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...

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...

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...

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)

... convolutional neural networks and channel attention mechanisms. We use seismic data and low-frequency impedance data to generate inputs of training...

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...

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

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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...

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...

Abstract: 3-D Volumetric Interpretation with Computational Stratigraphy Models

Lisa Goggin, Tao Sun, Maisha Amaru, Ashley Harris, Anne Dutranois, Andrew Madof

Houston Geological Society Bulletin

... of a fluvially-dominated delta was created. The depositional model is converted into seismic volumes of various frequencies (1D convolutional approach...

ABSTRACT: Maximum Likelihood Deconvolution: a New Perspective, by Jerry M. Mendel; #91035 (2010)

Search and Discovery.com

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

... Base) that are later needed for the low-frequency model generation. The well WTR-4A has more complete data and was used as reference well...

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...

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

Search and Discovery.com

A simultaneous denoising and event picking approach using supervised machine learning

Salman Abbasi, Motaz Alfarraj, Dmitry Borisov, Vikram Jayaram, Iftekhar Alam, Bakhtawer Sarosh

International Meeting for Applied Geoscience and Energy (IMAGE)

... problems (i.e., denoising and event detection) using a single network. A convolutional neural network is used to capture the high frequency times series...

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...

Convolution model theory-based intelligent AVO inversion method for VTI media

Yuhang Sun, Yang Liu, Hongli Dong

International Meeting for Applied Geoscience and Energy (IMAGE)

... network technology and propose an intelligent seismic AVO inversion method founded on the convolutional model theory. The proposed method formulates...

Bayesian variational auto-encoder for seismic wavelet extraction

Ammar Ghanim, Ricard Durall, Norman Ettrich

International Meeting for Applied Geoscience and Energy (IMAGE)

...-shift. b) using a model trained with time- and frequency-domain loss. c) using the same model as above, but with noise superimposed on the input. a) b...

Abstract: Impedance Inversion of Blackfoot 3D Seismic Dataset; #90171 (2013)

A. Swisi and Igor B. Morozov

Search and Discovery.com

... by using the methods below. 2) Model-based inversion is also called blocky inversion. This method is based on the convolutional seismic model: S =W * R + n...

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...

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...

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

..., and although an interpretive low frequency model is not used, the technique provides a robust inversion that honours the impedance trend of available well data...

Accurate seismic data interpolation based on multiband intelligent training

Xueyi Sun, Benfeng Wang, Tongtong Mo

International Meeting for Applied Geoscience and Energy (IMAGE)

... in the frequency domain (Porsani, 1985; Spitz, 1991; Naghizadeh and MD Sacchi, 2009; Li et al., 2018). The second is the rank reduction-based...

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

Garnham, Gail Riekie, Malu Jensen, Liz Pointing

Search and Discovery.com

... wavelet with a slighlty different frequency content to the Ricker 30 HZ. The results suggest that for the given Nelson reservoir model properties...

Stochastic inversion method based on a priori information of compression-sensing divided-frequency waveform indication

Ying Lin, Siyuan Chen, Guangzhi Zhang, Baoli Wang, Minmin Huang

International Meeting for Applied Geoscience and Energy (IMAGE)

... the models in different frequency bands are integrated in the frequency domain to obtain the final required elasticity parameter model. Next, we simplify...