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The AAPG/Datapages Combined Publications Database

Showing 324 Results. Searched 195,354 documents.

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Deep carbonate reservoir characterization with unsupervised machine-learning approaches

Xuanying Zhu, Luanxiao Zhao, Xiangyuan Zhao, Yuchun You, Minghui Xu, Tengfei Wang

International Meeting for Applied Geoscience and Energy (IMAGE)

... (PCA), T-distributed Stochastic Neighbor Embedding (t-SNE), Uniform Manifold Approximation and Projection (UMAP), and Convolutional Autoencoder (CAE...

2023

Fast viscoacoustic forward modeling method based on U-net Fourier neural operator

Wenbin Tian, Yang Liu

International Meeting for Applied Geoscience and Energy (IMAGE)

... variations within the data. On the other hand, the wavenumber-domain CNN operates as a trainable wavenumber filter, enabling nonlocal spatial convolutional...

2023

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...

2023

Survey merging using CycleGAN and patchy seismic images

Chaoshun Hu, Fan Jiang, Konstantin Osypov, Julianna Toms

International Meeting for Applied Geoscience and Energy (IMAGE)

... frequency and high frequency domains. When there are paired images, CycleGAN will be simplified to be a U-net model where the loss function is using...

2023

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...

2023

Deep nonlinear seismic prior for seismic interpolation

Yuhan Sui, Xiaojing Wang, Jianwei Ma

International Meeting for Applied Geoscience and Energy (IMAGE)

... to be a local linear event in the frequency domain. In the transform-based methods (Sacchi et al., 1998; Yu et al., 2015), seismic data is represented...

2023

Application of Both Physics-Based and Data-Driven Techniques for Real-Time Screen-Out Prediction with High Frequency Data

Jianlei John Sun, Arvind Battula, Brandon Hruby, Paymon Hossaini

Unconventional Resources Technology Conference (URTEC)

... (i.e., screen-out) using domain expert knowledge and three-segment curve fitting. Modified Inverse Slope Model In order to address the issues mentioned...

2020

Abstract: Color Correction for Gabor Deconvolution and Nonstationary Phase Rotation; #90171 (2013)

Peng Cheng and Gary F. Margrave

Search and Discovery.com

... deconvolution is based on a nonstationary convolution model of the seismic trace. Margrave (1998) presented a nonstationary convolutional model, which...

2013

Abstract: Color Correction for Gabor Deconvolution and Nonstationary Phase Rotation; #90171 (2013)

Peng Cheng and Gary F. Margrave

Search and Discovery.com

... deconvolution is based on a nonstationary convolution model of the seismic trace. Margrave (1998) presented a nonstationary convolutional model, which...

2013

Increasing The Resolution of Seismic Imaging With Spectral Blueing, Spectral Decomposition RGB And HSV Blending to Delineate The Fluvial Facies on Fluvio Deltaic Environment

Aji Darma Maulana, Nine Safira, Ongki Ari Prayoga, Egie Wijaksono, Alit Ascaria

Indonesian Petroleum Association

... surveys (Partyka et al., 1999). Spectral decomposition is carried out by converting seismic data into the frequency domain using time-frequency...

2022

Demultiple of High Resolution P-Cable Data in the Norwegian Barents Sea „ An Iterative Approach

A.J. Hardwick, S. Jansen, B. Kjolhamar

Petroleum Exploration Society of Australia (PESA)

... from the latest The final adapted model is then subtracted in the curvelet n. A data driven, iterative approach is domain. For the first time, through...

2017

Dual constrained reservoir modeling with geological factors and seismic attributes for exploration stage

Hongmei Luo, Yiran Xing, Changjiang Wang, Zhijing Zhang

International Meeting for Applied Geoscience and Energy (IMAGE)

... model as the covariate to realize the geostatistical modeling in the exploration stage. Consequently, the reliability and effectiveness of the modeling...

2023

Abstract: Fast and Accurate Impedance Inversion by Well-Log Calibration; #90171 (2013)

Igor B. Morozov and Jinfeng Ma

Search and Discovery.com

...) the convolutional equation; 2) time-depth constraints from the seismic data, 3) background low-frequency model from the logs or seismic/geological interpretation...

2013

Abstract: Harmonic Decomposition of a Vibroseis Sweep Using Gabor Analysis; #90174 (2014)

Christopher B. Harrison, Gary Margrave, Michael Lamoureux, Art Siewert, and Andrew Barrett

Search and Discovery.com

... (left) and the frequency domain (right) individual results (magenta) of time-dependent Gabor decomposition with respects to the fundamental, H2, H3, H4...

2014

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...

2013

Fault MLReal: A fault delineation study for the Decatur CO2 field data using neural network predicted passive seismic locations

Hanchen Wang, Yinpeng Chen, Tariq Alkhalifah, Youzuo Lin

International Meeting for Applied Geoscience and Energy (IMAGE)

... and performance of Convolutional Neural Networks (CNN). Considering we have labeled training data, referred to in domain adaptation circles...

2023

Deep convolutional neural networks for generating grain-size logs from core photographs

Thomas T. Tran, Tobias H. D. Payenberg, Feng X. Jian, Scott Cole, and Ishtar Barranco

AAPG Bulletin

...Deep convolutional neural networks for generating grain-size logs from core photographs Thomas T. Tran, Tobias H. D. Payenberg, Feng X. Jian, Scott...

2022

Rock-physics based time-lapse inversion in Delivery4D: synthetic feasibility study for CO2CRC Otway Project

Stanislav Glubokokvskikh, James Gunning, Tess Dance, Roman Pevzner, Dmitry Popik, Christian Proud

Petroleum Exploration Society of Australia (PESA)

... seismic AVO-inversion based on convolutional model of seismic trace. A subsurface model consists of 1D ‘layered cakes’, inverted independently...

2018

A deep learning-based inverse Hessian for full-waveform inversion

Mustafa Alfarhan, Matteo Ravasi, Tariq Alkhalifah

International Meeting for Applied Geoscience and Energy (IMAGE)

.... A smoothed version of this model is used as starting guess for FWI. A wavelet with a peak frequency of 5 Hz is utilized to perform the modeling of 25 shots...

2023

Revolutionizing seismic data compression: Unlocking the power of stable diffusion neural networks

Ayrat Abdullin, Umair Bin Waheed, Naveed Iqbal

International Meeting for Applied Geoscience and Energy (IMAGE)

... principal component analysis (DPCA). By leveraging a mixture model to represent the statistics of seismic traces and computing global principal components...

2023

Estimation of Reservoir Fluid Saturation from 4D Seismic Data: Effects of Noise on Seismic Amplitude and Impedance Attributes

Rafael Souza, David Lumley, Jeffrey Shragge

Petroleum Exploration Society of Australia (PESA)

... and therefore time-lapse data in the amplitude domain should be used to update reservoir fluid-flow model properties. In the UNISIM-H model ∆ are caused...

2016

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

Multiple, Diffractions and Diffracted Multiples in the South China Sea: How Dense Does Our Acquisition Geometry Need to be? (Geophysics Paper 16)

Rosemary K Quinn, Lynn B Comeaux

Geological Society of Malaysia (GSM)

... be horizontal over the scale of the SRME aperture in order for the model to be predicted accurately. Clearly, this is rarely the case, but as long...

2011

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

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...

2023

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