Predictive Well Flow Control for Lower CO2 Gas Production
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Solution Overview
Problem
Existing methods for reducing carbon dioxide (CO2) production in oil and gas well operations are inefficient and costly, whether through environmental release or underground sequestration, necessitating a more effective approach.
Innovation Solution
A predictive model trained on historical data from wells and processing plants is used to optimize flow rates of oil and gas wells to minimize CO2 production, considering factors like condensate and ethane-plus production, with control signals adjusting valve operations to achieve desired CO2 reduction levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If CO2 is released to the environment, then operational simplicity is maintained, but environmental harm increases
Solution Approach 1:
The system changes operational parameters by using a predictive model to determine optimized flowrates for each well. The model processes input data including gas flowrate data and CO2 concentration data to predict flowrate adjustments that reduce overall CO2 production while maintaining operational control through automated valve adjustments.
2Object-generated harmful factors
If CO2 sequestration is implemented, then environmental harm is reduced, but device complexity and operational cost increase
Solution Approach 1:
The system replaces complex mechanical sequestration machinery with a computational approach. A predictive model using algorithms (such as reduced gradient or linear regression) processes data and generates control signals that adjust existing valve mechanisms, eliminating the need for specialized sequestration equipment while achieving CO2 reduction.
Solution Approach 2:
The system enables the gas operation network to self-regulate CO2 production by using the predictive model to automatically determine optimal flowrate adjustments. The model processes operational data and generates control signals that autonomously adjust well flowrates, allowing the network to manage its own CO2 output without external intervention or complex additional infrastructure.
3Object-generated harmful factors
If well flowrates are reduced to decrease CO2 production, then CO2 levels decrease, but condensate production may also decrease
Solution Approach 1:
The system applies local quality by determining individualized flowrate adjustments for each well based on its specific characteristics and CO2 contribution. The predictive model processes data for each well separately and generates customized control signals, allowing selective adjustment of flowrates to minimize CO2 while preserving condensate production from wells where it is economically viable.
Data Source
AI summary
This specification relates to reducing CO2 levels of a gas operation network using a predictive model. The systems and methods described in this specification process an input data set that includes (i) gas flowrate data and (ii) CO2 concentration data. The systems and methods generate the predictive model by processing the input dataset. The systems and methods predict, by the predictive model, a CO2 production target for the gas operation network based on a gas flowrate predicted for each of the plurality of wells by the predictive model. The systems and methods generate control signals to control a respective valve at each well based on the CO2 production target and the predicted gas flowrate for each well. The systems and methods regulate CO2 levels of the gas operation network based on the CO2 production target by controlling the respective valves at each well.