In the operation of hydrocarbon liquid pipelines, Computational Pipeline Monitoring (CPM) systems are used for software based leak detection. When installed, CPM systems must meet the regulatory requirements such as API 1130 in the USA and CSA Z662 in Canada. API RP 1130 provides several methods that can be used to test a CPM system: forced parameter testing, simulated leak test (SLT), and fluid withdrawal testing (FWT). Leak tests are performed to establish and verify the leak detection capabilities of the installed CPM system and in some cases test the response of the personnel. One of the primary interests in leak testing is the realism or hydraulic accuracy of the leak signature, in order that the reported leak sensitivity results of the test are reflective of the real performance of the CPM system. Simulated leak tests (SLT’s) use an offline pipeline model to generate hydraulically accurate data which can be fed into the CPM model. SLT’s provide the most flexible and hydraulically accurate solution to simulating leaks, compared to some of the other API RP 1130 compliant test methods. SLT’s do not have leak location restrictions and also correctly models the flow and pressure hydraulic signature of a leak. The paper outlines a novel approach and method to leak simulation, based on its size and shape of the leak hole. This method can be used to represent various sizes of a leak, ranging from a pin hole to a large rupture along the seam. Implementation of the method in a simulator developed with commercial software is discussed. The results of the simulation, namely the hydraulic signatures from the simulated leak and the CPM response, are compared with the widely used leak simulation method using a constant leak rate. Finally, possible applications of this method are considered.
As defined in American Petroleum Institute Recommended Practice 1130 (API RP 1130), CPM system leak detection performance is evaluated on the basis of four distinct but interrelated metrics: sensitivity, reliability, accuracy and robustness. These performance metrics are captured to evaluate performance, manage risk and prioritize mitigation efforts. Evaluating and quantifying sensitivity performance of a CPM system is paramount to ensure the performance of the CPM system is acceptable based on a company’s risk profile for detecting leaks. Employing API RP 1130 recommended testing methodologies including parameter manipulation techniques, software simulated leak tests and/or removal of test quantities of commodity from the pipeline are excellent approaches to understanding the leak sensitivity metric. Good reliability (false alarm) performance is critical to ensure that control center operator desensitization does not occur through long term exposure to false alarms. Continuous tracking and analyzing of root causes of leak alarms ensures that the effects of seasonal variations or changes to operation on CPM system performance are managed appropriately. The complexity of quantifying this metric includes qualitatively evaluating the relevance of false alarms. The interrelated nature of the above performance metrics imposes conflicting requirements and results in inherent trade-offs. Optimizing the trade-off between reliability and sensitivity involves identifying the point that thresholds must be set to obtain a balance of a desired sensitivity and false alarm rate. This paper presents an approach to illustrate the combined sensitivity/reliability performance for an example pipeline. The paper discusses considerations addressed while determining the methodology such as stakeholder input, ongoing CPM system enhancements, sensitivity/reliability trade-off, risk based capital investment and graphing techniques. The paper also elaborates on a number of identified benefits of the selected overall methodology.
This paper proposes the InstantGrid framework for on-demand construction of grid points. The framework comprises the following components: (1) a centralized model of software management using an application-centric software grouping scheme; (2) proactive configuration of grid middleware, which shortens the time in composing and switching between execution environments; (3) performance optimization techniques using I/O caching and discriminative file sharing mechanisms; and (4) an in-memory execution mode that enables a machine to participate in grid without affecting the OS/data stored in the permanent storage. Compared with traditional approaches, this new framework is designed to substantially simplify software management in grid systems, and is capable to instantly turn any computer (be it a cluster node or a desktop PC) into a grid-ready platform with the desired execution environment. The advanced features also facilitate ad-hoc formation of grid platforms in computers having idle resources. We describe a reference implementation of InstantGrid for constructing Linux-based grid points. Experimental results demonstrate that a 256-node grid point with commodity grid middleware can be constructed in 5 minutes from scratch.
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