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DISCREPANCY OF MCMP DERIVED FROM EXPERIMENTS AND PREDICTION MODELS OF SOME INDONESIAN OIL FIELDS

Scientific Contributions Oil and Gas · Vol. 37 No. 2 (2022) · hlm. 69–78

DOI
10.29017/SCOG.37.2.627
ISSN
2541-0520, 2089-3361
Terbit
2022-02-15
Penerbit
Testing Center for Oil and Gas LEMIGAS
Bahasa
eng
Lisensi
creativecommons.org/licenses/by/4.0

Abstrak

Most of oil fi elds in Indonesian have been categorized as mature fi elds, since the primary stages of theoil production nearly fi nished. Therefore EOR technology is the only option to rejuvenate those old oil fi eldsto increase the oil recovery. CO2 miscible fl ooding, one of the proven EOR technology, can be implementedin some Indonesia oil fi elds if they fulfi ll the screening criteria for CO2 injection. Laboratory works initiallyshould be carried out to determine some parameters for calibrating the reservoir simulation program. Themost important parameter is MCMP (multiple contact miscibility pressure), this pressure level can be usedto determine the displacement effi ciency of the CO2 injection. Above the MCMP will be more effi cientcompare to below MCMP injection pressure. MCMP is normally can be obtained in the lab by a Slim tubeapparatus. In case there are no oil and gas sample available, some correlations based on the empiricalfi eld data are also available in the literature as well as EOS (equation of state) for predicting MCMP. Somereservoir fl uids MCMP have been evaluated using those three methods. Then, discrepancies were calculatedto compare the results of Slim tube tests, correlations and EOS calculation. Four correlations such as NPC(National Petroleum Council), Cronquist et al, Yellig-Metcalfe, Holm-Yosendal and one EOS modeling ofPeng-Robinson (1978) have been proposed to predict the MCMP fourteen reservoirs. Moreover, those MCMPwere also run using Slim tube. Holm-Yosendal correlation has nine reservoirs and secondly Yellig-Metcalfemethod possesses six reservoirs with discrepancy below 10% compare to MCMP obtained from Slim Tubetests. While the other methods are not appropriate as well as Peng-Robinson EOS modeling without anylaboratory data for calibration.

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  • Universitas Syiah Kuala
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Rekan penulisOrganisasiArtikel bersama
Sugihardjo SugihardjoSebelas Maret University3
Emi WidiyantiAfiliasi tidak diketahui2
Usman PasaraiAfiliasi tidak diketahui2
Usman UsmanUniversitas Syiah Kuala2
Tri Muji SusantoroAfiliasi tidak diketahui2
Suliantara SuliantaraAfiliasi tidak diketahui2
Bambang WidarsonoAfiliasi tidak diketahui2
Herru L SetiawanAfiliasi tidak diketahui2
Mohamad RomliAfiliasi tidak diketahui2
Diana DwiyanartiAfiliasi tidak diketahui2
Putri PermatasariAfiliasi tidak diketahui1
Moh Rizwan RizalAfiliasi tidak diketahui1
Putri PermatasariSebelas Maret University1
Moh Rizwan RizalSebelas Maret University1
Suminah SuminahAfiliasi tidak diketahui1
Muhammad Ivan RizkiAfiliasi tidak diketahui1
Suminah SuminahSebelas Maret University1
Muhammad Ivan RizkiSebelas Maret University1
Bunga KiranaAfiliasi tidak diketahui1
Emi WidiyantiSebelas Maret University1
Bunga KiranaSebelas Maret University1
Ahshaina RamadhaningtiyasAfiliasi tidak diketahui1
Yulia Lanti Retno DewiAfiliasi tidak diketahui1
Eny LestariAfiliasi tidak diketahui1
Dwiningtyas PadmaningrumAfiliasi tidak diketahui1
Agung WibowoSebelas Maret University1
Joko SutrisnoAfiliasi tidak diketahui1
Hestuti EniAfiliasi tidak diketahui1
Utomo Pratama IskandarAfiliasi tidak diketahui1
Herru Lastiadi SAfiliasi tidak diketahui1
Edward ML TobingAfiliasi tidak diketahui1
Utomo Pratama IAfiliasi tidak diketahui1
Djoko SunarjantoAfiliasi tidak diketahui1
Panca WahyudiAfiliasi tidak diketahui1
Herizal HerizalAfiliasi tidak diketahui1
Aziz M LubadAfiliasi tidak diketahui1
Nurkamelia NurkameliaAfiliasi tidak diketahui1
Panca W. SukarnoAfiliasi tidak diketahui1
Junita T MusuAfiliasi tidak diketahui1

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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)
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en">DISCREPANCY OF MCMP DERIVED FROM EXPERIMENTS AND PREDICTION MODELS OF SOME INDONESIAN OIL FIELDS</dc:title>
	<dc:creator xml:lang="en">Sugihardjo, Sugihardjo</dc:creator>
	<dc:subject xml:lang="en">CO2 Injection</dc:subject>
	<dc:subject xml:lang="en">MMCP (Multiple Contac Miscibility Pressure)</dc:subject>
	<dc:subject xml:lang="en">EOS (Equation of State)</dc:subject>
	<dc:description xml:lang="en">Most of oil fi elds in Indonesian have been categorized as mature fi elds, since the primary stages of theoil production nearly fi nished. Therefore EOR technology is the only option to rejuvenate those old oil fi eldsto increase the oil recovery. CO2 miscible fl ooding, one of the proven EOR technology, can be implementedin some Indonesia oil fi elds if they fulfi ll the screening criteria for CO2 injection. Laboratory works initiallyshould be carried out to determine some parameters for calibrating the reservoir simulation program. Themost important parameter is MCMP (multiple contact miscibility pressure), this pressure level can be usedto determine the displacement effi ciency of the CO2 injection. Above the MCMP will be more effi cientcompare to below MCMP injection pressure. MCMP is normally can be obtained in the lab by a Slim tubeapparatus. In case there are no oil and gas sample available, some correlations based on the empiricalfi eld data are also available in the literature as well as EOS (equation of state) for predicting MCMP. Somereservoir fl uids MCMP have been evaluated using those three methods. Then, discrepancies were calculatedto compare the results of Slim tube tests, correlations and EOS calculation. Four correlations such as NPC(National Petroleum Council), Cronquist et al, Yellig-Metcalfe, Holm-Yosendal and one EOS modeling ofPeng-Robinson (1978) have been proposed to predict the MCMP fourteen reservoirs. Moreover, those MCMPwere also run using Slim tube. Holm-Yosendal correlation has nine reservoirs and secondly Yellig-Metcalfemethod possesses six reservoirs with discrepancy below 10% compare to MCMP obtained from Slim Tubetests. While the other methods are not appropriate as well as Peng-Robinson EOS modeling without anylaboratory data for calibration.</dc:description>
	<dc:publisher xml:lang="en">Testing Center for Oil and Gas LEMIGAS</dc:publisher>
	<dc:date>2022-02-15</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/627</dc:identifier>
	<dc:identifier>10.29017/SCOG.37.2.627</dc:identifier>
	<dc:source xml:lang="en">Scientific Contributions Oil and Gas; Vol. 37 No. 2 (2014); 69-78</dc:source>
	<dc:source xml:lang="id">Scientific Contributions Oil and Gas; Vol 37 No 2 (2014); 69-78</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/627/417</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2022 SCIENTIFIC CONTRIBUTIONS OIL AND GAS (SCOG)</dc:rights>
	<dc:rights xml:lang="en">https://creativecommons.org/licenses/by/4.0</dc:rights>
</oai_dc:dc>