Hydrotreatment Reactor Pressure-Loss Warning Using ARIMA
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Solution Overview
Problem
Hydrotreatment units in refineries face unpredictable and exponential pressure loss due to bed clogging, leading to unscheduled shutdowns and significant financial losses, as existing methods either reduce production capacity or require lengthy catalyst removal procedures, without effectively preventing the issue.
Innovation Solution
A method using the ARIMA time series model to predict pressure loss in hydrotreatment reactors by analyzing exogenous variables like H2 consumption, coke flow, and gas flow, combined with a Shewhart control chart to issue alerts, allowing for early detection and prevention of operational failures before they occur.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If production capacity is reduced to operate longer, then the unit can avoid shutdown, but financial loss increases due to reduced processing capacity
Solution Approach 1:
The patent applies preliminary action by using the ARIMA time series model to predict pressure loss trends and issue early warnings before bed clogging becomes critical. This allows operators to schedule maintenance proactively rather than reactively, and to adjust operating parameters in advance to extend campaign life without immediately reducing production capacity.
2Reliability
If catalyst layer is removed to solve pressure loss, then the problem is addressed, but unit shutdown time increases causing financial loss
Solution Approach 1:
The patent enables preliminary action by predicting pressure loss trends and issuing early warnings before bed clogging reaches critical levels. This allows operators to schedule catalyst removal during planned shutdowns rather than emergency stoppages, reducing unplanned downtime and allowing for more efficient maintenance scheduling.
Solution Approach 2:
The patent implements feedback through continuous monitoring of pressure loss and comparison with ARIMA model predictions. When actual pressure loss deviates from predicted values, the system generates alerts that trigger investigative actions, enabling early detection of abnormal clogging patterns and timely intervention to prevent catastrophic failures.
3Reliability
If filters and catalyst gradient are used, then bed clogging is prevented, but the problem still occurs eventually
Solution Approach 1:
The patent implements feedback through continuous monitoring of pressure loss and comparison with ARIMA model predictions. When actual pressure loss deviates from predicted values, the system generates alerts that trigger investigative actions, enabling early detection of abnormal clogging patterns and timely intervention to extend campaign life beyond what standard filters and catalyst gradients achieve alone.
Data Source
AI summary
The present invention relates to a method for detecting and warning of operational failures. The methodology was developed for hydrotreatment units and more specifically for monitoring pressure loss in hydrotreatment reactors, but it can be applied to any process that benefits from plant monitoring, especially in cases where the evolution of the undesirable event cannot be mapped by known equations. Adaptations for using in other process plants can be carried out by any specialist in that area, it is only necessary to map the variables that must be observed and define the monitoring needs in terms of acquisition interval, as well as the alarm settings that will depend on the dynamics of the process itself.