Blended Mapping Matrix for Downhole Fluid Composition
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Solution Overview
Problem
Current downhole fluid analysis tools face challenges in accurately determining the composition of formation fluids, particularly near fluid type boundaries, and in optimizing sampling processes without returning samples to the surface, due to limitations in spectral data interpretation and hardware dependency.
Innovation Solution
The method involves obtaining in-situ optical spectral data using a downhole formation fluid sampling apparatus, estimating fluid types, determining blending coefficients, and creating a blended mapping matrix to predict fluid parameters by projecting spectral data onto this matrix, which can handle fluid mixtures and reduce errors near type boundaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional spectral analysis methods are used for downhole fluid analysis, then the measurement process is simpler, but the measurement precision deteriorates near fluid type boundaries
Solution Approach 1:
The patent segments the continuous spectral data into distinct fluid type categories (oil, gas, water, CO2) by identifying characteristic absorption features at specific wavelengths. This segmentation allows the system to handle complex multi-component fluid analysis by breaking it down into discrete classification steps, improving measurement precision near fluid boundaries without proportionally increasing device complexity
Solution Approach 2:
The patent transforms raw spectral data into classification parameters by measuring optical density at specific wavelengths (e.g., 1650 nm for water, 1725 nm for CO2, 1500-1600 nm for oil) and using these parameter changes to distinguish between fluid types. This parameter transformation approach enhances measurement precision by focusing on discriminative spectral features rather than analyzing the entire spectrum
2Adaptability or versatility
If multiple fluid types are analyzed simultaneously, then the adaptability improves, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent introduces an intermediary classification system that uses optical density measurements at specific wavelengths as intermediate parameters to distinguish between multiple fluid types. By measuring OD at characteristic wavelengths (1650 nm for water, 1725 nm for CO2, 1500-1600 nm for oil) and using these as intermediary indicators, the system can simultaneously analyze multiple fluid types without directly confronting the full complexity of the spectral data
Solution Approach 2:
The patent applies local quality analysis by focusing on specific wavelength regions that are characteristic of different fluid types rather than analyzing the entire spectrum uniformly. Each fluid type is detected by examining local spectral features at its characteristic wavelengths, enabling multi-fluid type analysis while reducing overall measurement difficulty
3Productivity
If sampling processes are optimized without surface return, then the productivity increases, but the loss of information increases
Solution Approach 1:
The patent enables the downhole sampling system to perform self-service fluid analysis by integrating spectral measurement and classification capabilities directly into the downhole tool. The system measures optical spectra, classifies fluid types, and determines composition parameters downhole without requiring surface analysis, thereby maintaining high productivity while minimizing information loss through real-time downhole characterization
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 enhances the accuracy of fluid composition prediction and operational parameter adjustments in real-time, improving the effectiveness of downhole sampling processes by providing precise fluid characterization without the need for surface sampling.
Implementation Method 1
can measure absorption spectra of formation fluids under downhole conditions
Implementation Method 2
The output of each channel represents an optical density (i.e., the logarithm of the ratio of incident light intensity to transmitted light intensity)
Data Source
AI summary
Optical spectral data associated with a formation fluid flowing through a downhole formation fluid sampling apparatus is obtained. Based on the obtained optical spectra data, a plurality of measures each relating the formation fluid to a corresponding one of a plurality of different fluid types are estimated. Blending coefficients each corresponding to a different one of the different fluid types are determined and utilized with the predetermined mapping matrices, each corresponding to a different one of the different fluid types, to obtain a blended mapping matrix. A parameter of the formation fluid is then predicted based on a projection of the obtained spectral data onto the blended mapping matrix.