Machine Learning Publications
Selected articles, papers and conference contributions referencing Machine Learning.
2024
Leveraging AI Requires Finesse, But Delivers Huge Rewards
Aminzadeh, F
The American Oil & Gas Reporter, Editor's Choice November 2024
Araque-Pérez, C.J., Teixidó, T., de Lis Mancilla, F., Morales, J
Tectonophysics, July 2024
Lessons learnt for tuning a Machine Learning fault prediction model
Pratama, H., Oke, M., Mogg, W., Markus, D., Huck, A., & de Groot, P
First Break, February 2024
2023
How Machine Learning saves time and
de Groot, M., Refayee, H., and van Hout, M., \]
DEW Journal, February 2023
How reusing trained machine learning models accelerates and improves the work of operational geoscientists.
de Groot, P. ,and Refayee, H., \]
First Break, February 2023
Dixit, A., Mandal, A., Ganguli, S. S., & Sanyal, S
Geophysics, 88(2), R225-R242.
2022
Machine learning and seismic attributes for prospect identification and risking: an example from Offshore Australia
Farfour, M., Foster, D. J., \]
Second International Meeting for Applied Geoscience & Energy 2022
3D seismic facies segmentation using supervised and
Brouwer, F., De Groot, P. \]
Denver Geophysical Society, Machine Learning/Artificial Intelligence Workshop, 20 Oct. 2022
Reconstructing seismic images and creating pseudo-3D volumes: a machine learning approach
De Groot, P., Huck, A. and M. van Hout \]
First Break, volume 40, February 2022
2021
Machine Learning workflows to create pseudo-3D from 2D seismic.
De Groot, P. and Huck, A., \]
SEG Digital Intelligence Series, 2nd edition Artificially Intelligent Earth Exploration, Virtual Workshop, 30 Nov. – 2 Dec. 2021
Filling gaps, replacing bad data zones and super-sampling of 3D seismic volumes through Machine Learning.
de Groot, P. and van Hout, M., \]
EAGE 2021 Annual Conference, Oral presentation in Digitalization & AI: Seismic Data Processing I, Tuesday, 19 October 2021 at 14:45.
Experiences with Machine Learning and Deep Learning Algorithms for Seismic, Wells and Seismic-to-Well Applications.
Jaglan, H., Kocsis, G., Lakhliffi, A., and de Groot, P. \]
EAGE 2021 Annual Conference, Oral presentation in Digitalization & AI: Reservoir and Wells, Thursday, October 21, 2021 at 15:55.
Incorporating acquisition geometry in deep learning-based full waveform inversion.
Saadat, M., Hashemi, H., Nabi-Bidhendi, M. and de Groot, P., \]
EAGE 2021 Annual Conference, E-Poster: FWI and Velocity Analysis. Geophysics 2, Thursday, October 21, 2021, 8:30 AM - 11:30 AM
Visualizing Hydrocarbon Migration Pathways Associated with the Ringhorne Oil Field, Norway: An Integrated Approach
Connolly, D., Rimaila, K., Lakhlifi, A., Kocsis, G., Fæstø, I., Yarushina, V., and Wang, H. \]
Interpretation October 2021
Deep Learning Seismic Object Detection Examples.
de Groot, P., Pelissier, M., Refayee, H., and van Hout, M., \]
DEW Journal, July 2021
Seismic classification: A Thalweg tracking/machine learning approach.
de Groot, P., Pelissier, M., and van Hout, M., \]
First Break, Vol. 39, pg. 59-64, March 2021.
2020
Dixit, A., A. Mandal, C. P. Kumar, 2020
Society of Petroleum Geophysicists (SPG), 13th Biennial International Conference & Exposition, February 23-25, 2020, Kochi, India.
Dixit, A., & Mandal, A
Journal of Natural Gas Science and Engineering, 83, 103586.
2019
Pseudo-Wells based HitCube 'trace-matching' and Machine Learning Inversions: Seismic Reservoir Characterization in a Challenging Environment
Kocsis, G. and Jaglan, H. \]
EAGE Subsurface Intelligence Workshop, Bahrain
Delineation of a buried volcanic system in Kora prospect off New Zealand
Kumar, P. C., Sain, K., and Mandal, A. \]
Journal of Applied Geophysics 161
The Use of Machine Learning to Enhance Faults and Fractures Detection in Seismic Data
Refayee, H., and Hemstra, N., \]
1st Applied Geoscience Conference
Interpretation of Hydrocarbon Migration Pathways Using Latest Developments in Machine Learning - Green Canyon, Gulf of Mexico
Rimaila, K., \]
GeoGulf (GCAGS; Gulf Coast Association of Geological Societies)
2018
Kumar, P. C., & Mandal, A
Exploration Geophysics, 49(3), 409-424.
2016
Chimney Atlas to Quantify Top Seal and Charge Risk: Case Study from Maari Oil Field, Taranaki Basin, New Zealand
Connolly, D. and De Groot, P. \]
EAGE 78th EAGE Conference & Exhibition
Interpretation of gas chimney from seismic data using artificial neural network: A study from Maari 3D prospect in the Taranaki basin, New Zealand
Singh, D., Kumar, P.C. and Sain, K. \]
Journal of Natural Gas Science and Engineering
Interpretation of gas chimney in the Maari 3D field of southern Taranaki Basin, New Zealand
Singh, D., Kumar, P.C. and Sain, K. \]
SEG Technical Program
2015
Atlas of gas chimney occurrences associated with oil and gas fields and dry holes: Case studies from deepwater Gulf of Mexico
Connolly, D. \]
SEG Technical Program
Visualization of vertical hydrocarbon migration in seismic data: Case studies from the Dutch North Sea
Connolly, D. \]
Interpretation
Neural Network Application of Curvature Attribute for Fracture Analysis
Rimaila, K., Mustaqeem, A. and Baranova, V. \]
GeoConvention 2015: New Horizons
2014
Using gas chimney detection to assess hydrocarbon charge and top seal effectiveness - offshore, Namibia
Connolly, D., Kemper, J. and Thomas, I. \]
76th EAGE Conference & Exhibition
2012
Combining Absorption and AVO Seismic Attributes Using Neural Networks to High-Grade Gas Prospects
Rahimi Zeynal, A., Aminzadeh, F. Clifford, A. \]
SPE Western Regional Meeting
2011
A Guide to the Practical Use of Neural Networks
Brouwer, F.C.G., Connolly, D. and Tingdahl, K. \]
2008
Using Integrated Gas Chimney Processing, Frequency Attenuation attributes, and Seismic Facies Classification to Delineate Oil Filled Reservoirs: Case studies from the Oriente Basin, Ecuador
Connolly, D., Aminzadeh, F., Selva, C. and Curia, D. \]
Top 10 Poster Presentation AAPG convention
Detecting Fault-Related Hydrocarbon Migration Pathways in Seismic Data: Implications for Fault-Seal, Presure, and Charge Prediction
Connolly, D.L, Brouwer, F. and Walraven, D. \]
Gas chimney detection based on improving the performance of combined multilayer perceptron and support vector classifier
Hashemi, H., Tax, D.M.J., Duin, R.P.W., Javaherian, A. and De Groot, P. \]
Nonlinear Processes in Geophysics
High Frequency Attenuation and Low frequency shadows in Seismic Data Caused by Gas Chimneys, Onshore Ecuador
Welsh, A., Connolly, D.L., Selva, C., Curia, D. and Huck, A. \]
70th EAGE Conference & Exhibition
2006
Integrating neural networks and fuzzy logic for improved reservoir property prediction and prospect ranking
Aminzadeh, F. and Brouwer, F. \]
76th SEG Annual Meeting
Visualizing Gas Chimney Volumes Reduces Exploration Risk: A Case Study from Onshore Louisiana
Klutts, J., Connolly, D.L., Aminzadeh, F. and Brouwer, F. \]
76th SEG Annual Meeting
2005
A neural networks based seismic object detection technique
Aminzadeh, F. and De Groot, P. \]
SEG Technical Program
Assessing hydrocarbon risk with neural network classification methods
Aminzadeh, F., Ross, C. and Brouwer, F. \]
EAGE 67th Conference & Exhibition Madrid
Using gas chimneys in seal integrity analysis: A discussion based on case histories
Heggland, R. \]
Evaluating fault and cap rock seals
Determining Migration Pathway in Marco Polo Field Using Chimney Technology
Walraven, D., Connolly, D.L. and Aminzadeh, F. \]
EAGE 67th Conference & Exhibition Madrid
2004
Hydrocarbon Phase Detection and Other Applications of Chimney Technology
Aminzadeh, F. and Connolly, D. \]
AAPG Int. Conference
Neural network applications
Aminzadeh, F. and De Groot, P. \]
Soft computing for qualitative and quantitative seismic object detection and reservoir property prediction
Examples of multi-attribute, neural network-based seismic object detection
De Groot, P., Ligtenberg, H., Oldenziel, T., Connolly, D. and Meldahl, P. (Statoil). \]
3D Seismic Technology; Application to the Exploration of Sedimentary Basins
Hydrocarbon Migration and Accumulation Above Salt Domes - Risking of Prospects by the Use of Gas Chimneys
Heggland, R. \]
Salt-Sediment Interactions and Hydrocarbon Prospectivity: Concepts, Applications and Case Studies for the 21st Century
Sealing quality analysis of faults and formations by means of seismic attributes and neural networks
Ligtenberg, H. \]
EAGE Proceedings of Fault and Top Seals conference
Predicting seal risk and charge capacity using chimney processing: Three Gulf of Mexico case histories
Walraven, D., Aminzadeh, F. and Connolly, D. \]
SEG National Convention
2003
Application of gas chimney technology in the Lamprea area, offshore GOM
Alvarado, J., Aminzadeh, F. and Connolly, D. \]
SEG annual meeting
Geo-Hazard Detection with Chimney Cubes
Connolly, D. L. and Aminzadeh, F. \]
Offshore Technology Conference
Application of Chimney Cubes in the Design of Geochemical Surveys
Heggland, R. (Statoil). \]
AAPG conference
Vertical Hydrocarbon Migration at the Nigerian Continental Slope: Applications of Seismic Mapping Techniques
Heggland, R. (Statoil). \]
AAPG conference
Sealing quality analysis of faults and formations by means of seismic attributes and neural networks
Ligtenberg, H. \]
EAGE Fault and Top Seal conference
Unravelling the petroleum system by enhancing fluid migration paths in seismic data using a neural network based pattern recognition technique
Ligtenberg, H. \]
Geofluids magazine
Chimney detection and interpretation - revealing sealing quality of faults, geohazards, charge of and leakage from reservoirs
Ligtenberg, H. and Connolly, D. \]
Migration and interaction in sedimentary basins and orogenic belts
2002
Looking for gas chimneys and faults
Aminzadeh, F. and Connolly, D. \]
AAPG Explorer
Geohazard detection and other applications of chimney cubes
Aminzadeh, F., Connolly, D., Heggland, R. (Statoil), Meldahl, P. (Statoil) and De Groot, P. \]
The leading Edge
Determining migration path from seismically derived gas chimneys
Aminzadeh, F., De Groot, P., Berge, T. (Forest Oil), Oldenziel, T. and Ligtenberg, H. \]
AAPG Hedberg Conference
Seismic evidence of vertical fluid migration through faults, Applications of Chimney and Fault detection
Heggland, R. (Statoil) \]
AAPG Hedberg Conference
Neural network prediction of permeability in El Garia Formation, Ashtart oilfield, offshore Tunesia
Ligtenberg, H. and Wansink, G. (formerly dGB). \]
Soft computing and intelligent data analysis in oil exploration
2001
Using gas chimneys as an exploration tool, Part 1 and Part 2
Aminzadeh, F., De Groot, P., Berge, T. (Forest Oil) and Valenti, G. (AGIP). \]
World Oil
Unsupervised segmentation in seismic data analysis
Grennberg Fismen, B., Clausen, S., Yang, L., Carlin, M., Kavli, T. (all Sintef) and Wansink, G. (formerly dGB). \]
ICIP conference
Examples of seismic chimney detection and interpretation
Ligtenberg, H. \]
Subsurface sediment mobilisation conference
Neural network prediction of permeability in El Garia Formation, Ashtart oilfield, offshore Tunesia
Ligtenberg, H. and Wansink, G. (formerly dGB). \]
Journal of Petroleum Geology JPG
Identifying faults and gas chimney using multiattributes and neural networks
Meldahl, P. (Statoil), Heggland, R. (Statoil), Bril, A. and De Groot, P. \]
The Leading Edge
Improving seismic chimney detection using directional attributes
Tingdahl, M.K., Bril, A.H. and De Groot, P.F.M. \]
Journal of Petroleum Science and Engineering
A new confidence bound estimation method for neural networks, an application example
Wansink, G. (formerly dGB), Yang, L. (Sintef), et al. \]
63rd EAGE conference
2000
Reservoir parameter estimation using a hybrid neural network
Aminzadeh, F., et al. \]
Computer and Geoscience
Detection of Seismic Chimneys by neural networks, a New Prospect Evaluation Tool
Heggland, R. (Statoil), Meldahl, P. (Statoil), Bril, A. and De Groot, P. \]
62nd EAGE conference
Seismic chimney interpretation examples from the North Sea and the Gulf of Mexico
Heggland, R. (Statoil), Meldahl, P. (Statoil), De Groot, P. and Aminzadeh, F. \]
American Oil & Gas Reporter
Semi-automated detection of seismic objects by directive attributes and neural networks, method and applications
Meldahl, P. (Statoil), Heggland, R. (Statoil), Bril, B. and De Groot, P. \]
62nd EAGE conference
Neural network-based prediction of porosity and water saturation from time-lapse seismic; a case study
Oldenziel, T., De Groot, P. and Kvamme, L. (formerly Statoil). \]
First Break
An evaluation of confidence bound estimation methods for neural networks
Yang, L. (Sintef), et al. \]
ESIT
1999
Seismic Reservoir Characterisation Using Artificial Neural Networks
De Groot, P. \]
19th Mintrop seminar
Volume Transformation by way of Neural Network Mapping
De Groot, P. \]
61st EAGE Conference
The chimney cube, an example of semi-automated detection of seismic objects by directive attributes and neural networks: Part 1; Methodology
Meldahl, P. (Statoil), Heggland, R. (Statoil), De Groot, P. and Bril, A. \]
69th SEG conference
The chimney cube, an example of semi-automated detection of seismic objects by directive attributes and neural networks: Part 2; Interpretation
Meldahl, P. (Statoil), Heggland, R. (Statoil), De Groot, P. and Bril, A. \]
69th SEG conference
1998
Neural networks introduction
El Oul, J. \]
1996
Neural Network experiments on synthetic seismic data
Braunschweig, B., Bremdal, B.A. and De Groot, P. \]
Artificial Intelligence in the Petroleum Industry
1993
Reservoir characterization from 3D seismic data using artificial neural networks and stochastic modelling techniques
De Groot, P.F.M., Campbell, A.E., Kavli, T. and Melnyk, D. \]
55th EAGE Conference