Probability of Detection and False Detection for Subsea Leak Detection Systems: Model and Analysis
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TECHNICAL ARTICLE—PEER-REVIEWED
Probability of Detection and False Detection for Subsea Leak Detection Systems: Model and Analysis Alireda Aljaroudi . Faisal Khan . Ayhan Akinturk . Mahmoud Haddara . Premkumar Thodi
Submitted: 22 September 2015 / Published online: 27 October 2015 Ó ASM International 2015
Abstract Ensuring the integrity of subsea process components is one of the primary business objectives of the oil and gas industry. Leak detection system (LDS) is one type of system used to safeguard reliability of a pipeline. Different types of LDS use different technologies for detecting and locating leaks in pipelines. One technology, which is gaining wide acceptance by the industry, is the fiber opticbased LDS. This technology has great potential for subsea pipeline applications. It is the most suited for underwater applications due to the ease of installation and reliable sensing capabilities. Having pipelines underwater in the deep sea presents a great challenge and a potential threat to the environment and operation. Thus, there is a need to have a reliable and effective system to provide the assurances that the monitored subsea pipeline is safe and functioning as per operating conditions. Two important performance parameters that are of concern to operators are the probability of detection and probability of false alarm. This paper presents a probabilistic formulation of the
A. Aljaroudi (&) F. Khan M. Haddara Memorial University, St. John’s, NL, Canada e-mail: [email protected] F. Khan e-mail: [email protected] M. Haddara e-mail: [email protected] A. Akinturk National Research Council, St. John’s, NL, Canada e-mail: [email protected] P. Thodi INTECSEA, WorleyParsons Group, St. John’s, NL, Canada e-mail: [email protected]
probability of detection and probability of false detection for a fiber optic-based LDS. Keywords Probability of detection (PD) Probability of false alarm (PFA) Leak detection system (LDS) Oil and gas pipeline Nomenclature BSS Brillouin-Stimulated scattering CW Continuous wave LDS Leak detection system NP Noise Power PD Probability of detection PFA Probability of false alarm PMD Probability of missed detection SNR Signal-to-noise ratio c Speed of light (Km/s) d Location of the temperature change dP= Temperature coefficient (mW/°C) dT dP= Strain coefficient (mW/le) de n Refractive index Aeff Effective area of the fiber Leff Effective length of the fiber gB Gain Po Reference power PB(measured) Measured Brillouin power PCW Input probe power PP Pulse power ae Strain coefficient expressed in MHz/le aT Temperature coefficient expressed in MHz/ °C De Strain change DT Temperature change DTmeasured Measured temperature change
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Dt Va vB s k vo Dt Xth
J Fail. Anal. and Preven. (2015) 15:873–882
Minimum detectable temperature change Acoustic velocity Brillouin frequency shift Pulse width Wavelength of the incident light Reference Brillouin frequency at no strain and at the ambient temperature (MHz) Traveled time Temperature change threshold
False detection resul
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