API MPMS 13.2-2018 Manual of Petroleum Measurement Standards Chapter 13-Statistical Aspects of Measuring and Sampling Section 2-Methods of Evaluating Meter Proving Data (SECOND EDI.pdf

1、Manual of PetroleumMeasurement StandardsChapter 13Statistical Aspects ofMeasuring and SamplingSection 2Methods of EvaluatingMeter Proving DataSECOND EDITION, APRIL 2018Special NotesAPI publications necessarily address problems of a general nature. With respect to particular circumstances, local, sta

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11、requirement in order to conform to the standard; the term “should” denotes a recommendation or that which is advised but not required in order to conform to the standard; the term “may” is used to express permission or a provision that is optional; the term “can” is used to express possibility or ca

12、pability.Informative elementsAs used in a standard, “informative” denotes elements that identify the document, introduce its content, and explain its background, development, and its relationship with other documents or provide additional information intended to assist the understanding or use of th

13、e document.Normative elementsAs used in a standard, “normative” denotes elements that describe the scope of the document and that set out provisions that are required to implement the standard.This document was produced under API standardization procedures that ensure appropriate notification and pa

14、rticipation in the developmental process and is designated as an API standard. Questions concerning the interpretation of the content of this publication or comments and questions concerning the procedures under which this publication was developed should be directed in writing to the Director of St

15、andards, American Petroleum Institute, 1220 L Street, NW, Washington, DC 20005. Requests for permission to reproduce or translate all or any part of the material published herein should also be addressed to the director.Generally, API standards are reviewed and revised, reaffirmed, or withdrawn at l

16、east every five years. A one-time extension of up to two years may be added to this review cycle. Status of the publication can be ascertained from the API Standards Department, telephone (202) 682-8000. A catalog of API publications and materials is published annually by API, 1220 L Street, NW, Was

17、hington, DC 20005.Suggested revisions are invited and should be submitted to the Standards Department, API, 1220 L Street, NW, Washington, DC 20005, standardsapi.org.iiiContentsPage1 Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

18、 . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Normative References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Terms, Definitions, and Acronyms . . . . . . . . . . . . . . . . . . . . . . . . . .

19、 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Significance and Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Elements that Influence Meter Factors . . . . . . . . . . . . . . . .

20、. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 General Suggestions to Improve the Monitoring Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Data Signals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

21、 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 Ways to Monitor Meter Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58.1 General . . . . . . . . . . . . . . . . . . . . . . . . .

22、 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58.2 Logging. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58.3 Run Char

23、ting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88.4 Univariate Control Charting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

24、. . . . . . . . 108.5 Multivariate Control Charts for Meter Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14Annex A (informative) Tests for Normality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

25、. . . . . . . . 17Annex B (informative) Other Charts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21Annex C (informative) Data Tables for Charts in Main Body . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

26、 . . . . . . 24Annex D (informative) Runs Rules. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

27、. . . . . . . . . . . . . . . . . . . . . . . 31Figures1 Three Patterns that Suggest Further Investigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 Basic Run Charts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

28、 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Run Chart of Deviations from the Curve with Fixed Limits of 0.15 % Deviation from the Curve on the Primary y-axis and Relative Density on the Secondary y-axis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 Control

29、 Chart of Meter Factors using sd of Trial Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Control Chart of Meter Factors using Range % of the Trial Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 Control Chart of Meter Factors using Mov

30、ing Range (mR) of the Meter Factors . . . . . . . . . . . . . . . . . . . 127 Control Chart of Meter Factors Using Limits Calculated from Moving Averages . . . . . . . . . . . . . . . . . . 138 Generalized Multivariate Chart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

31、 . . . . . . . . . . . . . . . . . . . . . . 159 Multivariate Chart for Table 3 Data and the Associated Four Univariate Charts . . . . . . . . . . . . . . . . . . . 16A.1 Normal Probability Plot for Table 3 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

32、. . . . . . . . 17A.2 Normal Probability Plots for Non-normal Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19B.1 Run Chart using Policy Run-to-Run Limit of 0.05 % . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

33、 . 21B.2 Control Chart with Limits Calculated from Percentiles of the Meter Factors . . . . . . . . . . . . . . . . . . . . . . 22Tables1 Responses to Consider when Limits are Exceeded . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Meaning of Column Titles

34、 in Table 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 Meter Factor Log . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 Relative

35、Contribution of Each Component to the T-squared Statistic . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16A.1 Data for the QQ Plot in Figure A.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18A.2 Anderson-Darling Statisti

36、cs for Table 3 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20A.3 Shapiro-Wilk Statistics for Table 3 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20vContentsPageTables (Continued)

37、B.2 Data Set for the Control Chart Based on Percentiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22C.4 Underlying Data for Figure 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

38、4C.5 Underlying Data for Figure 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26C.6 Underlying Data for Figure 6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

39、 . . . . . . . . 27C.7 Underlying Data for Figure 7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29viIntroductionMinimizing petroleum measurement errors, estimating remaining errors and informing affected parties of error

40、s is important to the petroleum industry. A consistent basis for estimating the size and significance of errors is essential for communication among affected parties. A fundamental source of measurement error is the inaccuracy of the meter factor which is a number that represents the performance of

41、a meter throughout a batch.Meter factors are monitored to gain confidence in the reported volumes and to detect trends or sudden deviations as indications of when to perform maintenance on or calibration of measurement equipment. The purpose of this standard is to suggest procedures for monitoring v

42、ariations in meter factors so that uncertainties are understood and consistent with the objectives of parties affected by the measurement operations. The procedures for monitoring meter performance, limits on meter factor variations and actions to take because of these variations are left to the agr

43、eement among the parties affected by the measurement operations which can depend on company policy, contract agreements, regulations and laws.vii1Section 2Methods of Evaluating Meter Proving Data1 Scope This standard establishes the basic concepts and procedures to estimate and report meter performa

44、nce uncertainty in consistent and comparable ways.2 Normative References The following referenced documents are indispensable for the application of this document. For dated references, only the edition cited applies. For undated references, the latest edition of the reference document (including an

45、y amendments) applies.API Manual of Petroleum Measurement Standards (MPMS) Chapter 1, Online Terms and Definitions DatabaseAPI MPMS Chapter 4, Proving SystemsAPI MPMS Chapter 5, MeteringAPI MPMS Chapter 12, Calculation of Petroleum QuantitiesAPI MPMS Chapter 13.3, Measurement Uncertainty Quantities3

46、 Terms, Definitions, and AcronymsFor the purposes of this document, the following terms and definitions apply. Terms of more general use may be found in the API MPMS Chapter 1, Online Terms and Definitions Database. Acronyms are defined in the text at first use.3.13 standard deviation limitA control

47、 limit equal to 3 standard deviations from the arithmetic mean of the set.NOTE For a set of normal data this limit is also known as the 3-sigma limit.3.2action limitsHorizontal lines found on a run chart or control chart which, if exceeded, suggests that some sort of action is necessary to modify th

48、e underlying process or to modify the reports generated from the process. Related terms: tolerance limit, warning limit.3.3central lineA line on a control chart or run chart that represents the central value.3.4central valueThe mean value of the statistic under consideration. Synonym: central tenden

49、cy.3.5control chartA graphical method for evaluating whether a process is in or out of statistical control.2 API MPMS CHAPTER 13.23.6control limitsHorizontal lines on a control chart used in the evaluation of whether or not a process is in statistical control.3.7control logA tabular method for evaluating whether a process is in or out of statistical control.3.8datetimeA number with integer and decimal parts used to designate a particular point in time in which the integer represents the day and the decimal represents the fraction of the day.3.9measurement resolutionThe smalles