Analysis of Predicting Drilling Fluid Loss Using Formation Fracture Modeling and Enhanced Accuracy Through Subsurface Layer Slope Analysis and Petrophysical Logs

Managing fluid spillage during oil and gas drilling is a significant challenge, contributing heavily to operational costs. Effective control and cost reduction depend on predicting and mitigating these incidents. Landslides and mud losses often occur in structurally fractured areas, making fracture diagnosis and modeling crucial for prevention and management. While using well wall imager (FMI) diagrams is a common method for identifying fractures, their high costs and limitations mean they are employed in only a few wells, insufficient for comprehensive model development. This research explores detecting reservoir rock fractures using common petrophysical data, which is cost-effective and widely available in most drilled wells. By analyzing data from four wells, including stratigraphic matching techniques, gamma diagrams, and layer slope development information, and validating with FMI diagrams, the study finds that diameter meter graphs, photoelectric index, sound wave transmission speed, and gamma ray spectrometer readings are responsive to fractures. This responsiveness facilitates the identification of fractured areas, providing a more economical and accessible method for fracture detection and fluid spillage management in drilling operations