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Keywords: machine learning
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Proceedings Papers
Advancements in Incident Investigations in the Oil & Gas Industry - Moving Beyond Conventional Methodologies
Available to PurchasePublisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221951-MS
... safety knowledge management adnoc international petroleum exhibition & conference human factor incident investigation oil and ga industry tree analysis incident investigation process machine learning investigation process incident investigation methodology abu dhabi international...
Proceedings Papers
Reservoir Pressure Prediction Using Combined AI and Material Balance Approach
Available to PurchasePublisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221813-MS
... timesteps, not perfect match at well level, etc. The objective of this study is to develop a combined AI and physics driven method for fast and robust procedure to estimate reservoir pressure in space and time, based on a hybrid approach using production injection data, machine learning and material...
Proceedings Papers
Optimizing Reservoir Management Through Strategic Data Acquisition and Machine Learning-Enhanced Water Saturation Surveys
Available to PurchasePublisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221814-MS
... needs and conditions. These include production data, well logs, and seismic data, among others. This data is utilized to construct a resilient proxy model utilizing machine learning algorithms, leading to precise predictions of field water production. Moreover, these runs are completed in a matter...
Proceedings Papers
Quantifying Inter-Well Connectivity and Sweet-Spot Identification through Wavelet Analysis and Machine Learning Techniques
Available to PurchaseRamanzani Kalule, Javad Iskandarov, Emad Walid Al-Shalabi, Hamid Ait Abderrahmane, Strahinja Markovic, Ravan Farmanov, Omar Al-Farisi, Muhammad A. Gibrata, Magdi Eldali, Jose Lozano, QingFeng Huang, Lamia Rouis, Giamal Ameish, Aldrin Rondon
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221817-MS
... that can be efficiently extracted ( Tahmasebi et al ., 2017 ). Abstract This study leverages wavelet analysis and machine learning (ML) techniques, including a 1D Convolutional Neural Network (1D CNN), to analyze inter-well connectivity and pinpoint an optimal new drilling location (sweet spot...
Proceedings Papers
A Novel Data-Driven Approach for Capacitance Resistance Models in Multi-Phase Flow Systems
Available to PurchasePublisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221825-MS
... and, with the integration of machine learning algorithms, have been extended to applications in gas, gas-alternating-water injection, and other enhanced oil recovery mechanisms. In this paper, we introduce a novel data-driven formulation that reduces the number of optimization parameters by 50% compared to traditional CRM...
Proceedings Papers
Maximizing Efficiency in Giant Gas Fields Harnessing Virtual Flow Meters to Optimize Testing Frequency and Enhance the Data Reliability
Available to PurchaseAyesha Alsaeedi, Nagaraju Reddicharla, Mohamed Albadi, Mohamed Alzeyoudi, Maryam Alhammadi, Zainah Al Agbari, Prabhaker Reddy Vanam, Khawla Alnaqbi, Sarath Konkati, Salah Al-Ghailani
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221843-MS
... analytics. Unlike physical flow meters, VFMs do not require direct measurement of fluid flow. Instead, they rely on a combination of real-time sensor data, production test results, and machine learning algorithms to estimate daily production rates of gas, condensate, and water. This approach offers a range...
Proceedings Papers
The Used of an Intelligent Data Assimilation Protocol for Plume Characterization of CO2 Sequestration in Saline Aquifers
Available to PurchasePublisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221849-MS
... subsurface storage machine learning deep learning artificial intelligence expert system pressure data inverse problem injection well evolution saline aquifer neural network model spatial distribution forward-looking model plume gas plume inverse model workflow permeability permeability...
Proceedings Papers
A Multi Modal Geologist Copilot GeoCopilot: Generative AI with Reality Augmented Generation for Automated and Explained Lithology Interpretation While Drilling
Available to PurchaseM. V. G. Jacinto, L. H. L. de Oliveira, T. C. Rodrigues, G. C. de Medeiros, D. R. Medeiros, M. A. Silva, L. C. de Montalvão, M. Gonzalez, R. V. de Almeida
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221864-MS
.... Recent advancements in Machine Learning (ML) and Artificial Intelligence (AI) have shown promise in enhancing data reliability and real-time lithology prediction. The early explorations by Rogers et al. (1992) , Benaouda et al. (1999) , and Wang and Zhang (2008) laid the groundwork, utilizing well...
Proceedings Papers
Credentials for Tomorrow: Micro Neuro Mesh-Based Curriculum Innovations in Petroleum Engineering
Available to PurchasePublisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221877-MS
... Driving the Need for Change Several tailwinds are propelling the necessity for a micro-credentials-based curriculum in petroleum engineering: Technological Advancements: Rapid advancements in technology, including artificial intelligence, machine learning, and automation, are revolutionizing...
Proceedings Papers
An Investigation of the Influence of Liquid Nitrogen on Tight Sands Through Micro-CT Scan Imaging
Available to PurchasePublisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221886-MS
.... , V. Kaynig , C. Rueden , K.W. Eliceiri , J. Schindelin , A. Cardona & H. Sebastian Seung ( 2017 ) Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification . Bioinformatics , 33 , 2424 – 2426 . Davies , R. , G. Foulger...
Proceedings Papers
Machine Learning Accelerates and Facilitates the Prediction of Stuck Pipe Events
Available to PurchasePublisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-222438-MS
... , Arévalo et al. 2022 ), among others, have prepared the ground for a more accurate detection of downhole hazards, such as conditions leading to stuck pipe. This paper presents the utilization of machine learning (ML) to analyze surface data, detect stuck pipe events and classify such events into categories...
Proceedings Papers
Novel Petrophysical Characterization of Complex Microporous Carbonates in the UAE: A Comprehensive Case Study
Available to PurchasePublisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-222450-MS
... petrophysical evaluation result lattice evaluation result machine learning microporous rock type micp data reservoir property water saturation Introduction Microporous carbonates represent a vast part of Thamama group reservoirs. The subjects of study are two Thamama group reservoirs which...
Proceedings Papers
Enhancing Reservoir Model Agility: Integrating New Drilling and Performance Data into Business Planning - A Case Study
Available to PurchasePublisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-222467-MS
... Key Components Integration of Subsurface Workflows The agile workflow integrates various subsurface workflows, enabling the generation of multiple geological realizations and reservoir simulations. This integration is powered by high-performance computing and machine learning solutions, which...
Proceedings Papers
Intelligent ESPs Diagnostic Model Based on Big Data and Machine Learning
Available to PurchasePublisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-222485-MS
... Abstract There are various types of available data, with different data structures, dimensions, and intervals. Conventional big data algorithms can lead to poor interpretability. In this study, novel methods are proposed based on big data analysis and machine learning. First, the data...
Proceedings Papers
Navigating the Future of Maritime Operations: The AI Compass for Ship Management
Available to PurchaseJ. Joshva, S. Diaz, S. Kumar, A. Suboyin, N. AlHammadi, O. Baobaid, F. Villasuso, M. Konig, A. Binamro, L. Saputelli
Publisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-222508-MS
... to revolutionize the efficiency, safety, and sustainability of maritime operations, presenting transformative insights for the industry's advancement. machine learning artificial intelligence efficiency maritime operation maritime industry operation safety value chain maintenance sustainability...
Proceedings Papers
Placement Quality Index to Enhance Proppant Placement—Part I: The Machine-Learning Model
Available to PurchasePublisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-222306-MS
... also lead to insufficient injection rate, post-breakdown, to place proppant. A machine-learning (ML) model based on in-depth multidomain analysis can assist in such cases in the design and execution phase. Part I of the paper here covers the extensive ML modeling. The following Part II will cover...
Proceedings Papers
Integrating Neural Operators and Transfer Learning for Efficient Carbon Storage Forecasting
Available to PurchasePublisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-222406-MS
... operator and transfer learning fno model machine learning neural operator transfer learning computational cost dataset fourier neural operator saturation prediction operational condition INTRODUCTION The growing concern over climate change has led to an increased focus on strategies...
Proceedings Papers
Empowering Drilling and Optimization with Generative AI
Available to PurchasePublisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221862-MS
... critical issues, and capture knowledge for future wells, all while overcoming the challenges of accessing and interpreting large SQL databases. deep learning large language model natural language machine learning artificial intelligence sql query engineer empowering drilling and optimization...
Proceedings Papers
Generative AI and Large Language Model Assisted Causal Discovery and Inference for Driving Process Improvements
Available to PurchasePublisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221872-MS
... graph with the help from a LLM by augmenting its capabilities using contextual information. Retrieval Augmented Generation Based LLM prompting for Causal Graph Data-driven process management coupled with machine learning have been successful in driving commercial value to oil and gas operators...
Proceedings Papers
Domain Driven Methodology Adopting Generative AI Application in Oil and Gas Drilling Sector
Available to PurchasePublisher: Society of Petroleum Engineers (SPE)
Paper presented at the ADIPEC, November 4–7, 2024
Paper Number: SPE-221883-MS
... operation machine learning natural language decision-making abu dhabi international petroleum exhibition engineer international petroleum exhibition & conference drilling database application drilling report dataset query generative ai Introduction Drilling industry in oil and gas...
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