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The AAPG/Datapages Combined Publications Database

Showing 55,891 Results. Searched 195,354 documents.

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Supervised Learning Applied to Rock Type Classification in Sandstone Based on Wireline Formation Pressure Data; #42539 (2020)

Jose Victor Contreras

Search and Discovery.com

... with oral presentation given at 2019 AAPG Geoscience Technology Workshop, Boosting Reserves and Recovery Using Machine Learning and Analytics, Houston, Texas...

2020

Characterization of Depositional Facies Using Artificial Intelligence Method Based on Electrical Log Data

Muhammad Dhery Mahendra, Michella Ayu Pramesti, Vania Utami, Muhammad Rizqy Septyandy, Rezky Aditiyo

Indonesian Petroleum Association

...., Girelli, T. J., & Junior, F. C, 2020, Evaluation of machine learning methods for lithology classification using geophysical data. Computers...

2020

Deep carbonate reservoir characterization with unsupervised machine-learning approaches

Xuanying Zhu, Luanxiao Zhao, Xiangyuan Zhao, Yuchun You, Minghui Xu, Tengfei Wang

International Meeting for Applied Geoscience and Energy (IMAGE)

...Deep carbonate reservoir characterization with unsupervised machine-learning approaches Xuanying Zhu, Luanxiao Zhao, Xiangyuan Zhao, Yuchun You...

2023

Stratigraphic constraint for deep learning image segmentation of geological units

Boillot Lionel, Thouvenot Alexandre, Kuhn de Chizelle Julien, Guillon Sébastien

International Meeting for Applied Geoscience and Energy (IMAGE)

... Alaudah, Y., P. Michalowicz, M. Alfarraj, G. AlRegib, 2019, A machine learning benchmark for facies classification: Interpretation, 7, no. 3, 1A– T725, doi...

2023

Extended Abstract: Machine Learning Facies Classification as Applied to the Upper Devonian Duvernay Formation, Western Canadian Sedimentary Basin

Elisabeth G. Rau, Kathy Breen, Scott C. James, Stacy C. Atchley, Anna M. Thorson

GCAGS Transactions

..., Extremely randomized trees: Machine Learning, v. 63, p. 3–42, . Hall, B., 2016, Facies classification using...

2019

Abstract: Evaluation of a Machine Learning Approach to Detecting Channels in Seismic Volumes; #91204 (2023)

Marc Servais, Estanislao Kozlowski, Graham Baines, Andrew Davies

Search and Discovery.com

... and density. Using the synthetic seismic volume as input and channel masks derived from the facies grids as labels, we adopt a supervised learning approach...

2023

A Supervised Machine-Learning Approach to Stratigraphic Surface Picking in Well Logs from the Mannville Group of Alberta, Canada; #42403 (2019)

Justin Gosses, Licheng Zhang

Search and Discovery.com

... and Beyond: AAPG Studies in Geology 64, Chapter: 7. Hall, B., 2016, Facies classification using machine learning: The Leading Edge, v. 35/10, p. 906-909. Olea...

2019

Abstract: Geological Control in Machine Learning based Seismic Facies Recognition; #91204 (2023)

Sihai Zhang

Search and Discovery.com

...Abstract: Geological Control in Machine Learning based Seismic Facies Recognition; #91204 (2023) Sihai Zhang Geological Control in Machine Learning...

2023

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

... propose a method to accelerate seismic interpretation using an interactive approach to deep learning that allows geoscientists to be in complete...

Unknown

Abstract: Can Machine Learning Help Predict Channel Stacking Patterns in Deep-Water Systems?;

Noah Francis Vento, Lisa Stright, Stephen Hubbard, Brian Romans

Search and Discovery.com

... overall more successful for classifying channel body position than the unsupervised learning algorithms for both facies models. The classification...

Unknown

What samples must seismic interpreters label for efficient machine learning?

Ryan Benkert, Mohit Prabhushankar, Ghassan AlRegib

International Meeting for Applied Geoscience and Energy (IMAGE)

..., 2019a, A machine-learning benchmark for facies classification: Interpretation, 7, no. 3, SE175–SE187, doi: https://doi.org/10.1190/INT-2018-0249.1...

2023

The Power of Predictive Analytics in Oil Field Development: Integrating Machine Learning with Reservoir Hydrocarbon Data to Enable Enhanced Oil Recovery of Hugin Formation within the Theta Vest Structure

Lilik T. Hardanto, Fenny Chrisman

Indonesian Petroleum Association

...-lapse/4D seismic data to perform facies classification instead of conventional approaches. Machine learning can enhance the efficiency of Enhanced Oil...

2021

Abstract: Deep Learning Seismic Inversion for Reservoir Facies- Data Driven Workflow; #91204 (2023)

Bilal Saeed Syed, Samiran Roy

Search and Discovery.com

...Abstract: Deep Learning Seismic Inversion for Reservoir Facies- Data Driven Workflow; #91204 (2023) Bilal Saeed Syed, Samiran Roy Deep Learning...

2023

Breakthrough Business Opportunities in the Oil Industry for YPs and Small TeamŽ Geoscientists; #70325 (2018)

Susan Nash

Search and Discovery.com

... to performance history / history matching Probabilistic Rock Type Classification (Paradigm) • Generate probabilistic facies volumes calibrated...

2018

Introduction to Special Issue: Geoscience Data Analytics and Machine Learning

Michael J. Pyrcz

AAPG Bulletin

...Introduction to Special Issue: Geoscience Data Analytics and Machine Learning Michael J. Pyrcz 2022 2145 2148 106 11 MOTIVATION FOR THIS SPECIAL...

2022

Abstract: Integrating Petrophysics, Seismic Attributes, and Machine Learning for Shale Facies Identification and Prediction;

Justin Palmer, Lisa Goggin, Adam Halpert, Christopher Skelt, Laura Bandura, Huafeng Liu

Search and Discovery.com

...Abstract: Integrating Petrophysics, Seismic Attributes, and Machine Learning for Shale Facies Identification and Prediction; Justin Palmer, Lisa...

Unknown

Leveraging Unsupervised Machine Learning on Seismic Images of Miocene Deposits in the Carpathian Foredeep Basin for Facies Classification

Reva Wiratama, Fikrah Elhifzi Harahap, Imoleayo Fashagba, Kamil Cichostępski

Indonesian Petroleum Association

...Leveraging Unsupervised Machine Learning on Seismic Images of Miocene Deposits in the Carpathian Foredeep Basin for Facies Classification Reva...

2022

Sweet Infill Well Locations Prediction Using Multiple Supervised and Unsupervised Machine Learning Models

Mochammad Naufal Septifiandi, Ferdiansyah Rahman, Muhammad Husni Mubarak Lubis

Indonesian Petroleum Association

...Sweet Infill Well Locations Prediction Using Multiple Supervised and Unsupervised Machine Learning Models Mochammad Naufal Septifiandi, Ferdiansyah...

2023

Unsupervised Machine Learning Applications for Seismic Facies Classification

Satinder Chopra, Kurt J. Marfurt

Unconventional Resources Technology Conference (URTEC)

...Unsupervised Machine Learning Applications for Seismic Facies Classification Satinder Chopra, Kurt J. Marfurt URTeC: 557 Unsupervised Machine...

2019

An Innovative and Simple Approach to Spatially Evaluate a Proxy for Stress Shadow Effect of Unconventional Reservoir Completion Activity

Shane J. Prochnow, Alena Grechishnikova, Paymon Hossaini, Mohamed Ibrahim, Sandra Saldana

Unconventional Resources Technology Conference (URTEC)

... investigated the impact of completion parameters on the production performance of the wells in the Eagle Ford Shale by using machine learning models. Kong...

2022

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