Hector G. Lopez-Ruiz
Science Specialist
Aramco R&D
Dr. Hector G. Lopez-Ruiz is a Research Science Specialist with extensive experience in developing AI-driven solutions for the energy sector. As a key contributor to the SOFFIA project, he has spearheaded efforts to integrate satellite imagery, economic modeling, machine learning, and AI to address complex challenges in economic and energy forecasting.
Hector’s expertise spans geospatial analytics, environmental data processing, and predictive modeling, with a particular focus on downstream energy markets.
Participates in
TECHNICAL PROGRAMME | Energy Technologies
The Energy Transition: The Role of Digitalisation, AI, and Cybersecurity
Forum 23 | Technical Programme Hall 4
29
April
14:30
16:00
UTC+3
The energy transition is a complex and multifaceted challenge that requires innovative solutions to manage complex energy systems, optimize operations. Digitalisation and AI are key enablers of this transition, providing the tools and frameworks needed to transform the energy industry and meet future challenges. This presentation explores the latest advancements in these areas and discusses how they are transforming the energy industry.
One such advancement is the development of SOFFIA-AI (Satellite Observation For Forecasting, Intelligence and Analytics), an advanced platform that integrates satellite data, economic indicators, and artificial intelligence to provide actionable insights for energy market stakeholders. By utilizing H3 hexagonal grids—subcity-level spatial units—SOFFIA-AI bridges the gap between complex data streams and actionable intelligence, enabling precise, data-driven decision-making in downstream energy markets.
The presentation will demonstrate SOFFIA-AI's application in trading and market analytics, focusing on its ability to enhance real-time nowcasting and forecasting of regional energy demand. By leveraging data sources such as methane emissions, nightlight intensity, and Google Trends, the platform provides traders with granular insights into market dynamics, empowering them to anticipate shifts in demand, improve hedging strategies, and make informed trading decisions.
Furthermore, the presentation will explore SOFFIA's innovative use of large language models (LLMs) to extract, summarize, and analyze unstructured data, including market reports, news articles, and regulatory updates. This integration enables seamless access to relevant market information, significantly enhancing decision-making processes. By combining these AI-driven tools with high-resolution geospatial data, SOFFIA provides an unparalleled framework for informed decision-making.
Through case studies in the Middle East, the presentation highlights how SOFFIA's integrated approach reduces uncertainty, enhances decision accuracy, and drives sustainability. For instance, SOFFIA's real-time demand forecasts could enable traders in the Gulf region to optimize their portfolios, achieving an improvement in efficiency. Similarly, its ability to identify regional demand spikes has supported better logistical planning and inventory management for downstream players.
The discussion will also touch upon scalability, emphasizing how SOFFIA's modular architecture allows seamless adaptation to various downstream segments, including chemicals and retail. By focusing on actionable insights derived from sophisticated AI tools, SOFFIA empowers stakeholders across the downstream value chain to make data-driven decisions, leading to both economic and environmental benefits.
Overall, this presentation showcases the transformative potential of digitalisation, AI, and cybersecurity in the energy sector, highlighting the latest advancements and innovations that are driving a sustainable energy transition.
One such advancement is the development of SOFFIA-AI (Satellite Observation For Forecasting, Intelligence and Analytics), an advanced platform that integrates satellite data, economic indicators, and artificial intelligence to provide actionable insights for energy market stakeholders. By utilizing H3 hexagonal grids—subcity-level spatial units—SOFFIA-AI bridges the gap between complex data streams and actionable intelligence, enabling precise, data-driven decision-making in downstream energy markets.
The presentation will demonstrate SOFFIA-AI's application in trading and market analytics, focusing on its ability to enhance real-time nowcasting and forecasting of regional energy demand. By leveraging data sources such as methane emissions, nightlight intensity, and Google Trends, the platform provides traders with granular insights into market dynamics, empowering them to anticipate shifts in demand, improve hedging strategies, and make informed trading decisions.
Furthermore, the presentation will explore SOFFIA's innovative use of large language models (LLMs) to extract, summarize, and analyze unstructured data, including market reports, news articles, and regulatory updates. This integration enables seamless access to relevant market information, significantly enhancing decision-making processes. By combining these AI-driven tools with high-resolution geospatial data, SOFFIA provides an unparalleled framework for informed decision-making.
Through case studies in the Middle East, the presentation highlights how SOFFIA's integrated approach reduces uncertainty, enhances decision accuracy, and drives sustainability. For instance, SOFFIA's real-time demand forecasts could enable traders in the Gulf region to optimize their portfolios, achieving an improvement in efficiency. Similarly, its ability to identify regional demand spikes has supported better logistical planning and inventory management for downstream players.
The discussion will also touch upon scalability, emphasizing how SOFFIA's modular architecture allows seamless adaptation to various downstream segments, including chemicals and retail. By focusing on actionable insights derived from sophisticated AI tools, SOFFIA empowers stakeholders across the downstream value chain to make data-driven decisions, leading to both economic and environmental benefits.
Overall, this presentation showcases the transformative potential of digitalisation, AI, and cybersecurity in the energy sector, highlighting the latest advancements and innovations that are driving a sustainable energy transition.
