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1-20 of 49
Keywords: Artificial Intelligence
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Proceedings Papers
Improved Data-Driven Method for the Prediction of Elastic Properties in Unconventional Shales from SEM Images
Available to Purchase
Paper presented at the SPWLA 29th Formation Evaluation Symposium of Japan, September 12–13, 2024
Paper Number: SPWLA-JFES-2024-N
... symposium grayscale intensity geological subdiscipline intensity 0 spatial arrangement mineralogy texture prediction rock type mudstone arrangement textural loocv glcm matrix deep learning artificial intelligence reservoir characterization classification pixel young information japan...
Proceedings Papers
Learnings from 10 Years of Applications of a Probabilistic Approach to Subsurface Modelling - Impact of Ensemble Modelling in Digital Transformation
Available to Purchase
Paper presented at the SPWLA 29th Formation Evaluation Symposium of Japan, September 12–13, 2024
Paper Number: SPWLA-JFES-2024-B
... realization subsurface modelling artificial intelligence application workflow probabilistic approach japan reservoir characterization formation evaluation symposium scenario digital transformation risk management climate change simulator algorithm ensemble modelling co 2 Abstract Oil...
Proceedings Papers
Application of Bagging Ensemble Machine Learning Models to Predict Porosity of Sandstone Formations Using Well Log Data
Available to Purchase
Paper presented at the SPWLA 29th Formation Evaluation Symposium of Japan, September 12–13, 2024
Paper Number: SPWLA-JFES-2024-A
... Formation Evaluation Society (JFES) and the submitting authors. This paper was prepared for the JFES 29th Annual Symposium held from September 12-13, 2024. ABSTRACT Machine learning (ML) which is a subset of artificial intelligence is being used in the field of upstream oil and gas industry to enhance its...
Proceedings Papers
2-Dimensional Upscaling Using Deep Learning
Available to Purchase
Paper presented at the SPWLA 29th Formation Evaluation Symposium of Japan, September 12–13, 2024
Paper Number: SPWLA-JFES-2024-G
.... To overcome these deficiencies, this study focused on applying deep learning, a powerful tool in the field of Artificial Intelligence (AI), to upscaling of both the singlephase property(absolute permeability) and the multi-phase property (relative permeability). First, a large dataset was generated...
Proceedings Papers
Machine Learning-Based Classification for Mapping CO 2 Presence using Seismic Data
Available to PurchaseM Farid B M Amin, Satyabrata Nayak Parsuram, Debjyoti Das, Modekhai Mordekhai, Taufan Rusady, Samiran Roy, Kian Wei Tan
Paper presented at the SPWLA 29th Formation Evaluation Symposium of Japan, September 12–13, 2024
Paper Number: SPWLA-JFES-2024-F
... of Mines. He has worked in different job responsibilities during his professional journey in Halliburton. His primary areas of interest are data analytics, velocity modeling, pre-stack seismic analysis, artificial intelligence and machine learning in G&G aspects. He has conducted numerous training...
Proceedings Papers
Application of Machine Learning in Downhole CO2 Measurement Using Formation Tester
Available to Purchase
Paper presented at the SPWLA 29th Formation Evaluation Symposium of Japan, September 12–13, 2024
Paper Number: SPWLA-JFES-2024-C
... for downhole fluid identification sensor design, formation pressure test and sampling modeling, and automation of wireline formation testers using artificial intelligence and machine learning techniques. Dai received a PhD degree in analytical chemistry, with a specialization in chemometrics and NIR...
Proceedings Papers
RPM-Based Petrophysical Characterization of a Depleted Gas Reservoir Using the Adaptive Stiff Sand Model (ASSM) for Possible CCUS Applications
Available to Purchase
Paper presented at the SPWLA 29th Formation Evaluation Symposium of Japan, September 12–13, 2024
Paper Number: SPWLA-JFES-2024-E
... rock rock type well logging geological subdiscipline sandstone reservoir characterization permeability seismic inversion petrophysical characterization rpm-based petrophysical characterization flow in porous media log analysis physic template porosity moduli construction artificial...
Proceedings Papers
Expanding the Use of Nuclear Magnetic Resonance (NMR) and Machine Learning for Reservoir Characterization of an Offshore Gas Field – Rock Typing and Capillary Pressure Profiling
Available to Purchase
Paper presented at the SPWLA 29th Formation Evaluation Symposium of Japan, September 12–13, 2024
Paper Number: SPWLA-JFES-2024-J
... well logging rock type machine learning log analysis saturation type nuclear magnetic resonance artificial intelligence reservoir characterization permeability fluid dynamics flow in porous media core analysis formation evaluation symposium hfu-fzi rock type gas field substitution nmr...
Proceedings Papers
Fluid Characterization in Tight Carbonate Reservoirs Assisted by Novel Non-Electrical Logging Techniques: Case Studies of Central Sichuan Basin, China
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Paper presented at the SPWLA 28th Formation Evaluation Symposium of Japan, September 13–14, 2023
Paper Number: SPWLA-JFES-2023-E
.... reservoir upstream oil & gas geologist complex reservoir artificial intelligence mineral machine learning well logging carbonate reservoir asia government china government reservoir characterization sedimentary rock geology water saturation fluid identification chlorine concentration...
Proceedings Papers
A Machine Learning-Based Workflow for Integration of Wireline, LWD, and Core Data
Available to Purchase
Paper presented at the SPWLA 28th Formation Evaluation Symposium of Japan, September 13–14, 2023
Paper Number: SPWLA-JFES-2023-U
.... CONCLUSIONS Artificial intelligence and machine learning are emerging as powerful tools to aid in reservoir analysis and characterization. This paper has presented the application of CbML for normalizing data in a field study based on core data available in key wells. Quality assurance and QC indicated...
Proceedings Papers
Application of New Technology on Effective Secondary Pore and Fracture Evaluation in Sinian Dengying Dolomite Formation, Sichuan Basin
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Paper presented at the SPWLA 28th Formation Evaluation Symposium of Japan, September 13–14, 2023
Paper Number: SPWLA-JFES-2023-F
... geologist reservoir asia government artificial intelligence rock type reservoir characterization calibration effectiveness dolomite evaluation sedimentary rock structural geology china government machine learning vug resistivity reservoir effectiveness fracture core calibration...
Proceedings Papers
Artificial Intelligent (AI) Assisted Formation Evaluation and Reservoir Monitoring in a CO 2 Producing Field: Case Studies From Offshore Peninsular Malaysia
Available to Purchase
Paper presented at the SPWLA 28th Formation Evaluation Symposium of Japan, September 13–14, 2023
Paper Number: SPWLA-JFES-2023-T
... will discuss few case studies utilizing artificial intelligence (AI) and machine learning (ML) workflow in petrophysical evaluation based on the existing legacy data set and the newly acquired cased hole pulse neutron spectroscopy data. Some best practices in data training, model prediction and validation...
Proceedings Papers
Leveraging the Computing Power To Extract the Full Value from Old Core Resistivity Measurement Data for Shaly Sand Log Analysis
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Paper presented at the SPWLA 28th Formation Evaluation Symposium of Japan, September 13–14, 2023
Paper Number: SPWLA-JFES-2023-S
.... upstream oil & gas solver core analysis geology artificial intelligence machine learning japan government mineral log analysis 28th formation evaluation symposium numerical solver multi-salinity analysis synthetic data equation ffri measurement geologist asia government well logging...
Proceedings Papers
AI-Boosted Geological Facies Analysis in Crust-Mantle Transition Zone
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Paper presented at the SPWLA 28th Formation Evaluation Symposium of Japan, September 13–14, 2023
Paper Number: SPWLA-JFES-2023-J
... analysis in this study. japan government geology upstream oil & gas artificial intelligence asia government reservoir surveillance geologist borehole imaging rock type sedimentary rock log analysis oman government production monitoring silicate borehole image reservoir...
Proceedings Papers
Quantifying the Surface Ruggedness of the Rock Outcrops by Using 3D Digital Outcrop Models
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Paper presented at the SPWLA 27th Formation Evaluation Symposium of Japan, September 14–15, 2022
Paper Number: SPWLA-JFES-2022-K
... artificial intelligence coast formation evaluation symposium roughness kyushu university department university outcrop correlation nogita coast spatial resolution change japan engineering resource engineering The 27th Formation Evaluation Symposium of Japan, September 14-15, 2022 QUANTIFYING...
Proceedings Papers
Tight Sandstone Reservoir Pore Structure Characterization from Conventional Well Logging Data Based on Machine Learning Method
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Paper presented at the SPWLA 27th Formation Evaluation Symposium of Japan, September 14–15, 2022
Paper Number: SPWLA-JFES-2022-M
... the distribution of effective tight sandstones. permeability log analysis reservoir porosity upstream oil & gas machine learning chang 8 well logging mercury injection saturation characterization artificial intelligence formation evaluation symposium ansai region development university...
Proceedings Papers
Machine Learning To Predict Large Pores and Permeability in Carbonate Reservoirs Using Standard Logs
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Paper presented at the SPWLA 26th Formation Evaluation Symposium of Japan, September 30–October 7, 2021
Paper Number: SPWLA-JFES-2021-E
... permeability model has resulted in enhanced completion decisions for well-work operations (additional perforation and re-perforation campaigns). reservoir characterization log analysis drilling operation flow in porous media machine learning artificial intelligence well logging upstream oil...
Proceedings Papers
Improvement of Accuracy for Estimating Permeability Distribution Using Deep Learning
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Paper presented at the SPWLA 26th Formation Evaluation Symposium of Japan, September 30–October 7, 2021
Paper Number: SPWLA-JFES-2021-D
...-2 to draw the multiple images of facies distribution constrained by well data using Generative Adversarial Network (GAN). flow in porous media machine learning artificial intelligence upstream oil & gas well data soft data th october 2021 reservoir characterization deep learning...
Proceedings Papers
Development of Geothermal Reservoir Simulator for Predicting Water-Steam Flow Behavior Considering Non-Equilibrium State and MINC/EDFM Model
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Paper presented at the SPWLA 25th Formation Evaluation Symposium of Japan, September 25–26, 2019
Paper Number: SPWLA-JFES-2019-C
... Artificial Intelligence kinetic rate constant therm fracture non-equilibrium state permeability The 25th Formation Evaluation Symposium of Japan, September 25-26, 2019 Development of Geothermal Reservoir Simulator for Predicting Water-Steam Flow Behavior Considering Non-equilibrium State and MINC...
Proceedings Papers
Improved Permeability Estimation: From Static to Dynamic To Understand Productivity Better
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Paper presented at the SPWLA 25th Formation Evaluation Symposium of Japan, September 25–26, 2019
Paper Number: SPWLA-JFES-2019-Q
...) for the formation evaluation in an exploration well. The result was used not only to optimize the drill stem test, but also it showed the good match with DST, and provided the general practice in this field for later well correlations. Artificial Intelligence flow in porous media permeability evaluation...
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