Monopole Sonic Logging AI for Slowness Precision
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Solution Overview
Problem
Acoustic logging processes face challenges in accurately measuring compressional and shear slownesses due to low signal-to-noise ratios and interference from various wave modes, especially in non-nominal conditions such as hard formations, gas presence, and borehole casing, which complicates real-time and post-processing efforts.
Innovation Solution
An automated method utilizing physics-guided artificial intelligence and machine learning to adaptively measure borehole refracted wave compressional and shear slownesses, leveraging both first-arrival and pure semblance-based modules, with dynamic weighting functions and outlier rejection techniques to enhance accuracy across varying conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional coherence processing methods are used, then the processing is simple and fast, but the measurement precision deteriorates due to low signal-to-noise ratios and interference from multiple wave modes
Solution Approach 1:
The patent segments the complex acoustic logging problem into multiple independent processing modules: a first arrival module that identifies initial wave arrivals, a pure semblance module that processes coherence, and an artificial intelligence module that integrates results. This segmentation allows each module to specialize in specific aspects of the problem, improving overall measurement precision while maintaining manageable complexity through modular architecture.
Solution Approach 2:
The patent implements dynamic adaptability by allowing the system to automatically adjust processing parameters and select between different processing paths based on real-time signal conditions. The artificial intelligence module dynamically weights contributions from different modules and adapts to varying signal-to-noise ratios and wave mode interference levels, enabling high precision measurements across diverse borehole conditions without requiring manual intervention.
2Measurement precision
If manual intervention and reprocessing are used for non-nominal conditions, then the measurement precision improves, but the productivity deteriorates due to time-consuming manual operations
Solution Approach 1:
The patent implements self-service through an automated quality control system with artificial intelligence that independently evaluates measurement reliability, identifies non-nominal conditions, and triggers appropriate reprocessing actions without human intervention. The system performs self-diagnosis and self-correction, maintaining high measurement precision across all conditions while ensuring continuous real-time productivity by eliminating manual operation bottlenecks.
Solution Approach 2:
The patent incorporates feedback mechanisms where the artificial intelligence module continuously monitors measurement quality and signal conditions, automatically adjusting processing parameters and selecting optimal processing paths based on real-time performance. This closed-loop feedback system ensures high precision measurements are maintained while maximizing productivity by eliminating the need for manual intervention even in challenging non-nominal conditions.
3Adaptability or versatility
If conventional processing methods are used, then the device complexity is low, but the adaptability deteriorates when dealing with diverse borehole conditions such as hard formations, gas presence, and casing
Solution Approach 1:
The patent creates a universal processing system that handles diverse borehole conditions through multiple functional modules: the first arrival module handles initial wave identification, the pure semblance module processes coherence measurements, and the artificial intelligence module integrates results and adapts to various conditions including hard formations, gas presence, and casing. This multi-functional architecture provides broad adaptability while managing complexity through specialized sub-systems that can be selectively activated.
Solution Approach 2:
The patent implements dynamic adaptability where the processing system automatically adjusts its behavior based on detected borehole conditions. The artificial intelligence module dynamically selects and weights different processing approaches depending on whether the system encounters hard formations, gas zones, cased holes, or nominal conditions, enabling universal adaptability across all scenarios without requiring complex manual configuration or separate specialized systems.
4Productivity
If real-time processing is implemented, then the productivity improves, but the measurement precision deteriorates due to limited computing time and lack of human interaction
Solution Approach 1:
The patent segments the processing into fast first-arrival detection, parallel pure semblance computation, and intelligent integration phases, allowing critical real-time measurements to be computed quickly while more sophisticated precision-enhancing operations proceed in parallel or with minimal delay. This segmentation enables real-time productivity while maintaining measurement precision through distributed computational architecture.
Solution Approach 2:
The patent implements dynamic processing where the system automatically adjusts computational depth and processing intensity based on signal quality and time constraints. The artificial intelligence module dynamically determines the appropriate level of processing for each measurement, applying full precision analysis when time permits and signal quality allows, while maintaining real-time responsiveness when constraints require faster processing, thus balancing productivity and precision dynamically.
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 enables reliable and accurate real-time measurement of compressional and shear slownesses in diverse borehole environments, reducing the need for manual intervention and improving the quality of sonic logging data, even in challenging conditions.
Implementation Method 1
a transmitter configured to transmit a sonic waveform into a formation
Implementation Method 2
a receiver configured to record a response from a borehole
Data Source
AI summary
A method and system for measuring a compressional and a shear slowness. The method may comprise disposing a downhole tool into a wellbore. The downhole tool may comprise a transmitter, wherein the transmitter is a monopole, and a receiver, wherein the receiver is a monopole receiver. The method may further comprise broadcasting the sonic waveform into the formation penetrated by the wellbore, recording a reflected wave on one or more receivers, wherein the reflected wave is a compressional wave or a shear wave, processing the reflected wave into at least one measurement, and applying a validation scheme to the at least one measurement. The system may be a downhole tool comprising a transmitter configured to transmit a sonic waveform into a formation, wherein the transmitter is a monopole, and a receiver configured to record a reflected wave, wherein the receiver is a monopole receiver.