Supervised machine learning sedimentological characterization workflow: A tool to bridge the gap between qualitative and quantitative facies interpretation and uncertainty quantification

Anis Seksaf, Boris Kostic, Chloé Château, Daniel Clay, Kamel Tamene, Meriem Bertouche, Jan Van Der Wal, Raja Ramalingam, Abd El-Aziz Sabry, Boland Ghadeer Taleb, Chen Chao

International Meeting for Applied Geoscience and Energy (IMAGE)

...Supervised machine learning sedimentological characterization workflow: A tool to bridge the gap between qualitative and quantitative facies...

Integrating Machine Learning into Drawdown Workflows to Deliver Sustainable Well Performance

Yosmar Gonzalez, James Courtier, Claudia Garces, Edward Moncayo, Iris Wang

Unconventional Resources Technology Conference (URTEC)

...., 2001) method is a powerful ensemble machine learning technique used for both classification and regression tasks. It operates by generation...

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)

... facies classification with unsupervised learning, and seismic attribute estimation with deep learning models. As demonstrated by our results, DASF...

Natural Fracture Presence Prediction in Unconventional Reservoirs Using Machine Learning and Geostatistical Methods - Workflow and HFTS1 Case

Peace C. Eze, Lin Y. Hu

Unconventional Resources Technology Conference (URTEC)

...Natural Fracture Presence Prediction in Unconventional Reservoirs Using Machine Learning and Geostatistical Methods - Workflow and HFTS1 Case Peace C...

Unconventional Reservoir Microstructural Analysis Using SEM and Machine Learning

Amanda S. Knaup, Jeremy D. Jernigen, Mark E. Curtis, John W. Sholeen, John J. Borer IV, Carl H. Sondergeld, Chandra S. Rai

Unconventional Resources Technology Conference (URTEC)

...Unconventional Reservoir Microstructural Analysis Using SEM and Machine Learning Amanda S. Knaup, Jeremy D. Jernigen, Mark E. Curtis, John W. Sholeen...

Facies-induced bias in machine learning-enhanced seismic lithology (inversion)

Hongliu Zeng, Bo Zhang, Mariana Olariu

International Meeting for Applied Geoscience and Energy (IMAGE)

...Facies-induced bias in machine learning-enhanced seismic lithology (inversion) Hongliu Zeng, Bo Zhang, Mariana Olariu Facies-induced bias in machine...

Using deep learning for automatic detection and segmentation of carbonate microtextures

Claire Birnie, Viswasanthi Chandra

International Meeting for Applied Geoscience and Energy (IMAGE)

... advances in digital image analysis using machine learning methods provide a promising way forward to resolve this critical gap. In this study, we investigate...

Well Log Prediction Using Machine Learning

Sundeep Sharma

Oklahoma City Geological Society

...Well Log Prediction Using Machine Learning Sundeep Sharma 2021 50 55 Vol. 72 (2021) No. 2. (March/April) Bergen, K. J., Johnson, P. A., Maarten, V...

Detailed petroleum system insights using deep learning: A case study from the Scarborough Gas Field, offshore Australia

Scotty Salamoff, Julian Chenin, Benjamin Lartigue, Nguyen Phan, Paul Endresen

International Meeting for Applied Geoscience and Energy (IMAGE)

...Detailed petroleum system insights using deep learning: A case study from the Scarborough Gas Field, offshore Australia Scotty Salamoff, Julian...

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user1

Search and Discovery.com

... Inversion with Machine Learning for Reservoir Characterization Mohammed Farfour1, Said Gaci2 1 Sultan Qaboos University Algerian Institute of Petroleum 2...

Machine-learning prediction of slope channel facies using outcrop analog data: Tres Pasos Formation, Magallanes Basin, Chile

Patrick Ronnau, Lisa Stright, Stephen M. Hubbard, Brian W. Romans

International Meeting for Applied Geoscience and Energy (IMAGE)

...Machine-learning prediction of slope channel facies using outcrop analog data: Tres Pasos Formation, Magallanes Basin, Chile Patrick Ronnau, Lisa...

Seismic Interpretation with Machine Learning

Rocky Roden, Deborah Sacrey

GEO ExPro Magazine

...Seismic Interpretation with Machine Learning Rocky Roden, Deborah Sacrey GEO Physics Seismic Interpretation with Machine Learning Machine learning...

Convolution Neural Networks … If They can Identify an Oncoming Car, can They Identify Lithofacies in Core?; #42312 (2018)

Rafael Pires de Lima, Fnu Suriamin, Kurt Marfurt, Matthew Pranter, Gerilyn Soreghan

Search and Discovery.com

... consists of hundreds of mixed-object categories and millions of images. Although machine learning has been significantly used in geoscience fields...

Refining our understanding of the subsurface geology using deep learning techniques

Salma Alsinan, Philippe Nivlet, Hamad Alghenaim

International Meeting for Applied Geoscience and Energy (IMAGE)

.../10.1190/segam2021-3580362.1. Alaudah, Y., P. Michalowicz, M. Alfarraj, and G. AlRegib, 2019, A machine-learning benchmark for facies classification...

Statistical Analysis of the Petrophysical Properties of the Bakken Petroleum System

Aimen Laalam, Habib Ouadi, Ahmed Merzoug, Abderraouf Chemmakh, Aldjia Boualam, Sofiane Djezzar, Ilyas Mellal, Meriem Djoudi

Unconventional Resources Technology Conference (URTEC)

...in Using Big Data Analysis and Robust Machine Learning Algorithms. Lefever, Julie A. 2007. “Bakken Formation Middle Member Lithofacies 2.” North Dako...

Abstract: Recognizing facies in the Red River Formation of North Dakota using a Convolutional Neural Network; #90301 (2017)

Stephan H. Nordeng, Ian E. Nordeng, Jeremiah Neubert, Emily G. Sundell

Search and Discovery.com

...Abstract: Recognizing facies in the Red River Formation of North Dakota using a Convolutional Neural Network; #90301 (2017) Stephan H. Nordeng, Ian E...

Unsupervised machine learning for seismic facies classification applied in presalt carbonate reservoirs of the Bzios Field, Brazil

Dbora Ribeiro Barretto, Pedro Henrique Cunha de Macedo, Wagner Moreira Lupinacci, Raisa Carvalho Silva

International Meeting for Applied Geoscience and Energy (IMAGE)

...Unsupervised machine learning for seismic facies classification applied in presalt carbonate reservoirs of the Bzios Field, Brazil Dbora Ribeiro...

Mapping Oil-Prone Facies in 3D for Field Development and Optimizing Production: A Midland Basin Case Study

Paritosh Bhatnagar, Venkatesh Anantharamu, Ron Bianco

Unconventional Resources Technology Conference (URTEC)

... with a machine learning approach to map oil-prone saturation facies using high trace density seismic data. The results are validated at blind well locations...

How to Illuminate the Reservoir from Surface Seismic Data? Integrated Deep Learning Aided Waveform Inversion

Search and Discovery.com

A Physics-Guided Deep Learning Predictive Model for Robust Production Forecasting and Diagnostics in Unconventional Wells

Syamil Mohd Razak, Jodel Cornelio, Young Cho, Hui-Hai Liu, Ravimadhav Vaidya, Behnam Jafarpour

Unconventional Resources Technology Conference (URTEC)

.... 702 – 715. Bressan T. S., Souza M. Kehl de, Girelli T. J., Junior F. C. (2020) Evaluation of machine learning methods for lithology classification using...

Abstract: Integration of Multiple Seismic Tools to Identify Thin Tight Carbonate Reservoir in Northern Kuwait Field; #91204 (2023)

Abdulaziz Al-Busairi, Talal Al-Ghais, Subrata Bhukta, Reyad Abu-Taleb, Meshal Al-Wadi, Balqees Al-Ibrahim, Duaa Al-Kandari

Search and Discovery.com

... the waveform inversion, geostatistical waveform classification and machine learning based tools like the probabilistic fault-likelihood and thin-likelihood...

Supervised and Unsupervised Neural Networks Technique in Facies Classification and Interpretation

Jayanti Anggraini, Mega Ardhiani Puspa

Indonesian Petroleum Association

...Supervised and Unsupervised Neural Networks Technique in Facies Classification and Interpretation Jayanti Anggraini, Mega Ardhiani Puspa © IPA, 2011...

Abstract: Machine Learning Prediction of Slope Channel Facies Using Outcrop Analog Data, Tres Pasos Formation, Magallanes Basin, Chile; #91201 (2022)

Patrick Ronnau, Lisa Stright, Stephen M. Hubbard, and Brian W. Romans

Search and Discovery.com

...Abstract: Machine Learning Prediction of Slope Channel Facies Using Outcrop Analog Data, Tres Pasos Formation, Magallanes Basin, Chile; #91201 (2022...

PREDICTING LITHO-FACIES FROM SEISMIC DATA: A MACHINE LEARNING APPROACH ON SEISMIC ATTRIBUTES

Reza Nugraha, Galang Purnomo Adi, Depi Restiadi, and Luthfi Wira Wicaksana

Indonesian Petroleum Association

...PREDICTING LITHO-FACIES FROM SEISMIC DATA: A MACHINE LEARNING APPROACH ON SEISMIC ATTRIBUTES Reza Nugraha, Galang Purnomo Adi, Depi Restiadi...

Application of Artificial Intelligence on Black Shale Lithofacies Prediction in Marcellus Shale, Appalachian Basin

Guochang Wang, Yiwen Ju, Timothy R. Carr, Chaofeng Li, Guojian Cheng

Unconventional Resources Technology Conference (URTEC)

... neural network (ANN), and support vector machine (SVM), can solve complex nonlinear problems. In addition, learning algorithms based on AI could also...