Enterprise Sustainability Action Plans From Continuous Performance Tracking
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Solution Overview
Problem
Challenges exist in efficiently tracking and improving sustainability parameters across hydrocarbon enterprise operations, including energy, carbon, waste, and water consumption, to achieve net zero carbon emissions and enhanced environmental sustainability.
Innovation Solution
A sustainability platform system that collects data from various sources, analyzes sustainability parameters, generates action plans, and continuously updates these plans based on real-time feedback to optimize operations and reduce environmental impact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual tracking methods are used for sustainability parameters, then implementation simplicity is maintained, but tracking efficiency and measurement precision deteriorate
Solution Approach 1:
The patent replaces manual tracking mechanisms with an automated computing system that collects, processes, and analyzes sustainability data from multiple sources. This substitution of mechanical/manual operations with computational systems directly improves tracking efficiency while the automated nature manages the complexity burden.
Solution Approach 2:
The system enables self-service by automatically collecting data from various sources, generating action plans, and updating sustainability reports without requiring manual intervention for each step. The computing system serves itself by autonomously processing data and generating insights, improving efficiency while the standardized processes manage complexity.
2Measurement precision
If comprehensive sustainability data collection is implemented across all enterprise operations, then measurement precision and reliability improve, but device complexity and use of energy increase
Solution Approach 1:
The patent segments the sustainability data collection system into distinct modules that collect specific parameters (energy, carbon, waste, water) from different enterprise operations. This segmentation allows comprehensive data collection while managing complexity through modular architecture, where each module handles a specific aspect independently.
Solution Approach 2:
The computing system is designed with multi-functionality, serving as a universal platform that collects, processes, analyzes, and reports sustainability data across all enterprise operations. This universal system improves measurement precision through centralized standardized processes while managing complexity through integrated design.
3Productivity
If traditional sustainability reporting methods are used, then ease of operation is maintained, but productivity and loss of time worsen
Solution Approach 1:
The patent implements continuous data collection and automated processing of sustainability parameters, eliminating interruptions and manual batch processing. The system continuously monitors enterprise operations, automatically updates sustainability reports, and generates action plans in real-time, significantly improving reporting productivity while reducing the time required through automated continuous operation.
Solution Approach 2:
The system performs preliminary actions by pre-collecting and pre-processing sustainability data from enterprise operations before formal reporting is needed. Action plans are generated in advance based on analyzed data, and the system is prepared to quickly produce updated reports when required, improving productivity while reducing last-minute reporting time.
4Productivity
If automated action plan generation is implemented, then productivity and measurement precision improve, but device complexity and ease of operation worsen
Solution Approach 1:
The patent implements feedback mechanisms where the computing system automatically analyzes sustainability data, generates action plans, implements them, and then measures their effectiveness. This closed-loop feedback system improves productivity by automating the entire cycle while the standardized feedback processes help manage system complexity through structured information flow.
Solution Approach 2:
The system replaces manual action plan development with automated computational analysis and generation. The computing system autonomously processes sustainability data, identifies improvement opportunities, and generates actionable plans, improving productivity while the algorithmic approaches manage the complexity of automation.
Data Source
AI summary
A method includes receiving an updated sustainability report associated with enterprise operations of an enterprise, such that the enterprise operations correspond to production data corresponding to operational tasks performed in a hydrocarbon production system, facility data corresponding to utility operations within buildings associated with the enterprise, or both. A computing system performing the method previously received a sustainability report associated with the enterprise operations. The method involves identifying at least one sustainability parameter change between the sustainability report and the updated sustainability report that is greater than at least one threshold, identifying engineering workflow systems to determine action plans associated with improving the at least one sustainability parameter, and sending the updated sustainability report to the one or more engineering workflow systems. The method may include sending commands to one or more devices associated with the one or more enterprise operations based on the action plans.