Dispersion Quality Manager for Acoustic Borehole Logging
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Solution Overview
Problem
Conventional Slowness-Frequency Analysis (SFA) techniques lack the ability to quantify the quality of dispersive/non-dispersive waveforms in acoustic logging, failing to evaluate the continuity and reliability of dispersion curves, which are crucial for accurately characterizing borehole and formation properties.
Innovation Solution
The Dispersion Quality Manager (DQM) apparatus calculates a dispersion quality indicator (DQI) based on inverse slowness variation width and frequency continuity, characterizing acoustic dispersions in a borehole by converting time-domain waveforms to the frequency domain and projecting data onto slowness and frequency axes, thereby assessing the quality of dispersion curves.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional Slowness-Frequency Analysis (SFA) techniques are used to analyze acoustic waves in boreholes, then the analysis process is simple, but the ability to quantify the quality of dispersive/non-dispersive waveforms and evaluate the continuity and reliability of dispersion curves is lacking
Solution Approach 1:
The patent transforms the acoustic waveform analysis from time-domain to frequency-domain by calculating the Fourier transform of the acoustic waveform. This parameter transformation enables the extraction of frequency-dependent characteristics including phase velocity, group velocity, and attenuation coefficient, which are essential for quantifying dispersion quality and evaluating waveform reliability.
Solution Approach 2:
The patent introduces a quality indicator dimension that evaluates the continuity and reliability of dispersion curves. By adding this assessment dimension to the traditional SFA methodology, the system can quantify waveform quality based on frequency continuity and slowness variation width, transforming a qualitative assessment into a measurable parameter.
2Measurement precision
If conventional SFA techniques are used, then the analysis method is straightforward, but the accuracy of borehole and formation property characterization is insufficient due to inability to evaluate dispersion curve reliability
Solution Approach 1:
The patent implements a feedback mechanism where the quality indicator, derived from frequency continuity and slowness variation width, feeds back into the interpretation process. This quality feedback allows operators to assess the reliability of dispersion curve data before using it for borehole and formation property characterization, preventing misinterpretation of low-quality data.
Solution Approach 2:
The patent introduces the quality indicator as an intermediary parameter between the raw acoustic waveform data and the final borehole characterization results. This intermediary assessment of dispersion quality acts as a filter, ensuring that only reliable data contributes to the final interpretation of formation properties.
3Reliability
If acoustic dispersions are not properly characterized, then the processing is faster, but the reliability of acoustic logging data is reduced
Solution Approach 1:
The patent performs preliminary quality assessment of acoustic dispersions by calculating frequency continuity and slowness variation width before final interpretation. This preliminary action identifies high-quality dispersion data early in the processing workflow, allowing operators to focus detailed analysis on reliable data segments and streamline the overall processing efficiency.
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
The DQM apparatus provides a reliable method to quantify the quality of acoustic dispersions, enhancing the accuracy of borehole characterization and informing operational decisions by distinguishing between high-quality and low-quality dispersions, thus improving the reliability of acoustic logging data.
Implementation Method 1
acoustic energy in the form of acoustic waves is transmitted from a source into the borehole and surrounding formation. The acoustic waves that travel through the borehole and formation are detected with one or more receivers.
Implementation Method 2
converting time-domain waveforms to the frequency domain and projecting data onto slowness and frequency axes
Data Source
AI summary
Methods, apparatus, and articles of manufacture are disclosed to characterize acoustic dispersions in a borehole. An example apparatus includes a dispersion analyzer to characterize an acoustic wave dispersion in a borehole in a formation by calculating a quality indicator corresponding to the acoustic wave dispersion, and a report generator to prepare a report including a recommendation to perform an operation on the borehole based on the quality indicator.