Abstract This paper presents the development and practical application of Artificial Intelligence (AI) as a technical assistant to access information, automate workflows, and optimize reservoir characterization processes, with a particular focus on reservoir dynamic characterization through monitoring API gravity diagnostics, flow rates, and the interpretation of pressure-production tests (decline curves with a homogeneous and infinite reservoir model) in a real-case scenario. AI was employed to identify complex patterns, extract technical information from large volumes of data from diverse sources, automate monitoring, conduct preliminary diagnostics of reservoir behavior, and interpret pressure-production tests. This approach enhances value chain efficiency, reduces response times, optimizes well and field management, and opens new opportunities for reservoir optimization.
Mateos et al. (Tue,) studied this question.