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The AAPG/Datapages Combined Publications Database

Showing 622 Results. Searched 200,357 documents.

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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...

2003

Transformer-based network for an efficient ground roll suppression

Randy Harsuko, Omar Saad, Tariq Alkhalifah

International Meeting for Applied Geoscience and Energy (IMAGE)

...). This is attributed to the new components introduced to the model, namely the learnable positional encoding, the 1D convolutional encoder-decoder...

2024

Seismic resolution enhancement with self-supervised learning

Shijun Cheng, Tariq Alkhalifah, Haoran Zhang

International Meeting for Applied Geoscience and Energy (IMAGE)

... classic approaches, working to recover high-frequency content by minimizing the discrepancy between real seismic data and model predictions (Berkhout...

2024

Abstract: Kirchhoff Imaging with Adaptive Greens Functions for Compensation for Dispersion, Attenuation, and Velocity Imprecision; #90187 (2014)

Andrew V. Barrett

Search and Discovery.com

... frequencies appear to propagate at the velocity of the asymptotic high frequency. If we know the attenuation constant ‘Q’, and if the model for attenuation...

2014

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)

...; Tarantola, 1984). However, the success of FWI is closely linked to factors like the accuracy of the starting model, the frequency range of the recorded...

2023

Abstract: Variable-factor S-transform for Time-frequency Decomposition, Deconvolution, and Noise Attenuation; #90172 (2014)

Todor I. Todorov, Gary F. Margrave

Search and Discovery.com

... to the physical phenomena of the seismic wave propagation in the earth over the traditional stationary convolutional model. Margrave and Lamoureux...

2014

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...

Unknown

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

Seismic inversion with dictionary learning using unsupervised machine learning

Debajeet Barman, Mrinal K. Sen

International Meeting for Applied Geoscience and Energy (IMAGE)

... (ML) has recently gained immense popularity in almost every field. This popularity is attributed to the invention of the Convolutional Neural Network...

2022

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

Extending Engine Change Out Respective to Running Hours Using Data Driven Using One Dimension (1-D) Convolutional Neural Network Algorithm

Subhan Malik, Harry Poetra Soedarsono

Indonesian Petroleum Association

...Extending Engine Change Out Respective to Running Hours Using Data Driven Using One Dimension (1-D) Convolutional Neural Network Algorithm Subhan...

2024

Real-time hydraulic fracturing monitoring using deep learning clustering of microseismic data

Chenglong Duan, Lianjie Huang, Michael Gross, Michael Fehler, David Lumley

International Meeting for Applied Geoscience and Energy (IMAGE)

... high-frequency borehole microseismic data for real-time monitoring of fracture growth. Using the output of the UNet, we perform Gaussian mixture model...

2022

Marchenko focusing using convolutional neural networks

Mert S. R. Kiraz, Roel Snieder

International Meeting for Applied Geoscience and Energy (IMAGE)

...Marchenko focusing using convolutional neural networks Mert S. R. Kiraz, Roel Snieder Marchenko focusing using convolutional neural networks Mert...

2022

The impact of the synthetic seismic data generation method on automated AI-based horizon interpretation

F. Vizeu, J. Zambrini, A. Canning

International Meeting for Applied Geoscience and Energy (IMAGE)

... by using the convolutional model with full control of the synthetic wavelet, and add noise to it. To convert the 2D data into 3D we use a technique...

2023

Efficient seismic image super-resolution

Adnan Hamida, Motaz Alfarraj, Abdullatif A. Al-Shuhail, Salam A. Zummo

International Meeting for Applied Geoscience and Energy (IMAGE)

... a GAN-based model with four convolutional layers for both the generator and discriminator. Fehler and Keliher (2011) SEAM Phase I synthetic dataset...

2022

Extrapolated surface-wave dispersion inversion

Hongyu Sun, Laurent Demanet

International Meeting for Applied Geoscience and Energy (IMAGE)

... with respect to S-wave velocity of the model. With decreasing frequency, surface waves become sensitive to deeper velocity structures. The lower...

2022

Abstract: Automated Fault Detection from 3-D Seismic Using Artificial Intelligence „ Practical Application and Examples from the Gulf of Mexico and North Slope Alaska;

Andrew Pomroy, Zachary Wolfe

Search and Discovery.com

... in the realm of seismic attributes given its well established strengths in image pattern analysis and recognition. With this in mind, a Convolutional...

Unknown

High-resolution prestack seismic inversion of reservoir parameters using an arch network

Ting Chen, Yaojun Wang, Yuan Yuan, Gang Yu, Guangmin Hu

International Meeting for Applied Geoscience and Energy (IMAGE)

... to be normalized at the beginning, and then 2 wells are used to construct the initial low-frequency model for the conventional pre-stack inversion. The initial...

2022

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...

2023

Seismic sparse time-frequency representation via GAN-based unsupervised learning

Youbo Lei, Yang Yang, Naihao Liu, Shengtao Wei, Jinghuai Gao, Xiudi Jiang

International Meeting for Applied Geoscience and Energy (IMAGE)

... the optimization problem. However, STFR is often based on a mathematical model designed with the domain knowledge. Moreover, it suffers from the expensive...

2022

Convolutional neural networks as an aid to biostratigraphy and micropaleontology: a test on late Paleozoic microfossils

Rafael Pires De Lima, Katie F. Welch, James E. Barrick, Kurt J. Marfurt, Roger Burkhalter, Murphy Cassel, Gerilyn S. Soreghan

PALAIOS

...) Inception V3 CNN architecture reached a 3.5% top-5 error (frequency in which the model cannot predict the correct class as one of the top five most...

2020

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...

2013

-- no title --

user1

Search and Discovery.com

... Lithotypes Classification with Convolutional Neural Networks Evgeny E. Baraboshkin1, Evdokiya A. Panchenko2, Andrey E. Demidov1, Ardiansyah...

Unknown

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