Information about pipeline integrity is today primarily obtained from two sources:

  • A limited number of sensors (infield pipelines)
  • ROV’s and intelligent pigging

These methods have limitations. Most of the sensors used are intrusive. Intrusive sensors have the advantage that very accurate measurements can be made, but every penetration of the pipeline wall represents a potential weak point. Hence, only a limited number of sensors are mounted on a pipe. Communication distance is the other major limiting factor with respect to sensors. The sensors are powered from the subsea controller and the communication signals are usually transmitted in the power cable. The communication signal strength limits the distance between sensor and subsea controller. A third factor limiting the use of sensors along the pipe is power supply. At present external cables are used for this purpose, but these are vulnerable to damages. 

The use of ROV’s and intelligent pigging tend to be expensive, and in many cases requiring shut-down of the system. This implies only infrequent monitoring along the full length of the pipeline.

Many of the degradation phenomena that may be harmful to pipelines are closely related to local conditions, e.g. the geometry of welds or local material properties. Such local features are not addressed actively in assessments today, due to lack of models to calculate their effects and lack of an overall system to keep track of such details. Neither is the previous load history (installation) for the pipeline actively used due to a lack of knowledge about imposed strains and insufficient understanding on its effect of degradation and cracking phenomena. These are challenges that must be solved in order to improve reliability of lifetime monitoring and management of pipeline performance.

Summarizing some of the benefits:

  • Improved basis for decision making
  • Decreased need for pigging
  • When pigging is not an option
  • Help in planning targeted inspection programs
  • When inspection is difficult, e.g. ultra deep water
  • In environmentally sensitive areas
  • Improved production regularity
  • Input to flow assurance tools
  • A reliable leakage detection system
  • Improved residual life predictions

Published September 25, 2006

Data collection

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