Abstract: Neural Network and 3D Seismic Techniques Improve the Prediction of Facies Distribution within a Submarine Channel Complex; #90063 (2007)

Search and Discovery.com

Estimated Ultimate Recovery Using the Digital Analogue Shale Model

Michael Friedel, Raul Rechden

Unconventional Resources Technology Conference (URTEC)

... of the self-organizing map. Neural Networks 37, 52-65. Malek, M.A., S. Harun, S.M. Shamsuddin, and I. Mohamad, 2008: Imputation of time series data via Kohonen...

Utilizing Machine Learning to Improve Reserves Estimation and Production Forecasting Accuracy

Ashutosh Sharma, Ishank Gupta, Thai Phi, Shubhranshu Ashesh, Ram Kumar, Fabio German Borgogno

Unconventional Resources Technology Conference (URTEC)

... (Breiman 1997), and artificial neural networks (Schmidhuber 1992, 2015), among others. In this study, multiple regression techniques are harnessed to develop...

Fact-Based Re-Frac Candidate Selection and Design in Shale - A Case Study in Application of Data Analytics

Shahab D. Mohaghegh

Unconventional Resources Technology Conference (URTEC)

... that were used to perform datadriven analysis and modeling. Those days they were simply referred to as artificial neural networks, or intelligent systems...

Machine Learning Methods for Handling Parameter Space Sampling Bias in Unconventional Well Performance Prediction

Oliver Rojas Conde, Henry Galvis Silva, Sebastien Matringe

Unconventional Resources Technology Conference (URTEC)

... significant modeling challenges that have spurred innovation in ML methodologies. Early studies relied on artificial neural networks (ANNs...

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)

.... Li, and P. Nivelt, 2020, Seismic facies classification using supervised convolutional neural networks and semi supervised generative adversarial...

Seismic data interpolation via frequency-constrained 3D inception Unet

Yen Sun, Paul Williamson

International Meeting for Applied Geoscience and Energy (IMAGE)

... streamers, in marine acquisitions. We started with a “standard”, 3D convolutional neural network (CNN) architecture: while computationally intense, a 3D...

Topological Data Analysis of Marcellus Play Lithofacies

Andrea, Cortis

Unconventional Resources Technology Conference (URTEC)

..., and Neural Network Classifiers are often used to make sense of vertical log profiles data. These methods, however, often produce less than satisfactory...

Karst geomorphology analysis for geohazard assessment via seismic relief and dip attributes in Jx carbonate field, Central Luconia Province, Malaysia

Nurul Fatin Izzatie Salman, Mohamed Elsaadany, Abdul Halim Abdul Latiff

Geological Society of Malaysia (GSM)

... relief and dip attributes, which efficiently distinguish the karst features and define the structural morphology of karsts. Dendritic karst networks...

Introduction of a Rock Typing Methodology in Crystalline Basement Reservoirs (Yemen),#40524 (2010)

Jan Steckhan and Roman Sauer

Search and Discovery.com

... present in the basement, it was decided to run a rock-type model rather than a mineral model. This rock-type model has been based on a supervised neural...

Production Forecasting for Shale Gas Well in Transient Flow Using Machine Learning and Decline Curve Analysis

Dongkwon Han, Sunil Kwon, Hanam Son, Janghyun Lee

Unconventional Resources Technology Conference (URTEC)

... using artificial neural networks. Paper SPE 164542 presented at the SPE Unconventional Resources Conference in held Woodlands, Texas, 10-12, April...

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

Uchenna Odi, Thomas Nguyen

Unconventional Resources Technology Conference (URTEC)

... significant progress and advancement specifically in the field of image recognition and object detection. Convolutional Neural Networks (CNNs...

Joint physics-based and data-driven time-lapse seismic inversion: Mitigating data scarcity

Yanhua Liu, Shihang Feng, Ilya Tsvankin, David Alumbaugh, Youzuo Lin

International Meeting for Applied Geoscience and Energy (IMAGE)

... and revitalization of deep neural networks, significant research efforts have been devoted to data-driven ML methods for seismic processing (Hale, 2013...

Edge-InversionNet: Enabling efficient inference of InversionNet on edge devices

Zhepeng Wang, Isaacshubhanand Putla, Weiwen Jiang, Youzuo Lin

International Meeting for Applied Geoscience and Energy (IMAGE)

.... J. Dally, 2016, Deep compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding: International Conference...

Stratigraphic Analysis of the Main Member of the Upper Cibulakan Formation at E Field, Offshore Northwest Java, Indonesia

Henry W. Posamentier, Wayne Suyenaga, Diah Rufaida, Robert Meyrick, S. George Pemberton

Indonesian Petroleum Association

... and Reservoirs of Indonesia; a Core Workshop, Indonesian Petroleum Association Workshop Notes, 59-90. Gurney, K., 1997. An Introduction to Neural Networks...

Integration of GR Spectroscopy, Geological Core Description, Acoustic Logging, and Geomechanics for Improved Characterization of Mudstone Reservoirs

Christon Achong, Patricio Desjardins

Unconventional Resources Technology Conference (URTEC)

... characterization and logging suite dataset, artificial neural networks could be used effectively to identify mudrock lithofacies and explain factors controlling...

An Integrated Machine Learning Framework for Optimizing Unconventional Resources Development

Hui Zhou, Benjamin Lascaud

Unconventional Resources Technology Conference (URTEC)

... vector machine and neural networks that provide predictive analytics of the data. Clearly unconventional reservoirs are now very well poised for machine...

Can Transfer Learning Be Used to Forecast Production in Frontier Basins? A Case Study from the Powder River Basin

Dillon Niederhut, Gabriel A. Quintero

Unconventional Resources Technology Conference (URTEC)

... applications in reservoir engineering have primarily focused on physics-informed or simulation-constrained neural networks that directly approximate...

Application of Machine Learning Methods to Assess Progressive Cavity Pumps (PCPs) Performance in Coal Seam Gas (CSG) Wells

Fahd Saghir, M. E. Gonzalez Perdomo, Peter Behrenbruch

Australian Petroleum Production & Exploration Association (APPEA) Journal

... data, applying classical clustering algorithms will produce inaccurate results (Vidaurre et al. 2014). Therefore, neural network based clustering...

Reservoir Delineation Using Spectral Decomposition, Spectral Inversion and Neural Network Analysis for an Oily Reservoir in Offshore Thailand, #41092 (2012)

Dan Cox, John Castagna, Gabriel Gil, Robert Ripple, Scott Rubio, Jerry Moon, Robert Roever, Andrew Laird, Geoff Peace, Ronald The, James Mitchell, John Pringle, Nyan Htein

Search and Discovery.com

...Reservoir Delineation Using Spectral Decomposition, Spectral Inversion and Neural Network Analysis for an Oily Reservoir in Offshore Thailand, #41092...

Innovative disorder seismic attribute for reservoir characterization

Qiang Fu, Saleh Al-Dossary

International Meeting for Applied Geoscience and Energy (IMAGE)

..., 2002, Interactive seismic facies classification using textural attributes and neural networks: The Leading Edge, 21, 1042–1049, doi: https://doi.org...

Multiscenario-based deep learning workflow for high-resolution seismic inversion on Brazil presalt 4D

Yang Xue, Dan Clarke, Kanglin Wang

International Meeting for Applied Geoscience and Energy (IMAGE)

... analysis. • Step 2: Train the U-net U-Net is an improved convolutional neural network (CNN) with a U-shaped architecture, developed for biomedical...

Bringing ML models into mainstream applications by enabling cloud platform connections

Rafael Pinto, Ilya Agurov, Roman Emreis, Iurii Koniaev-Gurchenko, Dmitrii Zolotukhin, Viktar Huleu, Evgeny Shulikin, Andrey Derevyanka, Pavel Shashkin, Maksim Krug, Ivan Grechikhin, Anton Petrov, Simon Shaw, Brian Macy, Chengbo Li, Chuck Mosher, Anand Malgi

International Meeting for Applied Geoscience and Energy (IMAGE)

... generative adversarial networks to enable large-scale seismic image enhancement: Presented at the 33rd Conference on Neural Information Processing...

Well Log Data Analytics: Overview of Applications to Improve Subsurface Characterisation

Irina Emelyanova, Chris Dyt, M. Ben Clennell, Jean-Baptiste Peyaud, Marina Pervukhina

Australian Petroleum Production & Exploration Association (APPEA) Journal

... by applying both data- and knowledge-driven modelling methods. Data-driven modelling applies machine learning (ML) techniques (e.g. artificial neural...

Rapid History Matching of Petroleum Production from Well Logs and 4D Seismic via Machine Learning Techniques in the Norne Field, Offshore Norway

Jones Ebinesan, Greg Smith, Ritu Gupta

Australian Petroleum Production & Exploration Association (APPEA) Journal

... and ML algorithms such as random forest and neural networks. The data from the Norne Field in the North Sea has been used because it has numerous...