Seismic imaging profile noise suppression based on self supervised deep learning: a case study in the Yellow Sea

Qiang Xu

International Meeting for Applied Geoscience and Energy (IMAGE)

..., and G. Hu, 2022, Ground truth-free 3-D seismic random noise attenuation via deep tensor convolutional neural networks in the time-frequency domain...

A strategy for acoustic impedance direct inversion in depth domain

Ruiqian Cai, Chengyu Sun, Shizhong Li

International Meeting for Applied Geoscience and Energy (IMAGE)

..., the time-domain inversion methods, which are based on convolutional model, fail to be directly applied to the depth-domain seismic inversion. To carry...

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...

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...

Improve automatic migrated gather processing with feature engineering and 4D convolutional neural networks

Wen Pan, Harry Rynja, Ramakrishna Dandu, Zaifeng Liu, Shuzhen Ye, Antonio De Lilla, Jay Chen, Jeremy Vila

International Meeting for Applied Geoscience and Energy (IMAGE)

... the information from adjacent inline and crossline gathers in addition to time/depth-offset domain. The new model is trained and tested on six surveys and the test...

Semi-automated prestack seismic inversion workflow using temporal convolutional networks

Hussain Alfayez, Robert Smith, Ayman Suleiman, Nasher AlBinHasan

International Meeting for Applied Geoscience and Energy (IMAGE)

... problems, the model often needs access to a long history of the input sequence. Regular convolutional neural networks (CNN) struggle to capture long-term...

Explainable AI: Can neural networks recognize first arrivals after wave separation?

Yanwen Wei, Zhenyu Zhu, Jicai Ding, Yichuan Wang

International Meeting for Applied Geoscience and Energy (IMAGE)

..., Applications of seismic polarization analysis: Geophysics, 59, 119–130. Sabbione, J. I., and M. D. Sacchi, 2016, Restricted model domain time Radon...

High precision microseismic phase picking and monitoring based on advanced deep learning

Jiayu Qiao, Jingye Li, Yaru Xue, Wenhua Xu, Yangkang Chen

International Meeting for Applied Geoscience and Energy (IMAGE)

.... In this paper, a convolutional neural network model based on a self-attention mechanism is proposed. It can not only meet the requirement that the input...

Enhancing seismic data quality: A machine learning approach to denoising and signal damage reduction

Mark Roberts, Olga Brusova, Leandro Gabioli, Alejandro Valenciano

International Meeting for Applied Geoscience and Energy (IMAGE)

... in the common shot domain and a self-supervised ML signal-add back model in the common channel domain. The supervised ML-based denoise (Brusova et al., 2021...

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

Search and Discovery.com

Mitigating elastic effects of acoustic full-waveform inversion with deep learning and application to field data

Dimitri Voytan, Adriano Gomes, Debanjan Datta, Ren-douard Plessix, Anu Chandran, Ken Matson

International Meeting for Applied Geoscience and Energy (IMAGE)

... convolutional network approach presented by Li et al. (2019) to a realistic 3D synthetic velocity model under a narrow-azimuth marine streamer acquisition...

Seismic diffractions separation and imaging based on convolutional neural network

Jiaxing Sun, Jidong Yang, Zhenchun Li, Jianping Huang, Jie Xu

International Meeting for Applied Geoscience and Energy (IMAGE)

...Seismic diffractions separation and imaging based on convolutional neural network Jiaxing Sun, Jidong Yang, Zhenchun Li, Jianping Huang, Jie Xu...

Relative geologic time generation based on 3D-CNNs and domain adaptation

Xin He, Bangli Zou, Yifeng Fei, Gang Yu, Dajun Li

International Meeting for Applied Geoscience and Energy (IMAGE)

...Relative geologic time generation based on 3D-CNNs and domain adaptation Xin He, Bangli Zou, Yifeng Fei, Gang Yu, Dajun Li Relative geologic time...

Time-lapse seismic joint inversion based on Zoeppritz equation in depth domain

Wenjin Li, Jingye Li, Lei Han, Zhen Liao

International Meeting for Applied Geoscience and Energy (IMAGE)

... records can be represented by convolutional models as： d = W * r , where, W represents time-domain seismic wavelets， thus the depth migration can...

Deep learning based wavefield separation method for VSP data

Gang Feng, Qin Su, Zhe Yang, Wei Yang, Jian-Hua Wang

International Meeting for Applied Geoscience and Energy (IMAGE)

... parameters are shown in Table 1. Table 1 forward parameters Type parameters Wavelet Domain frequency Maximum record time Time sample rate Ricker...

Deep water OBN multiple prediction from local reflectivity in the Stolt domain

Cesar Ricardez

International Meeting for Applied Geoscience and Energy (IMAGE)

...)] (2) This multiple model is then directly subtracted in the (x,y,t) domain or could be adapted using traditional L2 energy minimization techniques...

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

Search and Discovery.com

Bayesian variational auto-encoder for seismic wavelet extraction

Ammar Ghanim, Ricard Durall, Norman Ettrich

International Meeting for Applied Geoscience and Energy (IMAGE)

...: Extracted wavelets using Inference C. From the top: a) using a model trained with time-domain loss, the model failed at retrieving the complicated phase...

Seismic absolute acoustic impedance inversion using domain adversarial based transfer learning

Anjali Dixit, Animesh Mandal

International Meeting for Applied Geoscience and Energy (IMAGE)

... time perform accurate impedance estimation on source data using the developed framework based on adaptive domain adversarial neural network (aDANN...

Abstract: CO2 Distribution Prediction Using Machine Learning Based Proxy Model in Geological Carbon Sequestration;

Zhi Zhong, Alexander Sun

Search and Discovery.com

... knowledge and assumptions on input data distributions. In particular, our cDC-GAN model is designed to learn cross-domain mappings between high...

RNN-based seismic velocity model building: Improving generalization using hybrid training data

Hani Alzahrani, Jeffrey Shragge

International Meeting for Applied Geoscience and Energy (IMAGE)

... feature in these approaches is the use of time-domain gathers for network input, which requires all time-domain data be simultaneously input...

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...

DL-fused elastic FWI: Application to marine streamer data

Pavel Plotnitskii, Oleg Ovcharenko, Vladimir Kazei, Daniel Peter, Tariq Alkhalifah

International Meeting for Applied Geoscience and Energy (IMAGE)

.... METHOD OVERVIEW The idea of this method is to directly map high-wavenumber model updates from time-domain FWI into low-wavenumber model updates (Figure...

Separation of simultaneous source wavefields using convolutional neural network

Zhehao Li, Hua-Wei Zhou, Kang Fu

International Meeting for Applied Geoscience and Energy (IMAGE)

... not exhibit image Gaussian noise features, we modified the network to train the model in common receiver gathers domain to directly predict...

3D real-time imaging for electromagnetic fracturing monitoring based on deep learning

Zhigang Wang, Yao Lu, Ying Hu, Yinchu Li, Ke Wang, Dikun Yang

International Meeting for Applied Geoscience and Energy (IMAGE)

... and the American Association of Petroleum Geologists 3D real-time imaging for electromagnetic fracturing monitoring based on deep learning model...