Towards an Ai-Based Advisor for Capturing Interpretive Trails and Supporting Geological Exploration Activities

Many activities in the Oil & Gas (O&G) industry rely on expert interpretation over unstructured data and interpretation of elaborate geological concepts. Keeping track of the consumption and production of conceptual knowledge and data is crucial to structure such investigative processes. Nevertheless, capturing and structuring activities of this nature is a complex requirement if an advisor system is to be designed and implemented to support decision making in such domain. We propose a novel representation to keep track and model experts’ interaction with different systems, along with multimodal data and conceptual knowledge they consume and produce during interpretive activities. The proposed representational approach aims at supporting the design and implementation of intelligent advisor systems for knowledge-intensive processes, such as the ones observed in the multidisciplinary domain of O&G.