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Keywords: machine learning
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Proceedings Papers
Enhance the Vertical Resolution of Conventional Well Logs Using Auto-Encoder
Available to Purchase
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-25025-EA
... , A. , 2019 . Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems . 2nd Edition, O'Reilly Media, Inc. , Sebastopol. Goodfellow , I. , Bengio , Y. , Courville , A. , 2016 . Deep learning . Li , H...
Proceedings Papers
A Novel Quantitative Statistical Methodology For Identifying Operational Effects On Gas Breakthrough In Horizontal Wells
Available to PurchaseLiang Sun, Rubing Han, Lihui Xiong, Jian Yang, Hang Zhao, Yuankeli Lou, Shuzhe Shi, Wei Du, Yuwei Jiao
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-25031-MS
... control and optimum gas injection strategies. geologist artificial intelligence gor geology machine learning gas injection method main control factor gas breakthrough enhanced recovery dependent variable producer variation trend different stage bhfp gas injection strategy bhip...
Proceedings Papers
Navigating an E&P Operator’s Journey to Cloud-Planning, Execution, Challenges and Impact
Available to Purchase
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-25046-MS
... In addition to processing power, cloud-based analytics enables companies to run complex simulations, interpret seismic data, and make more informed decisions in exploration and production (E&P). With the integration of machine learning algorithms, cloud platforms allow for deploying advanced...
Proceedings Papers
Multiplex Visibility Graphs-Based Hybrid Deep Learning Method for Recognizing Pipeline Operation Conditions Using Operating Data
Available to Purchase
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-25065-MS
... is a reasonable way to improve recognition accuracy. neural network machine learning deep learning artificial intelligence multivariate time sery accuracy multiplex visibility graph pipeline system operation condition information visibility graph liquified natural gas (lng) time sery attention...
Proceedings Papers
3D Geomechanical Modeling and Application of Upper Clastic Rock Formation in Penglai Gas Field, China
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Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24834-MS
... zone well logging machine learning upper clastic rock layer poisson strata rock mechanic parameter transit time horizontal geostress strength clastic rock section mpa experiment time difference Introduction Geomechanical parameters typically encompass rock mechanical properties...
Proceedings Papers
Combining Variation Diffusion Model and Multi-Source Experimental Data to Establish Digital Cores for Reservoir Exploration and Development
Available to Purchase
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24845-MS
... characteristic fluid dynamics deep learning machine learning permeability experimental data simulation digital core model porosity china chengdu north petroleum exploration application information development technology co Introduction In the exploration and development of oil and gas fields...
Proceedings Papers
Physics-Informed Machine Learning for Hydraulic Fracturing—Part III: The Transfer Learning Validation
Available to Purchase
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24850-MS
.... The tradeoff between data and physics in different models, as shown in Fig. 1 , demonstrates that leveraging physics-based models can strike a balance between speed and accuracy. Physics-informed machine learning (PIML) techniques and physics-informed neural networks (PINNs) enable the model to function...
Proceedings Papers
Fine Geological Modeling of Fractured Reservoir in Dual-Medium Buried Hill Based on BP Neural Network and Horizontal Well Parameter Correction
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Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24858-MS
... hill in the later stage. fracture characterization neural network hydraulic fracturing reservoir characterization geology complex reservoir artificial intelligence machine learning geologist directional drilling rock type log analysis sedimentary rock drilling operation horizontal...
Proceedings Papers
Customized Approach to History Matching of Mature Offshore Field under EOR Implementation – Case Study from Malaysia
Available to PurchaseM. Raghunathan, P. Shankar, A. N. Abu Bakar, L. Foo, S. Ayub, S. Ismail, K. Salleh, N. A. Zulkifli, A. I. Abu Bakar, M. B. Mohd Mabror
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24861-MS
... production data optimization problem history machine learning permeability presented multiplier structural geology flow in porous media reservoir characterization application mismatch drive mechanism Introduction Reservoir models are key deliverables in sub-surface studies to assist key...
Proceedings Papers
A Novel Approach for the Prediction of Real-Time Rate of Penetration in Drilling for Petroleum by Combining the Attention-Based Bidirectional-Long Short-Term Memory and Long Short-Term Memory
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Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24898-MS
... & disposal prediction relative error optimization drilling data artificial intelligence att-bilstm-lstm model bit selection penetration rop drilling rate eng machine learning bingham model short-term memory modified bourgoyne&young bidirectional-long short-term memory error comparison...
Proceedings Papers
Embracing Greenfield Uncertainties Through Tailored-Made Assisted History Matching Approach
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Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24687-MS
... pressure data gas lift artificial intelligence modeling & simulation objective function mismatch function presented uncertain parameter embracing greenfield uncertainty production data machine learning variant case international petroleum technology conference static model Introduction...
Proceedings Papers
Complex Risk Assessment of Offset Wells Using Cognitive Analysis
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Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24705-MS
... drilling drilling fluids and materials risk management natural language cognitive system drilling operation volve field expert system drilling fluid management & disposal sequence npt risk and uncertainty assessment artificial intelligence wellbore design text processing machine learning...
Proceedings Papers
Revolutionising Pad Trajectory Design: An Innovative Algorithm for Enhanced Design Efficiency and Quality
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Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24720-MS
... operation while maximizing the return of investment. trajectory design optimization problem well planning artificial intelligence joint point machine learning evolutionary algorithm surface location pad design collision risk drilling operation trajectory constraint severity...
Proceedings Papers
Managing Liquid Loading Using A Physics Inspired Data-Driven Method
Available to PurchasePrithvi Singh Chauhan, Zhuoran Li, Wenyue Sun, Utkarsh Sinha, Meher Surendra, Varad Sabharwal, Sathish Sankaran
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24769-MS
... loading. Finally, for the liquid loaded wells on well cycling operation (intermittent production), a machine learning model is developed to optimize cycling parameters based on features extracted from a sequence of past cycles. The trained models predict the optimum shut-in and production time to maximize...
Proceedings Papers
Application of Self-Supervised Autonomous Agent Framework With Growing Scheme for Digital Transformation of Elder/Existed Well Potentials Discovery
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Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24776-MS
... in detailed existed-well assessment tasks. agent geology geologist rock type artificial intelligence arxiv natural language application accuracy mechanism large language model manuscript deep learning machine learning interpretation agent framework curve reconstruction specific task...
Proceedings Papers
Trapped and Movable CO 2 in Geologic Carbon Storage: Deep-Learning Forecasting and Generalization Study
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Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24804-MS
... deep learning neural network geology co 2 artificial intelligence machine learning climate change scenario saline aquifer modeling & simulation chemical flooding methods inference dataset geologist subsurface storage enhanced recovery dataset solubility residually accuracy...
Proceedings Papers
A New Depth Prediction Technique Based on Particle Swarm Optimization Algorithm with Multiple Main Controlling Factors Constraints
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Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24820-MS
... and more stable error fluctuation range. deep learning geology neural network reservoir characterization artificial intelligence prediction machine learning algorithm prediction accuracy depth prediction pso-bp prediction result geologist optimization problem evolutionary algorithm...
Proceedings Papers
A Novel Approach to Enriching Well Master Data, Leveraging a Composable Modular Services Architecture Underpinned by AI/ML and the OSDU Data Platform
Available to PurchaseLee Hin Wong, Normanisah Bt Mat Ghani, Anis Shahida Shahibullah, Sugiarto Hartono, Lyu Ping, M. Maxime, P. Prashanth
Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24905-MS
... underpinned by Artificial Intelligence (AI) / Machine Learning (ML) and the OSDU Data Platform. The approach was conceived with the goal of improving Well Master Data quality and its objective, problem statement, solution architecture, challenges and impact on sustaining Upstream data quality are outlined...
Proceedings Papers
Leveraging Artificial Intelligence to Revolutionize Rigless ESP Planning and Intervention Optimization
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Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24946-MS
... analytical formulas and machine learning algorithms to analyze well data and recommend the optimal Rigless ESP system. Engineers input key downhole parameters and production forecasts into the software, which then rigorously analyzes the data to provide precise, evidence-based recommendations. The Advisor's...
Proceedings Papers
Compositional Modeling of Associated Gas Injection in Ultra-Low Permeability Reservoirs: Multi-Effects of Gas Components on Reservoir In-situ Hydrocarbon
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Paper presented at the International Petroleum Technology Conference, February 18–20, 2025
Paper Number: IPTC-24995-MS
... to determine hydrocarbon phase behavior during gas recycling. Finally, fluid properties and oil-gas interaction affected by gaseous components were calculated and predicted via phase equilibrium calculation and machine learning algorithm. The crude oil data was obtained from real reservoir. Experiment data...
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