements such as well log measurements. Usually, the facies are classified manually by experienced geologists, so it takes a long time and is less efficient. In this paper, two machine learning (Support vector machine and K-Nearest Neighbor) were adopted to increase the effectiveness and shorten the time process of facies classification in Z Field, Indonesia. The machine learning algorithm was carried out in 4 steps, i.e. data selection, training phase, verification, and validation stage. The machine learning input data are density log, gamma ray log, resistivity log, SP log; and the output facies target are Sandstone, Siltstone, Claystone, and Limestone. The data is divided into train data for the training process and test data to validate the machine learning output. In Support vector machine results, the training accuracy is 70.1% and the testing accuracy is 47.4%, while in KNearest Neighbor results, the training accuracy is 70.1% and the testing accuracy is 63.3%. This result showed K-Nearest Neighbor has better accuracy than the support vector machine in facies classification in the Z field.
Co-Authors Akba Gushari Bagus Jaya Santosa Bagus Jaya Santosa Dies Elita Budiyanti Dwa Desa Warnana Ferdiyan, Akmal Irwan Setyowidodo, Bagus Jaya Santosa Muhammad Aulia Fikri Muhammad Firmansyah Hafidzullah Novlian Adonia Borolla Paradongan Siahaan Prabowo*, Urip Nurwijayanto Pradini Rahalintar puput eka suryani Puput Eka Suryani Rachman, Gazali Rakha Reswara Sehah Sehah Sukmaji Anom Raharjo Suluh Jatmiko Totok Wijayanto Totok Wijayanto, Totok Zainal Abidin Zainal Abidin Zulfan Zulfan