with an estimated length, width and depth. In this way, the effective area of metal loss can be calculated and used in acknowledged formulas to predict the estimated burst pressure of the pipe due to the detected anomaly. Another important factor in the ongoing improvement of sizing algorithms is customer feedback to the ILI vendors. Every anomaly in a pipeline is unique and it is impossible to replicate in the shop what exists in all cases in the field. Open lines of communication usually exist between the inspection companies and the pipeline operators as to what was reported and what was actually visually observed in an excavation. After an inspection, the collected data is downloaded and compiled so that an analyst is able to accurately interpret the collected signals. Most pipeline inspection companies have proprietary software designed to view their own tool's collected data. The three components of the MFL vector field are viewed independently and collectively to identify and classify corrosion features. Metal loss features have unique signals that analysts are trained to identify. Estimation of corrosion growth rate High-resolution MFL tools collect data approximately every 2 mm along the axis of a pipe and this superior resolution allows for a comprehensive analysis of collected signals. Pipeline Integrity Management programs have specific intervals for inspecting pipeline segments and by employing high-resolution MFL tools an exceptional corrosion growth analysis can be conducted. This type of analysis proves extremely useful in forecasting the inspection intervals. Other features that an MFL tool can identify Although primarily used to detect corrosion, MFL tools can also be used to detect features that they were not originally designed to identify. When an MFL tool encounters a geometric deformity such as a dent, wrinkle or buckle, a very distinct signal is created due to the plastic deformation of the pipe wall. Crack detection There are cases where large non-axial oriented cracks have been found in a pipeline that was inspected by a magnetic flux leakage tool. To an experienced MFL data analyst, a dent is easily recognizable by trademark "horseshoe" signal in the radial component of the vector field. What is not easily identifiable to an MFL tool is the signature that a crack leaves. References DUMALSKI, Scott, FENYVESI, Louis – Determining Corrosion Growth Accurately and Reliably MORRISON, Tom, MANGAT, Naurang, DESJARDINS, Guy, BHATIA, Arti – Validation of an In-Line Inspection Metal Loss Tool, presented at