Automated Inversion Workflow for Downhole Corrosion Detection
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Solution Overview
Problem
Corrosion detection in downhole metal pipes with multiple concentric casing strings is complex due to the challenges in managing electromagnetic logging tool operations and data interpretation, requiring efficient and automated methods for accurate corrosion inspection.
Innovation Solution
An automated electromagnetic defect/corrosion inspection workflow that includes automatic ghost removal, iterative adjustments, override flexibility, advanced quality control, pipe or zone-based customization, and computational time control, utilizing a post-processing inversion algorithm to process electromagnetic data and estimate metal loss in concentric metallic tubulars, primarily applicable to the eddy-current technique.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If electromagnetic logging tools are used to detect corrosion in multiple concentric casing strings, then corrosion detection capability is improved, but data interpretation complexity increases
Solution Approach 1:
The patent segments the complex EM logging system into distinct functional modules: signal generation, data acquisition, inversion processing, and interpretation. Each module handles specific aspects of corrosion detection independently, making the overall system more manageable and interpretable despite dealing with multiple concentric casing strings
Solution Approach 2:
The patent introduces intermediate processing steps including inversion algorithms and calibration procedures that act as mediators between raw EM data and final corrosion interpretations. These intermediaries transform complex multi-string EM responses into simplified corrosion indicators that are easier to interpret
2Measurement precision
If manual processing of electromagnetic data is used, then interpretation accuracy can be maintained, but processing time increases
Solution Approach 1:
The patent implements preliminary calibration procedures and pre-computed response libraries that prepare reference data before actual corrosion detection. This preliminary action enables faster real-time processing while maintaining accuracy by comparing measured data against pre-prepared inversion models
Solution Approach 2:
The patent incorporates iterative inversion algorithms with feedback mechanisms that automatically adjust processing parameters based on data quality assessments. This feedback loop maintains interpretation accuracy while reducing manual intervention time by allowing the system to self-correct and optimize processing automatically
3Productivity
If automated processing workflows are implemented, then processing efficiency is improved, but complexity of the workflow increases
Solution Approach 1:
The patent designs a universal automated workflow framework that handles multiple corrosion detection scenarios (single string, multi-string, different corrosion types) through a single integrated process. This multi-functional approach improves efficiency by eliminating the need for separate manual procedures while managing complexity through standardized processing routines
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This workflow enables efficient and accurate corrosion inspection with minimal human interaction, providing rapid results essential for the oil and gas industry by automating the processing of electromagnetic data to determine pipe characteristics and corrosion levels in downhole tubulars.
Implementation Method 1
One type of corrosion detection tool uses electromagnetic (EM) fields to estimate pipe thickness or other corrosion indicators. As an example, an EM logging tool may collect EM log data, where the EM log data may be interpreted to correlate a level of flux leakage or EM induction with corrosion.
Implementation Method 2
an EM logging tool may collect EM log data, where the EM log data may be interpreted to correlate a level of flux leakage or EM induction with corrosion
Data Source
AI summary
A methods for the detection of pipe characteristics. The method may comprise disposing a defect detection tool in a wellbore, processing measurements from the defect detection tool in the wellbore to obtain a well log, storing the well log in a database, importing the well log from the database into inversion software, loading a well plan into the inversion software, determining collar locations on at least one concentric pipe in the wellbore utilizing a collar locator algorithm in the inversion software using the well log and well plan, calibrating a forward model in the inversion algorithm utilizing a calibration algorithm in the inversion software, generating an output log utilizing the inversion algorithm in the inversion software on the inversion zone, and determining false metal loss in the output log using the output log.