Nested Casing Thickness Profiling With Inversion-Based Induction Processing
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Solution Overview
Problem
Existing methods for multi-frequency, multi-spacing tool measurements in multi-casing corrosion analysis fail to accurately determine thickness profiles along the depth of multiple nested metallic pipes due to ghost effects and non-linearities, especially in cases with four or more nested casings.
Innovation Solution
A method involving multi-frequency non-collocated sensor data processing using an inversion-based process with an axisymmetric modeling solver to deconvolve the tool transfer function, allowing for the determination of thickness profiles by running an inversion loop and utilizing Gauss-Newton model-based inversion to correct for double indications of casing collars and corrosion defects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional multi-frequency multi-spacing processing methods are used, then measurements can be acquired from multiple casings, but ghost effects and double indications occur causing inaccurate thickness profiles
Solution Approach 1:
The patent applies inversion theory to reverse the forward modeling process. By inverting the tool response function, the system can distinguish between true defects and ghost effects caused by multiple nested casings. The inversion process reconstructs the actual thickness profile by mathematically reversing the measurement transformation, thereby eliminating double indications and ghost effects that plague traditional direct processing methods.
Solution Approach 2:
The patent introduces a transfer function as an intermediary element between the tool measurements and the actual casing thickness. This transfer function models the tool's response characteristics and acts as a mediator that, when inverted, allows the system to separate true defect signals from artifact signals. The transfer function serves as the mathematical bridge that enables accurate extraction of thickness profiles from complex multi-casing environments.
2Measurement precision
If general non-linear numerical inversion is applied to determine thickness profiles, then accurate profiles can be obtained for multiple nested pipes, but the processing complexity increases significantly
Solution Approach 1:
The patent segments the complex inversion problem into manageable components by processing measurements at different frequencies and spacings separately before integrating them through the inversion process. This segmentation allows the system to handle the complexity of multiple nested casings by addressing each measurement component systematically, reducing the overall computational burden while maintaining accuracy.
Solution Approach 2:
The patent utilizes parameter changes through multi-frequency and multi-spacing measurements to simplify the inversion process. By varying the measurement parameters (frequency and spacing) and observing how the tool response changes, the system can linearize certain aspects of the inversion problem. This parameter variation approach transforms the purely non-linear inversion into a more manageable process that maintains accuracy while reducing computational complexity.
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 approach effectively alleviates the double indication of casing collars and corrosion defects, enabling accurate thickness profiling of multiple nested casings, even in complex scenarios with up to five nested casings.
Implementation Method 1
processing induction multi-spacing and multi-frequency non-collocated sensor data measured by a downhole well tool disposed proximate a plurality of nested metallic casings
Data Source
AI summary
Systems and methods to determine a thickness profile of nested metallic pipes can include processing long sections (windows) of induction multi spacing and multi frequency noncollocated sensor measurements (attenuation and phase). The systems and methods also include using an inversion based process to deconvolve the tool transfer function from the surrounding pipe structure and its anomalies by running an axisymmetric finite element method (FEM modeling solver with a model in an inversion loop.