Borehole Waveform Dispersion Analysis via Travel Time Alignment
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Solution Overview
Problem
Conventional acoustic logging methods face challenges in obtaining accurate dispersion curves due to noise and interference from scattering waves, tool waves, and formation heterogeneity, leading to poor signal-to-noise ratios and unreliable data, especially in complex borehole environments.
Innovation Solution
The method involves calculating travel time curves to align and enhance waveform trains, followed by adaptive filtering in the frequency-wavenumber domain to suppress non-target modes and noise, resulting in improved signal-to-noise ratios and more accurate dispersion curve calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional multi-mode dispersion extraction methods are used, then the analysis assumes homogeneous formation, but formation heterogeneity causes scattering waves and noise that contaminate target modes
Solution Approach 1:
The patent segments the waveform data by dividing it into multiple common-gathers based on different source-receiver offsets. This segmentation allows selective processing of different wave modes in different offset ranges, enabling reliable dispersion extraction from heterogeneous formations by focusing on zero-offset or near-zero-offset data where target modes are less contaminated by scattering waves
Solution Approach 2:
The patent applies different processing strategies to different parts of the waveform data. Specifically, it uses offset-dependent filtering where the filtering approach varies based on the source-receiver offset, allowing optimal extraction of target modes from each segment while adapting to local formation characteristics and noise conditions
2Measurement precision
If raw waveform data is used directly, then all wave modes are present, but non-target modes and noise contaminate the target mode dispersion measurement
Solution Approach 1:
The patent performs preliminary alignment of waveforms using calculated travel time curves before dispersion extraction. This preliminary action of aligning waveforms based on expected travel times prepares the data in advance, making the subsequent dispersion measurement more accurate by ensuring that target mode arrivals are properly synchronized across different receivers
Solution Approach 2:
The patent introduces an adaptive filter as an intermediary between the raw waveform data and the dispersion extraction process. This filter selectively attenuates non-target modes and noise while preserving target mode signals, acting as a mediator that cleans the data before final analysis without requiring complex manual processing
3Reliability
If travel time alignment is applied to enhance target modes, then signal-to-noise ratio improves, but computational processing time increases
Solution Approach 1:
The patent changes the parameter of waveform alignment by using calculated travel time curves to shift waveforms to a common reference time. This parameter change in the time domain alignment process enhances the signal-to-noise ratio by constructively adding target mode energy while suppressing random noise, and the computational efficiency is maintained by using analytical travel time calculations rather than iterative optimization
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 significantly enhances the quality of dispersion analysis, providing stable and accurate dispersion curves essential for both basic and advanced acoustic logging applications, even in heterogeneous formations.
Implementation Method 1
acoustic logging tools measure different dispersive borehole wave modes propagating along the longitudinal borehole axis
Implementation Method 2
dispersions characterize the relationship between wave slowness and wave number/frequency
Implementation Method 3
calculating a travel time curve for a selected target mode of the gathered waveforms; aligning waveforms of the selected target mode based on the travel time curve
Implementation Method 4
adaptively filtering the aligned waveforms to suppress non-target mode waves and generate filtered waveforms
Data Source
AI summary
A method for enhanced dispersion analysis begins with obtaining a plurality of measured waveforms, for example from two or more receivers of an acoustic logging tool placed in a borehole. The measured waveforms are divided into common gathers, and waveforms of each common gather are enhanced. The enhancement begins by calculating a travel time curve for a selected target mode of the common gather waveforms. Using the travel time curve, waveforms of the selected target mode are aligned to have zero apparent slowness. The aligned waveforms are filtered to suppress non-target mode waves. The aligned waveforms are then enhanced, and used to generate an enhanced dispersion curve of the selected target mode.