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API STD 1130

Computational Pipeline Monitoring

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Organization: API
Publication Date: 1 October 1995
Status: inactive
Page Count: 23
scope:

1 Scope

1.1 PURPOSE

This publication focuses on the design, implementation, testing and operation of Computational Pipeline Monitoring (CPM) systems which use an algorithmic approach to detect anomalies in pipeline operating parameters. The primary purpose of these systems is to provide tools that assist Pipeline Controllers in detecting commodity releases that are within the sensitivity of the algorithm. It is intended that the CPM system would provide an alarm and display other related data to the Pipeline Controllers to aid in decision-making. The Pipeline Controllers would undertake an immediate investigation, confirm the reason for the alarm and initiate a response to the anomaly when it represents an operational upset or commodity release.

The purpose of this publication is to assist the pipeline operator in the selection, implementation, testing, and operation of a CPM system. When used in conjunction with other API publications, this publication will prove useful to identify the complexities, limitations and other implications of detecting anomalies on liquid pipelines using CPM systems.

1.2 CONTENTS

This publication includes definitions, source and reference documents, concepts of data acquisition, discussion of design and operation of a pipeline as related to CPM, field instrumentation for CPM purposes, alarm credibility, Pipeline Controller response, incident analysis, record retention, maintenance, system testing, training, considerations for setting alarm limits, trending and recommendations for data presentation. The relationship between the Pipeline Controller and the CPM system is also discussed.

1.3 SCOPE LIMITATIONS

This publication is intended to apply to single phase, liquid pipelines. It is recognized that one particular methodology or technology may not be applicable to all pipelines; each pipeline system is unique in design and operation. In addition, detection of releases by these means is technically complex with detectable limits difficult to quantify, so limits must be determined and validated on a system-by-system basis.

This publication is not all inclusive. The reader must have an intimate knowledge of the pipeline and may have to refer to other publications for background information.

The user of this publication must be familiar with the requirements of local jurisdiction regulations that must be considered in the application of CPM to pipelines.

CPM is intended as another tool to be used in pipeline operation. Pipeline Controllers must be familiar with the pipeline to effectively operate CPM systems. Operational usage and application of CPM systems require human judgment and intervention. An example of this type of action would be activation of Emergency Flow Restricting Devices (EFRDs).

This publication complements but does not replace other procedures for monitoring the integrity of the line. For example: trained Pipeline Controllers analyzing SCADA-presented operating data can be effective at detecting many commodity releases. Also, third party reports; pipeline patrols; employee on-site examinations are other effective procedures used to verify integrity of the pipeline. This publication is in keeping with standard industry practice and commonly used technology; however, it is not intended to exclude other effective commodity release detection methods.

CPM systems, as well as other commodity release detection techniques, each have a detection threshold below which commodity release detection cannot be expected. This publication will not reduce the threshold at which a commodity release can be detected.

Figure 1 (along with the discussion in Appendix B) indicates that CPM is only addressing commodity releases above some practical detection limit.

Document History

November 1, 2002
Computational Pipeline Monitoring for Liquid Pipelines
PURPOSE This publication focuses on the design, implementation, testing and operation of CPM systems that use an algorithmic approach to detect hydraulic anomalies in pipeline operating parameters....
API STD 1130
October 1, 1995
Computational Pipeline Monitoring
1 Scope 1.1 PURPOSE This publication focuses on the design, implementation, testing and operation of Computational Pipeline Monitoring (CPM) systems which use an algorithmic approach to detect...

References

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