API. In-line. SECOND ED. This standa systems for liquid pipeli tethered, se detecting m pipeline geo. The standar technologie. This standa performanc including. API STANDARD • In-Line Inspection System Selection—Requirements for selecting an in-line inspection system for a specific pipeline application. (September ) introduction of API (title) highlights the importance of API (In-Line Inspection systems qualification standard) was introduced in.
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During the update of this specification, reference to standards such as API [ 1] and PDAM1  have been reviewed and some terminology has been aligned. API Inline Inspection Systems - Download as PDF File .pdf) or read online. Sistema de Inspección de Tuberías. API - - Download as PDF File .pdf) or read online. Guidance on Achieving ILI First Run Success-Dec
Figure 2 shows the potential impact an error in length measurement can have. These corrected measurements were then compared against the LPIT TM measurements to determine if there was any improvement in the accuracy. The results are as provided in the following sections.
Data Analysis The data considered for the purpose of this study was taken from different excavation locations. Data extraction provided us with 13 indications belonging to the pitting corrosion category and 9 indications belonging to the general corrosion category. The Laserscan SM measurements were used as the reference data set to calculate the error in depth as well as length measurements for each data point.
Different standard statistical techniques were utilized to measure the bias, if any, in the ILI data using the Depth and Length as the parameters of interest. They are: 1. Paired t-test  2. Wilcoxon signed ranks test  3. Passing-Bablok method  The two data sets, ILI and Laserscan SM, were treated as paired data, as it was assumed that since both measurements are for the same anomaly, values in one data set would change with the other .
As is shown in Figure 3, the bias plots  for both the depth and length measurements show a clear bias. This was verified using the kolmogorov-smirnov test at a significance level of. Figure 4. Skewness Kurtosis Figure 4: Results from Kolmogorov-Smirnov test demonstrating that the error does follow a normal distribution.
Now, assuming normality, an estimation of the bias assuming a constant bias was performed at a significance level of.. Since the mean error was found to be positive, the estimated bias was added to the depth measurements in the control group for validation and the results compared to the uncorrected error. The results are as provided in Table 1. Similar calculations, when carried out on the control data for general corrosion, revealed a similar phenomenon.
The SSE for uncorrected measurements was found to be , while the SSE for corrected measurements was found to be The data, when subjected to the non-parametric wilcoxon signed ranks test revealed results almost identical to the results presented.
Further investigation of the data seemed to indicate that the magnitude of the error seemed to be a function of the reported depth measurement itself. Therefore, the data was then subjected to the Passing-Bablok comparison test.
The results showed marked improvement over the uncorrected data. One thing to be noted here is that while the sum squared error seems to be lower for the non-parametric wilcoxon-bablok method, the absolute maximum error was found to be more in the parametric case. In other words, using a constant bias would cause the outliers to be even more pronounced.
The calculations for Length The MFL tool reports depth as a relative measurement as a percentage of the wall thickness. This normalizes the data and therefore, the scatter doesn t seem as pronounced. Since the length measurements are absolute mm , the effect of outliers on the analysis is 9 10 quite pronounced. These errors include, but are not limited to, systematic errors errors that result from known, but unaccounted for causes, such as sensor liftoff , random errors lack of repeatability and other errors with no identified cause , and anomaly-specific errors errors in sizing particular to geometries or assemblies of anomalies.
If the methodology is found to be no longer valid, any performance specifications that were validated by the methodology must be revalidated by an acceptable methodology. All reported significant errors in detection, identification, and sizing shall be investigated. Significant errors are those that are outside the performance specification. Four sets of requirements are given: 1. Project requirements. Pre-inspection requirements. Inspection requirements. Post-inspection requirements. All in-line inspection project requirements, pre-inspection, inspection, and post-inspection requirements and procedures shall be documented.
Prior to the actual inspection, the pipeline geometry and planned pipeline operating conditions shall be reviewed to ensure they are consistent with the information previously provided. The operator shall disclose to the service provider any and all changes in geometry or planned operating conditions before the in-line inspection system is launched into the pipeline.
The service provider shall work closely with the operator to minimize the likelihood of damage to the pipeline or the inspection system. The service provider shall confirm that the in-line inspection system to be used for the inspection is consistent with that used to define the required performance specifications. The steps shall include a function test to ensure the tool is operating properly. Pre-inspection function tests may include, but are not limited to: a. Confirmation that an adequate power supply is available and operational.
Confirmation that all sensors, data storage, odometers, and other mechanical systems are operating properly. Confirmation that adequate data storage is available.
Confirmation that all components of the inspection tool are properly initialized. Records of the pre-inspection function tests should be made available to the operator, if requested. The electronics shall be checked to make sure that they are properly sealed and functional.
The service provider shall set the appropriate tool detection threshold on the above-ground markers to ensure proper detection. The requirements include activities that occur from the time the in-line inspection tool is placed into the launching device until it has been removed from the receiving device.
The in-line inspection tool shall be placed into the launching device and shall be launched in accordance with defined requirements and proper procedures.
All system handling, placement, and launching activities shall be carefully monitored. Variations from the required operating conditions shall be identified and documented. The actual location of each above-ground marker shall be measured and documented.
If the above-ground markers are not placed at the planned reference points, the actual locations shall be identified and documented. The in-line inspection tool shall be removed from the receiving device in accordance with predefined requirements and proper procedures. All handling and removal activities should be carefully monitored. These activities are intended to validate that the inline inspection tool has operated correctly during the inspection run.
These steps shall include but are not limited to: a. Confirmation that a continuous stream of data was collected during the inspection. Confirmation that the data meets basic quality requirements. Data checks are typically based on direct measurement data, data completeness, and data quality. Deviations shall be noted and their effects communicated to the operator and included in the report. Direct measurement data is typically used to make general judgments about the basic operation of an inspection tool during a run.
Such data shall be utilized as one of the post-inspection data checks. The amount of data collected allows an initial assessment of data completeness. The amount of data collected is typically accessible after processing the recorded data. Completeness of data shall be checked after the initial processing of the data. Deformation with metal loss. Manufacturing indication. Crack like indication. Metal loss at weld seam.
Detection thresholds and probabilities of detection. Probabilities of proper identification. Sizing accuracies. Anomaly measurement accuracies. Location and orientation accuracies. Inspection parameters e. Sizing system components e. Analysis algorithms e. The description shall identify the source of data or analyses used for qualification: The description should also summarize the statistical techniques used to determine the performance specification.
These may include: Wall thickness range. Temperature range inside pipeline. Maximum and minimum pressure. Minimum bend radius. Minimum internal diameter. Tool length, weight. Maximum length of pipeline that can be inspected in one run may be coupled with run times and pipeline conditions.
Axial sampling frequency or distance. Circumferential sensor spacing in nominal pipe. Date of survey. Pipeline parameters: Pipe manufacturing method.
Outside diameter. Nominal wall thickness. Pipe grade. Line length. In-line inspection data quality. Any quality issues with the in-line inspection data, such as sensor malfunction, should be stated within the summary and described in the report.
Data analysis parameters. Clear communication of data analysis parameters should be included. At a minimum, measurement threshold, reporting threshold, and interaction criteria should be included. See Appendix D. Odometer distance or absolute distance. Identification of upstream girth weld. Distance from feature to upstream girth weld.
Feature classification e. Circumferential position. Identification of upstream and downstream markers. Distance from anomaly to upstream and downstream markers. Tool speed. Feature characterization. Metal-loss features e. Width profile or shape. Deformation features e. Length, width. Crack features e. Width colonies , proximity to welds. Metallurgical features. Dimension s. Position through the wall, hardness. Inspection survey parameters: Changes in the essential variables may affect the quality and accuracy of the data recorded by an in-line inspection system see 7.
If any of these are different during the inspection from the values given in the performance specification, they shall be listed within the summary. These options are recommended to aid in the integration of inspection results with pipeline integrity assessment programs. The following paragraphs provide some examples for metal loss ILI system results reporting. Modifications can be made for other ILI technologies.
Number of internal metal-loss features. Number of external metal-loss features. Number of metal-loss features in defined sections. Histograms of range of data scatter for each type of anomaly, based on the statistical data obtained from the inspection.
Circumferential position plot of all metal-loss features over the full pipeline length. Circumferential position plot of all internal metal-loss features over the full pipeline length. Circumferential position plot of all external metal-loss features over the full pipeline length. Circumferential position plot of all metal-loss features as function of relative distance to the closest girth weld.
Circumferential position of all deformation features over the full pipeline length. If this option is applied, the following information should be included in the report of ILI system results: Assessment methodology. Severity Ratio and definition if a severity ratio is used. Pipeline parameters used in calculations i. An effective quality management system includes processes that assure consistent products and services are being delivered, that those processes are properly controlled to prevent delivery of unsatisfactory services, and that adequate measures are in place to ensure that the products and services provided continue to meet the needs of a pipeline operator.
For those organizations without a quality management system, this section provides a basis for establishing a quality system to meet specific in-line inspection system needs. As a minimum, this review shall, where applicable, include: Identify which parties involved will be responsible for performing the specific tasks required for successful completion of the in-line inspection project.
A review of procedures to determine if they were followed during the entire inspection process. A review of the pipeline data provided by the pipeline operator to ensure the free passage of the in-line inspection tool. A determination that inspection capabilities of the specified in-line inspection tool meet the specific objectives of the pipeline operator.
Evaluation of the analysis requirements of the pipeline operator, including any specific codes or standards used to ensure that the pipeline operator receives correct and accurate results from the in-line inspection.
Organizations that have an existing quality management system that meets or exceeds the requirements of this section The organizations shall have a documented quality system for the scope of activities encompassed in this standard.
The quality system documentation shall be made available to the pipeline operator upon request. Records of qualification processes and procedures and personnel qualifications records in accordance with ASNT ILI-PQ shall be made available to the operator upon request. Provisions shall be included for maintaining the quality of developed and utilized software applications.
Software maintenance, configuration management and auditing should be performed in accordance with accepted industry practices.
These procedures shall document the steps required to ensure that the individuals assigned to perform the task can perform the work in a consistent manner. The detail deemed necessary will depend on the task as well as the training and qualification requirements established by the supplying organization.
Training and personnel qualifications requirements shall be included in the procedures. Any procedure or work instruction that is required shall be available to the individual performing the work.
Those procedures should also be available for review by the pipeline operator upon request. Procedures shall be reviewed and modified on a periodic basis. Minimum record keeping-requirements shall be documented. These records shall include not only the inspection data related to the pipeline, but shall also include records pertaining to the setup of the equipment, personnel involved in the performance of the inspection and analysis of data, and a record of the inspection equipment used for the inspection.
Records shall be maintained to the level that will allow the recreation of the system set up for inspection system verification and validation purposes. Additional information may also be maintained as part of the inspection record as determined between service providers and the pipeline operator. Inspection records shall be retained for a time period no less than that required for legal or regulatory purposes.
Adequate measures shall be taken to protect the records from loss or damage. When developing storage and regeneration procedures for inspection data, changes in data collection technology should be considered. A revision control system shall include procedures for withdrawal of outdated information, including documents, files, forms, and software. This includes documents and software internal to the organization as well as documents, files, and software released to the end-user.
These records shall sufficiently document the changes to allow an evaluation of the effects on the essential variables of the previous design. The same procedures apply to the design of services provided to a pipeline operator. Service process changes shall also be documented to review the effectiveness of the change. Feedback from the pipeline operator should be a component of any design change procedure to be used when evaluating the effectiveness of changes to the design of either an in-line inspection system or service.
This shall include the checks required to ensure the proper equipment has been selected, qualified, properly calibrated, and successfully operated in the field. This shall also include the checks required to ensure that the data has been properly analyzed, and the date successfully delivered to the pipeline operator.
Quality control procedures shall also include those procedures necessary to demonstrate that all personnel are qualified in accordance with the requirements of this standard.
Procedures shall contain provisions for personnel to have the ability to interrupt the process when a quality control nonconformance is discovered and initiate immediate corrective action procedures to prevent further or more severe nonconformance.
Records shall be maintained of these quality checks and retained in the record keeping system selected by the organization. Qualification processes and procedures shall also be maintained as part of the Quality Management System. These procedures shall include requirements for the identification of all equipment used, requirements of the individuals performing the task, and provisions for the calibration of applicable test equipment that is traceable to a national standard.
The equipment used for the inspection shall be uniquely identified to permit traceability. The use of serial numbers or other tracking references provides a history of equipment used and a way to monitor that equipment for changes in operation and functionality that may affect proper operation.
If the historical information process is used for verifying inspection results, the data collected for this purpose shall be matched to the traceability of the ILI System utilized under this section.
Equipment traceability requirements shall extend to support equipment that directly affects the successful completion of a project when used in conjunction with the in-line inspection tool.
Such devices typically include above ground marker systems, locating systems, playback and data processing equipment, data reduction and analysis software, and associated test equipment. The accuracy of the inspection results compared to verification dig inspections. An analysis of the number and types of erroneous calls over a period of time, for each type of inspection system, based upon the stated performance specification or service requirement. Other performance measures should be developed to further analyze the effectiveness of the processes being measured.
These procedures should include steps to prevent the nonconformance from recurring.
This requires provision for adequate supervision commensurate with personnel experience and peer review crosscheck as necessary to assure accuracy of data. Processes to prevent nonconformance from initially occurring shall also be part of the quality system. These processes are often included in the research and development program.
These reviews are performed to ensure the overall effectiveness of the Quality Management System is maintained and continues to meet the goals of the organization. Effective improvement requires feedback from employees and the pipeline operator, a review of new technology developments, and a continuous observation and measurement of the results of the output of the organization. The quality management system shall include provisions to allow management to periodically evaluate the effectiveness of the procedures and processes within the quality system.
These internal audits shall be performed at defined intervals, and the records of the audits shall be maintained. Records of any corrective actions taken shall also be maintained. The relevant organization will provide indicators of the success of their processes. Key measures of those indicators shall be established. The process measures selected shall include measures relevant to the products and services provided.
Basic measures include: Consideration may be given to parties that have no financial, competitive, or other incentive that may be in conflict with the financial, proprietary or intellectual nature of the organization being audited. Prior to performing the audit, the scope and procedure of the audit shall be clearly defined, discussed, and approved by the service provider. The run success percentage that measures the number of acceptable runs made versus the total number of runs made over a selected period of time.
A measure of the turn-around time of inspection data as measured from completion of the fieldwork to the time of delivery of the in-line inspection report.
These terms are algebraically defined as follows: Table 4 lists features that may be detected along with their POIs. Table 5 lists PODs and sizing accuracies for metal-loss anomalies. Were survey-acceptance criteria met? Were Data Quality checks completed when applicable?
Review orientation of taps, tees, etc. Check for abnormal joint lengths Review Historical Information Initial a. Check for previous assessments i. Review previous dig information [Further review is required if significant differences in anomaly characteristics or location accuracy are identified.
This appendix provides a sample set of procedures that have been successfully used in prior field verifications. Other mutually agreed upon procedures may also be used. Field verifications involve two different distance measures: Aboveground measurements are typically made from known position of pipeline components, welds, or other physical items whose location relative to the pipeline location and chainage is known.
In-line inspection distances are determined from odometer wheel counts and represent approximate chainage values. Significant sources of errors in aboveground measurements can result from: Errors in distances measured by in-line inspection tools can result from problems with the odometer wheels due to debris, slippage, or sticking. In-line inspection distances can often be recalibrated using as-built pipeline data or other information. Basic Procedure for Feature Location In typical inspection reports, the location of a feature is referenced to fixed aboveground pipeline components e.
Below ground components are not typically used for reference points because they cannot be easily located aboveground. From the inspection report, identify and determine the distances to the nearest known upstream and downstream reference points.
For the example shown in Figure 5, weld the target location is Step 2: Mark off and stake the aboveground distance from both reference points.
A gap or overlap is common. The length of the gap or overlap is affected by the accuracy of surface measurements and the odometer counts.
For the example shown in Figure 6, the gap is 9. If a very large gap is seen, check to determine that the correct reference points have been used in marking off the aboveground distances. Discussions between the service provider and the operator should be used if there are gaps or overlaps that are greater than the location accuracy in the performance specification. Step 3: REMARKS Using both upstream and downstream reference points and interpolating gaps or overlaps increases the accuracy with which a target feature is located.
Targeting an upstream or downstream girth weld for an anomaly located within a pipe joint provides a ready reference from which to measure a short relative distance to locate the anomaly. When the location of a target feature is in doubt, individual pipe joints can sometimes be identified by comparing the physical distance between upstream and downstream girth welds with the distance noted on the inspection report.
The reported and actual position of the longitudinal weld can also help verify locations. Basic Procedure—Verification Measurements 1. Clean pipe thoroughly, preferably by abrasive blasting, etc. Inspect for cracking e. Measure depth of anomaly.
Measure length longitudinal and width circumferential of anomaly. Provide a rubbing of the anomaly geometry including the surrounding area and take a photo, if possible.
Measure the actual wall thickness in multiple areas close to the anomaly. Mark on Feature Location Sheet actual measured distance to girth weld, circumferential position, feature type, feature dimensions, actual wall thickness, etc. Measure and document exposed anomalies. Field data useful in comparing verification results with reported data 1. Field distance measurement system used. All modifications applied to the original Feature Location Sheet. Distances measured in the field typically at least one upstream and one downstream is necessary.
Observed difference between aboveground location and found position. Length of the joint. Position of the longitudinal weld if applicable. Length of neighboring pipe joints and their longitudinal weld position if possible. Position and extent of pipe area investigated. Method used to measure the actual defect geometry. Specifications of the method, e. Photos of the location with scales and remarks of dimensions. A data record for each verification anomaly should be prepared.
The data record may include, but not be limited to: Distance to upstream and downstream aboveground reference points. Metal loss profile including the spacing increments and depth measurements ; alternatively, an etching of the anomaly and or a diagram with the maximum depth indicated.
Metal loss interaction Figure 7: Whether or not multiple measured metal loss anomalies interact to form a larger single anomaly; the criteria governing the relationship between the distances X1 and X2 and Y1 and Y2 is specified for each inspection. Information on the accuracy of field measurements.
Label each photograph with the following information, as a minimum. Pipeline system identifier. Right-of-way number. Pipeline stationing.
Job number. Anomaly item number from inspection report. Excavation date. Nominal Pipeline O.
Pipe nominal wall thickness. Actual pipe wall thickness clean pipe close to anomaly. Clock circumferential position of longitudinal weld facing downstream: Distance to upstream and downstream girth welds. Date of photo.
Pipeline identification, i. Anomaly item number. Actual depth, length, width and clock orientation. Distance to nearest girth weld. For example, a graphical view of the sizing accuracy can be created by plotting the comparison of depth of individual anomalies as reported by the ILI service provider and the measurement results of a field excavation. Figure 8 shows an example of a graph that supports ILI system results are consistent with the performance specification. To enable a valid comparison, the physical units and statistical parameters of the different measurement methods must be unitized at the beginning.
Gauging and UT devices usually assess the general wall thickness and the remaining wall independently while MFL ILI provides relative wall loss values instead. Once this is calculated it becomes rather obvious how and where these typical field measurement techniques depend on the wall thickness and how this compares to the ILI accuracy. A UT device was used. The specified accuracy was 0. Binomial distributions represent the probability of a particular outcome based on an initial assumption or hypothesis.
The outcome is the set of reported anomalies found to be within tolerance through verification measurements with the initial assumption that the performance specification has been met.
Each percentage entry is the probability of the number of comparisons or less within tolerance out of the total number of comparisons. Typically, if the probability given in a binomial distribution table is small e. In other words, the performance specification has not been met. Distribution tables can be used to demonstrate that the verification results are consistent with the performance specification. A Type I error is the probability of rejecting the initial assumption the performance specification was met when it is, in fact, true.
Type I errors are related to the consistency of the verification measurements with the performance specification. The probability of a Type II error reflects the precision with which the true certainty is known.
Type II errors are possible whenever the performance specification is not rejected. Tables listing the probabilities of Type II errors are large, cumbersome, and not generally used. Based on this, Table 8 can be derived as more practical for use.
It provides the overall number of verification measurements N versus the number of verification measurements, that must be in tolerance Nin in order to establish consistency with performance specifications. The ILI system results are not consistent with the performance specification. Following are some examples of how to use distributions to verify if the performance specification has been met. Example 1: Twenty-five verification measurements are made. The ILI system results are consistent with the performance specification.
There are 19 comparisons in tolerance. Since 19 is larger than 17, the ILI system results are consistent with performance specifications. Example 2: Ten verification measurements are made. There are 5 comparisons in tolerance. Since 5 is less than 6, the ILI system results are not consistent with performance specifications. Example 3: Another table would need to be generated.
Confidence Intervals Confidence intervals provide an alternative way of determining the precision of which the true certainty is known.
There are many ways of using confidence intervals to assess whether the ILI system results are consistent with the Performance. These methods are generally Service-Provider or operator-specific, and as such, are not discussed in detail in this Standard. Common methods consider the lower range of certainty, the position of the certainty stated in the performance specification within the confidence interval, and the amounts of data used to develop the performance specification.
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