Proof Is in the 'Proving'

Flow measurement is essential in a variety of businesses, including and especially in the liquid hydrocarbon (petroleum) industry. An ongoing challenge is to provide accurate flow measurement while anticipating and correcting problems in the measurement system. An important objective of flow measurement is to control costs, particularly in flowmeter maintenance and unaccounted-for product losses.

10/01/2004


At A Glance

 

  • Multiple calibrations at one flow rate

  • 'Proving' proves beneficial

  • Accurate measurements control costs

  • Standards provide guidance

  • Software simplifies the job

Flow measurement is essential in a variety of businesses, including and especially in the liquid hydrocarbon (petroleum) industry. An ongoing challenge is to provide accurate flow measurement while anticipating and correcting problems in the measurement system.

An important objective of flow measurement is to control costs, particularly in flowmeter maintenance and unaccounted-for product losses. Measurement guidelines that follow focus on basic meter proving , but could help anyone wanting to reduce measurement or calibration costs:

  • Select a flowmeter for high accuracy and increased reliability;

  • Employ calibration methods with lower uncertainty;

  • Acquire meaningful data of significant quality;

  • Use data from calibrations to predict or prevent flowmeter failure;

  • Use data to minimize product losses and increase uptime; and

  • Implement software solutions to maximize operational efficiency.

What is 'proving'?

Proving is a measurement term common in the hydrocarbon industry. It refers to multiple (typically 5) comparisons or calibrations at a single flow rate. These comparisons are performed on site, under operating conditions. The goal of proving is to develop a correction factor, also called a meter factor, which corrects for the influence of actual operating conditions (flow rate, pressure, temperature, etc.). Benefits of proving include:

  • Verification of flowmeter accuracy;

  • Documentation of flowmeter reliability;

  • Reduced uncertainty;

  • Lower incidence of product loss; and

  • Enhanced prediction of flowmeter failure.

The number or frequency of provings required in any given circumstance must be determined by each operation according to its own priorities. Every situation should be assessed with regard to mean failure time of the flowmeter and the financial impact of the meter's inaccuracy. How often to prove is directly proportional to how much inaccuracy and profit loss a business is willing to tolerate.

Achieving benefits from proving requires good equipment and procedures. American Petroleum Institute (API) standards, published in the ' Manual of Petroleum Measurement Standards (MPMS),' provide guidance about proving. Although these standards were written specifically for hydrocarbon fluids, the underlying principles and procedures can be applied to any industry wanting to improve its measurement capabilities.


This example from 'Prove-It' by Flow Cal Inc. shows a meter factor control chart used to trend meter performance. Red lines are limits of meter accuracy. Low bars indicate something has changed the meter's accuracy or that a failure has occurred.

API standards are guided by the '1 in 10,000 rule' to provide greater uniformity of results for custody transfer of hydrocarbons. An accuracy rate of one part in ten thousand is the basis for:

  • Collecting primary data (to 5 significant digits);

  • Collecting secondary data;

  • Calculating intermediate and final values (results); and

  • Calibrating provers (the calibrator).

So what does it prove?

Differences in collecting primary data affect results. Consider this scenario: An operator uses his shop scale to calibrate a mass flowmeter. The chosen scale measures only in one-pound increments. If the shop scale indicates 100 lb compared to the meter's 100.00 lb, it would appear that the meter is 100% accurate. However, you must consider that proving has an uncertainty of 1%.

Since the scale lacks precision, mathematical accuracy of the comparison is plus or minus 1%. If the operator continues to measure 100-pound batches, the results would vary from 99 to 101 pounds. To lower the uncertainty of each proving, the scale and meter readings must include more significant digits (e.g., 100.01 lb). The table illustrates how the number of significant digits impacts results.

Good quality software simplifies the implementation of API standards. A number of programs are available to manage data effectively and thereby reduce measurement costs. Software typically improves adherence to standards, minimizes the operator's influence on results, and provides information for better overall management of costs. When choosing software for a particular operation, consider the following features:

  • Automated data collection;

  • Ability to acquire quality, meaningful data;

  • Preprogrammed tolerances;

  • Automated data verification;

  • Historical evaluation of results;

  • Data or result exceptions; and

  • Predictive intelligence for meter failure or inaccuracy.

The graphic from 'Prove-It' by Flow Cal Inc., a proving software package popular in the hydrocarbon industry, shows how the meter factor control chart is applied.

ISO (International Organization for Standardization) and ANSI (American National Standards Institute) also have standards related to meter proving. Higher quality measurement and lower measurement costs can be achieved regardless of which standards and software tools are applied.

Effect of the '1 in 10,000 Rule'

Scale Reading

% Uncertainty

100 lb=

1,000 lb=

10,000 lb=



Author Information

Steve Whitman is president of Coastal Flow Measurement Inc. (




No comments
The Engineers' Choice Awards highlight some of the best new control, instrumentation and automation products as chosen by...
The System Integrator Giants program lists the top 100 system integrators among companies listed in CFE Media's Global System Integrator Database.
The Engineering Leaders Under 40 program identifies and gives recognition to young engineers who...
This eGuide illustrates solutions, applications and benefits of machine vision systems.
Learn how to increase device reliability in harsh environments and decrease unplanned system downtime.
This eGuide contains a series of articles and videos that considers theoretical and practical; immediate needs and a look into the future.
Sensor-to-cloud interoperability; PID and digital control efficiency; Alarm management system design; Automotive industry advances
Make Big Data and Industrial Internet of Things work for you, 2017 Engineers' Choice Finalists, Avoid control design pitfalls, Managing IIoT processes
Engineering Leaders Under 40; System integration improving packaging operation; Process sensing; PID velocity; Cybersecurity and functional safety
This article collection contains several articles on the Industrial Internet of Things (IIoT) and how it is transforming manufacturing.

Find and connect with the most suitable service provider for your unique application. Start searching the Global System Integrator Database Now!

SCADA at the junction, Managing risk through maintenance, Moving at the speed of data
Flexible offshore fire protection; Big Data's impact on operations; Bridging the skills gap; Identifying security risks
The digital oilfield: Utilizing Big Data can yield big savings; Virtualization a real solution; Tracking SIS performance
click me