This session is focused in advanced technologies that offer reduced environmental footprint, improved safety and higher efficiency in field operations, including Seismic, Potential, EM, Electrical methods. Topics will include new kinds of sensors and sources, innovative methods for deploying and retrieving sensors and sources in onshore and offshore environments, higher degree of automation in field operations using, for instance, drones, Remotely Operated Vehicle (ROV), Autonomous Underwater Vehicle (AUV), and Unmanned Surface Vehicle (USV). Also, fiber optics use as sensing element in applications such as Distributed Acoustic Sensing (DAS), Distributed Temperature Sensing (DTS), and Distributed Strain Sensing (DSS) are included in this session.

This session will explore the geological and hydrocarbon potential of the Equatorial Margin and Pelotas Basin, regions of growing interest for oil and gas exploration. Key topics will include the unique geological features, challenges in exploration, and the latest advances in seismic imaging and subsurface evaluation. Experts will discuss the opportunities and risks associated with developing resources in this region, as well as the regulatory and environmental considerations that impact exploration and production activities along the Equatorial Margin and Pelotas Basin.

Topics will include forensic geophysics, environmental geophysics for assessing contamination and ecosystem health, and hydrogeophysics for understanding groundwater systems. Additionally, we will discuss critical zone science and its relevance in studying the interactions between the Earth's surface and subsurface. (Geohazard e geotechnic)

This Mining Geophysics session aims to highlight the latest advances in mineral exploration geophysics, focusing on: (1) Deep crustal studies and their importance in understanding mineral systems; (2) Magnetotellurics (MT) for minerals; (3) 3D seismic for mineral exploration; (4) Processing and inversion of potential field data applied to mineral exploration; (5) Processing and inversion of electrical and electromagnetic (EM) methods; (6) Processing and inversion of gamma spectrometric data; (7) Borehole geophysics; (8) Hard rock petrophysics; (9) 3D modeling and interpretation of magnetic, gravity, electrical, and electromagnetic methods for mineral exploration and geological mapping; (10) Characterization of the footprint of mineral systems through geophysical, geochemical, petrophysical, and mineral mapping data; (11) Data visualization and integration; (12) Machine learning or artificial intelligence; (13) Critical and strategic minerals and (14) Case studies.

Artificial Intelligence (AI) is revolutionizing geophysics by improving data analysis, interpretation, and decision-making in subsurface applications. In seismic analysis, AI accelerates fault detection, horizon picking, and noise reduction, while in reservoir characterization, machine learning integrates seismic, petrophysical, and production data to predict rock properties and fluid distribution. AI also enhances mineral exploration, earthquake monitoring, and environmental monitoring in carbon capture, geothermal energy, and renewable projects, supporting the energy transition by optimizing site selection and resource management.While AI offers increased efficiency, improved accuracy, and enhanced decision-making, challenges remain, such as the need for high-quality data, interpretability of AI models, and training geophysicists to use these tools effectively. As the technology matures, its applications in geophysics are expected to expand, driving sustainable resource exploration and innovative energy solutions.

This section focuses on research and development in geophysics, showcasing innovative approaches and technologies driving the field forward. Topics include the development of advanced geophysical tools, methods, and workflows for enhanced subsurface characterization. Emphasis will be placed on cutting-edge research in seismic imaging, inversion techniques, and multi-physics integration. Additionally, the role of Artificial Intelligence, machine learning, and computational advancements in solving complex geophysical challenges will be highlighted.

This session will explore key aspects of the energy transition, focusing on diversifying energy sources and decarbonizing our systems. Topics will include Deep Sea Mining for critical minerals essential to clean energy technologies, Hydrogen (H₂) prospection as a promising alternative fuel, and Carbon Capture, Utilization, and Storage (CCUS) alongside Carbon Sequestration (CCS) to reduce greenhouse gas emissions. We will discuss the challenges and opportunities these technologies present in the shift toward a sustainable, low-carbon energy future.

Data and computer science innovations support geophysical developments by enhancing how we process, interpret, and utilize complex subsurface data for exploration, monitoring, and resource management. Big data analytics enables geophysicists to process massive datasets from seismic surveys, well logs, and remote sensing in real-time, uncovering patterns and insights faster than ever before. Machine learning and AI algorithms further automate tasks such as fault detection, reservoir characterization, and seismic facies classification, leading to more accurate and efficient interpretations.High-performance computing (HPC) accelerates computationally intensive techniques like full-waveform inversion (FWI) and reverse time migration (RTM), allowing geophysicists to produce detailed subsurface models. Robotics and automation also improve data collection in remote or hazardous areas, ensuring safety and precision. Together, these innovations enable geophysics to tackle challenges like optimizing renewable energy projects, improving carbon capture and storage (CCS) monitoring, and supporting the transition to sustainable energy solutions. By integrating data-driven technologies, geophysics can achieve greater efficiency, accuracy, and environmental responsibility.

Seismic Acquisition & Processing involves collecting and refining seismic data to create accurate subsurface images for resource exploration. This topic aims to cover Acquisition Geometries, Simultaneous Source, Multi Component, High Resolution for Shallow Subsurface, Borehole Seismic Methods, Micro & Passive Seismic, Seismic Processing methods.

Seismic Velocities & Imaging are crucial for interpreting subsurface structures in geophysics. Calibrated seismic velocities are essential for depth conversion, migration, and reservoir characterization. Imaging Theory & Wavefield Modelling, FWI (Full Waveform Inversion), Elastic Full Waveform Inversion (eFWI), Velocity Model Case Studies, ML & AI for Seismic Imaging & Velocities will be covered on this topic.

This topic aims to conver seismic interpretation case-studies and topics related to Quantitative Interpretation & AVO, Rock Physics, Anisotropy & Fractured Reservoirs, Seismic Attributes, ML & AI for Seismic Interpretation & Characterization

4D Seismic (Time-lapse Seismic) is a geophysical technique used to monitor changes in subsurface reservoirs over time by comparing repeated seismic surveys. Sub-topics related are Acquisition Geometries, Processing Methods, 4D interpretation, Reservoir Monitoring and Production Optimization, Quantitative Interpretation of 4D Seismic Data, 4D Seismic Applications in CCS (Carbon Capture and Storage)

Potential Methods are geophysical techniques that use variations in Earth's gravitational and magnetic fields to explore subsurface structures. Gravity surveys measure density contrasts to detect geological features like salt domes or basins, while magnetic surveys identify variations in rock magnetism, often used for mineral exploration and structural mapping. Topics related to it will be Gravity & Magnetic Data Acquisition and Processing, Gravity and Magnetic Inversion & Interpretation, Airborne, Marine, and Ground-Based Potential Field Surveys.

Electromagnetic (EM) and Electrical Methods are geophysical techniques used to investigate subsurface properties by measuring electrical conductivity and resistivity variations. EM methods, such as Magnetotellurics (MT) and Controlled-Source Electromagnetics (CSEM), detect conductive structures like hydrocarbons, mineral deposits, and geothermal reservoirs.

Direct integration of diverse datasets for subsurface imaging, integrated interpretation of multiple inversions using a generalizable framework, sequential and joint inversion of multiple datasets, statistical and machine learning-driven information extraction, or a hybrid approach combining these methods

Remote Sensing is a geophysical technique that uses satellite, airborne, and drone-based sensors to collect data about Earth's surface and subsurface without direct contact. It employs optical, infrared, radar, and hyperspectral imaging to map geological structures, mineral deposits, vegetation, and environmental changes. In geophysics, remote sensing aids in resource exploration, geological mapping, and hazard assessment by identifying surface expressions of subsurface features. Advances in sensor technology, data analytics, and artificial intelligence have enhanced remote sensing applications, making it a vital tool for efficient and large-scale geological investigations.

Space Geophysics explores Earth's subsurface and planetary structures using geophysical techniques applied in space environments. It involves studying Earth's magnetic and gravitational fields, ionospheric and magnetospheric interactions, and extraterrestrial geology through satellite missions, planetary landers, and remote sensing. Space geophysics aids in understanding Earth's deep interior, monitoring space weather, and exploring celestial bodies like the Moon and Mars for resource potential. Advances in satellite geodesy, planetary seismology, and magnetometry continue to enhance our knowledge of planetary processes and their implications for both Earth and space exploration.

Integrated Reservoir Characterization combines geological, geophysical, and engineering data to create a comprehensive model of the subsurface for optimal resource exploration and production. It involves integrating seismic interpretation, well logs, core analysis, petrophysical properties, and dynamic reservoir data to understand rock quality, fluid distribution, and reservoir behavior. This multidisciplinary approach improves reservoir modeling, enhances recovery strategies, and reduces uncertainties in decision-making. Geophysics, Geology, Petrophysics, Reservoir Engenieer, Rock Mechanics, Geomechanics, Well Construction are sub-topics related to this.

Geophysics plays a vital role in pre-salt exploration and development by addressing the challenges posed by thick salt layers that distort seismic signals. Advanced imaging techniques, such as Full Waveform Inversion (FWI) and Reverse Time Migration (RTM) enhance subsalt imaging, while integrated geophysical approaches—combining seismic, gravity, magnetics, and rock physics—improve reservoir characterization. Accurate imaging relies on velocity model building, which is refined through tomography and machine learning methods. Additionally, emerging technologies like 4D seismic and fiber optic sensing are advancing reservoir monitoring and production optimization tools. These innovations are unlocking new hydrocarbon potential in complex pre-salt plays.

Geophysics is crucial for maximizing recovery in mature fields by enhancing subsurface imaging, monitoring reservoir dynamics, and guiding targeted interventions. High-resolution seismic reprocessing, including 4D seismic and advanced inversion techniques, helps identify bypassed hydrocarbons and reservoir compartmentalization. Integrating geophysical data with production history, well logs, and machine learning models enhances reservoir forecasting and optimizes secondary and tertiary recovery strategies. Additionally, passive seismic monitoring and fiber optic sensing provide real-time insights into fluid movements and geomechanical changes, enabling data-driven decisions to extend the productive life of aging fields.

This section will discuss geophysical theories and techniques applied to onshore oil and gas exploration and production, covering data acquisition methods, such as onshore nodal seismic data, as well as noise attenuation techniques, high-resolution imaging, and inversion techniques. Additionally, papers showcasing the application of artificial intelligence in geophysical data processing and interpretation are expected.

The ultimate goal of this session is to bring together different scientific communities dealing with the modelling of dense granular flows, creating a multidisciplinary synergy around a common field to highlight the state-of-the-art, current research and future perspectives throughout the conference.

This session is dedicated to the study of Earth's magnetic field, including its oigin, changes, and impact on the planet. In a subset of geomagnetism field, paleomagnetism focuses on the magnetic properties of rocks, sediments and archeological materials. It examines how the Earth's magnetic field has changed over geological time