Neural Network Optimized Integrated Computational Elements for Downhole Fluid Analysis
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Solution Overview
Problem
Optical sensors used in downhole tools for the oil and gas industry face challenges in maintaining measurement accuracy and precision under extreme temperature and pressure conditions, as current design and fabrication methods do not adequately account for environmental factors, leading to inadequate data correction and reduced performance.
Innovation Solution
The implementation of a neural network-based optimization loop for designing and fabricating Integrated Computational Elements (ICEs) that incorporate environmental parameters into the calibration process, allowing for nonlinear identification and correction, and using a non-linear post-calibration algorithm with additional optical elements for improved performance across a wide range of conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If optical sensors are designed using conventional methods without environmental parameter integration, then manufacturing simplicity is maintained, but measurement precision deteriorates under extreme temperature and pressure conditions
Solution Approach 1:
The patent applies preliminary action by integrating environmental parameter measurements and correction algorithms into the sensor design phase. The sensor system pre-configures multiple sensors (temperature, pressure, humidity) and embedded processing capabilities before deployment, enabling real-time environmental compensation that maintains measurement accuracy under extreme conditions without requiring complex post-processing adjustments
Solution Approach 2:
The patent implements universality by creating a multi-functional sensor system that simultaneously performs primary measurements and environmental compensation. The integrated system combines multiple sensing elements (optical, temperature, pressure, humidity sensors) with embedded processing to provide both direct measurements and environmental correction functions within a single device architecture, improving measurement precision across diverse conditions
2Measurement precision
If environmental correction is applied through post-processing alone, then device complexity is minimized, but measurement precision deteriorates when influential factors are not accounted for at the sensor design stage
Solution Approach 1:
The patent uses intermediary elements by introducing dedicated environmental sensors (temperature, pressure, humidity sensors) as mediator components between the primary optical sensor and the correction algorithm. These intermediary sensors capture environmental parameters that affect the optical measurements, enabling the embedded system to perform accurate real-time compensation for atmospheric conditions, temperature variations, and pressure changes
Solution Approach 2:
The patent implements feedback by creating a closed-loop system where environmental sensors continuously monitor conditions, the embedded processor analyzes the combined data from primary and environmental sensors, and correction algorithms automatically adjust measurements in real-time. This feedback mechanism ensures that measurement precision is maintained dynamically across varying environmental conditions without manual intervention
3Reliability
If sensors are built with less optimal design for extreme environments, then manufacturing ease is improved, but reliability deteriorates under harsh operating conditions
Solution Approach 1:
The patent applies parameter changes by optimizing sensor design parameters specifically for extreme environment operation. This includes selecting materials and configuring sensor architectures with appropriate temperature coefficients, pressure ratings, and optical properties that maintain reliability under harsh conditions. The design adjusts key parameters such as film thickness, material composition, and structural configuration to ensure stable performance across the expected operational range
Solution Approach 2:
The patent uses composite materials by combining multiple material types with complementary properties to create a sensor system that withstands extreme environments. The design integrates optical materials, temperature-stable materials, pressure-resistant materials, and protective coatings in a composite structure that maintains sensor reliability under thermal stress, pressure variations, and harsh chemical conditions while remaining manufacturable
Data Source
AI summary
A method for ruggedizing an ICE design, fabrication and application with neural networks as disclosed herein includes selecting a database for integrated computational element (ICE) optimization is provided. The method includes adjusting a plurality of ICE operational parameters according to an environmental factor recorded in the database and simulating environmentally compensated calibration inputs. The method includes modifying a plurality of ICE structure parameters to obtain an ICE candidate structure having improved performance according to a first algorithm applied to the database and validating the ICE candidate structure with an alternative algorithm applied to the database. Further, the method includes determining a plurality of manufacturing ICEs based on the validation with the first algorithm and the alternative algorithm, and fabricating one of the plurality of manufacturing ICEs. A method for determining a fluid characteristic using a calibrated ICE fabricated as above and supplemental elements is also provided.