Distributed Optical Fiber Flow Measurement for Heterogeneous Well Inflow
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Solution Overview
Problem
Existing methods struggle to accurately quantify fluid flow rates and distributions within wellbores, leading to non-uniform fluid distribution and reduced production efficiency due to variations in geological formations and well structures.
Innovation Solution
Utilizing optical fibers to measure strain and distributed optical responses, combined with a predictive model and machine learning, to predict fluid flow rates and optimize well operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional flow measurement methods are used in wellbores, then device complexity is reduced, but measurement precision deteriorates due to inability to accurately quantify fluid flow rates and distributions
Solution Approach 1:
The patent replaces conventional mechanical flow measurement devices with an optical fiber-based measurement system. The optical fiber detects strain caused by fluid flow through the wellbore, converting mechanical flow information into optical signals that can be precisely measured and analyzed to determine fluid flow rates and distributions.
Solution Approach 2:
The patent introduces strain as an intermediary parameter to measure fluid flow. Instead of directly measuring flow rate, the system measures strain on the optical fiber caused by fluid flow, then uses this strain information as a mediator to infer the actual flow rates and distributions through predictive models.
2Measurement precision
If optical fiber measurement system is deployed, then measurement precision improves, but device complexity increases due to distributed optical response analysis
Solution Approach 1:
The patent extracts the core measurement function from the complex distributed optical response data by focusing on strain measurements. Instead of processing all optical response parameters, the system specifically extracts strain information caused by fluid flow, simplifying the data processing while maintaining measurement precision.
Solution Approach 2:
The patent uses predictive models and machine learning algorithms to create virtual representations of the wellbore flow conditions based on the optical fiber strain measurements. These models copy and simulate the complex fluid dynamics, allowing accurate flow rate predictions without directly measuring all physical parameters.
3Productivity
If heterogeneous inflow patterns are present, then productivity is reduced due to non-uniform fluid distribution, but adaptability is improved by using distributed measurements to identify flow variations
Solution Approach 1:
The patent applies local quality analysis by measuring flow characteristics at different locations along the wellbore using the distributed optical fiber sensor. This allows identification of heterogeneous inflow patterns at specific zones, enabling targeted stimulation strategies to improve overall fluid distribution uniformity and productivity.
Solution Approach 2:
The system implements feedback by continuously monitoring distributed strain measurements along the optical fiber and using predictive models to determine actual flow rates. This feedback information is used to identify non-uniform flow distributions and guide well stimulation adjustments to improve productivity.
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
Enables precise quantification of fluid flow rates and distributions, improving well stimulation and production efficiency by adjusting hydraulic fracturing and operation strategies.
Implementation Method 1
predicting flow rates through outlets of the well, such as perforations, perforation clusters, open ports, and flow rates in different sections along the well may include predicting flow rates through the outlets by estimating strain on the optical fiber due to flows of fluids through the outlets
Implementation Method 2
The optical fiber may have optical properties adapted to change with respect to the fluid flow
Implementation Method 3
The measurement data may be obtained by, while the optical fiber is positioned in the wellbore: sending pulses of optical radiation into the optical fiber; and measuring a response of the optical fiber to the optical pulses at different points in time
Data Source
AI summary
Methods and systems for managing characterization of wells using data acquisitions tools are disclosed. The data acquisition tools may be positioned in portions of wells. While positioned in the wells, the data acquisition tools may be measured. The measurements may be ingested into models and may provide, as output, inferred conditions in the portions of the wells. The models may be created using simulation systems. The simulation systems may allow for conditions that may be present in wells to be simulated, and data acquisition tools to be exposed to the simulated conditions. While exposed to the simulated conditions, the data acquisition tools may be measured to establish associations that may be used to infer conditions that may be present in wells.