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All Journal JOURNAL OF EARTH ENERGY ENGINEERING Petro : Jurnal Ilmiah Teknik Perminyakan
Amega Yasutra
Institut TEknologi Bandung
Earth & Planetary Sciences Economics, Econometrics & Finance Energy Engineering Materials Science & Nanotechnology

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A Deliverability Method for Estimating Stabilized Gas Well Performance during Transient Periods on Unconventional Reservoir Amega Yasutra; Calvin Orliando
Journal of Earth Energy Engineering Vol. 10 No. 1 (2021)
Publisher : Universitas Islam Riau (UIR) Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jeee.2021.5620

Abstract

This study discusses the determination of the stabilized flow coefficient, C, in the Rawlins and Schellhardt equation. It is applicable in the reservoir with low porosity and permeability model, usually found in unconventional reservoirs. In determining the flow coefficient, a deliverability test method proposed by Hashem and Kazemi was used during the transient flow period of a gas well. Besides, in determining the deliverability exponent, n, used in the least squared analysis equation derived by Johnston and Lee in the determination of C stabilized so that from each value of n, there will be supporting data for determining stabilized flow coefficient. Finally, the application and previous method will determine the flow coefficient value based on reservoir model time stabilization. Later it compares with the John Lee equation and IPR constructs from the model and John Lee.
Predicting Stabilized Oil Well Inflow Performance Relationship on Unconventional Reservoir Amega Yasutra; Liviana Purwanto
Journal of Earth Energy Engineering Vol. 10 No. 2 (2021)
Publisher : Universitas Islam Riau (UIR) Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jeee.2021.5636

Abstract

Unconventional reservoirs are described as any reservoir that requires special recovery operations asides the conventional operating practices. However, low permeability affects the time it requires to attain stability. Presently, most of deliverability test is only carried out in a maximum 24-hour time. Limited test time makes it almost impossible to attain the reservoir stabilization time while carrying out the deliverability test. Meanwhile, to construct Inflow Performance Relationship (IPR) curve, the properties from stabilized time are required. This study aims to discuss how to predict the IPR curve by determining the stabilized flow coefficient value (C) on unconventional reservoir. Furthermore, the stabilized C was used to determine the Inflow Performance Relationship (IPR) for low porosity and permeability reservoir model, also known as Tight Oil Reservoir. The stabilized time and deliverability exponent value need to be determined before the stabilized C value. The stabilized time also know as pseudo-steady state time was evaluated from John Lee and Chaudry equation with validation from the reservoir model. The method proposed by Hashem and Kazemi, which employed the use of transient data in determining the flow coefficient value was also used. In addition, deliverability exponent (n) was determined using an equation proposed by Johnston and Lee. Furthermore, the backpressure equation from Rawlins and Schellhardt was used to construct the IPR curve.
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.
Maximum Allowable Annular Surface Pressure (MAASP) Standards Calculations Study; a Field Case Study Amega Yasutra; Ganesha R Darmawan; Muhammad Rafki
Journal of Earth Energy Engineering Vol. 12 No. 1 (2023)
Publisher : Universitas Islam Riau (UIR) Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jeee.2023.10047

Abstract

Well integrity failures may arise during the production phase of a well in a field. Those failures could create a Sustained Casing Pressure (SCP), a pressure that is measurable at the wellhead that can not be bled-off. SCP has to be addressed carefully to avoid any uncontrolled fluid flow to other formation or to surface. To maintain SCP value from degrading the other barrier integrity, the pressure threshold should be known and maintained for each annulus in a well. The maximum pressure threshold known as Maximum Allowable Annular Surface Pressure (MAASP). This case study will calculate MAASP from three wells in X field using three known method as outlined in API RP90-2 and ISO 16530-1. API RP 90-2 define two methods in calculation MAASP (known as MAASP – Maximum Allowavle Wellhead Operating Pressure), Simple Derating Method (SDM) and Explicit Derating Method (EDM). The result then compared and evaluted to know the differences, trend of MAASP for each methods, and create a generalization of MAASP/depth for field rule of thumb. For A annulus, the MAASP obtained using API RP90-2 SDM and EDM method is always greater than that obtained using the ISO 16530-1 method. However, for B annulus, the MAASP obtained using the API RP 90-2 SDM method varies, occasionally being greater or less than the ISO 16530-1 method. While in C annulus, the MAASP obtained using the API RP 90-2 SDM and EDM methods is always less than the ISO 16530-1 method. The MAASP/depth generalization will be presented for MAASP ISO 16530-1.
STUDY OF PERMEABILITY PREDICTION USING HYDRAULIC FLOW UNIT (HFU) AND MACHINE LEARNING METHOD IN “BSH” FIELD Babas Samudera Hafwandi; Dedy Irawan; Amega Yasutra
PETRO: Jurnal Ilmiah Teknik Perminyakan Vol. 12 No. 2 (2023): JUNI
Publisher : Jurusan Teknik Perminyakan Fakultas Teknologi Kebumian dan Energi Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/petro.v12i2.15763

Abstract

In this study, Decision Tree, Gradient Boosting, AdaBoost, Random Forest, Support Vector Machines, and K-Nearest Neighbor Machine Learning model are presented that use log and core data available as the basis for permeability prediction. The results were then compared to previously available method, namely Hydraulic Flow Unit (HFU) based on MAE and RMSE Value. The approach was taken by considering correlation relationships between existing log data in predicting permeability values. Three correlations, namely Spearman, Pearson, and Kendall, will be used to determine the relationship between existing log data and permeability. The machine learning model is then compared with the Hydraulic Flow Unit (HFU) Method in predicting the permeability value. The Novelty of this Machine Learning Model is to be able to predict permeability value, to solve the problem of accuracy using the existing method, and to save reasonable time to obtain permeability value by coring in the laboratory by utilizing standard computer available.
Co-Authors Abda Abda Babas Samudera Hafwandi Calvin Orliando Dedy Irawan Dedy Irawan Fahrizal Maulana Farrah Maurenza Frans Ondihon Sitompul Ganesha R Darmawan Hamzah, Kamal Iswara Lumban Tungkup Jalest Septiano Jon Felix Turnip Kamal Hamzah Liviana Purwanto Mochammad Wahdanadi Haidar Mohammed Sheikh Salem Al-Attas Muhammad Rafki Reza Wardhana Salem Al-Attas, Mohammed Sheikh Silvya Dewi Rahmawati Sri Dwi Mustaqim