DigiWells: Digital Well Center for Value Creation, Competitiveness and Minimum Environmental Footprint
SFI DigiWells is a center for research-based innovation funded by the Research Council of Norway and the industrial partners from 2020 to 2028. We are developing new knowledge that will help to drill and position wells in the optimal manner. Our main objectives are value creation, safe operation, and minimum environmental footprint.
About the project
Digitalisation, new sensors, new high-speed telemetry solutions, automation, autonomy, and improved work processes have the potential to enable a step change in the well delivery process. The centre will explore these possibilities by combining domain knowledge with fundamental research to accelerate the digital transformation of the well-delivery process. The centre aims to develop work processes for planning drilling and well operations, new sensors, and solutions for interoperability. We will tightly link the planning and the new technologies to real-time data assimilations, yielding solutions for automated and autonomous drilling and decision support systems for geosteering. New solutions will be demonstrated at the national research infrastructures OpenLab Drilling, Ullrigg and against operators’ field data.
The centre will become a collaborative arena for operators, service industry, public authorities, research institutions and academia in Norway and internationally. Results from the centre’s activity will enable innovation, business development, and value creation for the Norwegian society. Moreover, in collaboration with universities, the centre will educate the next generation of specialists who will help implement the achieved research results.
The DigiWells consortium connects the operators, service companies, and academic partners. It is the place where experts of different disciplines talk together.
Publications and outreach
Only lists those co-authored by our members:-
Book-chapter by: Djecta, H.E., Alyaev, S. , Fossum, K. , Bratvold, R.B., Muhammad, R.B., Srivastava, A. (2025)
Uncertainty-Aware Well Placement: Simulator-Verified Dual-Network Reinforcement Learning Approach Meets Particle Filters
Springer Nature
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Paper by: Cheraghi, Y., Alyaev, S. , Bratvold, R.B., Hong, A., Kuvaev, I., Clark, S., Zhuravlev, A. (2025)
Analyzing expert decision-making in geosteering: Statistical insights from a large-scale controlled experiment
Applied Computing and Geosciences
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PhD-thesis by: Muhammad, R.B., Bratvold, R.B., Alyaev, S. (2025)
A Probabilistic Reinforcement Learning Framework for Optimized Decision-Making in Geosteering
Universitetet i Stavanger
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Lecture by: Alyaev, S. (2025)
Real-Time Geological Inversion for Decision-Making and Stratigraphic Inversion Exercise
Geilo Winter School
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Paper by: Ambrus, A., Pacis, F.J.C., Alyaev, S. , Khosravanian, R., Kristiansen, T.G. (2025)
Exploration of Training Strategies for a Quantile Regression Deep Neural Network for the Prediction of the Rate of Penetration in a Multi-Lateral Well
Energies
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Paper by: Muhammad, R.B., Cheraghi, Y., Alyaev, S. , Srivastava, A., Bratvold, R.B. (2025)
Geosteering Robot Powered by Multiple Probabilistic Interpretation and Artificial Intelligence: Benchmarking Against Human Experts
SPE Journal
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Paper by: Zhang, L., Pacis, F.J.C., Alyaev, S. , Wiktorski, T. (2025)
Cloud-free question answering from internal knowledge bases: Building an AI for drilling applications
First Break
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Paper by: Muhammad, R.B., Srivastava, A., Alyaev, S. , Bratvold, R.B., Tartakovsky, D.M. (2025)
High-precision geosteering via reinforcement learning and particle filters
Computational Geosciences
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PhD-thesis by: Pacis, F.J.C., Wiktorski, T., Alyaev, S. (2025)
Applied Transfer Learning in Drilling Engineering
Universitetet i Stavanger
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Paper by: Behura, J., Alyaev, S. (2025)
Geophysics Bright Spots: Strategic geosteering workflow
The Leading Edge
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Lecture by: Muhammad, R.B., Cheraghi, Y., Alyaev, S. , Srivastava, A., Bratvold, R.B., Tartakovsky, D.M. (2024)
High-Precision Geosteering via Reinforcement Learning and Particle Filters
Monthly Data Assimilation seminar
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Book-chapter by: Muhammad, R.B., Cheraghi, Y., Alyaev, S. , Srivastava, A., Bratvold, R.B. (2024)
Enhancing geosteering with AI : Integrating a decision-making robot into a cloud-based environment and benchmarking against human experts
Society of Petroleum Engineers
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Conf-paper by: Alyaev, S. , Muhammad, R.B., Cheraghi, Y., Bratvold, R.B., Srivastava, A., Tartakovsky, D.M. (2024)
Optimizing Sequential Decisions in Geosteering: Reinforcement Learning vs Human Experts in Fast-Paced Uncertain Environment
CSSR Annual Conference 2024
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Paper by: Rammay, M.H., Alyaev, S. , Larsen, D.S., Bratvold, R.B., Saint, C. (2024)
Strategic geosteering workflow with uncertainty quantification and deep learning: Initial test on the Goliat Field data
Geophysics
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Conf-paper by: Alyaev, S. , Muhammad, R.B., Cheraghi, Y., Bratvold, R.B., Srivastava, A., Tartakovsky, D.M. (2024)
How to Explain Geology to a Robot? DISTINGUISHing Patterns for Optimal Geosteering Decisions
DigiWells Seminar 2024
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Conf-paper by: Alyaev, S. , Pacis, F.J.C., Wiktorski, T. (2024)
Cloud-Free Question Answering from Internal Knowledge Bases: Building an AI for Drilling Applications
DigiWells Seminar 2024
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Conf-paper by: Muhammad, R.B., Cheraghi, Y., Alyaev, S. , Srivastava, A., Bratvold, R.B. (2024)
Enhancing Geosteering With AI: Integrating a Decision-Making Robot Into a Cloud-Based Environment and Benchmarking Against Human Experts
SPE Norway Subsurface Conference
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Conf-paper by: Alyaev, S. , Pacis, F.J.C., Wiktorski, T. (2024)
Domain-adapted Embeddings Model Using Contrastive Learning for Drilling Text Data
FAIEMA 2024
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Book-chapter by: Pacis, F.J.C., Alyaev, S. , Pelfrene, G., Wiktorski, T. (2024)
Enhancing information retrieval in the drilling domain : Zero-shot learning with large language models for question-answering
Society of Petroleum Engineers
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Poster by: Alyaev, S. , Ambrus, A., Jahani, N., Elsheikh, A.H. (2024)
AI-based multi-modal interpretation and extrapolation of geophysical logs
19th international EnKF workshop
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Conf-paper by: Djecta, H.E., Cheraghi, Y., Muhammad, R.B., Alyaev, S. , Fossum, K. , Bratvold, R.B., Srivastava, A. (2024)
Improvement of Reinforcement Learning Strategies of the Pluralistic Robot Validated in Competitive Geosteering
Geosteering and Formation Evaluation Workshop by NORCE and NFES 2024
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Book-chapter by: Saputera, D.H., Jakobsen, M., Jahani, N., Dongen’, K.V., Alyaev, S. , Eikrem, K.S. (2024)
Inversion of Electromagnetic Induction Log in Anisotropic Media using an Adjoint Integral Equation Method
European Association of Geoscientists and Engineers (EAGE)
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Lecture by: Saputera, D.H., Jakobsen, M., Jahani, N., Dongen’, K.V., Alyaev, S. , Eikrem, K.S. (2024)
Inversion of Electromagnetic Induction Log in Anisotropic Media using an Adjoint Integral Equation Method
85th EAGE Annual Conference & Exhibition
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Lecture by: Pacis, F.J.C., Alyaev, S. , Pelfrene, G., Wiktorski, T. (2024)
Enhancing Information Retrieval in the Drilling Domain: Zero-Shot Learning with Large Language Models for Question-Answering
IADC/SPE International Drilling Conference and Exhibition
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Lecture by: Pacis, F.J.C., Wiktorski, T., Ambrus, A., Alyaev, S. (2023)
Exploration of Strategies to Improve Continual Learning From Irregular Sequential Drilling Data
OMAE 42nd International Conference on Ocean, Offshore & Arctic Engineering
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Conf-paper by: Pacis, F.J.C., Alyaev, S. , Wiktorski, T. (2023)
Demo: Chatbot for oil and gas data
DigiWells Seminar
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Paper by: Pacis, F.J.C., Ambrus, A., Alyaev, S. , Khosravanian, R., Kristiansen, T.G., Wiktorski, T. (2023)
Improving predictive models for rate of penetration in real drilling operations through transfer learning
Journal of Computational Science
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Book-chapter by: Pacis, F.J.C., Wiktorski, T., Ambrus, A., Alyaev, S. (2023)
Exploration of strategies to improve continual learning from irregular sequential drilling data
The American Society of Mechanical Engineers (ASME)
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Conf-paper by: Alyaev, S. (2023)
DISTINGUISH from the depth of detection to the probabilistic distance of prediction
DigiWells Seminar
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Lecture by: Alyaev, S. , Elsheikh, A.H., Ambrus, A., Jahani, N. (2023)
Direct Multi-Modal Inversion of Geophysical Logs Using Deep Learning
SIAM Conference on Mathematical & Computational Issues in the Geosciences (GS23)
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Conf-paper by: Muhammad, R.B., Srivastava, A., Alyaev, S. , Bratvold, R.B., Tartakovsky, D.M. (2023)
Integrating Reinforcement Learning and Particle Filter for Enhanced Geosteering Decision-Making
DigiWells Seminar
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Paper by: Jahani, N., Alyaev, S. , Ambia, J., Fossum, K. , Suter, E.C., Torres-Verdin, C. (2023)
Enhancing the Detectability of Deep-Sensing Borehole Electromagnetic Instruments by Joint Inversion of Multiple Logs Within a Probabilistic Geosteering Workflow
Petrophysics
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Paper by: Saputera, D.H., Jakobsen, M., Dongen, K.W.A.v., Jahani, N., Eikrem, K.S. , Alyaev, S. (2023)
3-D induction log modelling with integral equation method and domain decomposition pre-conditioning
Geophysical Journal International
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Conf-paper by: Saputera, D.H., Jakobsen, M., Alyaev, S. , Jahani, N., Eikrem, K.S. , Dongen, K.W.A.v. (2023)
3D Modeling and Inversion of Induction Logs. 2023 Highlights
DigiWells Seminar
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Lecture by: Saputera, D.H., Jakobsen, M., Jahani, N., Alyaev, S. , Eikrem, K.S. , Dongen, K.W.A.v. (2023)
Towards Real-Time 3D Modeling of Induction Logs Using an Integral Equation Method
84th EAGE Annual Conference & Exhibition
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Book-chapter by: Saputera, D.H., Jakobsen, M., Jahani, N., Alyaev, S. , Eikrem, K.S. , Dongen, K.W.A.v. (2023)
Towards Real-Time 3D Modeling of Induction Logs Using an Integral Equation Method
European Association of Geoscientists and Engineers (EAGE)
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Conf-paper by: Alyaev, S. , Ambrus, A., Jahani, N. (2022)
Demo: Sequential prediction with noisy GR log and naïve ROP prediction
DigiWells technical meeting
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Book-chapter by: Alyaev, S. , Ambrus, A., Jahani, N., Elsheikh, A. (2022)
Sequential Multi-Realization Probabilistic Interpretation of Well Logs and Geological Prediction by a Deep-Learning Method
SPWLA
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Book-chapter by: Cheraghi, Y., Alyaev, S. , Hong, A., Kuvaev, I., Clark, S., Zhuravlev, A., Bratvold, R.B. (2022)
What can we learn after 10,000 geosteering decisions?
Society of Petroleum Engineers
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Poster by: Ambrus, A., Alyaev, S. , Jahani, N., Elsheikh, A.H. (2022)
AI-based multi-modal interpretation of logs for ahead-of-bit probabilistic ROP prediction
Geosteering and Formation Evaluation Workshop by NORCE and NFES
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Book-chapter by: Ambrus, A., Alyaev, S. , Jahani, N., Pacis, F.J.C., Wiktorski, T. (2022)
Rate of Penetration Prediction Using Quantile Regression Deep Neural Networks
The American Society of Mechanical Engineers (ASME)
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Paper by: Alyaev, S. , Elsheikh, A. (2022)
Direct Multi-Modal Inversion of Geophysical Logs Using Deep Learning
Earth and Space Science
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Paper by: Pacis, F.J.C., Alyaev, S. , Ambrus, A., Wiktorski, T. (2022)
Transfer Learning Approach to Prediction of Rate of Penetration in Drilling
Lecture Notes in Computer Science (LNCS)
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Conf-paper by: Ambrus, A., Alyaev, S. , Jahani, N., Pacis, F.J.C., Wiktorski, T. (2022)
Rate of Penetration Prediction Using Quantile Regression Deep Neural Networks
ASME 41st International Conference on Ocean, Offshore and Arctic Engineering
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Conf-paper by: Alyaev, S. , Ambrus, A., Jahani, N., Elsheikh, A.H. (2022)
Predicting likely stratigraphy realizations from shallow logs with AI
NFES Monthly Technical Meeting
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Lecture by: Pacis, F.J.C., Alyaev, S. , Wiktorski, T. (2022)
Demo: Chatbot for NCS well data
Annual DigiWells Seminar 2022
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Book-chapter by: Rammay, M.H., Alyaev, S. (2022)
Calibration and Prediction Improvement of Decline Curve Models While Accounting for Model Error
European Association of Geoscientists and Engineers (EAGE)
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Conf-paper by: Alyaev, S. , Ambrus, A., Jahani, N., Elsheikh, A. (2022)
Sequential Multi-Realization Probabilistic Interpretation of Well Logs and Geological Prediction by a Deep-Learning Method
63d SPWLA Annual Symposium
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Conf-paper by: Alyaev, S. , Ambrus, A., Jahani, N., Elsheikh, A.H. (2022)
AI‐based multi‐modal prediction of stratigraphy to inform drilling performance
Annual seminar SFI DigiWells
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Poster by: Alyaev, S. (2022)
Gamification of shallow geosteering
Geosteering and Formation Evaluation Workshop by NORCE and NFES
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Conf-paper by: Pacis, F.J.C., Alyaev, S. , Ambrus, A., Wiktorski, T. (2022)
Transfer Learning Approach to Prediction of Rate of Penetration in Drilling
INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE (ICCS) 2022
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Conf-paper by: Pacis, F.J.C., Wiktorski, T., Alyaev, S. , Ambrus, A., Khosravanian, R., Kristiansen, T.G. (2022)
Exploring transfer learning for ROP prediction on the NCS
Annual seminar SFI DigiWells
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Paper by: Rammay, M.H., Alyaev, S. , Elsheikh, A. (2022)
Probabilistic model-error assessment of deep learning proxies: An application to real-time inversion of borehole electromagnetic measurements
Geophysical Journal International
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Conf-paper by: Rammay, M.H., Alyaev, S. , Bratvold, R.B., Larsen, D.S., Saint, C. (2022)
Real-time estimation of geological layers' profiles in an anisotropic environment while accounting for model-error: A case study on the Goliat field
Geosteering and Formation Evaluation Workshop by NORCE and NFES
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Conf-paper by: Cheraghi, Y., Alyaev, S. , Hong, A., Kuvaev, I., Clark, S., Zhuravlev, A., Bratvold, R.B. (2022)
What can we learn after 10000 geosteering decisions?
Geosteering and Formation Evaluation Workshop by NORCE and NFES
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Conf-paper by: Alyaev, S. , Jahani, N., Fossum, K. , Tveranger, J., Rammay, M.H., Larsen, D.S., Saint, C., Bratvold, R.B., Elsheikh, A.H. (2022)
Geosteering results: It's time to understand where the bit is heading
Annual seminar SFI DigiWells
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Paper by: Fossum, K. , Alyaev, S. , Tveranger, J., Elsheikh, A.H. (2022)
Verification of a real-time ensemble-based method for updating earth model based on GAN
Journal of Computational Science
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Paper by: Jahani, N., Garrido, J.A., Alyaev, S. , Fossum, K. , Suter, E.C., Torres-Verdin, C. (2022)
Ensemble-Based Well-Log Interpretation and Uncertainty Quantification for Well Geosteering
Geophysics
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Conf-paper by: Fossum, K. , Alyaev, S. , Tveranger, J., Elsheikh, A.H. (2022)
Verification of a real-time method for updating the geosteering earth model based on GAN
Geosteering and Formation Evaluation Workshop by NORCE and NFES
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Poster by: Saputera, D.H., Jakobsen, M., Alyaev, S. , Jahani, N., Eikrem, K.S. , Dongen, K.v. (2022)
GPU-accelerated integral equation method for 3D modelling of induction logs
Geosteering and Formation Evaluation Workshop by NORCE and NFES
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Conf-paper by: Alyaev, S. , Ambrus, A., Jahani, N., Elsheikh, A. (2021)
Sequential probabilistic multi-modal inversion and prediction with deep learning
DigiWells demo
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Conf-paper by: Muhammad, R.B., Bratvold, R.B., Alyaev, S. (2021)
Reinforcement learning for better geosteering decisions
DigiWells seminar
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Conf-paper by: Alyaev, S. (2021)
Geosteering for IOR: Results and further opportunities
DigiWells seminar
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Conf-paper by: Alyaev, S. , Ambrus, A., Pacis, F.J.C., Jahani, N., Wiktorski, T., Elsheikh, A. (2021)
Drilling Process Modelling with Deep Learning: Towards ROP Prediction
DigiWells seminar
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Conf-paper by: Alyaev, S. , Elsheikh, A., Ambrus, A., Jahani, N. (2021)
Deep learning for probabilistic inversion during geosteering
HPC, DEEP LEARNING, AND NUMERICS IN GEOPHYSICS
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Conf-paper by: Ambrus, A., Alyaev, S. , Ewald, R. (2021)
Drilling performance predicitons with drilling efficiency uncertainty (Demo in OpenLab Drilling)
Technical meeting
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Conf-paper by: Fossum, K. , Alyaev, S. , Suter, E.C., Tossi, G., Mele, M. (2021)
Reducing 3D uncertainty by an ensemble-based geosteering workflow: an example from the Goliat field
3rd EAGE/SPE Geosteering Workshop
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Paper by: Alyaev, S. , Tveranger, J., Fossum, K. , Elsheikh, A. (2021)
Probabilistic forecasting for geosteering in fluvial successions using a generative adversarial network
First Break
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Conf-paper by: Alyaev, S. , Fossum, K. , Tveranger, J., Elsheikh, A. (2021)
Using generative adversarial networks for probabilistic predictions of complex geology ahead of drilling
Mechanistic Machine Learning and Digital Twins for Computational Science, Engineering & Technology
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Conf-paper by: Fossum, K. , Alyaev, S. , Tveranger, J., Elsheikh, A. (2021)
Deep learning for prediction of complex geology ahead of drilling
ICCS 2021: INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE
Total: 70