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The AAPG/Datapages Combined Publications Database

Showing 624 Results. Searched 200,636 documents.

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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 JoggingŽ Field, Northwest Java Basin

Akbar Dwi Wahyono, Mualimin, Sudarmaji

Indonesian Petroleum Association

...(t) in terms of expansion : k K r t   xt     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, Whats 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

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