Acoustic Logging First Arrival Detection for Slowness Precision
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional acoustic logging methods face challenges in accurately separating and identifying waveform modes due to low signal-to-noise ratios and interactions between P-wave and leaky-P-wave signals, especially in complex borehole environments, leading to unreliable compressional and shear slowness evaluations, particularly in real-time processing.
Innovation Solution
A fast, self-adaptive acoustic logging process that employs a well-engineered algorithm and workflow for first arrival detection and tracking of refracted P-waves, reducing noise contamination and utilizing semblance methods to accurately determine compressional and shear slowness, even in the presence of dispersive borehole modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional coherence processing methods are used to separate waveform modes, then the processing is simple and fast, but the accuracy of identifying individual waveform modes deteriorates due to low signal-to-noise ratio and interactions between P-wave and leaky-P-wave signals
Solution Approach 1:
The patent segments the waveform analysis by separating the detection of first arrivals (P-waves) from subsequent mode identification. By focusing on the initial arrivals before mode interactions occur, the method isolates the cleanest signal portion for accurate P-wave slowness determination, then uses this as a foundation for further shear slowness extraction.
Solution Approach 2:
The patent performs preliminary detection of first arrivals and estimates P-wave slowness before attempting to identify other waveform modes. This preliminary action establishes a reliable reference point that guides subsequent processing, allowing the system to work forward from known accurate information rather than attempting to extract all parameters simultaneously from contaminated signals.
2Ease of manufacture
If traditional processing methods are used, then the algorithm is simple to implement, but the reliability of slowness determination deteriorates because the wrong borehole modes are processed
Solution Approach 1:
The patent introduces an intermediary step that uses first arrival detection and P-wave slowness estimation as a mediator between raw waveform data and final slowness determination. This intermediary process filters out incorrect mode identifications by establishing a reliable reference framework before final parameter extraction, ensuring that only correctly identified modes contribute to the final results.
Solution Approach 2:
The patent implements feedback mechanisms where the detected first arrival times and estimated P-wave slowness are used to guide and constrain subsequent mode identification processes. The system continuously refines its interpretations by comparing expected arrivals based on preliminary estimates against actual observed waveforms, correcting errors as it progresses through the analysis.
3Loss of time
If conventional methods are used for real-time processing, then computing time is reduced, but the quality of slowness answers deteriorates due to lack of human interaction and limited processing time
Solution Approach 1:
The patent makes the processing system self-sufficient by automating the detection and tracking of first arrivals, automatic estimation of P-wave slowness, and guided identification of shear slowness. The algorithm serves itself by using its own preliminary results to guide subsequent processing steps, eliminating the need for human intervention while maintaining high accuracy through self-correcting feedback loops.
Solution Approach 2:
The patent performs all critical preliminary actions automatically within the real-time constraint, including first arrival detection, P-wave slowness estimation, and setup of processing parameters. By completing these foundation-laying steps automatically and quickly, the system establishes a reliable framework that enables accurate final determination without requiring extended processing time or human input.
Data Source
AI summary
Disclosed are systems and methods for high precision acoustic logging processing for compressional and shear slowness. The method comprises measuring, by a sonic logging tool, sonic data associated with a formation within a borehole, attempting a detection of a first arrival within the sonic data determining whether the attempted detection of the first arrival is accurate, and in response to an accurate detection of the first arrival determining a travel time of the first arrival, generating a coherence map including the first arrival, and determining, based on the coherence map, a characteristic of the formation.