Abstract: A method and system for evaluating the sample coverage of ultrasonic or radiography (UT/RT) measurements of pipeline wall thickness for statistical validity. A data library contains distributions of in-line inspection (ILI) measurements for other pipelines, calibrated to correspond to UT/RT measurements as needed. The data library for these ILI-measured pipelines also includes statistics generated from Monte Carlo simulation, by way of which various sample coverage levels sample the ILI measurements, for determining whether a measurement exceeds a given threshold or meets another premise related to determining the extreme wall loss measurement for the pipeline. A pipeline with sampled UT/RT measurements is used to identify one or more ILI-measured pipeline datasets that are most similar, and the statistics from those most similar pipeline datasets determine whether the sample coverage of the UT/RT measurements is sufficient to draw conclusions about the extreme value of wall loss in the sampled pipeline.

Abstract: In accordance with aspects of the present disclosure, a computer-implemented method for predicting a material deterioration of a coupon inserted into the well line system is disclosed. The computer-implemented method can be stored on a tangible and non-transitory computer readable medium and arranged to be executed by one or more processors that cause the one or more processors to receive data related to the well line system; determine one or more predictors of material deterioration of a coupon based on the data; and predict a material deterioration of the coupon inserted into the well line system based on a mathematical model of the material deterioration using the one or more predictors.

Abstract: Methods and systems for using survival modeling methods with pipeline inspection data to determine causal factors for corrosion under insulation comprise determining a first corrosion condition of a pipeline joint at a first time; determining a second corrosion condition of the pipeline joint at a second, subsequent time; determining joint attributes, pipeline attributes, and location attributes associated with the pipeline joint; and repeating the process for a plurality of pipeline joints in one or more pipelines. This information is fed into a multiple regression and survival analysis process that determines regression coefficients reflecting the estimated degrees to which various factors contribute to corrosion under insulation. The survival analysis also determines one or more survival models capable of predicting when a given pipeline joint is likely to transition from a first corrosion state to a different second corrosion state, given values for its various attributes.

Abstract: A method and system for estimating the worst case corrosion in a pipeline for which pipeline wall thickness measurements are limited to sampled ultrasonic or radiography (UT/RT) measurements. A data library contains distributions of in-line inspection (IL) measurements for other pipelines, calibrated to correspond to UT/RT measurements as needed. These ILI datasets are randomly sampled multiple times, to obtain multiple sample sets from each ILI dataset. Candidate statistical distributions are evaluated for each sample set to determine which of the candidate statistical distributions most accurately estimates the worst case corrosion measured by ILI. A discriminant function is then derived from sample statistics and pipeline descriptors associated with the sample sets, along with the best candidate statistical distribution for that sample set.

Abstract: A method and system for estimating the worst case corrosion in a pipeline for which pipeline wall thickness measurements are limited to sampled ultrasonic or radiography (UT/RT) measurements. A data library contains distributions of in-line inspection (IL) measurements for other pipelines, calibrated to correspond to UT/RT measurements as needed. These ILI datasets are randomly sampled multiple times, to obtain multiple sample sets from each ILI dataset. Candidate statistical distributions are evaluated for each sample set to determine which of the candidate statistical distributions most accurately estimates the worst case corrosion measured by ILI. A discriminant function is then derived from sample statistics and pipeline descriptors associated with the sample sets, along with the best candidate statistical distribution for that sample set.

Abstract: A method and system for evaluating the sample coverage of ultrasonic or radiography (UT/RT) measurements of pipeline wall thickness for statistical validity. A data library contains distributions of in-line inspection (ILI) measurements for other pipelines, calibrated to correspond to UT/RT measurements as needed. The data library for these ILI-measured pipelines also includes statistics generated from Monte Carlo simulation, by way of which various sample coverage levels sample the ILI measurements, for determining whether a measurement exceeds a given threshold or meets another premise related to determining the extreme wall loss measurement for the pipeline. A pipeline with sampled UT/RT measurements is used to identify one or more ILI-measured pipeline datasets that are most similar, and the statistics from those most similar pipeline datasets determine whether the sample coverage of the UT/RT measurements is sufficient to draw conclusions about the extreme value of wall loss in the sampled pipeline.