Mud Circulation Control Under Drilling Uncertainty
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Solution Overview
Problem
Mud circulation systems in wellbore drilling operations face uncertainties such as sensing, actuator, model, and physical disturbances, leading to deviations from nominal system performance and potential instability.
Innovation Solution
A stochastic control method that adaptively updates steady-state/dynamic mud circulation models and controller designs to account for uncertainties, using a primary controller with Randomized Algorithm (RA) or Stochastic Model Predictive Control (SMPC), and a secondary controller to reprogram the primary controller when deviations occur, ensuring the mud circulation system operates within desired tolerance ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If steady state or dynamic models are used to control the mud circulation system, then the system can operate with a basic control framework, but the system performance deviates from expected performance due to uncertainties in the drilling environment and process
Solution Approach 1:
The patent transforms static steady-state or dynamic models into adaptive stochastic models that dynamically adjust to uncertainties. The controller continuously updates model parameters based on real-time measurements and uncertainty characterizations, enabling the system to adapt to changing drilling conditions while maintaining reliable control performance
Solution Approach 2:
The patent modifies the control approach by changing from fixed model parameters to stochastic parameters that account for uncertainties. The controller incorporates probability distributions and uncertainty bounds into model parameters, allowing the system to handle variations in drilling environment and process while maintaining expected performance
2Device complexity
If traditional control methods are used, then the controller structure remains simple, but the system cannot account for sensing, actuator, model, and physical disturbance uncertainties
Solution Approach 1:
The patent implements a feedback mechanism where the controller continuously monitors system performance, compares actual behavior with predicted behavior from stochastic models, and adjusts control actions based on the deviations. This feedback loop accounts for sensing uncertainties, actuator uncertainties, model uncertainties, and physical disturbances, maintaining system stability without requiring overly complex controller architecture
Solution Approach 2:
The patent introduces stochastic model parameters as intermediaries between the controller and the uncertain drilling environment. These intermediate parameters absorb and characterize uncertainties, allowing the controller to work with simplified models while still accounting for complex real-world variations through probability distributions and uncertainty bounds
Data Source
AI summary
A stochastic control method includes determining a property of a solid present in a drilling fluid circulating within a mud circulation system and identifying a mud circulation model that dictates operation of the mud circulation system. The mud circulation model is based on one or more models of one or more uncertainties encountered during a wellbore drilling operation. The method further includes determining an accuracy of the mud circulation model based on a difference between the determined property of the solid present in the drilling fluid and a solid property of the drilling fluid as provided by the mud circulation model, and programming a controller of the mud circulation system based on the mud circulation model to modify operation of the mud circulation system.