Inverse Model Managed Pressure Drilling Control
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Solution Overview
Problem
Managed pressure drilling (MPD) operations face challenges in accurately controlling bottomhole pressure due to the limitations of backpressure pumps, which require significant capital investment, occupy scarce space, and interfere with normal drilling rig operations.
Innovation Solution
The implementation of an inverse model in conjunction with a hydraulic model, utilizing real-time measurements and a nonlinear optimization algorithm to determine a wellhead pressure set point, which refines model parameters through random sampling and probability distributions, allowing for precise control of bottomhole pressure without the need for a backpressure pump.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a backpressure pump is used to control bottomhole pressure, then pressure control capability is improved, but device complexity and capital investment increase
Solution Approach 1:
The patent extracts the backpressure pump from the system and replaces it with a hydraulic model-based control method using choke manifold and flow control valves. This eliminates the need for complex equipment while maintaining pressure control capability through computational modeling and algorithmic prediction of bottomhole pressure based on surface measurements.
Solution Approach 2:
The patent replaces the mechanical backpressure pump system with a computational hydraulic model that uses nonlinear optimization algorithms and random sampling techniques to predict and control bottomhole pressure. This substitutes mechanical pressure application with intelligent software-based pressure management.
2Reliability
If a backpressure pump is installed, then pressure regulation is improved, but space requirements and operational interference increase
Solution Approach 1:
The patent removes the backpressure pump from the drilling rig configuration and replaces it with a virtual model running on existing rig computers. This eliminates the need for additional physical space while maintaining pressure regulation through hydraulic modeling and real-time data processing.
3Speed
If traditional hydraulic modeling is used, then computational speed is improved, but measurement accuracy and model reliability deteriorate
Solution Approach 1:
The patent performs preliminary random sampling of model parameters around their mean values before running the main hydraulic model. This pre-computation of parameter distributions and their propagation through the model improves both speed and accuracy by pre-characterizing the uncertainty ranges and using them to refine predictions in real-time.
Solution Approach 2:
The patent implements feedback loops where model predictions are continuously compared with actual measurements, and the discrepancies are used to update model parameters through the random sampling and optimization algorithms. This closed-loop feedback improves measurement precision while maintaining computational efficiency through iterative refinement.
Data Source
AI summary
A managed pressure drilling (MPD) operation may use an inverse model in conjunction with a hydraulic model and real-time drilling conditions and parameters as inputs to determine a wellhead pressure set point corresponding to a desired bottomhole pressure. For example, while drilling a wellbore penetrating a subterranean formation with a drilling system, measured data including a wellhead pressure may be acquired. A model may then be executed that applies a hydraulic model to an a priori model estimate vector to produce predicted data; converts the measured data to a measured data vector; applies a randomized maximum likelihood algorithm to the a priori model estimate vector, the predicted data, and the measured data vector to produce an a posterioiri model estimates; and applies the hydraulic model to the a posterioiri model estimates to produce an a posteriori prediction and a calculated wellhead pressure set point corresponding to a desired bottomhole pressure.