Alaska's North Slope wells are subject to a variety of mechanisms that cause corrosive damage to outer casing strings. These include: (1) near-surface casing damage resulting from the ingress of oxygenated (surface) water; (2) corrosive power fluids pumped down the inner annulus of venturi pump wells; and (3) exposure to formation salt water in intervals of poor cement quality. The importance of maintaining casing integrity for safety and environmental reasons, combined with the high cost of pulling tubing strings on the North Slope create a need for an economical means of evaluating outer casing string integrity with the tubing in place.
The successful use of AC magnetic wave, electromagnetic pipe inspection technology to qualitatively assess outer concentric string casing damage for certain well completions has been well documented for applications on Alaska's North Slope since 2006. Information and conclusions drawn in existing literature are all based on the comparison of tool recordings made in the field to the visual inspection of casings subsequently dug up or removed from the well. While these comparisons illustrate many good correlations between recorded metal loss indications and areas of severe metal loss observed in some completions, there remains a need to better quantify the minimum threshold for the extent of casing damage that can be detected via this method.
This paper presents the results of surface tests conducted on dual concentric string pipe configurations with an array of engineered metal loss features designed to test the tool's response to total volumetric metal loss and the spatial configuration of damage to the outer string. The tool's response to deep pitting on the external surface of the inner concentric string is tested as well. Conclusions are drawn in respect to the approximate size and shape of defects that can be expected to be detected for the concentric pipe configurations tested. The application of this knowledge to data recorded in the field will add greatly to the confidence of risk assessments made with this technology in well work decision processes.