Drilling Trajectory Optimization for Real-Time Borehole Alignment
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Solution Overview
Problem
Current drilling trajectory control systems are subjective, non-time sensitive, and not optimized, leading to potential borehole collision hazards and inefficiencies due to latency in receiving downhole data.
Innovation Solution
A method and system for optimizing drilling trajectories by receiving user and system input parameters, determining corrections to align the actual borehole trajectory with the planned trajectory, optimizing these corrections using selected optimization parameters, and generating results for adjusting drilling operations in real-time or near real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If real-time or near real-time data processing is implemented, then drilling efficiency and trajectory accuracy are improved, but system complexity and computational requirements increase
Solution Approach 1:
The system segments the trajectory optimization process into distinct modules: data reception module, correction determination module, optimization module, and result generation module. Each module handles specific computational tasks independently, allowing real-time processing without overwhelming system complexity.
Solution Approach 2:
The system performs preliminary actions by pre-defining multiple optimization types (geometric, mechanical, drillability, hydraulic, productivity) and their associated parameters before actual drilling operations. This pre-programming enables rapid real-time optimization without complex on-the-fly calculations.
2Manufacturing precision
If multiple optimization types with range parameters are applied, then trajectory alignment accuracy is improved, but computational time and processing load increase
Solution Approach 1:
The system applies partial optimization by allowing users to select specific optimization types and apply them selectively based on drilling conditions. Not all five optimization types need to be applied simultaneously, reducing computational load while maintaining sufficient trajectory accuracy through targeted optimizations.
Solution Approach 2:
The system changes parameters by defining optimization range parameters for each optimization type, allowing dynamic adjustment of correction magnitudes. This enables efficient computational processing by constraining the search space for optimal corrections within predefined ranges.
3Reliability
If automated trajectory correction is implemented, then operational safety is improved, but system complexity and automation level increase
Solution Approach 1:
The system implements feedback by continuously receiving actual borehole trajectory data, comparing it with the planned trajectory, determining corrections, and generating updated drilling directions. This closed-loop feedback mechanism ensures operational safety through automated monitoring and correction without requiring excessive automation complexity.
4Measurement precision
If real-time data reception and processing is implemented, then trajectory tracking accuracy is improved, but data transmission requirements and system resource usage increase
Solution Approach 1:
The system extracts only the essential parameters needed for trajectory optimization from the full set of downhole sensor data. By selecting and processing only relevant parameters (position, orientation, drilling conditions) rather than all available data, the system achieves accurate trajectory tracking with reduced data transmission and processing resources.
Data Source
AI summary
Processes to receive user input parameters and system input parameters associated with a borehole undergoing active drilling operations to continually update drilling directions with wholistically applied optimizations to bring the actual borehole trajectory closer to the planned borehole trajectory. The processes can project ahead of the drilling assembly to determine the actual trajectory of the borehole and generate corrections to reduce the gap between the actual and planned trajectory paths. Various optimizations can be applied to the corrections to avoid overstressing systems or reducing the borehole productivity. Conflicts between optimizations can be resolved using a weighting or ranking system. More than one set of corrections can be determined and a user or a machine learning system can be used to select the one set of corrections to use as the results to be communicated and applied to the drilling operation plan or a borehole system, such as a geo-steering system.