11302 Oblique Field Magnetic Flux Leakage Survey Complements Axial Field Data

Monday, March 14, 2011: 9:00 AM
Room 320 B (George R. Brown Convention Center)
James Simek*
T. D. Williamson/Magpie
Pipeline operators worldwide have implemented integrity management programs in an effort to improve operation and maintenance efficiency along with continued safe operation of pipeline systems.  Several types of monitoring and data collection activities are incorporated into these programs, with inline inspection tools providing data for detection and quantification of features that may impact the integrity of the pipeline system.  Magnetic flux leakage tools are among the most widely used in pipeline systems, typically providing information for metal loss features.  The tool configurations being offered have been expanded in recent years to allow multiple data sets to be collected concurrently.  Magnetic flux leakage tools incorporate fields that are axially aligned with the pipe for detection of general corrosion type features.   For extremely narrow metal loss or certain classes of seam weld features, tools with fields that are circumferentially aligned or transverse to the pipe axis are used.  Presently, multiple independent inline surveys are required to adequately address each of these feature classes. 

Providing the ability to collect both of these data sets in a single survey would allow operators to minimize the number of surveys required to address metal loss features that may be present within pipeline systems.  In addition to fewer surveys being required, the concurrent acquisition of multiple data sets will minimize the time required to perform comparisons of the data sets from each of the surveys.  This paper will discuss the results obtained from modeling and sample test data of magnetic flux leakage signals acquired when the magnetic fields are applied at an angle to the main axis of elongated metal loss features.  Several classes of features have been chosen for evaluation, including extremely narrow axially oriented features.