pipeline leak detection n.
Skip this Video
Loading SlideShow in 5 Seconds..
Download Presentation


1019 Views Download Presentation
Download Presentation


- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. PIPELINE LEAK DETECTION Eric Penner Josh Stephens 4/30/09

  2. Overview

  3. Introduction

  4. WHERE ARE PIPELINES LOCATED? • Roughly 500,000 miles of pipeline in US • 300,000 miles of gas pipeline • 200,000 miles of oil pipeline • About 1.2 million miles of pipeline in the world • Russia and Canada are next two on list with ~250,000 miles and 100,000 miles of pipeline, respectively


  6. Significant Incidents • Significant incidents meet any of the following conditions as defined by the PHMSA • Fatality or injury requiring hospitalization • $50,000 or more in total costs, measured in 1984 dollars • Highly volatile liquid releases of 5 bbls or more or other liquid releases of 50 bbls or more • Any liquid releases resulting in an unintentional fire or explosion


  8. WHAT ARE THE PRIME CAUSES? • Excavation damage is the number one cause • Most experts regard corrosion as second leading cause, feeling that a strong portion of those under the “All Other Causes” heading are corrosion related as well

  9. Methods of Leak Detection

  10. HARDWARE LEAK DETECTION Pros Cons • Generally good sensitivity • Able to detect large and small leaks quickly • Leak location can be estimated via instrumentation • Previous two points help minimize environmental and economic impact in event of leak • High level of instrumentation • Installation and maintenance costs can be relatively high • Complex installations • Considerable amount of below surface activity

  11. IN BRIEF: ACOUSTIC EMISSIONS • Method relies on escaping fluid giving off a low frequency acoustic signal • Acoustic sensors placed around entire length of pipeline to monitor interior pipeline noise • Baseline or “acoustic map” created • Deviation from baseline triggers system alarm

  12. IN BRIEF: VAPOR SENSOR METHOD • Vapor sensing tube placed along entire length of pipeline • Tube is permeable to material being transported • If leak occurs, some material diffuses into tube • Test gas is pumped through and analyzed for vapors of pipeline fluid

  13. IN BRIEF: ULTRASONIC FLOW METER • Generates an axial sonic wave in pipe wall • Difference in time for wave to travel upstream and downstream allows for computation of flow rate • Relies on mass flow balance

  14. FIBER OPTIC SENSING: BASICS • Probes placed along pipeline every 0.5 meters • Escaping hydrocarbons change surrounding temperature • Liquid leaks ↑ T • Gas leaks ↓ T (Joule Thompson effect) • Scattered light analysis • Raman (intensity based) • Brillouin (frequency based)

  15. Performance and Cost • Cost • 1200 km single pipeline • Roughly the distance from Houston to El Paso • ~$18 million in equipment costs alone • Figure does not include installation • Conclusion: fiber optic leak detection requires a sizeable upfront investment

  16. Software Leak Detection Instrumentation is used to measure internal parameters of the pipeline What methods are available? Balancing Systems Pressure Analysis Generalized Likelihood Ratio

  17. Balancing Systems Basic principle is conservation of mass Basic line balance does not compensate for changes in line pack due to pressure, temperature, or product composition Volume balance is an enhanced, automated technique, which does account for line pack correction by assessing changes in volume due to temperature and/or pressure variations using SCADA (Supervisory Control and Data Acquisition) Steady State assumed MI MO

  18. Why pressure measurements? • Stream 1 and 2 measured • Discrepancy in flow measurement Sensor 1 Leak Sensor 2 Case 1 0.4 0 0 Case 2 0 0.4 0 Case 3 0 0 -0.4

  19. Balancing Systems Example: 1250 m pipeline Can identify leaks as small as 5% of flow Flow metering at the end of each pipeline segment will not identify location of leak Cannot distinguish leak from bias Cannot find location of leak Cost: ~ $200,000 MI MO

  20. Pressure Analysis How is this implemented? Pressure indicators segmenting pipeline Changes in flow produce changes in pressure transients Propagate through the system until steady-state is reached SCADA values used to calculate theoretical hydraulic profile or baseline

  21. Pressure Analysis • Presence of a leak can be determined from specific deviation or combinations of several deviations • Example: 1250 m long pipeline • Leaks as small as 5% of nominal liquid flow • Located with an error smaller than 5 meters • Cost: ~ $200,000 • Cannot distinguish a leak from a bias • Limitations • Not only leaks cause disturbances in pressure changes (junctions, nodes, bends)

  22. GENERALIZED LIKELIHOOD RATIO • Statistical method modeled after flow conditions in pipeline • Mathematical model used that describes effects of leaks and biases on the flow process • Detects leaks in pipeline branch, location in the branch, and magnitude of the leak. • Identifies various types of gross errors

  23. GLR for Gross Error Identification Process Model Steady state model without leak is a measurement vector is the true value of state variables is the vector of random error = constraint matrix Measurement Bias Model b is the bias of unknown magnitude in instrument I = is a vector with unity in position i Process Leak Model A mass flow leak in process unit (node) j of unknown magnitude b can be modeled by; the elements of vector correspond to the total mass flow constraint associated with node j Procedure for single gross error When there is no gross error; S. Narasimhan and R.S.H. Mah. "Generalized Likelihood Ratio Method for Gross Error Identification." AIChe Journal 33, No.9(1987): 1514-1519.

  24. GLR for Gross Error Identification If a gross error due to a bias of magnitude b is present in measurement I, then; If a gross error due to process leak in magnitude b is present in node j, then; When a gross error due to a bias or process leak is present; let μ be the unknown expected value of r, we can formulate the hypotheses for gross error detection as Ho: is the null hypothesis that no gross errors are present and H1: is the alternative hypothesis that either a leak or a measurement bias is present. b and fi are unknown parameters. b can be any real number and fi will be referred to as a gross error vectors from the set F For a bias in measurement i For a process leak in node j

  25. GLR for Gross Error Identification We will use the likelihood ratio test statistics to test the hypothesis by: The expression on the right hand side is always positive. The calculation can be simplified by the calculation by the test statistics, T as: The maximum likelihood estimate : Substituting in the test statistics equation and denoting T by Ti: Where: This calculation is performed for every vector fi in set F and the test statistics T is:

  26. GLR Mechanical Energy balance Without leak Liquids Gases With leak of magnitude b and location lb Liquids Gases Miguel J. Bagajewicz and Emmanuel Cabrera. "Data Reconciliation in Gas Pipeline Systems." Ind. Eng. Chem. Res 42, No.22(2003): 1-11

  27. GLR Problem formulation Without Error: Subject to: With Error: Subject to: So:

  28. GLR Implementation Leak detection procedure: • Hypothesize leak in every branch and solve data reconciliation problem • Obtain GLR test statistic for each branch objno_leak –objwith_leak_k • Determine the maximum test statistic objno_leak - objwith_leak_k • We compare the max test statistic with the chosen threshold value: Max{objno_leak – objwith_leak_k}> threshold value: leak is identified and located in the branch corresponding to the maximum test statistic NOTE: Assuming only one possible error

  29. Sample Pipeline Network

  30. Simulation Procedure - Leak in Pipe 1 Calculator Optimizer Leak simulated in Pipe 1

  31. Simulation Results- Leak in Pipe 1

  32. Simulation Procedure - Leak in Pipe 8 Leak simulated in Pipe 8

  33. Simulation Results- Leak in Pipe 8

  34. GENERALIZED LIKELIHOOD RATIO • Results • More accurate to do GLR in Pro II as opposed to Excel • For a system with a single gross error, GLR can distinguish between a bias and a leak • Procedure more complex for multiple gross errors • Accuracy of the method increases with increasing magnitude of simulated bias

  35. Cost Comparison

  36. Economic Value • Which method is the most economic? • Cost = L + P + M + F • Where • L is the value of product lost due to leaks • P is the value of lost production (ie, that value of product that would have been shipped if a leak and shut down of the pipeline had not occurred) • M is the maintenance and installation cost of detection equipment • F is the value of fines levied for leaks

  37. CALCULATING L (PRODUCT LOST DUE TO LEAK) • Average leak size • PHMSA data provided an average leak size • Adjusted average leak size for sensitivity of detection method • Detecting smaller leaks reduces average leak size • Accounted for frequency of leaks being different • Detecting smaller leaks results in more detected leaks

  38. CALCULATING L (PRODUCT LOST DUE TO LEAK) • Price of oil and natural gas • Difficult to accurately predict either • Oil price varied between $40-$80 • Natural gas price varied between $4-$12 • Clean up costs due to leak included • Range from $700 to $5,000 per bbl

  39. CALCULATING P (LOST VALUE PRODUCT TRANSPORTED) • Not the same as leak loss • Calculated the value lost via shut down of pipeline to fix leaks • The value of what could have been transported during that down time • Amount flowing through pipeline: API Recommended best practices

  40. CALCULATING M (MAINTENANCE) AND F (FINES) • Maintenance assumed to be 5% of Base Cost for each method • Fines • EPA fines the costliest • Cost per bbl estimate • Clean Air Act • Clean Water Act • Industry examples • This estimate multiplied by leak size under each method to calculate the corresponding fine

  41. Methodology • GLR compared with Ultrasonic, Volume Balance, and Pressure Analysis Methods • Pressure analysis methods grouped together since there is no significant change in base cost or implementation among them • Excel database created to compare methods • Cost of crew, instrumentation, and different levels of tuning required were taken into account for each model • Various companies were contacted to estimate cost of different detection schemes

  42. Methodology • Simulations were run for varying nominal pipe diameters • 2 to 8 inches for gathering/distribution networks • 12 to 24 inches for single pipeline • Multiple scenarios tested for each • Range of values used for price of oil, natural gas, and for leak clean up • Pipeline length varied from 0.1 to 10,000 miles • Time for repair of leak assumed to be the same for all methods

  43. 6” Nominal Diameter: Oil

  44. 20” Nominal Diameter: Oil

  45. 20” Nominal Diameter: Natural Gas • Example • 8000 mi pipeline • ~ $1 million in cost difference between Ultrasonic and GLR

  46. Conclusion • GLR showed to be the most economic for both single pipelines and gathering/distribution networks • This held true for oil as well as natural gas • GLR shows more separation from the other methods in the case of oil, due to the higher product value • Implementing GLR results in less fines and less lost production

  47. Questions

  48. Hardware Comparison

  49. Corrosion Prevention • Corrosion-related cost to the pipeline industry is approximately $5.4 to $8.6 billion annually • Cathodic protection is required on all interstate pipelines and has been for decades • Technique uses a constant low voltage electrical current run through the pipeline to counteract corrosion – corrosion can create a galvanic cell • Pipeline coating is the other common corrosion prevention

  50. Pigs and Smart Pigs • Pigs are cylinder shaped plugs of the same diameter as the pipe • Smart pigs are fitted with electronic sensors that can help locate pipeline wall weaknesses prior to a leak appearing • Both scrape build-up off the interior wall of the pipeline, which also helps prevent corrosion