Dynamic Well Test Priority Index for Hydrocarbon Flow Attribution
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Solution Overview
Problem
Current well testing methods often rely on single-day measurements that may not accurately represent hydrocarbon well performance over extended periods, leading to delayed detection of changes in hydrocarbon flow, as wells are tested sequentially based on time since the last test, rather than on actual production or operational parameters.
Innovation Solution
A computer-implemented system that selects hydrocarbon wells for testing based on a combination of time since the last well test, production parameters, and other indicators, using a well test priority index that considers factors like production loss, water cut changes, and shut-in measurements to optimize the allocation of testing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If wells are tested sequentially based on time since the last test, then all wells are tested systematically, but wells with significant production changes are not detected promptly
Solution Approach 1:
The system changes the selection parameter from purely time-based to a composite index incorporating multiple production parameters (water cut, gas-oil ratio, production rate, pressure) that dynamically reflect well performance changes, enabling timely detection of significant production variations
Solution Approach 2:
The system continuously monitors production parameters and uses this feedback to dynamically adjust well testing priorities, ensuring that wells with significant changes are detected promptly while maintaining systematic coverage of all wells
2Reliability
If all wells are tested frequently, then accurate flow attribution is achieved, but testing resources are wasted on wells with stable performance
Solution Approach 1:
The system applies different testing frequencies to different wells based on their individual production characteristics and stability, with high-priority wells tested more frequently and stable wells tested less frequently, optimizing resource allocation while maintaining overall accuracy
Solution Approach 2:
The well test priority index dynamically adjusts testing priorities based on changes in production parameters, allowing the system to concentrate resources on wells experiencing significant changes while reducing testing frequency for stable wells
3Ease of operation
If a rotating schedule is used for well testing, then testing is simplified and systematic, but it cannot adapt to changing production conditions
Solution Approach 1:
The system transitions from a static rotating schedule to a dynamic priority-based selection system that automatically adapts to changing production conditions while maintaining systematic coverage, balancing operational simplicity with adaptability
Solution Approach 2:
The system uses real-time production parameter feedback to dynamically adjust well testing priorities, enabling automatic adaptation to changing conditions while preserving the systematic and simplified nature of automated schedule generation
Data Source
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AI summary
Selecting hydrocarbon wells for well testing. The selecting may include identifying hydrocarbon wells whose last well test took place prior to a predetermined date; identifying hydrocarbon wells with a parameter that exceeds a predetermined threshold; and selecting a predetermined number of hydrocarbon wells from the wells identified.