Bridging the gap: Deep learning on seismic field data with synthetic training for building Gulf of Mexico velocity models

Stuart Farris, Robert Clapp

International Meeting for Applied Geoscience and Energy (IMAGE)

... Clapp, Stanford University SUMMARY This study employs Convolutional Neural Networks (CNNs) to predict low-wavenumber seismic velocity models to serve...

Strike-slip fault skeletonization based on deep learning cascade ant tracking method

Zhipeng Gui, Junhua Zhang, Rujun Wang, Yintao Zhang, Chong Sun, Mei Yang

International Meeting for Applied Geoscience and Energy (IMAGE)

.... Then, utilizing advantages of ant tracking, fault skeletonization also called as fault thinning is operated. Model test and real data application show: (1...

Date-driven seismic velocity inversion via deep residual U-net

Yiran Huang, Chuang Pan, Qingzhen Wang, Jun Li, Jianhua Xu

International Meeting for Applied Geoscience and Energy (IMAGE)

..., into convolutional neural network, which can propagate useful discriminative information from the low level to the high level, and thus improve...

A two-stage deep learning workflow for automated seismic inversion

Haibin Di, Wenyi Hu, Aria Abubakar

International Meeting for Applied Geoscience and Energy (IMAGE)

... of four major steps, (i) large-scale structural model construction, (ii) initial property model estimation via a multi-task convolutional neural...

Enhancing fiber-optic DAS microseismic event detection in imbalanced data using embedding space optimization

Min Jun Park, Hassan Almomin, Bob Clapp

International Meeting for Applied Geoscience and Energy (IMAGE)

... networks are trained, followed by the extraction of embeddings to define class centers in the embedding space. The embedding model is then fine-tuned...

3D Seismic Facies Classification on CPU and GPU HPC Clusters

Sergio Botelho, Vishal Das, Davide Vanzo, Pandu Devarakota, Vinay Rao, Santi Adavani

Unconventional Resources Technology Conference (URTEC)

...; second, neural network design becomes increasingly challenging due to the higher number of parameters in the model and its larger training time. We...

GeoMind: An intelligent earth model building tool

Saleh Al Saleh, Ewenet Gashawbeza, Mustafa Marzooq, Hussam Banaja, Husain Al Shakhs, Jianwu Jiao

International Meeting for Applied Geoscience and Energy (IMAGE)

...GeoMind: An intelligent earth model building tool Saleh Al Saleh, Ewenet Gashawbeza, Mustafa Marzooq, Hussam Banaja, Husain Al Shakhs, Jianwu Jiao...

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...

Internal multiple elimination with an inverse-scattering theory guided deep neural network

Zhiwei Gu, Liurong Tao, Haoran Ren, Ru-Shan Wu, Jianhua Geng

International Meeting for Applied Geoscience and Energy (IMAGE)

... with the convolutional operation. Combining the CNN with the autoencoder can improve the feature extraction ability of the network model and have higher computational...

An Introduction to Deep Learning: Part III

Lasse Amundsen, Hongbo Zhou, Martin Landrø

GEO ExPro Magazine

... computer model that learns to perform classification tasks directly from images. The one that started it all was the 2012 publication ‘ImageNet...

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...

InvMixer An efficient deep neural network for seismic inversion

Tianyi Zhang, Mauricio Araya-Polo, Anshumali Shrivastava

International Meeting for Applied Geoscience and Energy (IMAGE)

... layers in UNet use learnable kernels with of size 3×3 or 5×5 to model the relationships between traces. Since a single convolutional layer has limited...

Magnetotelluric inversion using supervised learning trained with random smooth geoelectric models

Lian Liu, Bo Yang, Yixian Xu, Dikun Yang

International Meeting for Applied Geoscience and Energy (IMAGE)

... frequencies and observation stations, noise, and the model equivalence regarding its resolution (Backus & Gilbert 1967; Parker 1983). Geophysicists...

High-resolution angle gather tomography with Fourier neural operators

Sean Crawley, Guanghui Huang, Ramzi Djebbi, Jaime Ramos, Nizar Chemingui

International Meeting for Applied Geoscience and Energy (IMAGE)

... model building with a modified fully convolutional network: 88th Annual International Meeting, SEG, Expanded Abstracts, 2086–290, doi: https://doi.org...

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...

A rock physics inversion method based on physics-guided autoencoder network

Zhuofan Liu, Umair bin Waheed, Ammar El-Husseini, Jiajia Zhang

International Meeting for Applied Geoscience and Energy (IMAGE)

...- guided convolutional neural network: Interpretation, 7, no. 3, SE161–SE174, doi: https://doi.org/10.1190/INT-2018-0236.1. Bosch, M., T. Mukerji, and E. F...

High-resolution seismic reservoir monitoring with multitask and transfer learning

Ahmed M. Ahmed, Ilya Tsvankin, Yanhua Liu

International Meeting for Applied Geoscience and Energy (IMAGE)

... or hydrocarbon production. This study leverages convolutional neural networks (CNNs), multitask learning (MTL), and transfer learning (TL) to accurately...

Coloured Seismic Inversion, a Simple, Fast and Cost Effective Way of Inverting Seismic Data: Examples from Clastic and Carbonate Reservoirs, Indonesia

Keith Maynard, Paulus Allo, Phill Houghton

Indonesian Petroleum Association

..., and although an interpretive low frequency model is not used, the technique provides a robust inversion that honours the impedance trend of available well data...

Abstract: Towards the Identification of Coal Macerals through Deep Learning

Na Xu, Qingfeng Wang, Pengfei Li, Mark A. Engle

The Society for Organic Petrology (TSOP)

... are compared with the other three existing image segmentation methods, including K-means [4], Gaussian mixture model (GMM), [5] and convolutional neural...

Evaluation of AI-enhanced processing for automated passive seismic detection and location

Aaron Booterbaugh, Evgeny Naumov

International Meeting for Applied Geoscience and Energy (IMAGE)

... model and provide access to the rich datasets collected by both public arrays and Nanometrics’s private installations. CONVOLUTIONAL NEURAL NETWORK...

Abstract: 3-D Volumetric Interpretation with Computational Stratigraphy Models

Lisa Goggin, Tao Sun, Maisha Amaru, Ashley Harris, Anne Dutranois, Andrew Madof

Houston Geological Society Bulletin

... of a fluvially-dominated delta was created. The depositional model is converted into seismic volumes of various frequencies (1D convolutional approach...

ABSTRACT: Deep forest cover classification of consecutive landsat imageries over Borneo

Azalea Kamellia Abdullah, Mohd Nadzri Md Reba, Nur Efarina Jali, Sikula Magupin, Diana Anthony

Geological Society of Malaysia (GSM)

... learning image classification algorithms such as Convolutional Neural Networks (CNN) attains higher accuracy mapping with low human interruption. Deep...

Applying Conditional Generative Adversarial Networks for Seismic Data Reconstruction

Search and Discovery.com

Abstract: Interactive Deep Learning Assisted Seismic Interpretation Technology Applied to Reservoir Characterization: A Case Study From Offshore Santos Basin in Brazil;

Ana Krueger, Bode Omoboya, Paul Endresen, Benjamin Lartigue

Search and Discovery.com

... Convolutional Neural Networks (CNN), the deep neural network acts as an extension of the interpreter to assist in mapping sub-surface geological...

Abstract: Automated Fault Detection from 3-D Seismic Using Artificial Intelligence „ Practical Application and Examples from the Gulf of Mexico and North Slope Alaska;

Andrew Pomroy, Zachary Wolfe

Search and Discovery.com

... in the realm of seismic attributes given its well established strengths in image pattern analysis and recognition. With this in mind, a Convolutional...