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A PROXY MODEL TO PREDICT WATERFLOODING PERFORMANCE IN CHANNELING DELTAIC SAND RESERVOIR Amega Yasutra; Dedy Irawan; Frans Ondihon Sitompul
PETRO: Jurnal Ilmiah Teknik Perminyakan Vol. 9 No. 1 (2020): MARET
Publisher : Jurusan Teknik Perminyakan Fakultas Teknologi Kebumian dan Energi Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1194.198 KB) | DOI: 10.25105/petro.v9i1.5992

Abstract

In recent days, waterflooding activities carried out as a part of secondary recovery. Before performing waterflooding, engineers have to perform reservoir simulation first to predict reservoir performance in order to waterflood. Generally, reservoir simulation is conducted by using numerical simulation method. Numerical simulation gives precise results although it depens on the availiability, quality, and quantity of reservoir characteristic and injection operation data. In addition, numerical simulation also time-consuming and quite complex to use. Proxy model is kind of machine learning. It’s able to predict performance of waterflooding quickly and easier to use. The result isn’t differ too much with numerical simulation method. Proxy model is an equation model that construct form quite many experiment data. This research is trying to predict performance of normal 5 spot waterflooding in reservoir with channeling deltaic sand sedimentation by using proxy model. The proxy model will be tested on a real field case. The results indicate that proxy model is able, faster, reliable and easy to use to predict waterflooding performance in such type of reservoir.
CO2 Storage Screening Criteria Based on Seal Capacity in Indonesia Syifa Destiana; Dedy Irawan; Prasandi Abdul Aziz; Ika Merdekawati
Scientific Contributions Oil and Gas Vol 48 No 4 (2025)
Publisher : Testing Center for Oil and Gas LEMIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29017/scog.v48i4.1829

Abstract

CO2 storage screening ensuring the long-term containment of injected CO2 and the integrity of carbon capture and storage. In Indonesia, robust seal evaluation is constrained by the limited availability of caprock core data. This study develops a dimensionless Caprock Quality Index (CQI) as a practical CO2 storage screening tool based on displacement pressure (Pd) and caprock thickness (h). Displacement pressure is estimated using an empirical Pd equation derived from existing caprock core data. The CQI provides a quantitative classification of seal quality within the 0-1 range, where values closer to 1 indicate better caprock quality. Based on the data availability of this study, the results show that the Banggai and Salawati basins currently exhibit the highest CQI, indicating strong suitability for CO₂ storage. This study provides a framework for conducting preliminary CO₂ storage screening, particularly valuable in settings where caprock core data are sparse and contributes to the development of a more efficient, data-driven framework for future CCS planning and implementation.