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

Carlos Montana and Gary Margrave

Search and Discovery.com

.... In contrast with the stationary convolutional model, which can be formulated in a simple way either in the time or the frequency domain...

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...

Facies Classification Based on Well Logs by Using an Convolutional Neural Network

Search and Discovery.com

ABSTRACT: Shaping the Wavelet, by Wang, Yuchun E.; Huo, Shoudong; #90141 (2012)

Search and Discovery.com

Abstract: CO2 Distribution Prediction Using Machine Learning Based Proxy Model in Geological Carbon Sequestration;

Zhi Zhong, Alexander Sun

Search and Discovery.com

... knowledge and assumptions on input data distributions. In particular, our cDC-GAN model is designed to learn cross-domain mappings between high...

Bayesian variational auto-encoder for seismic wavelet extraction

Ammar Ghanim, Ricard Durall, Norman Ettrich

International Meeting for Applied Geoscience and Energy (IMAGE)

...: Extracted wavelets using Inference C. From the top: a) using a model trained with time-domain loss, the model failed at retrieving the complicated phase...

Automated velocity model building using Fourier neural operators

Guanghui Huang, Sean Crawley, Ramzi Djebbi, Jaime Ramos-Martinez, Nizar Chemingui

International Meeting for Applied Geoscience and Energy (IMAGE)

... efficiently computed in the Fourier domain. We show the advantages of using global FNOs over conventional convolutional neural networks (CNN), to achieve...

Feasibility Study Methodology for Fracture Analysis Studies Using Seismic Azimuthal Amplitude Variation: Application in Southern Mexico

Alexis Ferrer Balas, Nahum Campos, Jesus Garcia Hernandez

GCAGS Transactions

... the well from depth to time domain. Horizons in the vicinity of the well are also required. Their extent depends on the size we want to model and may...

Seismic simulations of experimental strata

Lincoln Pratson, Wences Gouveia

AAPG Bulletin

.... These reflection coefficients are then converted from the depth to the time domain using the model velocities. Note that the convolutional model is one...

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...

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...

Identification of vehicles from seismic signals using machine learning

Xiaoxuan Zhu, Ji Zhang, Jie Zhang

International Meeting for Applied Geoscience and Energy (IMAGE)

... to record seismic signals generated by passing vehicles. We then conduct analyses in the time domain to roughly categorize traffic vehicles into three...

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...

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...

Abstract: Short-time Wavelet Estimation in the Homomorphic Domain; #90174 (2014)

Roberto H. Herrera and Mirko van der Baan

Search and Discovery.com

... is also used in the log spectral averaging method. Seismic signals are nonstationary, i.e. they follow the time-invariant convolutional model only...

High-resolution angle gather tomography with Fourier neural operators

Sean Crawley, Guanghui Huang, Ramzi Djebbi, Jaime Ramos, Nizar Chemingui

International Meeting for Applied Geoscience and Energy (IMAGE)

... data and field data. Additionally, migrated data already occupies the same domain as the target velocity model (plus some kind of angle/extended image...

ABSTRACT: Quantitative Integration of 4D Seismic for Field Development; #90007 (2002)

Garnham, Gail Riekie, Malu Jensen, Liz Pointing

Search and Discovery.com

..., a dedicated time-lapse monitoring survey was acquired and, in 2000, a further 4D survey was acquired. Forward Convolutional Models of 4D Signature Forward...

Multi-realization seismic data processing with deep variational preconditioners

Matteo Ravasi

International Meeting for Applied Geoscience and Energy (IMAGE)

... is represented here by the latent space parameters of a fully-convolutional VAE, pre-trained directly on the available data sorted in a suitable domain...

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...

Abstract: Push the Limits of Seismic Resolution Using Surface Consistent Gabor Deconvolution; #90171 (2013)

Xinxiang Li and Darren P. Schmidt

Search and Discovery.com

... and the time-variant earth wavelet in a nonstationary convolutional trace model, which can be approximately factorized in the Gabor domain...

Coloured Seismic Inversion, a Simple, Fast and Cost Effective Way of Inverting Seismic Data: Examples from Clastic and Carbonate Reservoirs, Indonesia

Keith Maynard, Paulus Allo, Phill Houghton

Indonesian Petroleum Association

... response. Figure 4. Operator design process. The assumption is made that the seismic data is zero phase, so that a convolutional operator in the time...

Bridging the gap: Deep learning on seismic field data with synthetic training for building Gulf of Mexico velocity models

Stuart Farris, Robert Clapp

International Meeting for Applied Geoscience and Energy (IMAGE)

... Clapp, Stanford University SUMMARY This study employs Convolutional Neural Networks (CNNs) to predict low-wavenumber seismic velocity models to serve...

Geobody-oriented interpretable velocity fusion modeling in depth domain with seismic facies informed segmentation method

Meng Li, Qingcai Zeng, Hao Shou, Nan Qin, Chunming Wang, Tongsheng Zeng

International Meeting for Applied Geoscience and Energy (IMAGE)

... modeling and combines it with seismic inversion to improve the resolution of velocity model in depth domain. This work is based on the assumption...

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...

Deep learning-based Vz-noise attenuation for OBS data

Jing Sun, Arash Jafargandomi, Julian Holden

International Meeting for Applied Geoscience and Energy (IMAGE)

... component is its coherency in the common-receiver domain and incoherency in the commonshot domain. There have been a range of noise attenuation...