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The AAPG/Datapages Combined Publications Database
Showing 624 Results. Searched 200,636 documents.
Fine-Scale Lamination/Bedding, An Important Factor in Unconventional Reservoirs Hydrocarbon Productivity
Carlos Molinares-Blanco, D. Becerra-Rondon, H. Galvis-Portilla, D. Duarte
Unconventional Resources Technology Conference (URTEC)
...) and cherts (hard). The natural radioactivity of the rock was measured at every stratigraphic foot using a hand-held gamma-ray scintillometer model RS-120...
2022
AVO and Inversion Contribute to Makassar Exploration Efforts
William L. Soroka, Herry Andiarbowo, Anung Widodo
Indonesian Petroleum Association
... representation of true amplitude normal incidence P-wave reflectivity. From the convolutional model, it is understood that the seismic wavelet convolved...
1995
Transformer-based deep learning model for accurate rate of penetration prediction in drilling
Carlos Urdaneta, Cheolkyun Jeong, Xuqing Wu, Jiefu Chen
International Meeting for Applied Geoscience and Energy (IMAGE)
...Transformer-based deep learning model for accurate rate of penetration prediction in drilling Carlos Urdaneta, Cheolkyun Jeong, Xuqing Wu, Jiefu Chen...
2023
Abstract: P-wave AVAz Modeling: A Haynesville Case Study; #90224 (2015)
Jon Downton
Search and Discovery.com
... but for simplicity this paper focuses on convolutional modeling. Typically a 1D layered earth model is assumed for which the interpreter assigns elastic...
2015
Production Forecasting in Shale Reservoirs through Conventional DCA and Machine/Deep Learning Methods
Cenk Temizel, Celal Hakan Canbaz, Onder Saracoglu, Dike Putra, Ali Baser, Tomi Erfando, Shanker Krishna, Luigi Saputelli
Unconventional Resources Technology Conference (URTEC)
...-consuming process when one tries to estimate the multi-well pad performance in the field condition. In order to correctly model the flow of fluid...
2020
Application of intelligent fault identification and sealing evaluation technology in Lukeqin area
Sun bo, Lin Yu, Guo Xiang, Yin Xue Bin, Nie Zhiwei, Liu Hongyan
International Meeting for Applied Geoscience and Energy (IMAGE)
... as a whole. Through fault model construction, deep learning and direct prediction, the micro-fault prediction technology based on convolutional neural...
2024
Automatic facies classification using convolutional neural network for three-dimensional outcrop data: Application to the outcrop of the mass-transport deposit
Ryusei Sato, Kazuki Kikuchi, and Hajime Naruse
AAPG Bulletin
... point clouds used as training data for the convolutional neural network (CNN) model. (A, C) Original point cloud used as training data for the CNN model...
2025
Time-Lapse Petro-Elastic and Seismic Modeling to Evaluate Fracturing Efficiency in Low-Permeability Reservoirs
Masoud Alfi, Zhi Chai, Anshuman Pradhan, Travis Ramsay, Maria Barrufet, John Killough
Unconventional Resources Technology Conference (URTEC)
... inputs, normal incidence seismic traces are forward-modeled through the convolutional model shown in Eq. 10. A zero-phase Ricker wavelet with a central...
2018
Recursive DIP for seismic random noise attenuation
Yun Zhang, Benfeng Wang
International Meeting for Applied Geoscience and Energy (IMAGE)
..., filtering-based methods and time-frequency transform/sparse transformbased methods. These conventional denoising methods have achieved good results...
2022
Analysis of the Elastic Impedance Inversion and Lamda Mu Rho to Identify the Distribution of Sandstone Reservoirs and Hydrocarbon Fluids in the Jogging Field, Northwest Java Basin
Akbar Dwi Wahyono, Mualimin, Sudarmaji
Indonesian Petroleum Association
...(t) in terms of expansion : k K r t xt k ø k t k 1 where x(t) is the segment of the input trace that follows the convolutional model...
2015
Tiltmeter data inversion for reservoir integrity monitoring using numerical modelling and particle swarm optimisation
Reza Abdollahi, Abbas Movassagh, Dane Kasperczyk, Manouchehr Haghighi
Australian Energy Producers Journal
... on Surface Displacement Using Image-To-Image Convolutional Neural Network Model. Frontiers in Earth Science 9, 712681. doi:10.3389/feart.2021.712681 Hu C...
2025
Abstract: Recognizing facies in the Red River Formation of North Dakota using a Convolutional Neural Network; #90301 (2017)
Stephan H. Nordeng, Ian E. Nordeng, Jeremiah Neubert, Emily G. Sundell
Search and Discovery.com
...Abstract: Recognizing facies in the Red River Formation of North Dakota using a Convolutional Neural Network; #90301 (2017) Stephan H. Nordeng, Ian E...
2017
Abstract: Object Detection in SEM Images Using Convolutional Neural Networks: Application on Pyrite Framboid Size-Distribution in Fine-Grained Sediments;
Artur Davletshin, Lucy Tingwei Ko, Kitty Milliken, Priyanka Periwal, Wen Song
Search and Discovery.com
...Abstract: Object Detection in SEM Images Using Convolutional Neural Networks: Application on Pyrite Framboid Size-Distribution in Fine-Grained...
Unknown
Transfer Learning with Multiple Aggregated Source Models in Unconventional Reservoirs
J. Cornelio, S. Mohd Razak, Y. Cho, H-H. Liu, R. Vaidya, B. Jafarpour
Unconventional Resources Technology Conference (URTEC)
... Oilfield in the Middle East. Society of Petroleum Engineers. Mohd Razak S, Jafarpour B. (2020a) Convolutional neural networks (CNN) for feature-based model...
2022
The Perfect Frac Stage, Whats the Value?
Craig Cipolla, Ankush Singh, Mark McClure, Michael McKimmy, John Lassek
Unconventional Resources Technology Conference (URTEC)
..., and Alfred Hill. "Classification and Localization of Fracture-Hit Events in Low-Frequency Distributed Acoustic Sensing Strain Rate with Convolutional...
2024
Multi-information intelligent decision process for first-break picking
Fei Luo, Lanlan Yan
International Meeting for Applied Geoscience and Energy (IMAGE)
... analysis. Recently, several authors have employed convolutional neural networks as classifiers to determine the presence of a first arrival signal...
2024
Microsoft Word - image2023_final (10).docx
J0381057
International Meeting for Applied Geoscience and Energy (IMAGE)
...., 2020). Neural networks, as the backbone of deep learning, are usually composed of convolutional layers that are designed to be trained on large datasets...
Unknown
Physics-Assisted Transfer Learning for Production Prediction in Unconventional Reservoirs
J. Cornelio, S. Mohd Razak, A. Jahandideh, Y. Cho, H-H. Liu, R. Vaidya, B. Jafarpour
Unconventional Resources Technology Conference (URTEC)
.... Society of Petroleum Engineers. Mohd Razak S, Jafarpour B. (2020a) Convolutional neural networks (CNN) for feature-based model calibration under uncertain...
2021
Viable Solutions to Overcome Weaknesses of Deep Learning Applications in Production Forecasting: A Comprehensive Review
Y. Kocoglu, S. Gorell
Unconventional Resources Technology Conference (URTEC)
... process the same time series data in multiple different ways and can be combined with other workflows or networks such as Convolutional Neural Network...
2022
Detailed petroleum system insights using deep learning: A case study from the Scarborough Gas Field, offshore Australia
Scotty Salamoff, Julian Chenin, Benjamin Lartigue, Nguyen Phan, Paul Endresen
International Meeting for Applied Geoscience and Energy (IMAGE)
... to B) the interactive deep learning method for handling patches. The deep learning architecture presented is based on a Convolutional Neural Network...
2022
Improving Microseismic Denoising Using 4D (Temporal) Tensors and High-Order Singular Value Decomposition
Keyla Gonzalez, Eduardo Gildin, Richard L. Gibson Jr.
Unconventional Resources Technology Conference (URTEC)
... of data is achieved. In this research, we implement a high-order SVD (HOSVD) model reduction method for denoising and compressing microseismic...
2021
Combined P and S Waves Survey for Hydrocarbon Exploration
Basuki Puspoputro
Indonesian Petroleum Association
... velocity analysis and the convolutional model: IHRDC, Boston. Sheriff, R.E., 1984, Encyclopedic dictionary of exploration geophysics, 2nd edition...
1990
Abstract: Integrating Geologic and Geophysical Data in Geostatistical Inversion; #90187 (2014)
John V. Pendrel
Search and Discovery.com
... constraints are applied simultaneously The seismic and reservoir properties are related through a predictive rock physics model The facies definitions...
2014
Machine learning-based residual moveout picking
Farhad Bazargani, Wenjun Zhang, Anu Chandran, Zaifeng Liu, Harry Rynja
International Meeting for Applied Geoscience and Energy (IMAGE)
... in the migration velocity model. Accurate and efficient RMO picking is the key to the success of tomographic velocity model building workflows. Conventional RMO...
2022
Abstract: Azimuthal Fourier Coefficient Elastic Inversion; #90174 (2014)
Benjamin Roure and Jon Downton
Search and Discovery.com
... and the real data expressed as follows: Misfit R *W data i , j 2 (1) i, j The modeled data is calculated using a convolutional model where...
2014