Reservoir Fluid Model Value Assessment Using DFA Data
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Solution Overview
Problem
The existing methods for calculating the value of information from downhole fluid sampling and analysis in hydrocarbon-bearing reservoirs are flawed as they assume uncontested net present values, which may not always be valid, undermining the real value-adding potential of the data.
Innovation Solution
A method is developed that involves deriving and comparing fluid models from downhole and alternative fluid sampling methods using reservoir simulators to calculate net present values and optimize control variables, while accounting for uncertainty and risk aversion, to characterize the value of hydrocarbon-bearing reservoir fluid models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If downhole fluid sampling and analysis operations are used to derive fluid models, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent introduces a value assessment system that acts as an intermediary between the complex downhole sampling operations and the decision-making process. This system calculates value metrics based on fluid model comparisons, providing a simplified quantitative framework that bridges the gap between complex data collection and practical decision-making without requiring direct intervention in the sampling operations themselves
2Reliability
If multiple fluid models are compared using reservoir simulation, then reliability of value assessment is improved, but loss of time increases
Solution Approach 1:
The patent performs preliminary comparisons between multiple fluid models through reservoir simulation before final decision-making. By conducting these simulations in advance and establishing baseline value metrics, the system prepares reliable assessment data beforehand, reducing the time required for final decisions while maintaining assessment reliability through pre-established model comparisons
3Loss of information
If net present value calculations are performed for multiple scenarios, then information completeness is improved, but device complexity increases
Solution Approach 1:
The patent segments the value assessment process into distinct computational modules: fluid model generation from sampling data, reservoir simulation execution, net present value calculation for each scenario, and comparative value metric computation. This modular segmentation allows the complex multi-scenario analysis to be broken down into manageable, independent calculation stages that can be processed systematically
Data Source
AI summary
A method for deriving VOI for a hydrocarbon-bearing reservoir fluid model based on DFA data (“true fluid model”) versus an “incorrect fluid model” includes calculating first, second and third objective functions that are based on NPV(s) of simulated production by a reservoir simulator with different configurations. For the first objective function, the simulator is configured with the incorrect fluid model and control variables that are optimized to derive a first group of control variable values. For the second objective function, the simulator is configured with the true fluid model and the first group of control variable values. For the third objective function, the simulator is configured with the true fluid model and control variables that are optimized to identify a second group of control variable values. The objective functions can be deterministic, or can include statistics that account for uncertainty. A visualization of such results with uncertainty is also described.