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

..., machine learning, seismic inversion, well log interpretation. Accepted 1 February 2019, published online 17 June 2019 Introduction Wireline logs...

Petrophysical challenges with mudrocks in the Permian Basin: New concepts and workflows

Shuvajit Bhattacharya, Ray Eastwood, Brian Casey

International Meeting for Applied Geoscience and Energy (IMAGE)

...-based multi-mineral petrophysical inversion modeling using wireline logs and core data. We use TICC approach (unsupervised machine learning) for rock...

Geophysics in gold hydrogen exploration

Mengli Zhang, Yaoguo Li

International Meeting for Applied Geoscience and Energy (IMAGE)

... the petrophysical distribution and structural elements using machine learning approaches. Figure 5: Integration in geologic hydrogen exploration. Multi...

Seismic intelligent characterization of paleocave filling types in deeply buried carbonate reservoirs

Jiangyun Zhang, Fei Tian, Wenxiu Zhang, Wenhao Zheng, Wang Zhang, Zhongxing Wang

International Meeting for Applied Geoscience and Energy (IMAGE)

.... Zheng, W., W. Zheng, F. Tian, Q. Di, W. Xin, F. Cheng, and X. Shan, 2021, Electrofacies classification of deeply buried carbonate strata using machine...

Python and pandas, oh my: a rich ecosystem of open source tools for petrophysical and geological assessment

Search and Discovery.com

Abstract: Seismic Attributes „ A Promising Aid for Hydrocarbon Prediction in Deep Water of the Ceará Basin, Brazilian Equatorial Margin;

Karen Leopoldino Oliveira, Karelia La Marca, Heather Bedle

Search and Discovery.com

... and an unsupervised machine-learning technique called self-organizing maps were applied focusing on this Cenomanian-Turonian interval. These techniques...

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)

.... Kale et al. (2010), Gupta et al. (2017a), and Gupta et al. (2017b) integrated core, log, and production data using machine learning techniques to predict...

Seismic image-to-image translation using a conditional GAN with Bayesian inference

Xiaolei Song, Muhong Zhou, Petr Jilek, Rodney Johnston, Sean Cardinez, Kareem Vincent

International Meeting for Applied Geoscience and Energy (IMAGE)

.... Jervis, and P. Nivlet, 2019, 3D seismic facies classification using convolutional neural network and semi-supervised generative adversarial network: 89th...

Integrated reservoir characterization of low resistivity thin beds using three-dimensional modeling for natural gas exploration

Lim Yen Jun, Lo Shyh Zung

Geological Society of Malaysia (GSM)

.... Facies classification using machine learning. The 98 Leading Edge, (October), 906–909. Herron, D.A., 2011. First Steps in Seismic Interpretation...

Introduction to the special issue on geothermal energy

Kellen L. Gunderson, and Evan J. Earnest

AAPG Bulletin

... integrate expanded open-source and proprietary data sets, apply statistical tests, and compare PD performance to machine learning regressions trained...

Integrated Multi-Scale Reservoir Characterization: Wolfcamp Formation … Midland Basin

Joel Walls, Mark Ver Hoeve, Anyela Morcote, Michael Foster

Unconventional Resources Technology Conference (URTEC)

.... Then based on a multidimensional rock typing classification using machine learning (ML) techniques, plug locations were selected. SEM analysis was performed...

Abstract: Geological Modelling and Reservoir Simulation of a Petroleum Field in Malaysia

D. N. H. Lee, D. Baxendale, Edmund Huang

Geological Society of Malaysia (GSM)

... on all the available core data. Having determined the core lithofacies classification, the next step was to identify the different facies in the non-cored...

Abstract: Seismic Analysis with Wavelets and Deep Learning;

Samvith Rao, Akhilesh Mishra

Search and Discovery.com

... results have demonstrated that wavelets combined with deep learning can distinguish among different facies helping the interpreter to process new...

Deterministic versus unsupervised machine learning approach for facies modeling within the Late Devonian Duvernay Formation, Western Canada Sedimentary Basin, Alberta

Elisabeth G. Rau, Stacy C. Atchley, David W. Yeates, Anna M. Thorson, and Katherine H. Breen

AAPG Bulletin

...Deterministic versus unsupervised machine learning approach for facies modeling within the Late Devonian Duvernay Formation, Western Canada...

Surface-based modeling of 3D architectural elements controlled by near-wellbore modeling

Luis Carlos Escobar Arenas, Patrick Ronnau, Lisa Stright, Steve Hubbard, Brian Romans

International Meeting for Applied Geoscience and Energy (IMAGE)

... the Impact of Deep-Water Channel Architecture on the Probability of Correct Facies Classification Using 3D Synthetic Seismic Data: Colorado State...

Locate the Remaining Oil (LTRO) and Predictive Analytics: Application for Development Decisions on Marmul GNR Field, The Sultanate of Oman, #42191 (2018).

Cristian Masini, Sergey Ryzhov, Dmitry Kuzmichev, Rina Bouy, Saeed Majidaie, Denis Malakhov

Search and Discovery.com

... analytics history machine learning Machine learning full field forecast Development scenarios forecast LOCAT -THE-R MAINI G-OL(LT O)ANDPREDICTIVEANALV...

Enhanced Reservoir Characterization for Optimizing Completion Decisions in the Permian Basin Using a Novel Field-Scale Workflow Including Wells with Missing Data

Artur Posenato Garcia, Laura M Hernandez, Archana Jagadisan, Zoya Heidari, Brian Casey, Rick Williams

Unconventional Resources Technology Conference (URTEC)

... geostatistical and machine learning methods to reliably reconstruct missing PEF logs with a confidence interval through a rock-type-based approach which...

Generating high-quality labels for deep learning CO2 monitoring using local orthogonalization

Shuang Gao, Sergey Fomel, Yangkang Chen

International Meeting for Applied Geoscience and Energy (IMAGE)

.... Wrona, T., I. Pan, R. L. Gawthorpe, and H. Fossen, 2018, Seismic facies analysis using machine learning: Geophysics, 83, no. 5, O83–O95, doi: https...

ABSTRACT: Facies Modeling of Tight Gas Reservoir Using Neural Network: Case Study of NIKANASSIN Formation in Canadian Foothills; #90108 (2010)

Jack H. Deng

Search and Discovery.com

...ABSTRACT: Facies Modeling of Tight Gas Reservoir Using Neural Network: Case Study of NIKANASSIN Formation in Canadian Foothills; #90108 (2010) Jack H...

Using Production Quality Flow AI Based Facies With Integrated Multidisciplinary Workflow For Best Potential Targets Evaluation in Delaware Basin

Mauricio Vinassa, Dave Handwerger, Tom Tracey, Javed Iqbal, Hyder Jatoi

Unconventional Resources Technology Conference (URTEC)

... for the Permian Basin LA URTeC 3967521 2 A series of property-specific machine learning based facies models were created using a set of training wells...

To flow through an image: Advances in the use of ground-penetrating radar in hydrology inspired by the vision and work of Rosemary Knight

Stephen Moysey

International Meeting for Applied Geoscience and Energy (IMAGE)

... to investigating the three-dimensional geostatistical properties of the subsurface (Xu et al., 2020). In parallel, alternative machine learning approaches...

Insights into fluid movement and production discrepancies from PCA clustering on 4D seismic data

Evan Jowers, Heather Bedle

International Meeting for Applied Geoscience and Energy (IMAGE)

... facies discrepancies, fluid movement, and possible reservoir baffles. With the inclusion of production data, clusters produced from machine learning...

Incorporating Artificial Intelligence into Traditional Exploration Workflows in the Cooper-Eromanga Basin, South Australia

H. M. Garcia, W. G. "Woody" Leel Jr., M. Riehle, P. Szafian

International Meeting for Applied Geoscience and Energy (IMAGE)

.... For the classification, we used the color blend from the frequency decomposition calculated using the Far volume. The tool uses several machine learning...

Integrated carbonate reservoir types modeling based on the PRT deep learning and multi-parameters seismic inversion and its application

Chen Xin, Song Jiawen, Liu Qing, Sun Qian, Zhao Min, Qi Qunli, Weixiang Zhong, Dengyi Xiao, Tang Zichang, Fuli An, Wang Bo, Fan Hanzhou, Li Xiaoliang, Huang Kongzhi, Liu Qiang

International Meeting for Applied Geoscience and Energy (IMAGE)

... on the deep learning and seismic inversion was proposed. By integrated lithofacies classification, it can enhance the accuracy and reliability...

Enhancing Karstified Carbonate Characterization Through Focused Seismic Reprocessing and Machine Learning Utilization in Ubadari Field

M.R Husni Sahidu, Ilham Panggeleng, Sarah Putri, Scott Miller, Xiaobo Li

Indonesian Petroleum Association

... mapping of top Faumai Carbonates c. Fault interpretation supported by edge attributes and Machine Learning (ML) toolkit d. Using bandlimited impedance...