Automated Costing for Crude Distillation Unit Intermediate Products
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Solution Overview
Problem
Current oil and gas operating facilities face challenges in automated, integrated estimation of intermediate products, particularly in crude distillation units, due to disjointed computer systems and scattered data sources, leading to inefficiencies in data access, decision-making, and cost allocation.
Innovation Solution
A computer-implemented method that integrates field data from distillation column feed streams and maintenance history to perform mass and energy balances, determine reconciled data and thermodynamic properties, and generate key performance indicators (KPIs), enabling a decision support model for proactive and reactive data management and display in a user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If scattered discipline-specific applications are used for data management, then specialized training for each discipline is required, but users spend significant time fetching data from multiple sources
Solution Approach 1:
The patent merges scattered discipline-specific applications into a single integrated system that consolidates data from multiple sources (process control systems, maintenance management systems, enterprise resource planning systems) into a unified database, eliminating the need for users to access multiple separate applications and reducing data fetching time
2Measurement precision
If data are accessed by domain-specialized people with minimal collaboration, then specialized training is required, but different versions of truth with variance in data quality are created
Solution Approach 1:
The patent introduces an intermediary layer consisting of automated data reconciliation algorithms and validation rules that mediate between scattered data sources and users. This intermediary automatically resolves conflicts and ensures data quality consistency without requiring users to manually collaborate or understand complex data relationships
3Reliability
If disjoint processes are used for cost estimation, then data from multiple sources are required, but the decision-making process becomes slow and reactive
Solution Approach 1:
The patent implements continuous automated cost estimation that continuously integrates data from multiple sources and performs real-time calculations, replacing slow batch processing with continuous automated operations that provide up-to-date cost information without requiring manual intervention at each step
4Loss of information
If multiple scattered applications are used, then comprehensive data coverage is achieved, but rigid and static reports are generated
Solution Approach 1:
The patent transforms static report generation into a dynamic system that allows users to interactively explore cost data, filter by various criteria, and generate customized reports on-demand. The system maintains complete data from all sources while providing flexible, adaptive reporting capabilities that respond to user needs rather than delivering fixed predetermined reports
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances decision-making by providing real-time, accurate, and integrated data for resource allocation, improving cost estimation and operational efficiency in oil refineries, thereby maximizing profit margins and minimizing costs.
Implementation Method 1
Field data for distillation column feed streams and associated processes of a crude distillation unit
Implementation Method 2
Mass and energy balance around each distillation column is performed using the field data
Data Source
AI summary
Systems and methods include a computer-implemented method for intermediate crude oil distillation product estimates. Field data for distillation column feed streams and associated processes of a crude distillation unit of an oil refinery are received. Maintenance history events and estimates per event of each distillation column are received. Mass and energy balance around each distillation column are performed. Reconciled data and thermodynamic properties for each distillation column are determined. Key performance indicators (KPIs) for each distillation column are determined. A decision support model modeling activity-based information for the oil refinery is executed using the KPIs. Information regarding operation of the oil refinery at a current performance level is determined. Proactive and reactive data for distillation column estimate performance of each of the distillation columns are determined. The proactive/reactive data and KPIs for distillation column estimate performance of the distillation columns are provided for display in a user interface.