Type | Value | Early-bird (November 22th 2024) |
---|---|---|
Associate SBGf | R$ 2,642.00 USD 500 |
R$ 2,113.00 USD 400 |
Non-Member SBGf | R$ 3,170.00 USD 600 |
R$ 2,642.00 USD 500 |
Undergraduate Student (Associate) | R$ 660.00 USD 125 |
R$ 660.00 USD 125 |
Undergraduate Student (Non-Member) | R$ 660.00 USD 125 |
R$ 660.00 USD 125 |
Machine Learning (ML) is a field of Artificial Intelligence that has experienced rapid growth in the last ten years across diverse industries, including communications, financial services, security, transportation, and others. Applications of ML have produced dramatic results, enabling new opportunities and business models. Driving the adoption of ML are the volume and velocity of information, the application of deep learning techniques, and economic computing power. Applied to geoscience, these data-driven approaches are complementary tools for physical-based modeling, simulation, and inversion. ML facilitates an understanding of complex relationships among a large and diverse set of variables, valuable for generating and validating models and answering scientific questions. ML can enable fast high-quality decisions in the oil & gas industry, an essential component for viability given the industrys long-term outlook. Geoscience datasets are among the largest volumes of data in the industry. The data has a wide spectrum of properties with scales varying over many orders of magnitude. The workshop will allow the attendees to evaluate and compare the best developments of ML technology that have occurred in industry over the last five years.
Opening of Call for Abstracts: 19/07/2024
Abstracts Submission Deadline: 16/10/2024
Notification to authors: 30/10/2024
Presenter confirmation: 15/11/2024
Final Technical Program: 22/11/2024
Registration Early Open: 07/10/2024
Registration Early ends: 14/11/2024
Date/Hour | Theme | Speaker |
December 3rd, 2024 - 07:30-08:30 AM | Onsite Registration | |
December 3rd, 2024 - 08:30-09:30 AM | Introduction to Fourier Neural Operators and Their Applicability in Geophysics | Rodrigo Portugal (Halliburton) |
December 3rd, 2024 - 09:30-10:00 AM | Seismic Horizon Interpretation with Deep Learning: a case study in Santos Basin | Alexsandro Guerra Cerqueira (GAIA-UFBA), João P. Gomes (GAIA-UFBA), José L. Silva (GAIA-UFBA), Paulo Vidigal (GAIA-UFBA), Paulo Barros (GAIA-UFBA) |
December 3rd, 2024 - 10:00-10:30 AM | Automated fracture-zone prediction in multi-azimuth seismic data using deep learning | Lorena da Silva Oliveira Santos (Kognitus), Matheus Silva Gonçalves (Kognitus), Pablo Machado Barros (Petrobras), Pedro Henrique Silvany (Petrobras), Carlos Eduardo Borges de Salles Abreu (Petrobras), Alexandre Augusto Cardoso da Silva (Petrobras), Rogério Espíndola (COPPE-UFRJ), Maria Célia Lopes (COPPE-UFRJ), Lucas Dias (COPPE-UFRJ), Bruno Souza (COPPE-UFRJ) |
December 3rd, 2024 - 10:30-10:50 AM | Coffe Break | |
December 3rd, 2024 - 10:50-11:20 AM | Diffusion Model Based Artificial Seismic Image Generation | Pedro Gil Oliveira De Magalhães Couto (Petrobras), Thales Amaral Paes de Mesentier (Petrobras), Vitor Giudice Batista de Araujo Porto (Petrobras), Ronnypetson Souza da Silva (Petrobras) |
December 3rd, 2024 - 11:20-11:50 AM | Application of Deep Learning in 2D Seismic Analysis | Marcio Lemos Rodrigues (IesBrazil Technology & Innovation), Neida Ilana (IesBrazil Technology & Innovation), Carlos Saraiva (IesBrazil Technology & Innovation), Vanessa Lira (IesBrazil Technology & Innovation), Juliana Fernandes (IesBrazil Technology & Innovation) |
December 3rd, 2024 - 11:50-12:20 PM | Usage of deep learning techniques to recognize and map shallow faults at Albacora Leste Field | Rodrigo de Paiva Ferro (PRIO), Ana Krueger (Bluware), Neida Ilana Rios (IesBrazil Technology & Innovation), Humberto Bovolenta (PRIO), Andre Silva (PRIO), Pedro Henrique Guara Rocha Coelho (PRIO), Marina Jordao Martins (PRIO) |
December 3rd, 2024 - 12:20-02:00 PM | Lunch | |
December 3rd, 2024 - 02:00-03:00 PM | Keynote Speaker - Pavel Dimitrov - NVIDIA | Pavel Dimitrov (NVIDIA) |
December 3rd, 2024 - 03:00-03:30 PM | The The geoML project: spatial modeling in the 21st century | Ítalo Gomes Gonçalves (Federal University of Pampa), Marcus Vinicius Aparecido Gomes de Lima (Federal University of Pampa) |
December 3rd, 2024 - 03:30-04:00 PM | Feature augmentation techniques as an improvement process of acoustic seismic inversion. | Carlos Eduardo Pereira Pacheco (Halliburton), Reinaldo Mozart da Gama e Silva (Halliburton), Edson Alonso Falla Lusa (Halliburton), Matheus Lima Lemos de Oliveira (Halliburton), Aury Candido Bezerra (Petrobras) |
December 3rd, 2024 - 04:00-04:20 PM | Coffe Break | |
December 3rd, 2024 - 04:20-06:20 PM | Hands On Session - Accelerating Data Flow to OSDU With ML | Wladmir Frazao (AWS), Juliana Fernandes (IesBrazil Technology & Innovation) |
December 3rd, 2024 - 06:20-08:00 PM | Ice Breaker Reception | |
DAY 2 | ||
December 4th, 2024 - 07:30-08:30 AM | Onsite Registration | |
December 4th, 2024 - 08:30-09:30 AM | Keynote Speaker - Guilherme Veloso - Schlumberger | Guilherme Veloso (Schlumberger) |
December 4th, 2024 - 09:30-10:00 AM | Lithology prediction through convolutional neural networks and rock physics-based synthetic wells: an example from Gulf of Mexico | Felipe Ferreira de Melo (GeoSoftware), Ruth Kurian (GeoSoftware) |
December 4th, 2024 - 10:00-10:30 AM | Irreducible water saturation from Nuclear Magnetic Resonance raw data using Deep Learning | Bernardo Fraga (CBPF), Bernardo Coutinho (Petrobras), Clecio R. de Bom (CBPF) |
December 4th, 2024 - 10:30-11:30 AM | Coffe Break and Poster Session - (A) Elastic Time-Lapse Machine Learning Seismic inversion - (B) 3D Time-lapse Inversion using Machine Learning - (C) Time-lapse target-oriented velocity inversion with supervised CNN networks - (D) Unsupervised characterization technique based on the Correlation Integral approach for 3D seismic data interpretation - (E) Solimões Basin Onshore Brazil Igneous Intrusions Characterization Using an Interactive, Data-Centric Deep Learning Approach - (F) Well log and core integration to predict permeability in carbonates: A methodology using machine learning - (G) Advancing Seismic Data Exploration with Agentic AI Tools and LLMs | (A) Gilberto Corso (Federal University of Rio Grande Do Norte), Arthur Dantas da Costa (Federal University of Rio Grande Do Norte), Paulo Vinícius de Mendonça Carvalho (Federal University of Rio Grande Do Norte), Ramon C. F. Araújo (Federal University of Rio Grande Do Norte), Tiago Barros (Federal University of Rio Grande Do Norte), João M. de Araújo (Federal University of Rio Grande Do Norte) - (B) Paulo Vinícius de Mendonça Carvalho, Arthur Dantas da Costa, Gilberto Corso, Ramon C. F. Araújo, Tiago Tavares Barros, and João M. de Araújo - (C) Pavel Karmanov, Gilberto Corso, Ramon C. F. Araújo, Tiago Tavares Barros, and João M. de Araújo - (D) Pavel Karmanov (Indian Institute of Technology, Kharagpur), Paresh Nath Singha Roy (Indian Institute of Technology, Kharagpur), Ramakrushna Reddy (Indian Institute of Technology, Kharagpur) - (E) Ana Krueger (Bluware), Scott Salamoff (Bluware) - (F) Filipe de Moura Antonio Cordeiro (Federal University of Bahia), Alexsandro G. Cerqueira (Federal University of Bahia), Cícero da Paixão Pereira (Federal University of Bahia) - (G) Ignacio Sánchez Gendriz (Federal University of Rio Grande Do Norte) |
December 4th, 2024 - 11:30-12:00 PM | Latent Diffusion Model Conditioned by Segmentation Maps for 2D Geological Facies Generation | Renata Nascimento (Tecgraf Institute – PUC-Rio), Gabrielle Brandemburg dos Anjos (Tecgraf Institute – PUC-Rio), Julio Nobre Lopes (Tecgraf Institute – PUC-Rio), Andressa Oishi (Petrobras), Claudio Henrique Gomes (Petrobras), Erick Talarico (Petrobras), Eugenio Pacelli (Petrobras), Maria Clara Godinho (Petrobras) |
December 4th, 2024 - 12:00-12:30 PM | Automatic Detection of Breakouts Patterns in Acoustic Image Logs Using MSRF-Net | Renata Nascimento (Tecgraf Institute – PUC-Rio), Augusto Cunha (Tecgraf Institute – PUC-Rio), Gabrielle Brandemburg dos Anjos (Tecgraf Institute – PUC-Rio), Mayara Gomes (Tecgraf Institute – PUC-Rio), Nelia Reis (Tecgraf Institute – PUC-Rio), Raquel Guilhon (Tecgraf Institute – PUC-Rio), Candida Menezes de Jesus (Petrobras) |
December 4th, 2024 - 12:30-02:00 PM | Lunch | |
December 4th, 2024 - 02:00-02:30 PM | Data Science Workflow for Well Logs Quality Control | Maria Clara Machado de Almeida Duque (Schlumberger), Tamires Pereira Pinto da Silva (Schlumberger), Francisco Alamilla Martinez (Schlumberger), Luciana Velasco Medani (Schlumberger) |
December 4th, 2024 - 02:30-03:00 PM | Deep learning as a facilitator for borehole images | Adna Vasconcelos (Schlumberger), Thiago M. D. Silva (Schlumberger), Aurelio Kasakewitch Ribeiro (Petrobras), Jorge André Braz de Souza (Petrobras) |
December 4th, 2024 - 03:00-03:30 PM | Integration of gravity and seismic data for crustal thickness modeling in South America using Gaussian processes | Ítalo Gomes Gonçalves (Federal University of Pampa), Marcus Vinicius Aparecido Gomes de Lima (Federal University of Pampa) |
December 4th, 2024 - 03:30-03:50 PM | Coffe Break | |
December 4th, 2024 - 03:50-04:20 PM | Deep Learning to Map Mass Transport Deposits: Santos Basin case study | Manuel Parcero Oliveira (Petrobras), Ana Krueger (Bluware), Antonio Henrique da Fontoura Klein (UFSC) |
December 4th, 2024 - 04:20-04:50 PM | Deep Learning Methods for Methane Detection in EMIT Hyperspectral Imagery | Reynaldo Souza de Carvalho (UNICAMP), Carlos Roberto de Souza Filho (UNICAMP) |
December 4th, 2024 - 04:50-05:20 PM | Improving velocity model building with Physics Informed Neural Networks and Fourier Neural Operators | Bernardo Fraga (CBPF), Ana Paula Muller (Petrobras), Clecio de Bom (CBPF) |
December 4th, 2024 - 05:20-06:20 PM | Keynote Speaker | |
December 4th, 2024 - 06:20 PM | SBGf Happy Hour - Cachaçaria Mangue Seco |
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