Sector CBL Analysis for Cement and Casing Eccentricity in Narrow Annuli
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Solution Overview
Problem
Conventional cement bond logging tools face interpretative uncertainties due to factors like casing eccentricity and narrow annular spacing, leading to poor cement bond evaluation in hydrocarbon wells, which can cause fluid leakage, corrosion, and zonal isolation issues.
Innovation Solution
A method using sector cement bond log data with an extended acquisition time window, singular value decomposition, and local cluster modeling to analyze waveform components, enabling accurate cement zone identification, eccentricity detection, and channel detection in non-concentric casing strings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional CBL tools are used to evaluate cement bonds, then basic cement bond evaluation can be performed, but interpretative uncertainties increase due to casing eccentricity and narrow annular spacing
Solution Approach 1:
The patent divides the continuous CBL waveform data into discrete interface echoes (casing-cement interface, cement-formation interface) by segmenting the time window. This segmentation allows individual analysis of each interface reflection, enabling precise identification of cement bond quality at specific locations despite casing eccentricity and narrow annular spacing conditions.
Solution Approach 2:
The patent transforms the conventional single-dimension CBL waveform analysis into multi-dimensional analysis by introducing time window segmentation as an additional dimension. This allows the system to distinguish between different interface echoes (casing-cement, cement-formation) that occur at different time intervals, thereby resolving interpretative uncertainties caused by overlapping signals in narrow annular spaces.
2Measurement precision
If extended acquisition time window is used to capture multiple interface echoes, then cement top and channel detection accuracy improves, but data processing complexity increases
Solution Approach 1:
The patent performs preliminary action by pre-defining the extended acquisition time window to capture multiple interface echoes before data analysis begins. This preliminary setup ensures that all relevant echo information is captured in advance, allowing subsequent processing to focus on identifying and interpreting the already-captured echoes rather than acquiring additional data.
Solution Approach 2:
The patent applies skipping by rapidly processing the captured interface echoes through automated identification algorithms. Once the extended time window captures all relevant echoes, the system quickly identifies the cement top and channels by analyzing the timing and amplitude characteristics of each echo, thereby reducing the overall processing time despite the extended data acquisition window.
3Measurement precision
If sector CBL data with multiple azimuthal sectors is analyzed, then casing eccentricity detection capability improves, but computational requirements increase
Solution Approach 1:
The patent applies local quality by analyzing the amplitude characteristics of interface echoes in different azimuthal sectors locally. Instead of processing all sector data uniformly, the system identifies regions with abnormal echo amplitudes that indicate casing eccentricity, focusing computational resources only on those specific azimuthal sectors where anomalies are detected.
Solution Approach 2:
The patent changes parameters by comparing echo amplitude variations across different azimuthal sectors. When significant amplitude differences are detected between sectors, this parameter change indicates casing eccentricity. The system uses these parameter changes to detect and quantify eccentricity without requiring exhaustive analysis of all possible sector combinations.
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
Enhances the accuracy of cement top identification, casing eccentricity detection, and channel detection, reducing uncertainties and improving well integrity by providing insights into cement bonding quality and casing position.
Implementation Method 1
a transmitter that emits a sonic signal (e.g., acoustic waves) and one or more receivers that detect this signal after it has passed through the casing, cement, and formation
Implementation Method 2
each interface echo indicating an acoustic reflection generated when an acoustic wave emitted by the cement bond logging tool encounters an interface between different materials
Data Source
AI summary
Disclosed herein is a workflow for evaluating the cement between a casing string and the surrounding formation in a wellbore and for determining casing string eccentricity using sector cement bond log (CBL) data. This method involved using a cement bond logging tool with an extended acquisition time window to capture multiple interface echoes. From this sector CBL data, a data matrix of waveform information is generated, with each row representing waveform data from different azimuthal sectors. Through singular value decomposition, the principal components of the matrix are identified. Subsequent component analysis emphasizes significant components of waveforms. The significant waveform components are then used to model waveforms using local cluster modeling. The method proceeds by analyzing decomposed data to pinpoint cement zones, compute an eccentricity index for casing deviation, and detect cement channels.