Boosting Visualization of Image Logs in 3D Towards Automated Well-Centric Interpretation

Eya Ghamgui, Chandramani Shrivastava, Martin Carles, Josselin Kherroubi

Unconventional Resources Technology Conference (URTEC)

.... For example, using a lightweight deep learning model, the tool detects and visually highlights fracture features, while providing information...

Using mixture density networks for uncertainty and prediction in seismic reservoir characterization

Cornelius Rosenbaum, Ryan Warnick, Anar Yusifov, Reetam Biswas, Atish Roy

International Meeting for Applied Geoscience and Energy (IMAGE)

...–111. Khan, S., H. Rahmani, S. A. A. Shah, and M. Bennamoun, 2018, A guide to convolutional neural networks for computer vision: Synthesis Lectures...

Application of Machine Learning to Facies Classification of Carbonate Core Images

Sharinia Kanagandran

Southeast Asia Petroleum Exploration Society (SEAPEX)

... learning techniques. The study evaluated two commonly used machine learning algorithms, Random Forest (RF) and Convolutional Neural Networks (CNNs...

Abstract: Open-source Python Stack and Tools for Geoscientific Image Analysis and Interpretation -From research to deployment; #91204 (2023)

Mustafa Al Ibrahim

Search and Discovery.com

... learning as backend to automate the estimation partially or completely. Semantic segmentation modules use convolutional neural networks to extract rock...

Abstract: Different Flavors of the Marchenko-Equation-Based Internal Multiple Elimination Methods: the Trade-off between Fidelity, Computational Cost and Ease of Use; #91204 (2023)

Marcin Dukalski, Chris Reinicke

Search and Discovery.com

... that the target primaries are dressed with a convolutional filter representing the total overburden transmissions. Therefore, convolution...

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user1

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... by utilizing Convolutional Neural Networks(CNNs) and Wavelet-based approaches. This ensures a clear interpretation of subsurface characteristics for a better...

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)

... To build models with the ability to use cuttings extracted oil, model prediction is performed on topped dead oils and oil extracted from core. Figure 2...

A data-feature-policy solution for multiscale geological-geophysical intelligent reservoir characterization

Wenhao Zheng, Fei Tian, Qingyun Di, Jiangyun Zhang, Hui Zhou, Wang Zhang, Zhongxing Wang

International Meeting for Applied Geoscience and Energy (IMAGE)

... on Deep Belief Network, the geological prediction model was established. It was optimized by a double-loop filtering mechanism that selected the parameter...

Accelerated deep learning-based estimation of wavefront dips and curvatures and their application to 3D prestack data enhancement

Kirill Gadylshin, Ilya Silvestrov, Andrey Bakulin

International Meeting for Applied Geoscience and Energy (IMAGE)

... Attributes Deep Neural Network. It is based on automatic local wavefront attributes estimation using a specially trained convolutional deep neural network...

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...

Automated fault surfaces extraction from 3D fault imaging volume

Nam Nguyen, Alejandro Jaramillo

International Meeting for Applied Geoscience and Energy (IMAGE)

... be integrated into a geological model for identification of hydrocarbon bearing formations, improving structural trapping definition, and preventing drilling...

Improving Wolfcamp B3 Drilling and Production by Integrating Core, Mud logs, Electrical Logs, Seismic Inversion, Microseismic and Drilling Data

Hongzhuan Ye, Lowell Waite, Robert Meek

Unconventional Resources Technology Conference (URTEC)

... seismic inversion. Methods and Workflow Pre-stack seismic inversion attempts to remove the convolutional effects of the wavelet on the reflectivity...

Deep Convolutional Neural Networks for Seismic Salt-Body Delineation; #70360 (2018)

Haibin Di, Zhen Wang, Ghassan AlRegib

Search and Discovery.com

...Deep Convolutional Neural Networks for Seismic Salt-Body Delineation; #70360 (2018) Haibin Di, Zhen Wang, Ghassan AlRegib Deep Convolutional Neural...

An AI approach to using magnetic gradient tensor analysis for quick depth and property estimation

David A. Pratt, K. Blair McKenzie, Anthony S. White

Petroleum Exploration Society of Australia (PESA)

... into the expert system whereas, it is very difficult to understand how a trained neural net model relates to the underlying geology. The AI system...

Machine assisted drillhole interpretation of iron ore resource evaluation holes in the Pilbara

Daniel Wedge, Owen Hartley, Andrew McMickan, Eun-Jung Holden, Thomas Green

Petroleum Exploration Society of Australia (PESA)

... each drillhole. A 3D geological model can be created by identifying corresponding stratigraphic boundaries within multiple drillholes. These models...

Geophysics in gold hydrogen exploration

Mengli Zhang, Yaoguo Li

International Meeting for Applied Geoscience and Energy (IMAGE)

... and technological advances that can be reconfigured to support the hy- Figure 2: Illustration of geologic H 2 model including source rocks and reservoirs. The top...

Halokinetic rotating faults, salt intrusions, and seismic pitfalls in the petroleum exploration of divergent margins

Carlos L. Varela, Webster U. Mohriak

AAPG Bulletin

... and development of hydrocarbon reservoirs: A model from the Adelaide geosyncline, South Australia, in P. J. Post, D. L. Olson, K. T. Lyons, S. L. Palmes, P. F...

Probabilistic Modeling of Well Interference for Shale and Tight Development with Subsurface Uncertainty

Yuguang Chen, Ryan Burke, Tom Tran, Andrew Roark, Scott Hanson

Unconventional Resources Technology Conference (URTEC)

... realizations of model input parameters are considered for both petrophysical and geomechanical properties. Design of Experiments (DoE) are applied at each...

Using Machine Learning for Geosteering During In-Seam Drilling

Ruizhi Zhong, Ray L. Johnson Jr, Zhongwei Chen

Unconventional Resources Technology Conference (URTEC)

... effectively distinguish coals from noncoal formations during in-seam drilling. The developed machine learning model has the potential to identify coals...

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)

... methods such as grid searching require considerable computational effort. They are also prone to errors like any other model-based method. Despite efforts...

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2023 Rocky Mountain Section Meeting; - Abstracts, #91206 (2023).

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A Novel System for Determining Flaring Efficiency Utilizing Optical Methods and Artificial Intelligence

Ángel E. Esparza, Joe Etheridge

Unconventional Resources Technology Conference (URTEC)

... to implement multiple layers within neural networks and conduct operations in isolation of user’s active participation. Convolutional Neural Networks (CNN...

Outcrop to Subsurface Reservoir Characterization of the Mississippian Sycamore/Meramec Play in the SCOOP Area, Arbuckle Mountains, Oklahoma, USA

Benmadi Milad, Roger Slatt

Unconventional Resources Technology Conference (URTEC)

... of Devonian-Mississippian strata. (C) Lithological model of the Mississippian Sycamore-Meramec strata in the SCOOP area. Figure 2. Location of data...