API St 2560-2010 pdf download.Reconciliation of Liquid Pipeline Quantities.
1 Introduction 1.1 In the ideal world every drop of liquid received into a pipeline system and every drop delivered out of the system, as well as all liquid inventory within the system, would be mea- sured and accounted for precisely, and a comparison of all receipts and all deliveriesÑadjusted for inventory changesÑ would be exactly the same. The system would never experi- ence a loss or a gain. Unfortunately, this ideal pipeline bal- ance seldom exists in the real world. 1.2 Most pipeline systems typically experience some degree of loss or gain over time. This represents the normal loss/gain performance for a system. From time to time, losses or gains greater than normal may occur for a variety of rea- sons. Excessive or unexplained loss/gain often leads to con- tention between participating parties, sometimes requiring monetary settlements to adjust for abnormal loss/gain. In such cases, it is necessary to be able to (1) identify abnormal loss/gain as quickly as possible, (2) determine the magnitude of abnormal loss/gain, and (3) institute corrective actions. 1.3 Sometimes losses or gains are real, and adjustments must be made to correct shipper batches and/or inventories. Most of the time, though, there are no real physical losses or gains. The loss/gain that occurs in day-to-day operation is usually small (a fraction of a percent) and is caused by small imperfections in a number of measurements in a system. 1.4 In a sense, loss/gain is a measure of the ability to mea- sure within a system. Loss/gain should be monitored for any given system at regular intervals to establish what is normal for that system and to identify any abnormal loss/gain so that corrective action can be taken. 2 Scope 2.1 This publication provides methodologies for monitor- ing liquid pipeline loss/gain, and for determining the normal loss/gain level for any given pipeline system. Troubleshooting suggestions are also presented.
3 Field of Application 3.1 The primary application of this publication is in cus- tody transfer liquid pipeline systems in which there is provi- sion for measuring all liquids that enter the system, exit the system and liquid inventory within the system. The applica- tion is not intended for non-liquid or mixed phase systems. 3.2 The applications and examples in this document are intended primarily for custody transfer pipeline systems, but the principles may be applied to any system which involves the measurement of liquids into and out of the system and possibly inventory of liquids within the system. 4 Reference Publications API Manual of Petroleum Measurement Standards Chapter 2 ÒTank CalibrationÓ Chapter 4.8 ÒOperation of Proving SystemsÓ Chapter 12.1 ÒUpright Cylindrical Tanks and Marine VesselsÓ Chapter 12.2 ÒCalculation of Liquid Petroleum Quanti- ties Measured by Turbine or Displacement MetersÓ Chapter 12.3 ÒCalculation of Volumetric Shrinkage From Blending Light Hydrocarbons with Crude OilÓ Chapter 13.1 ÒStatistical Concepts and Procedures in MeasurementÓ Chapter 13.2 ÒStatistical Methods of Evaluating Meter Proving DataÓ 5 Definitions For the purposes of this document these speciÞc deÞnitions apply. 5.1 action limits: Control limits applied to a control chart or log to indicate when action is necessary to inspect or cali- brate equipment and possibly issue a correction ticket. Action limits are normally based on 95 percent to 99 percent conÞ- dence levels for statistical uncertainty analyses of the group of measurements.
5.4 control chart: A graphical method for evaluating whether meter proving operations are in or out of a state of statistical control. 5.5 control limits: Are limits applied to a control chart or log to indicate the need for action and/or whether or not data is in a state of statistical control. Several control limits can be applied to a single control chart or log to determine when var- ious levels of action are warranted. Terms used to describe various control limits are Òwarning,Ó Òaction,Ó and Òtoler- anceÓ limits. 5.6 mean or central value: The average or standard value of the data being plotted on a control chart, and is the reference value from which control limits are determined. 5.7 standard deviation: The root mean square deviation of the observed value from the average. It is a measure of how much the data differ from the mean value of all the data. Stan- dard deviation can also be a measure of conÞdence level. Note: For further information concerning the application of Standard Deviation, reference API MPMS Chapters 13.1 and 13.2 5.8 statistical control: The data on a control chart are in a state of statistical control if the data hover in a random fash- ion about a central mean value, and at least 99% of the data are within the three standard deviation control limits, and the data do not exhibit any trends with time.