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

Search and Discovery.com

Neural network assisted responses simulation and data correction of array laterolog in invaded formations

Yueyang Han, Lei Wang, Donghan Hao, Xiyong Yuan, Nan Wang, Zhen Yang, Jianwen Zhou, Liwei Li

International Meeting for Applied Geoscience and Energy (IMAGE)

... required per logging point, rendering them impractical for real-time applications. To overcome this issue, we set the formation model as the inputs...

Abstract: Predicting the Distribution of Subsurface Sedimentary Facies Using Deep Convolutional Progressive Generative Adversarial Network (Progressive GAN);

Suihong Song, Tapan Mukerji, Jiagen Hou

Search and Discovery.com

...Abstract: Predicting the Distribution of Subsurface Sedimentary Facies Using Deep Convolutional Progressive Generative Adversarial Network...

Abstracts: The Reflectivity Response of Multiple Fractures and its Implications for Azimuthal AVO Inversion; #90173 (2015)

Olivia Collet, Benjamin Roure, Jon Downton

Search and Discovery.com

... studying various rock physics models in order to model the impact of multiple fractures on the elastic parameters of an isotropic medium. Then, we...

Rapid Play Evaluation through AI Interpretation

Jacob Smith, Peter Szafian

Australian Petroleum Production & Exploration Association (APPEA) Journal

... inputs to interpretation and model­ ling (Han and Cader 2020). These techniques provide highquality imaging of faults in a fraction of the time...

Leveraging source-over-cable marine seismic field data for near offset reconstruction with deep learning

Owen Rohwer Huff, Jan Erik Lie, Andreas Kjelsrud Evensen, Aina Juell Bugge

International Meeting for Applied Geoscience and Energy (IMAGE)

... data collected with source-over-cable acquisition geometry as training data. First, a convolutional neural network (CNN) is trained to reconstruct...

Interpolated fast and computational-efficient multidimensional singular spectrum analysis (I-FMSSA) for compressive simultaneous-source data processing

Rongzhi Lin, Yi Guo, Fernanda Carozzi, Mauricio D. Sacchi

International Meeting for Applied Geoscience and Energy (IMAGE)

... of receivers recording the data stimulated by several sources fired at close and randomdistributed time intervals. Despite being a great idea from a source...

DASF: A high-performance and scalable framework for large seismic datasets

Julio C. Faracco, Otávio O. Napoli, João Seródio, Carlos A. Astudillo, Leandro A. Villas, Edson Borin, Alan Souza, Daniel Miranda, João Paulo Navarro

International Meeting for Applied Geoscience and Energy (IMAGE)

..., the attribute to be calculated, the ML model to be trained or the waiting time in the HPC system’s queues. Finally, once the system finishes...

Joint Identification of Lithology and Lithofacies in Core Images Based on Deep Learning

Han Wang, Feifei Gou, Hanqing Wang, Shengjuan Cai

Unconventional Resources Technology Conference (URTEC)

... the lithology identification model. Two lithofacies recognition models are trained for different lithology types. For a core image, the lithology is first...

Probabilistic seismic interpolation with the implicit prior of a deep denoiser

Matteo Ravasi

International Meeting for Applied Geoscience and Energy (IMAGE)

... velocity model that mimics the Volve field (see Ravasi et al. (2022) for more details on the data creation process). Second, we consider the Volve field...

Automation of passive seismic processing via machine learning and physics-informed methods

Ivan Lim Chen Ning, Laura Swafford, Mike Craven, Kevin Davies, Evan Earnest, Dean Thornton

International Meeting for Applied Geoscience and Energy (IMAGE)

... reduces the time required to process passive seismic data. INTRODUCTION Seismic event location processing requires the identification of phase arrivals...

Time-Lapse Petro-Elastic and Seismic Modeling to Evaluate Fracturing Efficiency in Low-Permeability Reservoirs

Masoud Alfi, Zhi Chai, Anshuman Pradhan, Travis Ramsay, Maria Barrufet, John Killough

Unconventional Resources Technology Conference (URTEC)

... inputs, normal incidence seismic traces are forward-modeled through the convolutional model shown in Eq. 10. A zero-phase Ricker wavelet with a central...

Diagenesis and pore pressure induced dim spots „ Advances on AVO analysis of high-impedance reservoirs

Antonio Pessoa, Mark Chapman, Giorgos Papageorgiou

International Meeting for Applied Geoscience and Energy (IMAGE)

... stress scenario. Pressure-dependent AVO Analysis Seismic and Well Data Interpretation To conduct this AVO analysis, we assume a convolutional model...

Improving Microseismic Denoising Using 4D (Temporal) Tensors and High-Order Singular Value Decomposition

Keyla Gonzalez, Eduardo Gildin, Richard L. Gibson Jr.

Unconventional Resources Technology Conference (URTEC)

...nd time. The compressed model demonstrated the improvement of big data analysis by cutting down the execution time from months to seconds. In a...

Application of Bayesian Optimized Deep Bi-LSTM Neural Networks for Production Forecasting of Gas Wells in Unconventional Shale Gas Reservoirs

Y. Kocoglu, S. Gorell, P. McElroy

Unconventional Resources Technology Conference (URTEC)

... (Shahkarami & Mohaghegh, 2020). Therefore, a comprehensive model that is less computationally expensive and less time consuming than history matching...

Abstract: Post-stack Inversion of the Hussar Low Frequency Seismic Data; #90187 (2014)

Patricia E. Gavotti, Don C. Lawton, Gary F. Margrave, and J. Helen Isaac

Search and Discovery.com

... on the convolutional model of the seismic trace according to the equation 1: , (1) where S is the seismic trace, W is the wavelet, R is the reflectivity and N...

Abstracts: Application of Neural Network Analysis and Post-Stack Inversion - Case Studies in Alberta; #90173 (2015)

Somanath Misra and Satinder Chopra

Search and Discovery.com

... the P-impedance from the post-stack data by way of model based inversion as well as neural network analysis. We are showing comparisons of the results...

Using Machine Learning for Geosteering During In-Seam Drilling

Ruizhi Zhong, Ray L. Johnson Jr, Zhongwei Chen

Unconventional Resources Technology Conference (URTEC)

... the relationship between the inputs and the output. In this study, the inputs of the machine learning model include common real-time surface...

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)

..., particularly deep learning convolutional neural networks have been used successfully in fault interpretation in seismic data around the world with different...

Simulating seismic data using generative adversarial networks

Bradley C. Wallet, Eyad Aljishi, Hussain Alfayez

International Meeting for Applied Geoscience and Energy (IMAGE)

... International Conference on Machine Learning, 70, 214–223. Chellapilla, K., S. Puri, and P. Simard, 2006, High performance convolutional neural...

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

John E. Buggenhagen

Montana Geological Society

... occurrence in Badger Basin. The extra time spent testing and optimizing the processing sequence proved vital to refining the final model...

Fluids characterization using cuttings extracts analyzed by gel permeation chromatography

G. Eric Michael, Julian Moore, Lloyd Jones, Alexandra Cely, Gulnar Yerkinkyzy, Tao Yang

International Meeting for Applied Geoscience and Energy (IMAGE)

... polystyrene are applied (Espada et al., 2011, Yarranton et al., 2015, Vargas and Chapman, 2015). For GPC, retention time is commonly referred to as retention...

Improving Resolution and Clarity with Neural Networks; #41911 (2016)

Christopher P. Ross

Search and Discovery.com

... and anisotropic model parameters simultaneously with wave-equation modeling. Well logs may be used as part of the low-frequency initial model building...

Abstract: P-wave AVAz Modeling: A Haynesville Case Study; #90224 (2015)

Jon Downton

Search and Discovery.com

... but for simplicity this paper focuses on convolutional modeling. Typically a 1D layered earth model is assumed for which the interpreter assigns elastic...

The Perfect Frac Stage, Whats the Value?

Craig Cipolla, Ankush Singh, Mark McClure, Michael McKimmy, John Lassek

Unconventional Resources Technology Conference (URTEC)

.... The data requirements for this early model were fracture treatment design and completion parameters. Semi real-time inputs included rate, treating...