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PRODUCTION FORECASTING USING ARPS DECLINE CURVE MODEL WITH THE EFFECT OF ARTIFICIAL LIFT INSTALLATION

Scientific Contributions Oil and Gas · Vol. 46 No. 1 (2023) · hlm. 9–18

DOI
10.29017/SCOG.46.1.1310
ISSN
2541-0520, 2089-3361
Terbit
2023-05-31
Penerbit
Testing Center for Oil and Gas LEMIGAS
Bahasa
eng
Lisensi
creativecommons.org/licenses/by/4.0

Abstrak

There are many methods for predicting the production performance of oil wells, using the simplest method by looking at the declining trend of production, such as Decline Curve Analysis (DCA), Material Balanced, or using reservoir simulations. Each of these methods has its advantages and disadvantages. The DCA method, the Arps method, is often used in production forecast analysis to predict production performance and estimate remaining reserves. However, the limitation of this method is that if the production system changes, the trend of decline will also change. At the same time, the application in the field of taking the trend of decreasing production does not pay attention to changes in the production system. This study aims to see that changes in the well production system will affect the downward trend of well production, estimated ultimate recovery (EUR) value, and well lifetime. To see the effect of these changes, the initial data tested used the results of reservoir simulations and field data. From the evaluation results, it is found that if the production system changes during the production time, for example, from changing natural flow using artificial lifting assistance, the trend taken from the production profile will follow the behaviour of the reservoir if the trend is taken in the last system from the production profile, not from the start of production. If the downward trend is taken without regard to the changing system, then the prediction results will not be appropriate

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  • Bandung Institute of Technology
  • Pertamina (Indonesia)
  • Tanri Abeng University
  • Islamic University of Riau
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Rekan penulisOrganisasiArtikel bersama
Dedy IrawanBandung Institute of Technology2
Fahrizal MaulanaBandung Institute of Technology2
Dedy IrawanBandung Institute of Technology2
Kamal HamzahAfiliasi tidak diketahui1
Mohammed Sheikh Salem Al-AttasAfiliasi tidak diketahui1
Jalest SeptianoBandung Institute of Technology1
Silvya Dewi RahmawatiBandung Institute of Technology1
Reza WardhanaBandung Institute of Technology1
Mochammad Wahdanadi HaidarPertamina (Indonesia)1
Joe Felix TurnipBandung Institute of Technology1
Sri Dwi MustaqimBandung Institute of Technology1
Zuher SyihabBandung Institute of Technology1
Tutuka AriadjiBandung Institute of Technology1
Rian Cahya RohmanaTanri Abeng University1
Dedy IrawanBandung Institute of Technology1
Jeffier WinartaAfiliasi tidak diketahui1
Fajril AmbiaIslamic University of Riau1
Jeffier WinartaBandung Institute of Technology1
Dedy IrawanBandung Institute of Technology1
Roihan NirwanaBandung Institute of Technology1
Syarif Fikri KamalAfiliasi tidak diketahui1
Welly Ahmad RamadanAfiliasi tidak diketahui1
Adam MuhammadBandung Institute of Technology1
Tjok Gede SatryanggaAfiliasi tidak diketahui1
Amritzar AimarAfiliasi tidak diketahui1
Seno KushidayatAfiliasi tidak diketahui1
KarnandoBandung Institute of Technology1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.lemigas.esdm.go.id/index.php/SCOG/oai, pertama di-harvest 10 Nov 2026, terakhir terlihat 10 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en">PRODUCTION FORECASTING USING ARPS DECLINE CURVE MODEL WITH THE EFFECT OF ARTIFICIAL LIFT INSTALLATION</dc:title>
	<dc:creator xml:lang="en">Maurenza, Farrah</dc:creator>
	<dc:creator xml:lang="en">Yasutra, Amega</dc:creator>
	<dc:creator xml:lang="en">Tungkup, Iswara Lumban</dc:creator>
	<dc:subject xml:lang="en">Production forecasting</dc:subject>
	<dc:subject xml:lang="en">Least-square method</dc:subject>
	<dc:subject xml:lang="en">Arps’ Model</dc:subject>
	<dc:subject xml:lang="en">Estimated Ultimate Recovery</dc:subject>
	<dc:description xml:lang="en">There are many methods for predicting the production performance of oil wells, using the simplest method by looking at the declining trend of production, such as Decline Curve Analysis (DCA), Material Balanced, or using reservoir simulations. Each of these methods has its advantages and disadvantages. The DCA method, the Arps method, is often used in production forecast analysis to predict production performance and estimate remaining reserves. However, the limitation of this method is that if the production system changes, the trend of decline will also change. At the same time, the application in the field of taking the trend of decreasing production does not pay attention to changes in the production system. This study aims to see that changes in the well production system will affect the downward trend of well production, estimated ultimate recovery (EUR) value, and well lifetime. To see the effect of these changes, the initial data tested used the results of reservoir simulations and field data. From the evaluation results, it is found that if the production system changes during the production time, for example, from changing natural flow using artificial lifting assistance, the trend taken from the production profile will follow the behaviour of the reservoir if the trend is taken in the last system from the production profile, not from the start of production. If the downward trend is taken without regard to the changing system, then the prediction results will not be appropriate</dc:description>
	<dc:publisher xml:lang="en">Testing Center for Oil and Gas LEMIGAS</dc:publisher>
	<dc:date>2023-05-31</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.lemigas.esdm.go.id/index.php/SCOG/article/view/1310</dc:identifier>
	<dc:identifier>10.29017/SCOG.46.1.1310</dc:identifier>
	<dc:source xml:lang="en">Scientific Contributions Oil and Gas; Vol. 46 No. 1 (2023); 9-18</dc:source>
	<dc:source xml:lang="id">Scientific Contributions Oil and Gas; Vol 46 No 1 (2023); 9-18</dc:source>
	<dc:source>2541-0520</dc:source>
	<dc:source>2089-3361</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.lemigas.esdm.go.id/index.php/SCOG/article/view/1310/pdf</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2023 © Copyright by Authors. Published by LEMIGAS</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
</oai_dc:dc>