Reservoir Valuation Using Incomplete Data and Analogous Selection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The valuation of new hydrocarbon reservoirs is hindered by missing parameters, leading to inaccurate estimates and potential misvaluation, as existing methods rely heavily on expert judgment and similarity functions without comprehensive data for analogous reservoir selection.
Innovation Solution
A system and method that automatically supplements incomplete descriptions of new reservoirs with estimated missing parameters and associated uncertainties, using cataloged characteristics of existing reservoirs to select an optimum subset of analogous reservoirs for valuation, employing pre-processing, parameter extraction, and machine learning techniques to enhance data completeness and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If expert judgment and similarity functions are used for reservoir valuation, then the valuation process can be performed with limited data, but the accuracy and reliability of the valuation deteriorates due to missing parameters
Solution Approach 1:
The system performs preliminary actions by automatically supplying missing reservoir parameters before the valuation process. The parameter supply mechanism pre-fills incomplete reservoir descriptions with estimated values, enabling the subsequent similarity function and expert judgment to operate on more complete data, thereby improving valuation accuracy without increasing operational complexity
Solution Approach 2:
The patent introduces an intermediary component - the automatic parameter supply system with uncertainty characterization - that bridges the gap between incomplete reservoir data and the valuation process. This intermediary supplies estimated parameters with associated uncertainty values, allowing the valuation to proceed with improved accuracy while maintaining ease of operation through automated intervention
2Measurement precision
If more parameters are collected for new reservoirs, then the valuation accuracy improves, but the complexity and time required for data collection increases
Solution Approach 1:
The system implements self-service by enabling new reservoirs to automatically supply their own missing parameters through the parameter supply mechanism. Instead of requiring external experts to manually collect and estimate parameters, the system uses the reservoir's existing data combined with similarity comparisons to automatically generate missing parameter values, reducing both complexity and time requirements
Solution Approach 2:
The patent replaces the manual mechanical process of expert parameter collection with an automated computational system. The similarity function and parameter supply mechanism automatically calculate and fill missing parameters based on mathematical comparisons with known reservoirs, substituting human expert labor with algorithmic processing that reduces complexity while improving accuracy
3Productivity
If incomplete reservoir descriptions are used for selecting analogous reservoirs, then the selection process is faster, but the reliability of analogous reservoir selection deteriorates
Solution Approach 1:
The system performs preliminary parameter supplementation before the analogous reservoir selection process. By automatically supplying missing parameters and characterizing their uncertainties in advance, the system ensures that the similarity function operates on more complete data, improving selection reliability without significantly impacting the overall process speed due to the automated nature of the parameter supply
Solution Approach 2:
The uncertainty characterization provides feedback to the selection process, allowing the system to weigh parameter comparisons based on their reliability. The similarity function can adjust its calculations based on uncertainty values, improving the reliability of analogous reservoir selection by accounting for data quality variations while maintaining efficient processing through automated feedback loops
Data Source
AI summary
A population comparison system, method and a computer program product. A stored list of population members, e.g., hydrocarbon reservoirs, includes parameters for corresponding known characteristics and analogous members for each member. A new population member input receives new member descriptions including parameters for each respective new member. A parameter extraction system automatically extracts an estimated value for each missing key parameter, providing a supplemented description. An analogous member selector automatically selects a subset of listed population members as analogous members for each new population member responsive to the supplemented description. The analogous members serve as a basis for uncertainty characterization from the joint parameter distribution and univariate distributions for each parameter.