Publications | Indonesian Petroleum Association

Machine Learning Approach in Identifying Wellbore Integrity Issue from Drilling Reports in Mahandini Field

Year: 2019 Authors: Wardana, R. S., Afriyanto, R., Nasution, D. S. Reference: IPA19-E-318

Keywords: casing, data management, drilling, machine learning, modelling,

Basins: Central Sumatra,

Proceedings Title : Proc. Indon. Petrol. Assoc., 43rd Ann. Conv., 2019

Activities during drilling and workover operations are reported regularly by field personnel in the Drilling Reports. Drilling reports contain a lot o...

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Fuzzy Logic and Digital Concept for Estimation of Oil and Gas Development

Year: 2019 Authors: Nugraha, C., Jamil, K., Lebang, Y. T. Reference: IPA19-F-2

Keywords: commercial, economics, machine learning, modelling, operations,

Basins:

Proceedings Title : Proc. Indon. Petrol. Assoc., 43rd Ann. Conv., 2019

Accurate cost estimating is required to improve decision making based on project economic evaluations. The process of cost estimation largely depends...

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Evaluation of Machine Learning Methods for Automatic Facies Classification As a Tool for Determining Sandstone and Limestone Reservoir tes

Year: 2019 Authors: Putra, I. R., Hibatullah, M. I., Salim, C., Syaifuddin, F. Reference: IPA19-SG-399

Keywords: machine learning, modelling, petrophysics,

Basins:

Proceedings Title : Proc. Indon. Petrol. Assoc., 43rd Ann. Conv., 2019

Facies classification using well log data is an important process in oil and gas exploration, which enables us to understand the reservoir character a...

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Machine Learning Technology to Improve Precision and Accelerate Screening Shallow Gas Potentials in Tunu Shallow Gas Zone, PT Pertamina Hulu Mahakam

Year: 2021 Authors: R. Herbet, D. Sugiharto, C. M. Adam, A. Satria, K. Ummah Reference: IPA21-G-220

Keywords: data management, gas, machine learning, seismic attributes,

Basins:

Proceedings Title : PROCEEDINGS, INDONESIAN PETROLEUM ASSOCIATION, Forty-Fifth Annual Convention & Exhibition, 1 - 3 September 2021

Tunu is a giant gas field located in the present-day Mahakam Delta, East Kalimantan, Indonesia. Tunu gas produced from Tunu Main Zone (TMZ), between 2...

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The Power of Predictive Analytics in Oil Field Development: Integrating Machine Learning with Reservoir Hydrocarbon Data to Enable Enhanced Oil Recovery of Hugin Formation within the Theta Vest Structure

Year: 2019 Authors: L. T. Hardanto, F. Chrisman Reference: IPA21-G-6

Keywords: LNG, data management, hydrocarbon, machine learning, modelling, reservoir,

Basins:

Proceedings Title : PROCEEDINGS, INDONESIAN PETROLEUM ASSOCIATION, Forty-Fifth Annual Convention & Exhibition, 1 - 3 September 2021

Machine learning is an algorithm based on pattern recognition and the concept that computers can learn without being programmed to perform specific ta...

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ISCA: Quick Real-Time Sand Potential Prediction Simulator based on Critical Drawdown Failure and Machine Learning Model

Year: 2021 Authors: A. I Biladi, M. E. A. Utama, J. A. Widagdo, V. Chandra, S. Chandra Reference: IPA21-SE-237

Keywords: machine learning, modelling, production, reservoir, sandstone,

Basins:

Proceedings Title : PROCEEDINGS, INDONESIAN PETROLEUM ASSOCIATION, Forty-Fifth Annual Convention & Exhibition, 1 - 3 September 2021

Sand production is almost an inevitable problem in oil and gas production facilities. As the reservoir depletes, sand grains from the reservoir begin...

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The Machine Learning's Classification Methods Comparison to Estimate Electrofacies Type, Lithology and Hydrocarbon Fluids from Geophysical Well Log Data

Year: 2021 Authors: D. A. Panggabean, J. H. Arief, L. K. Muhtar, M. N. Alamsyah Reference: IPA21-SG-196

Keywords: data management, machine learning, modelling, petrophysics,

Basins:

Proceedings Title : PROCEEDINGS, INDONESIAN PETROLEUM ASSOCIATION, Forty-Fifth Annual Convention & Exhibition, 1 - 3 September 2021

Supervised learning methods from machine learning are starting to be widely used in oil & gas data management. The usage of the method is adjusted...

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Reducing Uncertainties In Shear Wave Petrophysical Log Prediction By Using Deep Neural Network and Machine Learning Method

Year: 2021 Authors: M. F. Abdurrachman, M. D. Muhsin Reference: IPA21-SG-228

Keywords: machine learning, modelling, petrophysics,

Basins:

Proceedings Title : PROCEEDINGS, INDONESIAN PETROLEUM ASSOCIATION, Forty-Fifth Annual Convention & Exhibition, 1 - 3 September 2021

Shear-wave velocity (Vs) log is one of the essential petrophysical well logs for reservoir characterisation in oil and gas exploration. Unfortunately,...

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Virtual Rate Estimation Using Machine Learning for ESP Problems Identification

Year: 2022 Authors: Wibawa, R.A., Gunawan, Gibran, M.A., Purba, M.O., Ichsan, C. Reference: IPA22-E-17

Keywords: ESP, machine learning, modelling, oil, production,

Basins: Central Sumatra,

Proceedings Title : Proc. Indon. Petrol. Assoc., 46th Ann. Conv., 2022

Electric Submersible Pumps (ESP) have been widely used in Sumatera Light Oil (SLO) operation units with more than 2500 production wells. Approximately...

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Artificial Lift Real-Time Monitoring Digitalization Method: An Advanced Approach With Artificial Intelligence to Achieve Efficient Well Surveillance By Utilizing Scada.

Year: 2022 Authors: Putra, H.L.N., Tanjungsari, F., Edyawan, W.S., Hidayat, A., Sugiyanto Reference: IPA22-E-247

Keywords: data management, machine learning, operations, production,

Basins:

Proceedings Title : Proc. Indon. Petrol. Assoc., 46th Ann. Conv., 2022

In Block X, there are a limited number of engineers and a vast number of wells that require to be monitored on a daily basis. Before 2018, engineers m...

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Prediction Project Task Completion Using Supervised Machine Learning Method: A Conceptual Approach

Year: 2022 Authors: Yudhy, M.R.A., Wijayanto, A.P. Reference: IPA22-F-104

Keywords: data management, machine learning, management, operations,

Basins:

Proceedings Title : Proc. Indon. Petrol. Assoc., 46th Ann. Conv., 2022

Project schedule forecasting is a core enabler of successful project management. Accurate schedule prediction leads to better resource management and...

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Field Production Optimization in Constrained Water Temperature at Surface Facility Using Machine Learning and Genetic Algorithm

Year: 2022 Authors: Ramdhan, Rimbualam, H.G., Ichsan, C. Reference: IPA22-F-69

Keywords: environment, facilities, machine learning, management, regulatory,

Basins: Central Sumatra,

Proceedings Title : Proc. Indon. Petrol. Assoc., 46th Ann. Conv., 2022

Wastewater from all oil and gas industries in Indonesia must comply with the quality standard set by the environmental minister regulation Number 19 Y...

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Integration of Artificial Intelligence - Machine Learning for Basic Sediment and Water (BSW) Prediction in Steam Flood Heavy Oil Central Gathering Station

Year: 2022 Authors: Jati, P.P., Anggi NS, A., Pratahardia P,T. Reference: IPA22-F-93

Keywords: HC processing, facilities, heavy oil, machine learning, production,

Basins: Central Sumatra,

Proceedings Title :

The Delta field is mature and currently facing a significantly declining production rate since it was at peak production in 1992 with 290,000 barrels...

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Self-Consistent Approximation for Porosity Segmentation

Year: 2022 Authors: Joshi, R.M., Kumar, A., Singh, K.H. Reference: IPA22-G-121

Keywords: carbonate, machine learning, petrophysics, reservoir, sedimentology,

Basins:

Proceedings Title : Proc. Indon. Petrol. Assoc., 46th Ann. Conv., 2022

Carbonate reservoirs have been known to be a major source of hydrocarbons; it is well known that approximately 60% of the oil and 40% of the gas reser...

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Enhancing Karstified Carbonate Characterization Through Focused Seismic Reprocessing and Machine Learning Utilization in Ubadari Field

Year: 2022 Authors: Sahidu, M.R.H., Panggeleng, I., Putri, S., Miller, S., Li, X. Reference: IPA22-G-154

Keywords: carbonate, field development, machine learning, seismic attributes, seismic interpretation, seismic processing,

Basins: Bintuni,

Proceedings Title : Proc. Indon. Petrol. Assoc., 46th Ann. Conv., 2022

Ubadari is an undeveloped gas field in Bintuni Bay (West Papua, Indonesia) about 70km west of the Tangguh LNG plant. Seismic reprocessing (2015 and 20...

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De-Risking Subsurface Uncertainties in Static Model Workflow for Ngimbang Carbonate Build-Up in Recently Discovered Field Located in North Madura II Block, Indonesia

Year: 2022 Authors: Ibrahim, A.M.B., Ernando, Z., Pradhana, V., Khalid, Z.A.B., Muhammad, F. Reference: IPA22-G-248

Keywords: carbonate, machine learning, modelling, reserves, reservoir,

Basins: East Java,

Proceedings Title : Proc. Indon. Petrol. Assoc., 46th Ann. Conv., 2022

EJ-7 field is a green field located about 65 km NE of Surabaya in the offshore Northeast Java Basin in water depth of about 25m. EJ-7 was drilled and...

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Leveraging Unsupervised Machine Learning on Seismic Images of Miocene Deposits in the Carpathian Foredeep Basin for Facies Classification

Year: 2022 Authors: Wiratama, R., Harahap, F. E., Fashgaba, I., Chichostepski, K. Reference: IPA22-G-269

Keywords: machine learning, modelling, seismic interpretation,

Basins:

Proceedings Title : Proc. Indon. Petrol. Assoc., 46th Ann. Conv., 2022

The application of machine learning (ML) in seismic interpretation has become widely shared in geosciences, and this is due to its ability to be accur...

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Seismic Avo Attributes and Machine Learning Technique to Characterize A Distributed Carbonate Build Up Deposit System in Salawati Basin Eastern Indonesia

Year: 2022 Authors: Effendi, Y., Utoro, E.S., Lestari, S., Hardanto, L.T. Reference: IPA22-G-275

Keywords: carbonate, machine learning, modelling, reservoir, seismic attributes,

Basins: Salawati,

Proceedings Title : Proc. Indon. Petrol. Assoc., 46th Ann. Conv., 2022

PT. RH Petrogas is the operator for acreage in the Salawati Basin in Eastern Indonesia and is interested in exploring this area further, particularly...

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Machine Learning and Deep Learning for Digitizing Scanned Images of Seismic Reflection Data

Year: 2022 Authors: Abdullah, A., Sukmono, S., Constantino, J., Machado, V. Reference: IPA22-G-99

Keywords: data management, machine learning, seismic attributes, seismic interpretation,

Basins:

Proceedings Title : Proc. Indon. Petrol. Assoc., 46th Ann. Conv., 2022

We present the use of Machine Learning algorithm of K-Nearest Neighbors (KNN) and Deep Learning algorithm of Artificial Neural Network for converting...

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Automated reservoir and production surveillance: A digital solution for hydrocarbon field optimization

Year: 2023 Authors: Adil, A., Silva, J., Sankaran, S. Reference: IPA23-E-30

Keywords: data management, machine learning, modelling, production,

Basins:

Proceedings Title : Proc. Indon. Petrol. Assoc., 47th Ann. Conv., 2023

One of the key focus areas of oilfield digitalization efforts is the design and development of integrated production optimization workflows. The goal...

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The Hybrid Theory-Guided Data Science-Based Method: Unlocking The Full Potential Of Seismic Reservoirs characterization

Year: 2023 Authors: Saputra, R., Mathur, A., Mandong, A. Reference: IPA23-G-88

Keywords: data management, machine learning, modelling,

Basins:

Proceedings Title : Proc. Indon. Petrol. Assoc., 47th Ann. Conv., 2023

Machine learning has been used for many decades, particularly for deep neural networks that were introduced in the 1960s and have been applied to vari...

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Preliminary Prioritization on Steam Flood Injection in "Kasai" Heavy Oil Field Using Random Forest Regression Method

Year: 2023 Authors: Rafi, M., Faiz, M., Destya, A. Reference: IPA23-SE-24

Keywords: EOR, heavy oil, machine learning, modelling,

Basins: South Sumatra,

Proceedings Title : Proc. Indon. Petrol. Assoc., 47th Ann. Conv., 2023

Steam flood injection is a thermal recovery method that involves injecting steam, or specific water at particular temperatures, through special inject...

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Sweet Infill Well Locations Prediction Using Multiple Supervised and Unsupervised Machine Learning Models

Year: 2023 Authors: Septifiandi, M.N., Rahman, F., Muhammad Husni Mubarak Lubis, M.H.M. Reference: IPA23-SE-84

Keywords: machine learning, modelling, petrophysics, production, reservoir,

Basins:

Proceedings Title : Proc. Indon. Petrol. Assoc., 47th Ann. Conv., 2023

Machine learning has been widely used in oil and gas industry for exploration and production. This method efficiently increases productivity, reduces...

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Illuminating the Dual Casing Exit Operation’s “Blind Spot” With a Supervised Machine Learning Model to Improve the Milling Roadmap in Offshore Mahakam

Year: 2024 Authors: Karsten, C., Herdiansyah R., Kartaatmadja, H., Wibisono, L., Hendarno, B., W. Reference: IPA24-E-173

Keywords: AI, drilling, machine learning, milling, optimization,

Basins: Kutei,

Proceedings Title : Proc. Indon. Petrol. Assoc., 48th Ann. Conv., 2024

As one of the mature fields in Indonesia, Offshore Mahakam’s executives are always exploring for new ideas to be developed which could optimize...

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Unlocking Efficiency in Gas Lift System Operation: A Data Driven Approach for Early Problem Identification Using Machine Learning and Digitalized Two-Pen Recorder Chart

Year: 2024 Authors: Mustaqim, S., D., Yasutra, A. Reference: IPA24-E-314

Keywords: Random Forest, accuracy, continuous gas lift, gas lift wells, machine learning,

Basins:

Proceedings Title : Proc. Indon. Petrol. Assoc., 48th Ann. Conv., 2024

Conventional monitoring and identification of problems in continuous gas lift wells are time-consuming, involving data collection and analysis activit...

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Reducing Operational Cost for Online Scada Well Surveillance Coverage Expansion by Implementing Scada Radio Branching Combined with Machine Learning Approach at Rokan Oil Field

Year: 2024 Authors: Gustiadi, R., Gibran M., A., Prayogi, B., Putra, K., M., E., Rigellindi, R. Reference: IPA24-E-370

Keywords: SCADA, cost, machine learning, oil, surveillance,

Basins: Central Sumatra,

Proceedings Title : Proc. Indon. Petrol. Assoc., 48th Ann. Conv., 2024

At present in the Rokan Oil Field there are 2800 Sumatera Light Oil (SLO) producer wells within a 6200 sq.km area. Of these wells, 1500 (54%) are not...

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Application of Machine Learning to Predict Cementation Factor Along Well Intervals and Its Implications for Sand Problem, Study Case: Wanda Complex Field, Indonesia

Year: 2024 Authors: Wicaksono, A., Alfigo Tryozi S. Z., A.Bhaskara Aji, B., Ginting P., L., G., Yondo, A. Reference: IPA24-E-91

Keywords: cementation factor, electrical log data, machine learning, reservoir pressure, sand problems,

Basins: West Java,

Proceedings Title : Proc. Indon. Petrol. Assoc., 48th Ann. Conv., 2024

The Wanda Complex field was first developed in 1971 and produces from the sandstone reservoir of Talangakar Formation. Over time, oil production in th...

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Utilizing Machine Learning for Enhanced Energy Efficiency and Emission Reduction in Air-Cooled Exchangers through Heat Duty Monitoring and Fin Fan Motor Control Optimization in the North Belut Facility

Year: 2024 Authors: Cahyono, Y., Tanjungsari, F. Reference: IPA24-F-56

Keywords: EPMS, air-cooled exchanger fans, cost efficiency, emissions, machine learning,

Basins: West Natuna,

Proceedings Title : Proc. Indon. Petrol. Assoc., 48th Ann. Conv., 2024

As global energy demand continues to rise, alongside challenges such as declining gas production and environmental concerns, optimizing efficiency, an...

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An Innovative Machine Learning-Based Workflow for Leveraging The Success Ratio of Reservoir Fluid Identification Using Gas while Drilling Data in Mutiara Field, Kutai Basin

Year: 2024 Authors: Ardhana, R., Nur, P., Battu, D., P., Said, D., K., Pasaribu, H., H. Reference: IPA24-G-120

Keywords: Gas While Drilling (GWD), fluid identification accuracy, machine learning, reservoir fluid identification, success ratio,

Basins: Kutei,

Proceedings Title : Proc. Indon. Petrol. Assoc., 48th Ann. Conv., 2024

The acquisition of Gas While Drilling (GWD) data for the needs of geological surveillance and safety operation during drilling is a common practice in...

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Machine Learning Prediction for Fluid Identification in Kujung Formation East Java

Year: 2024 Authors: Bryan, F., C., Putri, V., I., Nengkoda, A., Sommeng, A., N., Kartohardjono, S. Reference: IPA24-G-193

Keywords: Kujung Formation, NMR logging, carbonate rocks, fluid interpretation, machine learning,

Basins: East Java,

Proceedings Title : Proc. Indon. Petrol. Assoc., 48th Ann. Conv., 2024

Kujung Formation in the East Java Basin has a lithology of carbonate rocks with three reservoirs which are dominated by secondary porosity. Kujung 1 r...

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Machine-Learning Augmentation for 3D Seismic Fault Interpretation to Resolve Complex Strike-Slip Indenter Tectonics Structural Style: Impact to Field Development and Exploration in Banggai-Sula Basin

Year: 2024 Authors: Suwarlan, W., Laya, K., P., Naufaldi, F., Khawarizmy, A., Waryono, I. Reference: IPA24-G-312

Keywords: 3D seismic, Banggai-Sula Basin, fault detection, machine learning, structural interpretation,

Basins:

Proceedings Title : Proc. Indon. Petrol. Assoc., 48th Ann. Conv., 2024

The continuous improvement and implementation of machine-learning technology have transformed the way structural interpretation conducted in 3D seismi...

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Extending Engine Change Out Respective to Running Hours Using Data Driven Using One Dimension (1-D) Convolutional Neural Network Algorithm

Year: 2024 Authors: Malik, S., Soedarsono, H., P. Reference: IPA24-SS-05

Keywords: GE Turbine LM2500+, Gas Generator Exhaust Temperature, engine change out, machine learning, preventive maintenance,

Basins:

Proceedings Title : Proc. Indon. Petrol. Assoc., 48th Ann. Conv., 2024

The current practice for engine change out of GE Turbine LM2500+ SAC, set at 25,000 for Hot Section Inspection, as per Instruction Operation and Maint...

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