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The AAPG/Datapages Combined Publications Database

Showing 324 Results. Searched 195,354 documents.

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Predicting Facies, Rock, and Geomechanical Properties Using Convolutional Neural Networks: A Case Study From an Unconventional Shale Reservoir

Ted Holden, Ruth Kurian, Mohammed Ibrahim, Daniel Hampson, Jonathan Downton

Unconventional Resources Technology Conference (URTEC)

...) Synthetic angle gathers are then generated for each pseudo-well using a convolutional model in which the P-wave reflection coefficients calculated using...

2023

Abstract: Grain Segmentation and Region Mask Generation in Digital Rock Images Using Convolutional Neural Networks;

Rengarajan Pelapur, Arash Aghaei, Connor Burt, Bidur Bohara

Search and Discovery.com

... neural networks. This model is trained on a database of rock models generated using a 3D process-based modeling technique. Convolutional Neural Network...

Unknown

An Introduction to Deep Learning: Part III

Lasse Amundsen, Hongbo Zhou, Martin Landrø

GEO ExPro Magazine

... computer model that learns to perform classification tasks directly from images. The one that started it all was the 2012 publication ‘ImageNet...

2018

Abstract: AI- Assisted Palynological Analysis Using an Expert-Trained Convolutional Neural Network: A Case Study form the Jurassic in the North Sea; #91204 (2023)

Rader Abdul Fattah, Merijn de Bakker, Alexander Houben, Roel Verreussel, Robert Williams

Search and Discovery.com

...Abstract: AI- Assisted Palynological Analysis Using an Expert-Trained Convolutional Neural Network: A Case Study form the Jurassic in the North Sea...

2023

Horizontal Stresses Prediction Using Sonic Transition Time Based on Convolutional Neural Network; #42587 (2023)

Esmael Makarian, Ayub Elyasi, Fatemeh Saberi, Olusegun Stanley Tomomewo

Search and Discovery.com

...Horizontal Stresses Prediction Using Sonic Transition Time Based on Convolutional Neural Network; #42587 (2023) Esmael Makarian, Ayub Elyasi, Fatemeh...

2023

Abstract: GAN-Based Multipoint Geostatistical Inversion Method and Application;

Pengfei Xie, Jiagen Hou

Search and Discovery.com

... technology. Multi-point statistics (MPS) generate model realizations by training image (TI) that are consistent with prior information. This method often...

Unknown

Multichannel seismic deconvolution via 2D K-SVD and convolutional sparse coding

Guiqian Zhang, Xiayu Gao, Bangli Zou, Yaojun Wang, Yingzhu Chen

International Meeting for Applied Geoscience and Energy (IMAGE)

... to the deconvolution objective function in the form of regularization. Frequency Decomposition of Seismic Profile According to the convolutional model...

2023

Abstract: Machine Learning Assisted Fracture Characterization with Borehole Image Logs in Geothermal Wells; #91204 (2023)

Chicheng Xu

Search and Discovery.com

... from multiple sources of data, we build a convolutional neural network model and train it with the labeled results from borehole image log. The model...

2023

Detect Oil Spill in Offshore Facility Using Convolutional Neural Network and Transfer Learning

Dharmawan Raharjo, Muhamad Solehudin

Indonesian Petroleum Association

...Detect Oil Spill in Offshore Facility Using Convolutional Neural Network and Transfer Learning Dharmawan Raharjo, Muhamad Solehudin This paper has...

2021

Abstract: Deep Learning Inversion on Seismic Cubes; #91204 (2023)

Aleksandr Koriagin, Alexey Kozhevin, Stepan Goriachev, Roman Khudorozhkov

Search and Discovery.com

... show how one can perform inference on full seismic cubes using convolutional neural networks and specific prediction aggregation techniques...

2023

Automated detection of ferromagnetic pipelines from magnetic total-field anomaly data using convolutional neural networks

Brett Bernstein, Yaoguo Li, Richard Hammack

International Meeting for Applied Geoscience and Energy (IMAGE)

...Automated detection of ferromagnetic pipelines from magnetic total-field anomaly data using convolutional neural networks Brett Bernstein, Yaoguo Li...

2023

Abstract: Reflectivity Color Correction in Gabor Deconvolution; #90211 (2015)

Carlos Montana and Gary Margrave

Search and Discovery.com

... relies on the fulfillment of a set of assumptions on which the convolutional model is based: stationarity, minimum phase wavelet, white reflectivity...

2015

ABSTRACT: Selected Topics in Seismic Dispersion

Christopher L. Liner

Houston Geological Society Bulletin

..., reflection and transmission coefficients, head waves, etc. The convolutional reflection models we use to model thick and thin bed thin response...

2012

Looking for a simplified and generalized training set in ML applications for gravity modelling

Luigi Bianco, Ciro Messina, Maurizio Fedi

International Meeting for Applied Geoscience and Energy (IMAGE)

... be seen as the building blocks of each gravimetric anomaly. Here, we discuss preliminary results obtained with a Convolutional Neural Network (CNN...

2023

Feature Detection for Digital Images Using Machine Learning Algorithms and Image Processing

Xiao Tian, Hugh Daigle, Han Jiang

Unconventional Resources Technology Conference (URTEC)

... is increased greatly. There are 16 weight layers in vgg16 model, including 13 convolutional layers and 3 fully-connected layers. There are 19 weight...

2018

Fracture-cavity carbonate reservoir identification based on channel attention mechanisms

Liuxin Yang, Yongqiang Ma, Guangxiao Deng, Zhen Wang

International Meeting for Applied Geoscience and Energy (IMAGE)

... attention mechanisms in a semi-supervised learning framework. The architecture of our inversion model consists of several attention blocks, which combine...

2023

Deep neural networks for 1D impedance inversion

Vladimir Puzyrev, Anton Egorov, Anastasia Pirogova, Chris Elders, Claus Otto

Petroleum Exploration Society of Australia (PESA)

... such as the 160-layer velocity model used as an example in this study require large synthetic datasets for training, which are not always possible...

2019

Abstract: Seismic Characterization of Complex Salt Dome Structures using Machine Learning; #91204 (2023)

Osama Alsalmi, Saleh Dossary, Gino Ananos

Search and Discovery.com

.... Convolutional Neural Networks (CNNs) gained popularity in image segmentation tasks. In this study, a machine learning model based on U-Net architecture is used...

2023

Do We Really Need Deep Learning? A Study on Play Identification using SEM Images

Hanyan Zhang, Max T. Kasumov, Deepak Devegowda, Mark E. Curtis

Unconventional Resources Technology Conference (URTEC)

... classification. For all image resolutions considered, surprisingly, the simplest and shallowest one-convolutional layer model performs remarkably well...

2021

Seismic simulations of experimental strata

Lincoln Pratson, Wences Gouveia

AAPG Bulletin

... of the resulting seismic section. Convolutional Model The convolutional seismic model convolves a seismic wavelet with a time series of reflection...

2002

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