Characteristic-Vector Tracking for Transparent Gas Supply Chains
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Solution Overview
Problem
The oil and gas supply-chain faces challenges in tracking commodities due to gaps in visibility across the supply-chain, leading to issues in maintaining transparency and integrity, particularly with digital commodities like sensor data and emission reporting.
Innovation Solution
Implementing a supply-chain characteristic-vectors system that includes air quality monitors and supervisory-control-and-data-acquisition systems at upstream and downstream amenities to sense environmental and operational parameters, transmit data to a remote server, and calculate characteristic-vectors associated with energy amounts, ensuring the tracking and verification of energy transactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional supply-chain tracking methods are used, then implementation cost is low, but visibility and transparency across the supply-chain deteriorates
Solution Approach 1:
The system segments supply-chain monitoring into distributed sensor nodes deployed at different locations (upstream, midstream, downstream). Each sensor independently measures specific parameters (temperature, pressure, composition) and transmits data to a centralized platform, enabling comprehensive visibility without requiring a monolithic complex system
Solution Approach 2:
A centralized data processing platform acts as an intermediary between distributed sensors and decision-makers. This platform aggregates, analyzes, and visualizes data from multiple sensor sources, transforming raw sensor readings into actionable supply-chain intelligence while maintaining system modularity
2Reliability
If comprehensive sensor deployment is implemented, then transparency and integrity are improved, but system complexity increases
Solution Approach 1:
The system employs universal sensor modules that can be deployed across multiple supply-chain stages (upstream, midstream, downstream) with identical hardware configurations. Each sensor unit performs multiple measurement functions (temperature, pressure, gas composition) simultaneously, ensuring consistent data quality and simplifying system deployment while maintaining integrity across the entire supply-chain
Solution Approach 2:
The system monitors changes in physical parameters (temperature, pressure, compositional ratios) to detect supply-chain anomalies. By establishing baseline parameter ranges and alerting on deviations, the system maintains high reliability through simple threshold-based detection rather than complex analytical models
3Measurement precision
If characteristic-vectors are calculated and tracked, then commodity tracking precision is improved, but data processing complexity increases
Solution Approach 1:
The system transforms raw sensor data into characteristic-vectors by calculating compositional ratios (e.g., C1/C2, C3/C4) and energy content metrics. These derived parameters provide precise commodity identification and tracking while using simple mathematical transformations rather than complex machine learning models, maintaining tractable data processing
Data Source
AI summary
In some configurations, a supply-chain characteristic-vectors merchandising system and a method for an environmental characteristic-vectors of a gas communicating from an upstream amenity to a downstream amenity in a supply-chain may be disclosed. The system may be configured to track oil and/or gas throughout the supply-chain by associating characteristic-vectors (e.g., environmental, operational, physical etc.) of the upstream amenity and the downstream amenity with the energy units of the gas transmitted through the supply-chain.