Feedstock Corrosion Prediction for Refinery Equipment Integrity
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Solution Overview
Problem
Refinery operators face challenges in accurately quantifying the corrosion effect of opportunity crudes and crude blends on processing equipment, leading to potential equipment damage and missed economic opportunities due to conservative selection practices.
Innovation Solution
A computer-implemented feedstock processing corrosion management system that uses assay data, processing information, and corrosion prediction to automate corrosion quantification and optimization, enabling the safe utilization of opportunity crudes and blended fractions by correlating corrosion rates with Total Acid Number (TAN) and Sulfur properties across various processing units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If operators use conservative selection practices to avoid corrosive feedstock, then equipment reliability is maintained, but productivity and profitability decrease due to missed economic opportunities
Solution Approach 1:
The patent replaces manual operator estimation with an automated computer-implemented corrosion prediction system that uses assay data, processing information, and corrosion models to calculate quantitative corrosion rates, eliminating reliance on subjective operator judgment and enabling more aggressive yet safe feedstock selection
Solution Approach 2:
The system incorporates feedback loops where corrosion predictions inform feedstock selection decisions, which are then validated against actual processing outcomes, allowing continuous refinement of corrosion models and progressively more accurate predictions that enable optimized productivity while maintaining reliability
2Ease of operation
If operators rely on manual estimation of corrosion effects, then decision-making is simple, but measurement precision deteriorates leading to inaccurate corrosion predictions
Solution Approach 1:
The system performs self-service by automatically gathering assay data, processing information, and corrosion model parameters, then calculating corrosion rates without requiring operator intervention in the complex computational processes, maintaining ease of operation while achieving high measurement precision through automated data-driven analysis
Solution Approach 2:
The patent introduces a computer-implemented corrosion prediction system as an intermediary between raw assay data and operator decision-making, translating complex chemical and processing parameters into quantitative corrosion rate predictions that are both precise and easily interpretable by operators
3Productivity
If operators process more diverse opportunity crudes to maximize profit, then productivity increases, but reliability decreases due to increased corrosion risk
Solution Approach 1:
The system enables dynamic adjustment of processing parameters based on predicted corrosion rates for different opportunity crudes, allowing operators to optimize feedstock selection and processing conditions to maximize productivity while maintaining reliability by staying within safe corrosion thresholds through quantitative parameter management
Data Source
AI summary
A computer implemented method includes obtaining, by the computer, assay data for a feedstock containing measurements for one or more aspects of the first feedstock, a first equipment model containing properties of processing units, and processing conditions containing one or more variables by which the first feedstock will be processed by the processing units. The computer determines a corrosion amount of the processing units using the processing conditions, the properties of the processing units contained in the equipment model, and the assay data for the feedstock, and stores/displays the corrosion amount of the processing units. A safety warning may be displayed, and the feedstock rejected if the corrosion amount exceeds a predetermined safety level for one or more of the processing units.