Geothermal Tremor Characterization for Low-Frequency Source Location
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Solution Overview
Problem
Tremor events in geothermal reservoirs are difficult to detect and locate due to their long duration, low frequency, and gradual emergence from background noise, making it challenging to identify permeable subsurface pathways for geothermal energy exploration.
Innovation Solution
A method involving seismic data processing, tremor event detection, and source identification using seismic receivers, which includes generating processed seismic data, calculating covariance matrices, fitting synthetic resonance spectra, and identifying candidate locations based on time-frequency representations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional seismic detection methods are used, then the detection process is simple, but tremor events cannot be effectively detected due to their long duration, low frequency, and gradual emergence from background noise
Solution Approach 1:
The patent segments the tremor detection process into multiple distinct stages: background noise characterization, tremor event detection, candidate location identification, and verification. Each stage processes specific features and produces intermediate results that feed into the next stage, allowing complex analysis to be broken down into manageable components that can be implemented systematically
Solution Approach 2:
The patent transitions from traditional single-dimension seismic signal analysis to multi-dimensional analysis by incorporating time-frequency representations, spatial distribution patterns across multiple receivers, and spectral characteristics. This dimensional expansion enables differentiation between tremor events and background noise through combined analysis of multiple feature spaces simultaneously
2Measurement precision
If traditional seismic analysis methods are used, then the processing is straightforward, but source location identification is inaccurate due to lack of distinct arrival times
Solution Approach 1:
The patent performs preliminary background noise characterization and establishes reference models before actual tremor detection. By pre-processing the data to understand the ambient conditions and expected tremor signatures, the system reduces the computational burden during actual event analysis and improves location accuracy without excessive processing time
Solution Approach 2:
The patent replaces traditional mechanical arrival-time-based localization methods with signal processing-based approaches including time-frequency analysis and pattern recognition. This substitution allows detection and localization of events that lack distinct arrival times by analyzing spectral and temporal patterns rather than relying on mechanical wave arrival detection
3Reliability
If comprehensive seismic data processing is performed, then tremor detection accuracy improves, but computational complexity and processing time increase
Solution Approach 1:
The patent applies partial action by focusing computational resources on the most discriminative features for tremor detection. Rather than processing all possible seismic parameters equally, the method selectively analyzes time-frequency characteristics, spectral ratios, and spatial patterns that provide the highest detection reliability, performing sufficient but not excessive processing
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
Enhances the ability to detect and locate tremor events, reducing exploration risks in geothermal energy projects by improving the efficiency of geothermal wellfield design and reservoir modeling.
Implementation Method 1
obtaining raw seismic data from seismic receivers distributed with reference to a geological zone
Implementation Method 2
generating spectral representations based on the raw seismic data or the processed seismic data
Implementation Method 3
generating, for respective pairs of seismic receivers, a covariance matrix including cross-spectra between respective pairs of the spectral representations
Implementation Method 4
generating a time-frequency representation of the processed seismic data based on a sum of covariance matrix
Implementation Method 5
fitting synthetic resonance spectra to the time-frequency representation of the processed seismic data on a per-time-instance basis
Data Source
AI summary
The described techniques relate to an improved method for geothermal imaging. The method may include obtaining raw seismic data from seismic receivers distributed with reference to a geological zone and detecting a tremor event from the raw seismic data. The detecting may include generating processed seismic data from the raw seismic data; generating spectral representations; generating, for pairs of seismic receivers, a covariance matrix including a cross-spectra between pairs of the spectral representations; generating a time-frequency representation of the processed seismic data; fitting synthetic resonance spectra to the time-frequency representation of the processed seismic data on a per-time-instance basis; and identifying a subset of the processed seismic data based on the fitting, where the subset of the processed seismic data is representative of the tremor event. After detecting the tremor event, method may include outputting candidate locations representative of a source of the tremor event.