In-Situ Fracture Sensing for Noisy Microseismic Well Productivity
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Solution Overview
Problem
Current methods of hydraulic fracturing monitoring, such as micro-seismic monitoring, face challenges due to signal noise masking small magnitude seismic signals, especially when monitoring wells or laterals are not available.
Innovation Solution
In-situ sensing devices of micrometer to millimeter size are pumped into fractures alongside proppants to monitor fracture extent and direction, inducing larger in-situ vibrations that can be better detected by seismic sensors, and data is processed using a deep learning framework to determine well productivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If seismic sensors are placed on surface or in neighboring wellbores, then monitoring coverage is achieved, but signal noise masks small magnitude seismic signals from fractures
Solution Approach 1:
The patent transitions from surface-based or wellbore-based seismic monitoring to in-situ monitoring within the fracture itself. By placing sensors directly in the fracture (a different spatial dimension), the system eliminates the noise problem associated with surface and wellbore environments while maintaining monitoring coverage.
Solution Approach 2:
The patent introduces proppant-coated sensors as an intermediary between the fracture and the monitoring system. These sensors are transported into the fracture with the proppant and serve as both the monitoring element and the medium that carries it to the target location, enabling precise local measurement without surface noise interference.
2Measurement precision
If in-situ sensors are pumped into fractures with proppants, then fracture extent and direction can be monitored, but sensor selection and noise management complexity increases
Solution Approach 1:
The patent changes the operational state of sensors from passive to active by classifying them as 'noisy' or 'clean' based on their measured data characteristics. This parameter change enables dynamic sensor selection where only sensors meeting quality thresholds are used for productivity estimation, simplifying the overall system despite the large number of deployed sensors.
Solution Approach 2:
The patent deploys an excessive number of sensors into the fracture (more than minimally required) and then selectively uses only the subset of sensors that meet quality criteria. This approach ensures that sufficient high-quality data is obtained for accurate fracture characterization and productivity estimation, overcoming the complexity of managing numerous sensors.
3Measurement precision
If vibration sources are used to activate in-situ sensors, then detectability of microseismic events is enhanced, but energy requirements increase
Solution Approach 1:
The patent uses periodic vibration sources (such as acoustic or mechanical vibrations applied at specific intervals) to activate in-situ sensors. This periodic activation allows sensors to be energized only when needed for detection, rather than requiring continuous power supply, thereby reducing overall energy consumption while maintaining detectability of microseismic events.
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 fracture characterization and improves the detectability of microseismic events, leading to better estimation of fracture half-length and well productivity potential.
Implementation Method 1
The in-situ sensors are configured to induce in-situ vibrations within the well. The in-situ seismic vibrations are larger than the microseismic vibrations emitted by the fracture.
Implementation Method 2
Vibration activated signals propagate better within earth layers making it easier to energize and activate the in-situ sensors.
Data Source
AI summary
Methods and systems for determining well productivity include acquiring measurement data from a plurality of in-situ sensors located within a hydraulically fractured subterranean formation; classifying the noise degree for sensors of the plurality based on the acquired measurement data; selecting sensors from the plurality by minimizing noise degree while maintaining coverage of the subterranean formation above a user defined threshold; extracting data from the selected sensors; and estimating fracture half-length and well productivity potential based on the extracted data.