Development of a graphical user interface for predicting damage zones of geological faults

Resumo

In the oil and gas industry, the characterization of fault damage zones is important to develop suitable production strategies. Owing to the high levels of deformation experienced in the past, fault damage zones typically exhibit regions with physical properties that are markedly different from those of the host rocks. Those regions can contain fracture networks triggering preferential flow paths or contain deformation bands creating barriers for fluid flow. For practical applications, the width of fault damage zones has been linked to the fault throw through power law relationships. However, the significant dispersion of outcrop observations has shown that other parameters such as lithology and mechanical properties of the host rock under deformation can be responsible for the scattering. Thus, the assessment of damage zones around geological faults has been performed through numerical analysis incorporating rock plasticity. Nevertheless, such simulations are computationally expensive. To address this limitation, the use of data-driven predictive modeling emerges as a promising alternative. In this context, the present study proposes the development of a user-friendly graphical interface application aimed at predicting damage zones around geological faults. The application utilizes fault geometry and calculated displacements at observation points, derived from a geological model, along with key rock geomechanical parameters such as Young’s modulus, Poisson’s ratio, friction angle, cohesion, critical pressure, and dilatancy angle. The process is efficiently performed using machine learning models, enabling the user to check the sensitivity of the damage zone width regarding the input parameters in real-time. The proposed tool offers a computationally efficient and interactive approach for the prediction and analysis of fault-associated damage zones, contributing to more informed decision-making in reservoir modeling and management within geologically complex settings.