Fiber Optic Wellbore Sensors for Resistivity and Porosity Monitoring
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Solution Overview
Problem
Current monitoring systems for oil reservoirs lack the ability to accurately and efficiently track fluid movement and hydrocarbon content changes, particularly in enhanced recovery techniques like water-flooding and carbon dioxide injection, due to limitations in measuring formation resistivity and porosity over time.
Innovation Solution
A fiber optic distributed sensing system is deployed within a wellbore, combining nuclear and ElectroMagnetic sensors to provide continuous measurements of resistivity and porosity, allowing for the creation of a petrophysical model that enhances the monitoring of fluid movement and reservoir characteristics, using joint data processing to improve resolution and depth of investigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional monitoring systems are used to track fluid movement and hydrocarbon content, then the system complexity is reduced, but the measurement precision and reliability of formation resistivity and porosity monitoring deteriorate
Solution Approach 1:
The patent combines nuclear sensors and EM sensors into a single integrated monitoring system, allowing simultaneous measurement of formation resistivity and porosity. This merging of multiple sensing technologies resolves the technical contradiction by achieving high measurement precision through multi-parameter sensing while managing system complexity through integrated data processing and a unified control architecture.
2Loss of information
If a single sensor type is used for monitoring, then the device complexity is minimized, but the depth of investigation and resolution of reservoir characteristics are insufficient
Solution Approach 1:
The monitoring system is designed with multi-functional capabilities by integrating both nuclear sensors (for porosity measurement) and EM sensors (for resistivity measurement). This universal system can simultaneously perform multiple monitoring functions including fluid movement tracking, hydrocarbon content determination, and reservoir characteristic analysis, thereby reducing information loss while managing complexity through a unified platform.
3Reliability
If conventional resistivity measurement methods are used, then the ease of operation is maintained, but the ability to monitor fluid saturation changes and hydrocarbon content deteriorates
Solution Approach 1:
The system uses EM fields as an intermediary to indirectly measure formation resistivity, which correlates with fluid saturation and hydrocarbon content. This intermediary approach allows reliable monitoring of subsurface properties without direct contact with the formation, maintaining ease of operation through remote sensing while achieving high reliability in fluid saturation and hydrocarbon content monitoring.
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 system enables reliable, time-lapse monitoring of fluid movement and reservoir properties, optimizing oil recovery rates and reducing drilling costs by providing detailed insights into fluid distribution and reservoir conditions, thereby improving decision-making during production phases.
Implementation Method 1
a first set of downhole sensors having one or more nuclear sensors with nuclear field sensitivity
Implementation Method 2
a second set of downhole sensors having one or more ElectroMagnetic (EM) sensors with electromagnetic field sensitivity
Data Source
AI summary
A fiber optic distributed sensing system for installation within a wellbore is provided. The system includes a first set of downhole sensors having one or more nuclear sensors with nuclear field sensitivity. The system additionally includes, a second set of downhole sensors having one or more ElectroMagnetic (EM) sensors with electromagnetic field sensitivity. The fiber optic distributed sensing system also includes a processor system configured to receive data measurements from the first and second sets of sensors and configured to conjointly process the data measurements into representations of physical attributes of the wellbore.