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The AAPG/Datapages Combined Publications Database
Showing 2,462 Results. Searched 201,049 documents.
Abstract: A Neural Network Application in Biostratigraphy, by J. Yang-Logan and J. M. Hornell; #90987 (1993).
Search and Discovery.com
1993
Detection of hydrocarbon reservoir boundaries using neural network analysis of surface geochemical data
Hari Doraisamy, Daniel H. Vice, Phillip M. Halleck
AAPG Bulletin
... conclude that application of neural networks to properly designed surface geochemical studies holds promise for use in defining the boundaries of known...
2000
Integration of deep neural networks into seismic workflows for low-carbon energy
Biondo Biondi, Joseph Jennings, Min Jun Park, Stuart Farris, Bob Clapp
International Meeting for Applied Geoscience and Energy (IMAGE)
...Integration of deep neural networks into seismic workflows for low-carbon energy Biondo Biondi, Joseph Jennings, Min Jun Park, Stuart Farris, Bob...
2022
Machine Learning and Deep Learning for Digitizing Scanned Images of Seismic Reflection Data
Agus Abdullah, Sigit Sukmono, João Constantino, Vladimir Machado
Indonesian Petroleum Association
..., Durrani T.S. (2003) Automated 3-D Horizon Tracking and Seismic Classification Using Artificial Neural Networks. In: Sandham W.A., Leggett M. (eds...
2022
Using Advanced Seismic Attribute Analysis to Reduce Risk in Frontier Exploration West Newfoundland Offshore, #40660 (2010)
Valentina V. Baranova, Azer Mustaqeem,
Search and Discovery.com
... within a formation triggers the dolomitization process, we used seismic attributes and neural networks to identify areas with karst morphology...
2010
Bulk Gas Volume Estimation Using Multi-Attribute Regression and Probabilistic Neural Network (PNN): A Case Study in a Gas Field from East Coast of India, #41100 (2012)
Amit K. Ray, Samir Biswal
Search and Discovery.com
..., v. 66/5, p. 1349-1358. Liu, Z. and Liu, J., 1998, Seismic controlled nonlinear extrapolation of well parameters using neural networks: Geophysics, v...
2012
Deep nonlinear seismic prior for seismic interpolation
Yuhan Sui, Xiaojing Wang, Jianwei Ma
International Meeting for Applied Geoscience and Energy (IMAGE)
..., most of deep neural networks are based on linear neurons, which is represented by a linear combination of the inputs and weights. However...
2023
Elastic-AdjointNet: A physics-guided deep autoencoder to overcome crosstalk effects in multiparameter full-waveform inversion
Arnab Dhara, Mrinal Sen
International Meeting for Applied Geoscience and Energy (IMAGE)
... as recurrent neural networks (RNNs) (Wang et al., 2021; Zhang et al., 2021). This reimplementation of PDEs may not be an attractive option...
2022
Seismic inversion with dictionary learning using unsupervised machine learning
Debajeet Barman, Mrinal K. Sen
International Meeting for Applied Geoscience and Energy (IMAGE)
...., and G. AlRegib, 2018, Petrophysical property estimation from seismic data using recurrent neural networks: 88th Annual International Meeting, SEG...
2022
Detect Oil Spill in Offshore Facility Using Convolutional Neural Network and Transfer Learning
Dharmawan Raharjo, Muhamad Solehudin
Indonesian Petroleum Association
... in oil spill detection using deep convolutional neural networks and transfer learning. We develop an “artificial eye” to automatically classify...
2021
New Insights into the Petroleum Potential of the Onshore Otway Basin, Victoria Australia
Lucas McLean-Hodgson, Bruce McConachie
Petroleum Exploration Society of Australia (PESA)
.... and de Groot, P. 2006 Neural networks and soft computing techniques, with applications in the oil industry. EAGE Publishing. Connolly, D., Aminzadeh, F...
2016
Data-driven Approach to Handling High-dimensional Data Input Space using Feature Selection Based Hybrid Machine Learning Methodology
Search and Discovery.com
N/A
Abstract: Improving Resolution of a Fault Probability Map by a Deep Learning Generative Adversarial Network;
Fan Jiang, Phil Norlund
Search and Discovery.com
... prediction results. GANs are deep neural net architectures composed of two networks, the generator (which generates new data instances...
Unknown
Abstract: Forecasting Water Production from Oil and Gas Wells Using Machine Learning Models, a Case Study from the Paradox Basin, Utah; #91208 (2024)
Omar Bakelli, Rohit Ramgire, Ting Xiao, Eric Edelman, Brian McPherson
Search and Discovery.com
.... This study investigates the application of Long Short-Term Memory (LSTM) networks and AutoRegressive Integrated Moving Average (ARIMA) models to forecast...
2024
Synthetic Well Log Generation Using Machine Learning Techniques
Oyewande Akinnikawe, Stacey Lyne, Jon Roberts
Unconventional Resources Technology Conference (URTEC)
... competition among a suite of machine learning algorithms such as Linear Regression, Artificial Neural Networks (ANNs), Decision Trees, Gradient...
2018
A fuzzy logic approach for the estimation of facies from wire-line logs
M. M. Saggaf, Ed L. Nebrija
AAPG Bulletin
... from their logs. The method has advantages when contrasted with other techniques that rely on multivariate statistics and neural networks. Compared...
2003
The Hybrid Theory-Guided Data Science-Based Method: Unlocking the Full Potential of Seismic Reservoirs Characterization
Rino Saputra, Akash Mathur, Awal Mandong
Indonesian Petroleum Association
... Saputra* Akash Mathur* Awal Mandong* ABSTRACT Machine learning has been used for many decades, particularly for deep neural networks that were...
2023
Separation of simultaneous source wavefields using convolutional neural network
Zhehao Li, Hua-Wei Zhou, Kang Fu
International Meeting for Applied Geoscience and Energy (IMAGE)
... to that by state-of-the-art inversion algorithms. The computational time of the deblending via neural networks can be significantly faster than...
2022
Abstract: Petrophysical Studies in the Characterization of Carbonate Reservoirs of Campos Basin – Brazil, by A. Carrasquilla, G. Nocchi, V. Briones, M. Torres, N. Franco Filho, F. Schuab, and P. Sanchez; #120034 (2012)
Search and Discovery.com
2012
Fast Track Reservoir Characterisation of a Subtle Paleocene Deep Marine Turbidite Field Using a Rock Physics and Seismic Modelling Led Workflow
H.J.S. Morris, R. Christensen, D. Gawith, M. Millwood-Hargrave
Indonesian Petroleum Association
.... Supervised Neural Nets The supervised neural networks used here works as a Multi-layer Perceptron (MLP). This network works by building up a number of many...
2008
Abstract: Correlation of swath bathymetric images with metrics derived from seismic and sidescan data
B. Nichols, R. Courtney, G. Fader, R. Parrott
Atlantic Geology
.... The tasks of preparing metrics, correlation and interpretation are forms of feature classification. A number of simple neural networks have been...
1993
Improving 3D seismic facies interpretation with an advanced deep learning method utilizing both spatial and temporal dependencies
Miao Tian, Sumit Verma, Yining Gao
International Meeting for Applied Geoscience and Energy (IMAGE)
... and recurrent neural networks: Journal of Petroleum Science and Engineering, 196, 107598, doi: https://doi.org/10.1016/j.petrol.2020.107598. Fourth...
2024
Abstract: The Future of Artificial Intelligence (AI) Applications in Geology
Edward R. Jones
Houston Geological Society Bulletin
... cluster analysis, artificial neural networks, decision trees text mining, and many resampling methods such as random forests and ensemble models...
2018