Real-Time CIS Data Validation for Pipeline Surveys

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Current close interval surveys (CIS) for cathodic protection systems on underground pipelines are time-consuming, costly, and logistically challenging, often resulting in infrequent data collection due to the extensive manual effort required.

Innovation Solution

The implementation of a method that validates the integrity of CIS data in real-time using special electronics and machine learning resources, allowing for immediate analysis and correction of data quality issues during the survey, thereby reducing the need for repeated surveys.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual close interval survey is performed to collect comprehensive pipe-to-soil potential data, then measurement precision is improved, but loss of time and productivity deteriorate significantly

Engineering Contradiction:

ImproveCIS data integrityVSAvoidSurvey completion time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system provides real-time feedback on data quality through validation rules that immediately identify improper readings, allowing surveyors to correct issues on-the-spot without needing to re-survey entire sections later

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

Manual mechanical data collection and post-survey analysis is replaced with automated electronic validation systems that process data in real-time using computer processors and validation algorithms

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If frequent CIS are performed to maintain pipeline safety, then reliability is improved, but loss of time and cost increase due to repetitive manual surveying

Engineering Contradiction:

ImprovePipeline safetyVSAvoidTime between surveys

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The validation system performs self-checking of data quality automatically during the survey process, eliminating the need for time-consuming post-survey manual analysis and enabling more frequent surveys without proportionally increasing time investment

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual post-survey analysis is replaced with automated electronic validation that occurs in real-time during data collection, allowing rapid identification of quality issues and enabling more frequent surveys

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If manual data collection is used for CIS, then measurement precision is maintained, but device complexity and operational difficulty increase

Engineering Contradiction:

ImproveSurvey data accuracyVSAvoidSurvey operation difficulty

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The system provides immediate feedback to surveyors about data quality issues, guiding them on what to do next without requiring them to perform complex manual analysis procedures

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

Complex manual data analysis procedures are replaced with automated electronic validation systems that handle quality assessment automatically, simplifying the operational process while maintaining precision

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20250180428A1Methods and systems for guiding corrosion surveys of underground pipeline

Publication Date: 2025.06.05 AMERICAN INNOVATIONS INC

AI summary

Close interval survey methods and devices disclosed herein receive and filter waveform data obtained while an operator is performing a close interval inspection of a cathodic protection system including a cathodically protected underground pipeline. The waveform data is analyzed and assign to one of a plurality of bin categories based on the analysis. Scoring metrics for the waveform data may be generated and evaluated to determine whether a likelihood of the wave form data being “good”, i.e., in compliance with one or more predefined criteria, is less than a minimum sufficient likelihood. If the likelihood of good waveform data is below a specified minimum threshold hold, corrective action may be suggested to an operator while the operation is performing the close interval survey. In this manner, disclosed methods and systems actively guide the operating during performance of the close interval survey.