Multilevel Smart Well Control Under Field Production Constraints
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Solution Overview
Problem
Existing reservoir dynamic simulators lack sufficient modeling capabilities and flexibility to directly control and optimize inflow control valve (ICV) devices in response to global field or group targets and constraints in intelligent oil and gas fields.
Innovation Solution
A computer-implemented method is introduced that applies choke settings and rig control settings to groups of wells, defining rule counts and frequencies for simulation runs, allowing for multilevel optimization of ICVs to honor field targets and constraints, enabling direct control of ICV devices in intelligent completion systems and optimizing production forecasts and development plans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing reservoir dynamic simulators are used, then simulation capability is maintained, but control and optimization of ICV devices in response to global field targets and constraints is insufficient
Solution Approach 1:
The patent segments the control system into multiple hierarchical levels: field-level controls, group controls, and well-level controls. This segmentation allows the simulator to handle complex field targets and constraints by breaking them down into manageable control units at different organizational levels, enabling direct control of ICV devices while maintaining overall system capability.
Solution Approach 2:
The patent introduces a new dimensional framework by implementing multilevel controls with hierarchical structure (field → group → well levels). This dimensional change transforms the traditional single-level simulation approach into a multi-dimensional control architecture, allowing simultaneous optimization across multiple scales and directly addressing global field targets.
2Productivity
If multilevel optimization techniques are applied, then production results greater than predefined thresholds are achieved, but system complexity increases
Solution Approach 1:
The patent implements dynamic control rules that automatically adjust ICV settings based on real-time field conditions and constraints. The system dynamically optimizes production by applying rig control settings with configurable rule counts and frequencies, allowing the control system to adapt to changing conditions without requiring manual intervention, thus achieving high productivity despite increased initial system complexity.
Solution Approach 2:
The patent incorporates feedback mechanisms where simulation results inform subsequent control adjustments. The system monitors production results against predefined thresholds and automatically adjusts ICV settings through iterative optimization cycles, enabling the complex multilevel system to self-regulate and maintain high productivity without proportional increases in operational complexity.
3Extent of automation
If rig control settings with rule counts and frequencies are implemented, then ICV devices are directly controlled, but computational requirements increase
Solution Approach 1:
The patent implements periodic control actions through rig control settings that specify rule frequencies for ICV adjustments. Instead of continuous computation, the system applies control rules at defined frequency intervals, reducing computational power requirements while maintaining effective direct control of ICV devices. This periodic approach allows automation without proportional increases in computational burden.
Solution Approach 2:
The patent applies preliminary action by pre-configuring rig control settings, rule counts, and frequency parameters before simulation execution. This allows the system to establish control strategies in advance, reducing the need for complex real-time computations during simulation runs while still achieving direct control of ICV devices through pre-planned optimization sequences.
Data Source
AI summary
Systems and methods include a computer-implemented method for performing an advanced control policy for a group of wells. Choke settings are applied to one or more control elements of each well in a group of wells. Rig control settings are applied to the group of wells. The rig control settings define, for each rule in a set of rules: a rule count limiting a number of times a rule is to be executed in a simulation run and a rule frequency identifying a time frequency by which the rule is to be executed during the simulation run. Settings are received for targets and constraints for the group of wells. The simulation run is executed for the group of wells using the choking settings, the rig control settings, and the settings for of the targets and constraints for the group of wells.