Abstract
Abstract Offshore desk studies play an important role in providing early insights into site conditions and engineering constraints within an offshore area of interest. However, traditional approaches to producing reports with supporting interpretation through static images and charts have limitations that hinder stakeholders from extracting new information through digital tools and data analytics. In the early stages of development considerations, asset concepts, and business requirements often evolve and change rapidly, necessitating a more dynamic and modern approach to data analysis. As the demand for renewable energy sources, including wind power in Brazil, continues to rise, effective planning strategies are required to optimize the placement and installation of offshore wind farms. Integrating diverse datasets, such as wind resource output, geological conditions, engineering constraints, and anthropogenic features, is essential to gain early insights and make informed decisions. In this context, utilizing a modern cloud-based data platform and harnessing the power of data analytics can significantly enhance the planning process. This paper emphasizes the importance of using a modern, cloud-based data platform to integrate existing (e.g., publicly available, or previously collected) and historical (e.g., initial or multi-year) datasets for early offshore infrastructure planning. Understanding wind resource output is a critical parameter in offshore wind development because it determines project economics; however, these early wind analyses are often decoupled from the ground-related conditions, resulting in inefficiencies in planning due to a lack of understanding of how these variations affect the development (i.e., seasonality). By leveraging a modern cloud-based data platform, all these disparate datasets can be efficiently integrated, stored, processed, and analyzed. Cloud-based solutions offer scalability and flexibility, enhancing the usefulness of data integrated from various sources. Furthermore, cloud platforms increase planning efficiency by providing a collaborative environment that facilitates interdisciplinary cooperation among stakeholders, including geoscientists, engineers, environmental experts, and regulators. The integration of data analytics techniques within the cloud-based platform brings added value to offshore infrastructure planning even at the earliest stages. Analytical algorithms, temporal modeling, and advanced tooling can uncover hidden patterns, correlations, and trends within the integrated datasets. The resulting information helps project owners identify potential infrastructure-related challenges. Several examples of advanced analytics from offshore Brazil are provided within the paper, showing how additional insights can be gleaned and concept planning can be expedited by utilizing a modern integrated approach to early site assessments.
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