Acoustic Emission Source Parameters for In Situ Stress Estimation
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Solution Overview
Problem
Current methods lack effective means to accurately determine in situ stress in earth formations, including principal stress magnitudes and orientations, which is crucial for understanding fracture propagation in subterranean wells.
Innovation Solution
The method employs acoustic emission source parameters through moment tensor analysis to estimate in situ stress ratios and orientations using sensors positioned along a wellbore, allowing for the classification of crack types and determination of principal stress directions without prior knowledge of environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If acoustic emission data is collected from multiple sensors along a wellbore, then measurement precision of in situ stress parameters is improved, but device complexity increases
Solution Approach 1:
The system divides the measurement task into multiple segments by deploying individual acoustic emission sensors at different positions along the wellbore. Each sensor captures acoustic signals from micro-fractures in specific zones, and the computer integrates data from all sensors to determine comprehensive in situ stress parameters. This segmentation allows precise local measurements to be combined into accurate global stress characterization.
Solution Approach 2:
The acoustic emission sensors serve multiple functions: detecting micro-fracture events, capturing stress release signals, and providing spatial distribution data. The same sensor array that monitors fracture propagation also directly provides information for calculating principal stress magnitudes, ratios, and orientations. This multi-functionality reduces the need for separate measurement systems while improving overall measurement precision.
2Loss of information
If moment tensor analysis is performed on acoustic emission data, then information about crack types and stress orientations is obtained, but processing time and computational complexity increase
Solution Approach 1:
The system performs moment tensor analysis on acoustic emission data as it is collected, rather than waiting for complete datasets. The computer processes signals from multiple sensors in real-time, calculating source parameters and stress indicators continuously. This preliminary processing ensures that critical information about crack types and stress orientations is captured immediately, reducing overall processing time while maintaining information quality.
Solution Approach 2:
The system replaces complex mechanical stress measurement methods with acoustic emission-based moment tensor analysis. Instead of using physical stress cells or mechanical probes that require direct contact with formation, the system uses acoustic signals from micro-fractures as natural indicators of stress state. This substitution reduces processing complexity while providing comprehensive stress characterization including principal stress directions and magnitudes.
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 the determination of principal stress ratios and orientations directly from acoustic emission data, providing valuable insights into stress regimes and identifying tectonically stressed environments, thereby enhancing the understanding of fracture mechanics in earth formations.
Implementation Method 1
Micro-fractures can be monitored by detecting sound waves, or acoustic emissions, that are produced during a fracturing process.
Data Source
AI summary
A method can include receiving acoustic emission data for acoustic emissions originating in a formation, performing a moment tensor analysis of the data, thereby yielding acoustic emission source parameters, determining at least one acoustic emission source parameter angle having a highest number of associated acoustic emission events, and calculating an in situ stress parameter, based on the acoustic emission source parameter angle. A system can include multiple sensors that sense acoustic emissions originating in a formation, and a computer including a computer readable medium having instructions that cause a processor to perform a moment tensor analysis of the data and yield acoustic emission source parameters, determine at least one acoustic emission source parameter angle having a highest number of associated acoustic emission events, and calculate an in situ stress parameter, based on the acoustic emission source parameter angle.