Reservoir Fluid Characterization Using Synthetic Composition
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Solution Overview
Problem
Characterizing hydrocarbon reservoir fluids under uncertainty is challenging due to limited information, contamination, and phase changes during production, leading to uncertain property measurements and obstructed conduit flow, which complicates normal production processes.
Innovation Solution
A computer-implemented method characterizes hydrocarbon reservoir fluids using probability density functions for API gravity and gas-oil ratio, with correlations adjusted based on analogous data to minimize errors and ensure accurate property representation, employing a similarity module to select relevant records from a database and modify correlations for accurate fluid property determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If basin modeling programs are used to predict fluid properties, then API gravity and GOR data are obtained, but the remaining fluid properties require subjective interpretation and association with known fluids
Solution Approach 1:
The patent creates a virtual copy of the reservoir fluid by generating a synthetic fluid composition that matches the measured API gravity and GOR values. This synthetic fluid serves as a proxy for the actual reservoir fluid, allowing all other fluid properties to be derived objectively from the matched composition without requiring subjective interpretation or association with known fluids from literature.
Solution Approach 2:
The patent replaces the manual, subjective process of associating fluid properties with known fluids from literature with an automated computational system. The system uses optimization algorithms and databases to automatically determine fluid composition and properties based on the measured API gravity and GOR, eliminating the need for human interpretation and association.
2Quantity of substance
If samples are obtained from well tests or drilling operations, then fluid samples are available for analysis, but samples arrive under different conditions and may be contaminated increasing measurement uncertainty
Solution Approach 1:
The patent performs preliminary characterization by measuring API gravity and GOR directly in the reservoir conditions before the fluid undergoes contamination or condition changes during sampling and transport. These preliminary measurements serve as the basis for deriving all other fluid properties, ensuring that the characterization is based on uncontaminated, in-situ measurements rather than post-sampling analysis.
Solution Approach 2:
The patent creates a virtual representation of the reservoir fluid composition that reproduces the measured API gravity and GOR values. This synthetic fluid model allows all other properties to be derived without needing physical samples, effectively replacing the contaminated physical samples with a clean, computationally-derived fluid representation.
3Reliability
If facilities are designed according to fluid properties, then proper flow conditions are ensured, but uncertain property predictions may lead to obstructed conduit flow
Solution Approach 1:
The patent employs an iterative optimization process that continuously refines the synthetic fluid composition to match the measured API gravity and GOR values. This feedback loop ensures that the derived fluid properties are consistently aligned with actual reservoir measurements, improving the reliability of facility design predictions and reducing the risk of conduit obstructions caused by inaccurate property assumptions.
Solution Approach 2:
The patent replaces uncertain, subjectively-derived fluid properties with objectively-calculated properties from the synthetic fluid model. This substitution provides more reliable and consistent fluid property predictions for facility design, reducing the uncertainty that could lead to conduit obstructions during production.
Data Source
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AI summary
The present invention is related to computer implemented method for characterizing a target fluid of a hydrocarbon reservoir under uncertainty providing a set of fluid properties from a limited amount of information.