Microseismic Event Characterization Using Distributed Acoustic Sensing
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Solution Overview
Problem
Current methods for detecting microseismic events in wellbore operations using distributed acoustic sensors face challenges such as directional sensitivity and noise, leading to frequency blind spots and reduced data resolution, which are costly and time-consuming, especially when relying on wireline operations or fiber optic recording methods.
Innovation Solution
The system employs distributed acoustic sensors to measure strain along a fiber optic cable, corrects for directional sensitivity and wavenumber filtering effects, and uses a Brune circular crack model for spectral analysis to determine seismic moment and moment magnitude of microseismic events, enabling efficient estimation of event characteristics without additional infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wireline operations with geophone tools are used to detect microseismic events, then measurement precision is improved, but loss of time and productivity are worsened due to expensive and time-consuming operations
Solution Approach 1:
The fiber optic cable is repurposed from its original communication function to also serve as a distributed acoustic sensor for microseismic detection. The existing cable infrastructure performs multiple functions: data transmission and seismic wave detection, eliminating the need for separate geophone tools and wireline operations.
Solution Approach 2:
The fiber optic cable detects its own vibrations caused by passing seismic waves without requiring external sensing equipment. The cable serves itself as both the transmission medium and the sensing element, eliminating the need for additional measurement devices.
2Productivity
If distributed acoustic sensors are used for fiber optic recording operations, then productivity is improved by avoiding wireline operations, but measurement precision is worsened due to directional sensitivity and noise causing frequency blind spots
Solution Approach 1:
The patent transforms the one-dimensional strain measurement along the fiber optic cable into three-dimensional seismic event characterization. By analyzing strain variations along the entire length of the cable and applying spectral analysis, the system reconstructs full seismic event properties including location, magnitude, and waveform characteristics in 3D space.
Solution Approach 2:
The patent replaces traditional mechanical geophone sensors with an optical-based distributed acoustic sensing system. Fiber optic cables use optical principles (light transmission and phase modulation) instead of mechanical mass-spring systems, eliminating mechanical noise and directional sensitivity limitations while maintaining measurement precision.
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 reduces costs and time by utilizing existing infrastructure to accurately determine microseismic event characteristics, allowing for improved hydraulic fracturing efficiency by mapping fracture networks and adjusting operation parameters based on precise event data.
Implementation Method 1
Distributed acoustic sensors detect strain within a wellbore along a fiber optic cable
Implementation Method 2
corrects for directional sensitivity and wavenumber filtering effects
Implementation Method 3
uses a Brune circular crack model for spectral analysis to determine seismic moment and moment magnitude
Data Source
AI summary
A well system includes a fiber optic cable positionable downhole along a length of a wellbore and a reflectometer communicatively coupleable to the fiber optic cable. The reflectometer detects and locates a microseismic event using strain detected in reflected optical signals received from the fiber optic cable. Further, the reflectometer computes a set of spectra for waveforms of the microseismic event. Additionally, the reflectometer aggregates each spectrum from the set of spectra that meet an acceptance threshold to generate an aggregate spectrum. Furthermore, the reflectometer applies a fault source model to the aggregate spectrum to determine a magnitude of the microseismic event.


