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The AAPG/Datapages Combined Publications Database
Showing 622 Results. Searched 200,357 documents.
Seismic data interpolation via frequency-constrained 3D inception Unet
Yen Sun, Paul Williamson
International Meeting for Applied Geoscience and Energy (IMAGE)
... a second label – the data transformed into the frequency-wavenumber domain; this requires the addition of a Fourier Transform layer to the architecture...
2022
Abstract: Short-time Wavelet Estimation in the Homomorphic Domain; #90174 (2014)
Roberto H. Herrera and Mirko van der Baan
Search and Discovery.com
... phases in both the wavelet and the reflectivity. Theory The seismic signal is described by the convolutional model (Ulrych, 1971): s(t) = w(t) ⋆ r...
2014
Deep Dix: Enhancing interval velocity model estimation through adversarial regularization
Joseph Stitt, Robert Clapp, Biondo Biondi
International Meeting for Applied Geoscience and Energy (IMAGE)
... that Convolutional Neural Networks (CNNs) have successfully generated mappings from low-frequency shot gathers to low-wavenumber Earth model...
2023
Filter-Bank Strategies for Efficient Computation of Radon Transforms for SNR Enhancement
Mauricio D. Sacchi
Search and Discovery.com
... and parabolic paths (for a frequency domain implementation) and linear and hyperbolic paths (for a time-variant/time domain numerical implementation...
Unknown
Filter-Bank Strategies for Efficient Computation of Radon Transforms for SNR Enhancement
Mauricio D. Sacchi
Search and Discovery.com
... and parabolic paths (for a frequency domain implementation) and linear and hyperbolic paths (for a time-variant/time domain numerical implementation...
Unknown
Automating the thresholding of multi-stage iterative source separation with priors using machine learning
Nam Pham, Rajiv Kumar, Sunil Manikani, Yousif Izzeldin Kamil Amin, Phillip Bilsby, Massimiliano Vassallo, Tao Zhao
International Meeting for Applied Geoscience and Energy (IMAGE)
... be the frequency-wavenumber (FK), wavelet, or seislet domain. The iterative source separation algorithm casts the problem as an inversion and solves the basis...
2024
Estimate near-surface velocity with reversals using deep learning and full-waveform inversion
Yong Ma, Xu Ji, Weiguang He, Tong Fei
International Meeting for Applied Geoscience and Energy (IMAGE)
..., R. G., 1999, Seismic waveform inversion in the frequency domain, Part 1: Theory and verification in a physical scale model: Geophysics, 64, 888–901...
2022
Seismic impedance inversion via neural networks and linear optimization algorithm
Bo Zhang, Yitao Pu, Ruiqi Dai, Danping Cao
International Meeting for Applied Geoscience and Energy (IMAGE)
..., and a low frequency model. The loss function of PINNs is designed to minimize the difference between real seismograms and synthetic seismic...
2024
Transfer learning seismic and GPR diffraction separation with a convolutional neural network
Alexander Bauer, Jan Walda, Dirk Gajewski
International Meeting for Applied Geoscience and Energy (IMAGE)
...Transfer learning seismic and GPR diffraction separation with a convolutional neural network Alexander Bauer, Jan Walda, Dirk Gajewski Transfer...
2022
Depositional Facies Identification in Wireline Log Patterns Using 1D Convolutional Neural Network (CNN) Deep Learning Algorithms
Galatio Giovani Prabowo, Muhammad Fahmi Ramdani, Abiyyu Daffa Revanzha, Brian Muara Sianturi, Natalia Angel Momongan
Indonesian Petroleum Association
... to use Python, generating dummy data, training data, and model testing. The chosen tool for this research is the Convolutional Neural Network (CNN...
2024
Bi-directional LSTM-based non-causal deconvolution
G. Roncoroni, I. Deiana, E. Forte, M. Pipan
International Meeting for Applied Geoscience and Energy (IMAGE)
.... This varying range of frequency in the input dataset gives us the ability to deal with different frequencies. Our training approach utilizes a convolutional...
2024
VSP Guided Reprocessing and Inversion of Surface Seismic Data
R. Gir, Dominique Pajot, Serge Des Ligneris
Southeast Asia Petroleum Exploration Society (SEAPEX)
... seismic data is known as the “convolutional model of the seismogram”. This model states that after proper data processing, the final seismic data has...
1988
Improved Resolution of Thin Turbiditic Sands in Offshore Sabah with Bandwidth Extension A Pilot Study (Paper C11)
G. Yu, N. Shah, M. Robinson, N. H. Nghi, A. A. Nurhono, G. S. Thu
Geological Society of Malaysia (GSM)
... by a convolutional-like process in the CWT domain as illustrated in Figure 2. This effectively reshapes the wavelet and broadens the spectrum. Any...
2012
Sparse time-frequency representation based on Unet with domain adaptation
Yuxin Zhang, Naihao Liu, Yang Yang, Zhiguo Wang, Jinghuai Gao, Xiudi Jiang
International Meeting for Applied Geoscience and Energy (IMAGE)
... propose the sparse time-frequency representation (STFR) based on Unet with domain adaptation (STFR-UDA) model for solving these issues. First, we...
2022
Looking for a simplified and generalized training set in ML applications for gravity modelling
Luigi Bianco, Ciro Messina, Maurizio Fedi
International Meeting for Applied Geoscience and Energy (IMAGE)
... be seen as the building blocks of each gravimetric anomaly. Here, we discuss preliminary results obtained with a Convolutional Neural Network (CNN...
2023
A method of relative impedance holography-inversion based on reflection coefficient inversion
Jiangfeng Zheng, Jialin Sun, Zongyu Zhen, Shaoxuan Li
International Meeting for Applied Geoscience and Energy (IMAGE)
...) 𝑤 Where r(t, f) is the time-frequency spectrum of r(t), 𝑡 𝑤 is half-length of the time window. Assuming a convolutional seismogram and known wavelet...
2022
Synthetic-data-driven deep learning method for elastic parameter inversion
Shuai Sun, Luanxiao Zhao, Huaizhen Chen, Zhiliang He, Jianhua Geng
International Meeting for Applied Geoscience and Energy (IMAGE)
... coefficient sequences; Finally, the Zoeppritz equation and the convolutional model is adopted to synthesize the AVO gather sets. The wavelets used...
2023
4D Finite Difference Forward Modeling within a Redefined Closed-Loop Seismic Reservoir Monitoring Workflow, #41922 (2016).
David Hill, Dominic Lowden, Sonika, Chris Koeninger
Search and Discovery.com
...-field coupled dynamic integrated earth model to surface. From which 3D grids of petro-elastic parameters for a range of reservoir simulations...
2016
Feature Detection for Digital Images Using Machine Learning Algorithms and Image Processing
Xiao Tian, Hugh Daigle, Han Jiang
Unconventional Resources Technology Conference (URTEC)
... is increased greatly. There are 16 weight layers in vgg16 model, including 13 convolutional layers and 3 fully-connected layers. There are 19 weight...
2018
Nonuniform dispersed source arrays for broadband seismic acquisition
Joaqun A. Acedo, Mauricio D. Sacchi
International Meeting for Applied Geoscience and Energy (IMAGE)
...-DSA data via the convolutional model and a source operator that plays the role of the restriction operator in CS (Candes, 2008). The latter contains...
2023
Seismic Forward Modeling of Semberah Fluvio-Deltaic Reservoir
Adi Widyantoro, Wahyu Dwijo Santoso
Indonesian Petroleum Association
..., or a convolutional process between the seismic waveform and a Gaussian function, has been applied to the rotated seismic lines in order to reduce high-frequency...
2021
Deep learning approach for denoising and resolution enhancement of poststack seismic data
Ruslan Malikov, Tatyana Yusubova, Izat Shahsenov
International Meeting for Applied Geoscience and Energy (IMAGE)
... complexity, frequency content, and signal-to-noise ratio (SNR). Synthetic seismic data without the added noise template is used to train the denoising model...
2024
Interactive channel interpretation using deep learning
Hao Zhang, Peimin Zhu, Zhiying Liao, Zewei Li, Dianyong Ruan
International Meeting for Applied Geoscience and Energy (IMAGE)
..., it is difficult to extract channels completely. With the development of machine learning technology, convolutional neural network (CNN) is widely...
2022
Development and Application of a Real-Time Drilling State Classification Algorithm with Machine Learning
Yuxing Ben, Chris James, Dingzhou Cao
Unconventional Resources Technology Conference (URTEC)
... drilling analytics system is automatic rig state detection. High frequency time series data (typically one data point per second) from multiple sensors...
2019
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