Downhole Sensing Tool Optimization for Condition Identification
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Solution Overview
Problem
Hydrocarbon well operations face inefficiencies and increased costs due to sub-optimal tool configurations, inaccurate sensors, and poor data inversion models, leading to potential well unsuitability and the need for costly repairs or replacements.
Innovation Solution
The implementation of a system and method that optimizes downhole condition identification using various types of downhole sensing tools, selected and arranged based on a predetermined evaluation plan accounting for tool availability and performance constraints, with measurements analyzed together to improve accuracy and inform operations such as perforation and well completion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple downhole sensing tools are deployed to improve measurement accuracy, then the accuracy of downhole condition identification is improved, but the device complexity and cost increase
Solution Approach 1:
The system divides the downhole sensing into multiple specialized tool types (acoustic, electrical, mechanical, chemical sensors) each targeting specific formation properties. This segmentation allows targeted measurement of different downhole conditions using appropriate specialized tools rather than attempting to measure everything with a single complex tool system.
Solution Approach 2:
The evaluation plan framework provides a universal approach that can accommodate multiple sensing tool types and configurations. The system uses a single integrated planning and analysis framework that works across different tool types, making the complexity management more manageable through standardized procedures.
2Loss of information
If more sensing tools are used to collect comprehensive downhole measurements, then the completeness of data is improved, but the loss of time during deployment and analysis increases
Solution Approach 1:
The system performs preliminary action by pre-defining the evaluation plan that specifies which sensing tools are needed and how they should be configured before deployment. This planning phase determines the optimal tool selection and configuration in advance, reducing on-site decision-making time and ensuring comprehensive data collection is achieved efficiently.
Solution Approach 2:
The system incorporates feedback mechanisms where measurements from the sensing tools are analyzed to identify downhole conditions, and this information feeds back into determining whether additional tools or re-measurement is needed. This iterative feedback process ensures data completeness while minimizing unnecessary time spent on redundant measurements.
3Measurement precision
If sophisticated inversion models are used to interpret sensor data, then the accuracy of condition identification is improved, but the difficulty of data processing and analysis increases
Solution Approach 1:
The system changes parameters by selecting and optimizing specific inversion model parameters based on the evaluation plan and the particular sensing tools being used. Rather than using a single complex inversion approach, the system adapts the inversion parameters to match the specific measurement characteristics, making the processing more manageable while maintaining accuracy.
Data Source
AI summary
A system includes different types of downhole sensing tools deployed in a borehole, wherein the different types of downhole sensing tools are optimized to identify a downhole condition based on a predetermined downhole evaluation plan that accounts for sensing tool availability and performance constraints. The system also includes at least one processing unit configured to analyze measurements collected by the different types of downhole sensing tools, wherein the collected measurements are analyzed together to identify the downhole condition. The system also includes at least one device that performs an operation in response to the identified downhole condition.