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Keywords: neural network
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Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3751735
... contrastive learning methodology in a semantic segmentation task. neural network machine learning partition upstream oil & gas reservoir characterization contrastive learning artificial intelligence learning segmentation volumetric supervised contrastive learning presented american...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3751782
... data for a specific seismic survey. upstream oil & gas reservoir characterization learning architecture deep learning machine learning scenario computation neural network dl architecture exploration geophysicist cutting-edge dl architecture resolution hu-net ensemble...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3751787
... assumptions of such methods. In this study, we apply a long short-term memory (LSTM) neural network model to core measurements of TOC and well log data, for the identification of TOC-rich zones in shale formations. Using data from the Duvernay and Barnett shale formations, we generate layer unit data sets...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3751804
... neural network machine learning architecture american association alignment procedure seismic amplitude boundary augmentation exploration geophysicist applied geoscience energy 10 society compute outlier rectangle An integrated workflow of improving the accuracy of first arrivals...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3751821
... a reasonable good velocity model. Here, we build the salt body using low frequency FWI with the aid of neural networks, specifically U-net. The inversion is implemented in a multi-scale fashion and the networks for flooding and unflooding the salt are applied after each scale. We start the inversion from...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3751887
... of recording. We created a convolutional neural network that can automatically detect microseismic events in DAS data. Prior work (Lellouch et al., 2021; Huot et al., 2021b), displayed the results of our network when tested on DAS data taken during well-stimulation phases. Here, we run our algorithm through 2...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3751935
... to that based on rigorous methods. upstream oil & gas well logging surrogate artificial intelligence machine learning neural network kl divergence workflow simulation accuracy exploration geophysicist quantification energy 10 modeling applied geoscience electromagnetic modeling deep...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3744720
... deep learning international application neural network reservoir characterization prediction figure 6 figure 5 applied geoscience american association society expanded abstract dataset figure 8 geophysics waveform inversion fwi exploration geophysicist inversion bandwidth extension...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3745050
... a combination of machine learning and the physics of wave propagation. Unlike a conventional supervised machine learning, we do not require known answers to train our network. The multicomponent shot gathers are input to a convolutional neural network (CNNs) based auto encoder whose outputs are used as P-wave...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3745217
... designs an automatic velocity spectrum picking method based on object detection, and applies neural network model named FCOS (Fully Convolutional One-Stage Object Detection) (Tian et al., 2019) to implement the automatic velocity spectrum picking. In this method, the velocity spectrum is processed...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3745255
... and the nonlinear operators. neural network reservoir characterization discriminator bayesian inference hicond-gan applied geoscience american association upstream oil & gas artificial intelligence bayesian rockavo operator international energy 10 latent zoeppritz equation inversion...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3728409
.... To help identify compartmenting faults across the field, we utilized a machine learning-based approach to quickly help predict the location of the faults. We also trained a probabilistic neural network to predict areas of high net-to-gross reservoir which we correlate to wells within our study area...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3728722
... is designed to improve the joint inversion results iteratively using multi-physics data by combining deep neural networks (DNNs) and the traditional inversion workflow together. Particularly, our proposed DLE joint inversion framework takes the individually inverted models, instead of sensing data...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3729456
...-resolution GPR images in real-time. Our method is based on a supervised attention-based neural network where we train the neural network using a multiscale supervision functionality and improve its feature learning capability using an attention-based block at multiple spatial scales. We also develop...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3729992
... Bayesian statistic and many other methods not mentioned here. More recently, there has been work in Bayesian approaches to neural networks, which endow the parameters of neural networks with prior distributions and exploiting the flexibility of neural network architectures to model complex behavior. We...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3730253
.... deep learning upstream oil & gas artificial intelligence inversion correction machine learning applied geoscience colombo procedure neural network reservoir characterization dataset exploration geophysicist asia government saudi arabia government international expec advanced...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3730701
... unsupervised machine-learning (ML) methodology for efficient and accurate seismic impedance inversion. The first stage utilizes the generalization capability of convolutional neural networks (CNN) to produce realistic estimates of the acoustic impedance (AI), whereas the second stage incorporates physics...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3734278
... & gas seismic model inversion neural network reservoir characterization applied geoscience geophysics dnn exploration geophysicist energy 10 noise full-waveform inversion expanded abstract fwi society waveform inversion american association classification application Estimate near...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3734615
... of the subsurface geology. deep learning reservoir characterization artificial intelligence neural network machine learning upstream oil & gas facies international exploration geophysicist deep learning technique energy 10 applied geoscience refining prediction seismic cube shale inorganic...
Proceedings Papers

Publisher: Society of Exploration Geophysicists
Paper presented at the SEG/AAPG International Meeting for Applied Geoscience & Energy, August 28–September 1, 2022
Paper Number: SEG-2022-3734950
... as a fully automatic facies predictor rather than a baseline interpretation tool. neural network prediction deep learning machine learning upstream oil & gas artificial intelligence facies international american association exploration geophysicist dataset reservoir characterization...

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