An automatic velocity picking method based on object detection

Ce Bian, Weifeng Geng, Ping Yang, Pengyuan Sun, Guiren Xue, Haikun Lin

International Meeting for Applied Geoscience and Energy (IMAGE)

... an automatic velocity spectrum picking method based on object detection, and applies neural network model named FCOS (Fully Convolutional OneStage Object...

Abstract: Hydrocarbon Generation and Expulsion Model for Upper Paleozoic Source Rocks in the Hangjinqi Area, Northern Ordos Basin, China;

Huijun Wang, Shuangfang Lu, Guiping Zhao

Search and Discovery.com

...Abstract: Hydrocarbon Generation and Expulsion Model for Upper Paleozoic Source Rocks in the Hangjinqi Area, Northern Ordos Basin, China; Huijun Wang...

Abstract: Missing Well-Log Data Prediction Using a Hybrid U-Net and LSTM Network Model; #91212 (2025)

Benard Sasu Oppong, Po Chen, En-Jui Lee, Wu-yu Liao

Search and Discovery.com

...Abstract: Missing Well-Log Data Prediction Using a Hybrid U-Net and LSTM Network Model; #91212 (2025) Benard Sasu Oppong, Po Chen, En-Jui Lee, Wu-yu...

Finding the reservoir in an intensely scattered wavefield: A case study from the Central Sichuan Basin, China

John Coffin, Mengmeng Zhang, Panos Doulgeris, Peter Haffinger, Angie Kelsay, Jinsong Li

International Meeting for Applied Geoscience and Energy (IMAGE)

... an elastic modelling scheme including interbed multiples and multiple mode conversions for the well-tie. A linear convolutional model results in perfectly...

GAN-based priors for Bayesian inference of subsurface geology at large scale

Kevin B. Daly, Tuan A. Tran, Brent D. Wheelock, Grant J. Seastream

International Meeting for Applied Geoscience and Energy (IMAGE)

... in the process stratigraphy simulations. One solution is to select a generative ML model with a fully convolutional architecture, where the latent coordinate...

Deep learning in salt interpretation from R&D to deployment: Challenges and lessons learned

Pandu Devarakota, Apurva Gala, Zhenggang Li, Engin Alkan, Yihua Cai, John Kimbro, Dean Knott, Jeff Moore, Gislain Madiba

International Meeting for Applied Geoscience and Energy (IMAGE)

... a critical role in velocity model building in both exploration and development fields. It is a time-consuming effort that requires key domain expertise...

Seismic reservoir characterization of the Strawn Group, northern part of the Eastern Shelf, King County, North-Central Texas: Case study

Osareni C. Ogiesoba

International Meeting for Applied Geoscience and Energy (IMAGE)

...-frequency model. These reflectivities are then convolved with the wavelet to get the synthetic seismogram which is compared with the actual seismic...

Improving pre-stack inter-trace variation extraction with a self-supervised learning approach

Yifeng Fei, Xin He, Bangli Zou, Jiandong Liang, Dajun Li

International Meeting for Applied Geoscience and Energy (IMAGE)

.... Notable examples include utilizing a geological and geophysical model-driven convolutional neural network (CNN) for the extraction of elastic parameter...

Understanding Seismic Amplitudes, by Steve Henry, #40135 (2004).

Search and Discovery.com

Chapter 7: Advanced Reservoir Characterization Using 3D Seismic Data in Badger Basin, Bighorn Basin, Wyoming

John E. Buggenhagen

Montana Geological Society

... by This method was selected due to its ability to output a smoothly-varying velocity function. This low-frequency velocity model...

Seismic image resolution enhancement with limited-well datasets using deep learning

Son Phan, Haibin Di, Wenyi Hu, Aria Abubakar

International Meeting for Applied Geoscience and Energy (IMAGE)

.... Lee, M. W., 1986, Spectral whitening in the frequency domain: USGS, 86–108. Li, J., X. Wu, and Z. Hu, 2021, Deep learning for simultaneous seismic...

An unsupervised intelligent stacking velocity analysis based on clustering

Lide Wang, Xingrong Xu, Jie Wu, Huahui Zeng, Yundong Yong, Yanxiang Wang

International Meeting for Applied Geoscience and Energy (IMAGE)

... efficiency and different standards. With the increasing application of wide-frequency, wide-azimuth and highdensity seismic exploration technology...

Convolutional Neural Networks for Semantic Segmentation of Micro-Pores in SEM Based Images of Shales

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Estimating subsurface geostatistical parameters from surface-based GPR reflection data using a deep-learning approach

Yu Liu, James Irving, Klaus Holliger

International Meeting for Applied Geoscience and Energy (IMAGE)

... task in a highly efficient manner. The proposed approach uses a convolutional neural network (CNN), which is trained on a vast database...

Fast self-supervised learning for reconstruction of 3D seismic data

Yinshuo Li, Wenkai Lu, We Cao

International Meeting for Applied Geoscience and Energy (IMAGE)

...) Complex convolution in the frequency domain Y f =CConv(X f ), X f =Xreal + iXimag , Yreal =Wreal Xreal − Wimag Ximag , (3) Yimag =Wreal Ximag + Wimag...

Data selection for velocity model estimation using a circular shot OBN survey

Felipe T. Costa, Sergio L. E. F. da Silva, Ammir A. Karsou, Felipe Capuzzo, Roger M. Moreira, Jorge Lopez, Marco Cetale

International Meeting for Applied Geoscience and Energy (IMAGE)

..., Seismic waveform inversion in the frequency domain, Part 1: Theory and verification in a physical scale model: Geophysics, 64, 888–901, doi: https...

SaltCrawler: AI solution for accelerating velocity model building

Engin Alkan, Yihua Cai, Pandu Devarakota, Apurva Gala, John Kimbro, Dean Knott, Gislain Madiba, Jeff Moore

International Meeting for Applied Geoscience and Energy (IMAGE)

... have recently increased in seismic imaging and velocity model building. We have seen many publications in this domain (Shi 2019, Zeng 2019, Kaul 2021...

Convolution neural networks fault interpretation in the Brazilian presalt

Hugo Garcia, Edimar Perico, Ana Moliterno, Alexandre Kolisnyk, Michael Lowsby

International Meeting for Applied Geoscience and Energy (IMAGE)

... (homogeneous and stratified salt) that causes imaging shadow zones, loss of high frequency content, and high Artificial intelligence algorithms...

Marchenko redatuming and seismic interferometry based internal multiple prediction for salt structures

Zhiwei Gu, Jianhua Geng, Ru-Shan Wu

International Meeting for Applied Geoscience and Energy (IMAGE)

...-pseudo-depth domain but simultaneously incur higher computational costs. Jakubowicz (1998) extends the Surface-Related Multiple Elimination (SRME...

Using Deep Learning and Distributed Machine Learning Algorithms to Forecast Missing Well Log Data; #42234 (2018)

Chijioke Ejimuda, Emenike Ejimuda

Search and Discovery.com

... model. The model accuracy was very low (about 10%). However, currently we are using auto encoder and convolutional neural network ResNet deep...

Deep learning based automatic marker separation

Atul Laxman Katole, Aria Abubakar, Edo Hoekstra, Srikanth Ryali, Tao Zhao

International Meeting for Applied Geoscience and Energy (IMAGE)

... entirely dispenses with convolutional and recurrence-based approaches, and instead rely on the attention mechanism to model the sequential nature...

Impact of an Integrated Seismic Data Processing Approach: A Case Study in Central Sumatra

Mars E. Semaan, Eddy Murhantoro, Maryanto, Achmad Bermawi, Budi Subianto, Hari Santoso

Indonesian Petroleum Association

... correction DMO / Pre-stack migration in the common offset domain NMO / Stack / Post-stack enhancement Frequency filtering / Scaling / Display...

Delineation of Gas Sands by Seismic Stratigraphy in the Pericocal Area, Orinoco Heavy Oil Belt, Venezuela: Section IV. Exploration Methods

J. Licheri, N. Parra

AAPG Special Volumes

... are interpreted in terms of geology and/or presence of fluids, according to the convolutional model. -- The parameters that allow changes in the seismic...

Identifying geologic facies through seismic dataset-to-dataset transfer learning using convolutional neural networks

Joseph Stitt, Adam Shugar, Rachael Wang

International Meeting for Applied Geoscience and Energy (IMAGE)

... for the baseline model we used is a public-domain survey called “Parihaka,” which contains offshore seismic data from the New Zealand government...

Reliable uncertainty estimation for seismic interpretation with prediction switches

Ryan Benkert, Mohit Prabhushankar, Ghassan AlRegib

International Meeting for Applied Geoscience and Energy (IMAGE)

... interpretation and provide a novel measure of uncertainty based on neural network forgetting. Specifically, we quantify uncertainty by the frequency in which...