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The AAPG/Datapages Combined Publications Database

Showing 8,497 Results. Searched 200,293 documents.

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Automatic well-log baseline correction via deep learning for rapid screening of potential CO2 storage sites

Misael M. Morales, Carlos Torres-Verdín, Michael Pyrcz, Murray Christie, Vladimir Rabinovich

International Meeting for Applied Geoscience and Energy (IMAGE)

... baseline correction for SP logs and the prediction of sweet spots for CO2 storage along a well. We develop a deep learning-based method for automatic...

2024

Machine Learning for Estimating Rock Mechanical Properties beyond Traditional Considerations

Yiwen Gong, Mohamed Mehana, Ilham El-Monier, Feng Xu, Fengyang Xiong,

Unconventional Resources Technology Conference (URTEC)

... insights and develop novel data-driven models. Regression tools could be as simple as least-square error or more advanced like Artificial Neural Network...

2019

Abstract: GIS-based map modelling using the weights of evidence method applied to acid rock drainage prediction in the Meguma Supergroup, Nova Scotia

Don Fox

Atlantic Geology

...Abstract: GIS-based map modelling using the weights of evidence method applied to acid rock drainage prediction in the Meguma Supergroup, Nova Scotia...

2000

ABSTRACT: Palaeogeographic and Geological Constraints on Coupled Ocean-Atmosphere Palaeo-Earth Systems Modeling for Source Rock Prediction in Frontier Basins; #90061 (2006)

Jim Harris, Rob Crossley, Frank Richards, Nick Stronach, Tim Hudson, Dan Burggraf, John Suter, Brad Huizinga, Samir Ghazi, Paul Markwick, Paul Valdes, and Roger Proctor

Search and Discovery.com

...ABSTRACT: Palaeogeographic and Geological Constraints on Coupled Ocean-Atmosphere Palaeo-Earth Systems Modeling for Source Rock Prediction...

2006

New Technology to Acquire, Process, and Interpret Transient EM Data; #41579 (2015)

Anton Ziolkowski, Richard Carson, David Wright

Search and Discovery.com

...) error criterion in filter design and prediction: Journal of Mathematics and Physics, v. 25, p. 261-278. Wright, D., A. Ziolkowski, and B. Hobbs, 2002...

2015

Modeling of an Unconventional Gas Accumulation Taking into Account Spatial Correlation, Greater Natural Buttes, Utah; #40655 (2010)

Ricardo A. Olea; Troy A. Cook; and James L. Coleman, Jr.;

Search and Discovery.com

... by the existing wells allowed preparation of a stochastic prediction of undiscovered resources, which range between 2.6 and 3.4 TSCF with a mean of 2.9 TSCF...

2010

Fractured Reservoir Characterization: Integrating Production and Seismic Data to Optimize Well Placement in Bluebell Field, Uinta Basin, NE Utah

Steven L. Adams, James Schuelke, Dennis Shannon, John Kucewicz, Christopher Latkiewicz

Unconventional Resources Technology Conference (URTEC)

..., the correlation was only 43 percent, with a probability error range of approximately one million barrels of fluid, resulting in an unacceptable prediction map...

2014

An Integrated Approach Towards Digital Outcrop Method In Natural Fracture Characterization: An Example From The Pre-Tertiary Alas Formation of North Sumatra Basin

Ilyas Anindita, Leon Taufani, Muhammad Gazali Rachman, Purnama Suandhi, Erlangga Septama

Indonesian Petroleum Association

...An Integrated Approach Towards Digital Outcrop Method In Natural Fracture Characterization: An Example From The Pre-Tertiary Alas Formation of North...

2022

Geological Facies Prediction Using Computed Tomography in a Machine Learning and Deep Learning Environment

Uchenna Odi, Thomas Nguyen

Unconventional Resources Technology Conference (URTEC)

...Geological Facies Prediction Using Computed Tomography in a Machine Learning and Deep Learning Environment Uchenna Odi, Thomas Nguyen URTeC: 2901881...

2018

Digital Seismograms: ABSTRACT

Carl H. Savit

AAPG Bulletin

...Digital Seismograms: ABSTRACT Carl H. Savit 1965 1766 1766 49 10. (October) To use digital seismograms economically and effectively, it is essential...

1965

A hybrid machine learning model for improving regression of mineral composition estimation using well logging data

Xiaojun Liu, Kezhen Hu, Stephen E. Grasby, Benjamin Lee

International Meeting for Applied Geoscience and Energy (IMAGE)

...) is added to model training to decrease the sensitivity and increase repeatability of model prediction. The comparison of metrics and correlation...

2024

Appendix D

Wayne K. Camp, Elizabeth Diaz, Barry Wawak

AAPG Special Volumes

... geometries: The Leading Edge, v. 20, p. 180–183. Keehm, Y., T. Mukerji, and A. Nur, 2004, Permeability prediction from thin sections: 3D...

2013

Hyperspectral imaging for the determination of bitumen content in Athabasca oil sands core samples

Michelle Speta, Benoit Rivard, Jilu Feng, Michael Lipsett, and Murray Gingras

AAPG Bulletin

... imaging is a remote sensing technique that can be defined as reflectance spectroscopy with a spatial context, where high-resolution digital imagery (∼1...

2015

Integrated Reservoir Characterization of Mississippian-Age Mid-Continent Carbonates, #30297 (2013)

Michael Grammer, Darwin Boardman, James Puckette, Jay Gregg, Priyank Jaiswal, Miranda Childress, Buddy Price, Beth Vanden Berg, Stephanie LeBlanc

Search and Discovery.com

... and tens of meter scale will aid the producer in identifying key producing intervals and also enhance the prediction of internal flow units and seals...

2013

Machine Learning Regressors and their Metrics to predict Synthetic Sonic and Brittle Zones

Ishank Gupta, Deepak Devegowda, Vikram Jayaram, Chandra Rai, Carl Sondergeld

Unconventional Resources Technology Conference (URTEC)

...nt uncertainty in prediction (± 2*mean square error). It is evident that random forest and extreme gradient boosting techniques also give among the lowest uncert...

2019

ABSTRACT: Water Depth, Seagrass, Algae, and Bottom Type Mapped with Airborne Multi-spectral Imagery in Tampa Bay

Raabe, E.A., Kovach, C.W.

GCAGS Transactions

... the physical outlining of features, dependent on the presence of visual clues and subject to operator expertise. The digital multi-spectral data offers...

2002

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