Autonomous Directional Drilling With Constraint-Based Trajectory Planning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing directional drilling methods lack consistency and efficiency, often relying on expert judgment and failing to leverage advanced technologies for autonomous decision-making and trajectory optimization, leading to potential risks and inefficiencies in reaching subsurface targets.
Innovation Solution
An autonomous directional drilling framework combines planning and execution with machine learning models and downhole intelligence to derive trajectory constraints, optimize paths, and provide real-time steering commands, leveraging tools like BHA and computational frameworks for improved accuracy and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional directional drilling methods relying on expert judgment are used, then operational flexibility is maintained, but consistency and efficiency deteriorate
Solution Approach 1:
The drilling system performs autonomous decision-making and trajectory optimization without continuous human intervention. The machine learning models and downhole intelligence automatically analyze data and generate steering commands, enabling the system to serve itself and achieve consistent, efficient drilling operations.
Solution Approach 2:
Traditional expert judgment and manual control are replaced with machine learning models and computational frameworks. The system uses algorithms to process downhole data and generate trajectory constraints, substituting human mechanical decision-making with automated computational processes that improve consistency and efficiency.
2Productivity
If advanced technologies for autonomous decision-making are implemented, then drilling efficiency is improved, but system complexity increases
Solution Approach 1:
The computational framework performs multiple functions including data acquisition, trajectory constraint derivation, path optimization, and steering command generation. By consolidating these functions into a single integrated system, the patent manages complexity while achieving improved drilling efficiency through autonomous operation.
Solution Approach 2:
The patent introduces a computational framework as an intermediary between downhole sensors and drilling control systems. This framework processes raw data, derives trajectory constraints, and generates steering commands, acting as a mediator that manages system complexity while enabling autonomous decision-making and improved efficiency.
3Measurement precision
If real-time trajectory optimization is performed, then accuracy of targeting is improved, but computational requirements and time consumption increase
Solution Approach 1:
The system derives trajectory constraints and optimizes paths in advance based on well plans and downhole data. By performing preliminary trajectory optimization and preparing steering commands before reaching critical sections, the system achieves accurate targeting without excessive computational delays during active drilling operations.
Solution Approach 2:
The system continuously monitors downhole conditions and compares actual trajectories against optimized paths. Real-time feedback from downhole sensors allows the system to adjust steering commands while maintaining accurate targeting, balancing computational requirements with the need for precise target location through iterative optimization.
Data Source
AI summary
A system and method that include receiving a well plan and determining a plurality of sections of the well plan and receiving data from surface and downhole to determine a current location of a drill bit. The system and method also include analyzing the well plan to automatically derive trajectory constraints that are associated with each of the plurality of sections of the well plan. The system and method additionally include determining a plurality of trajectory candidates that pertain to respective paths from the current location of a drill bit to respective targets included within each of the plurality of sections of the well plan based on a consideration of the trajectory constraints. The system and method further include determining a working plan that includes an optimal path from the current location of the drill bit to reach a final target based on the plurality of trajectory candidates.