Gas Processing CO2 Monitoring With Predictive Solvent Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing gas processing plants face challenges in efficiently monitoring and reducing CO2 emissions due to variations in feed source compositions and flow rates, leading to excessive energy consumption and emissions from flaring and natural venting.
Innovation Solution
A system and method utilizing sensors to acquire quantitative data on gas stream characteristics, employing predictive analytics and a regression model to estimate emissions, and adjusting solvent circulation rates and operational parameters to minimize CO2 emissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-generated harmful factors
If solvent circulation rate is increased to reduce CO2 emissions, then CO2 emission reduction is improved, but energy consumption increases
Solution Approach 1:
The patent implements dynamic adjustment of solvent circulation rates based on real-time feed composition and flow rate measurements. The system continuously monitors gas stream characteristics and automatically modifies solvent circulation to match actual processing needs, replacing static high-circulation operation with adaptive variable circulation. This resolves the contradiction by using solvent circulation only at levels necessary for each specific operating condition.
Solution Approach 2:
The system changes operational parameters (solvent circulation rate, valve positions) based on measured feed characteristics such as CO2 content and flow rate. By adjusting these parameters dynamically rather than maintaining fixed high levels, the system achieves emission reduction without proportional energy increase. The regression model predicts optimal parameter settings based on real-time feed composition data.
2Object-generated harmful factors
If real-time monitoring and adjustment systems are implemented, then CO2 emission reduction is improved, but device complexity increases
Solution Approach 1:
The patent implements a feedback control system where sensors continuously measure feed composition and flow rate, the regression model predicts CO2 emissions and optimal solvent circulation rates, and the control system adjusts valve positions accordingly. This closed-loop feedback mechanism automatically reduces emissions without requiring complex manual intervention or overly sophisticated control algorithms, resolving the contradiction between emission reduction and system complexity.
Solution Approach 2:
The system performs self-adjustment based on automatic feed composition analysis and emission prediction. The regression model and control algorithms enable the system to autonomously determine optimal operating parameters without extensive external control infrastructure. This self-service capability reduces emissions while limiting the increase in device complexity to only what is necessary for automatic monitoring and adjustment.
3Use of energy by moving object
If solvent circulation is optimized based on feed characteristics, then energy efficiency is improved, but measurement and control precision requirements increase
Solution Approach 1:
The system performs preliminary measurement of feed composition and flow rate characteristics before making solvent circulation adjustments. By measuring feed characteristics in advance and using the regression model to predict optimal settings beforehand, the system can make accurate adjustments without requiring extremely high real-time measurement precision during the adjustment moment itself. This preliminary action approach reduces the stringency of continuous measurement precision requirements while maintaining energy efficiency.
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
Reduces overall CO2 emissions by optimizing solvent circulation and energy use in gas treating systems, providing real-time monitoring and prediction capabilities.
Implementation Method 1
a gas treating solvent system configured for treating the plurality of gas streams
Data Source
AI summary
Described is a method for monitoring and predicting CO2 emissions at a gas processing plant. Quantitative data related to one or more characteristics of a gas stream of feed sources at the gas processing plant is continuously acquired. A correlation between the characteristics and a measured CO2 emission for the gas processing plant is determined. Using a prediction regression model, an amount of total CO2 being emitted by the gas processing plant is predicted based on the quantitative data.