Zulhen, Afrinaldi (2026) PEnentuan Kandidat Sumur Untuk Instalasi Electrical Submersible Pump (ESP) Upsizing Dengan Metode Analisis Cluster Dan AHP Pada Lapangan Migas JN DI PT. XYZ. Masters thesis, Institut Teknologi Sepuluh Nopember.
![[thumbnail of 6032241189-Master_Thesis.pdf]](http://repository.its.ac.id/style/images/fileicons/text.png) |
Text
6032241189-Master_Thesis.pdf - Accepted Version Restricted to Repository staff only Download (3MB) | Request a copy |
Abstract
Penurunan produksi pada lapangan migas tua merupakan tantangan utama yang dihadapi industri hulu, termasuk Lapangan JN milik PT. XYZ yang mengalami penurunan tekanan reservoir. Salah satu strategi optimasi yang diterapkan adalah program instalasi Electical Submersible Pump (ESP) Upsizing, yaitu peningkatan kapasitas pompa untuk meningkatkan laju produksi. Namun, pemilihan sumur kandidat kerap tidak efisien akibat keterbatasan pendekatan sistematis, variasi kondisi teknis sumur, dan kendala operasional di lapangan. Penelitian ini mengembangkan model pengambilan keputusan berbasis data melalui integrasi metode Analisis Cluster dan Analytical Hierarchy Process (AHP) untuk menentukan prioritas sumur kandidat ESP Upsizing secara objektif dan terukur. Sebanyak 24 sumur dianalisis menggunakan metode K-Means berdasarkan parameter teknis seperti Qmax, GOR, SBHP, FBHP, PI, dan BS&W untuk membentuk segmen sumur dengan karakteristik serupa. Selanjutnya, lima kriteria operasional utama, yakni target produksi, akses rig, cuaca, keamanan, dan operational cost dievaluasi melalui AHP untuk menentukan tingkat prioritas tiap sumur. Integrasi kedua metode ini menghasilkan pemetaan kandidat yang lebih terstruktur serta rekomendasi urutan pengerjaan yang mendukung efisiensi dan efektifitas intervensi sumur. Pendekatan ini tidak hanya relevan bagi Lapangan JN, tetapi juga dapat diadaptasi untuk proyek optimasi produksi pada lapangan migas lain dengan karakteristik serupa.
=================================================================================================================================
Declining production in mature oil and gas fields is a major challenge facing the upstream industry, including PT. XYZ's JN Field, which is experiencing a decline in reservoir pressure. One of the optimization strategies implemented is the Electrical Submersible Pump (ESP) Upsizing installation program, which increases pump capacity to increase production rates. However, candidate well selection is often inefficient due to limitations in systematic approaches, variations in well technical conditions, and operational constraints in the field. This study develops a data-driven decision-making model through the integration of Cluster Analysis and Analytical Hierarchy Process (AHP) methods to determine the priority of ESP Upsizing candidate wells objectively and measurably. A total of 24 wells were analyzed using the K-Means method based on technical parameters such as Qmax, GOR, SBHP, FBHP, PI, and BS&W to form well segments with similar characteristics. Furthermore, five main operational criteria, namely production targets, rig access, weather, security, and operational costs were evaluated through AHP to determine the priority level of each well. The integration of these two methods resulted in a more structured candidate mapping and recommended work sequences that support the efficiency and effectiveness of well interventions. This approach is not only relevant to the JN Field but can also be adapted for production optimization projects in other oil and gas fields with similar characteristics.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Hulu Migas, Analisis Cluster, AHP, ESP Upsizing. Upstream Oil and Gas, Cluster Analysis, AHP, ESP Upsizing. |
| Subjects: | Q Science > QA Mathematics > QA278 Cluster Analysis. Multivariate analysis. Correspondence analysis (Statistics) T Technology > T Technology (General) > T58.62 Decision support systems |
| Divisions: | Interdisciplinary School of Management and Technology (SIMT) > 61101-Master of Technology Management (MMT) |
| Depositing User: | Afrinaldi Zulhen |
| Date Deposited: | 14 Jan 2026 05:47 |
| Last Modified: | 14 Jan 2026 05:47 |
| URI: | http://repository.its.ac.id/id/eprint/129605 |
Actions (login required)
 |
View Item |