Hybrid DAS/DTS Wellbore Inflow Characterization
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Solution Overview
Problem
Determining fluid inflow rates and locations within a wellbore is challenging, especially when multiple production zones are present, as existing methods struggle to accurately identify where fluid is inflowing and quantify the inflow rates.
Innovation Solution
A method and system that combine distributed temperature sensing (DTS) and distributed acoustic sensing (DAS) technologies to determine temperature and frequency domain features, which are then used to identify fluid inflow locations and quantify inflow rates along the wellbore by processing temperature features such as depth derivative of temperature, temperature excursion, and baseline temperature excursion, and frequency domain features like spectral centroid and spectral spread.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If total flow detection at wellhead is used, then fluid production can be detected, but fluid inflow locations cannot be determined when multiple production zones are present
Solution Approach 1:
The patent segments the wellbore into multiple discrete zones along its length, with each zone monitored independently for temperature and acoustic signals. This allows identification of specific inflow locations within individual production zones rather than treating the entire wellbore as a single unit, thereby resolving the contradiction between total flow detection and location-specific measurement precision.
Solution Approach 2:
The patent transitions from one-dimensional wellhead flow measurement to three-dimensional distributed sensing along the wellbore circumference and length. By adding spatial dimensions through distributed temperature sensing and acoustic signal monitoring at multiple depths, the system recovers the spatial distribution information that was lost in traditional wellhead-only measurement.
2Measurement precision
If distributed sensing technologies are combined, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent merges distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) systems into a unified monitoring platform. By combining these two sensing modalities, the system achieves enhanced measurement precision for fluid inflow rate determination through multi-parameter analysis, while the integrated architecture manages the complexity that would arise from separate independent systems.
Solution Approach 2:
The hybrid sensing system serves multiple functions simultaneously: it detects temperature variations, captures acoustic signals, identifies inflow locations, and quantifies inflow rates. This multi-functionality consolidates what would otherwise require separate monitoring systems, thereby improving measurement precision without proportionally increasing device complexity.
3Measurement precision
If multiple temperature features are extracted, then fluid inflow identification accuracy improves, but data processing complexity increases
Solution Approach 1:
The patent performs preliminary extraction of multiple temperature features (depth derivative, temperature excursion, baseline temperature excursion) from the raw temperature data before conducting fluid inflow identification. This preliminary processing organizes the thermal data into meaningful characteristics that simplify subsequent analysis and improve identification accuracy without requiring complex real-time processing during the actual detection phase.
Solution Approach 2:
The patent introduces temperature features as intermediary variables that mediate between raw temperature measurements and fluid inflow identification. These features serve as processed intermediates that capture essential thermal signatures of fluid inflow, thereby improving identification accuracy while reducing the complexity of direct analysis of raw temperature data.
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 allows for accurate identification of fluid inflow locations and quantification of inflow rates, enhancing the management of fluid production by providing near real-time data on fluid inflow dynamics within the wellbore.
Implementation Method 1
determining a plurality of temperature features from a distributed temperature sensing signal originating in a wellbore
Implementation Method 2
determining one or more frequency domain features from an acoustic signal originating the wellbore
Data Source
AI summary
A method of determining fluid inflow rates within a wellbore comprises determining a plurality of temperature features from a distributed temperature sensing signal originating in a wellbore, determining one or more frequency domain features from an acoustic signal originating the wellbore, and using at least one temperature feature of the plurality of temperature features and at least one frequency domain feature of the one or more frequency domain features to determine a fluid inflow rate at one or more locations along the wellbore.