Well Trajectory Planning Optimization Model
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Solution Overview
Problem
Conventional well trajectory planning in oil and gas production is often manual, time-consuming, and lacks optimization, failing to adequately consider geologic, mechanical, and hydraulic constraints, as well as drilling environment uncertainty, leading to suboptimal well paths and increased costs.
Innovation Solution
A computer-based optimization model that integrates well trajectory planning with reservoir development planning, using a Markov decision process to generate optimal well trajectories and drilling operations plans, accounting for uncertain input data and adjusting parameters to minimize costs and maximize success probability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual well trajectory planning is used, then flexibility in decision-making is maintained, but the process becomes time-consuming and lacks optimization
Solution Approach 1:
The patent replaces manual mechanical planning processes with a computer-based optimization model that uses mathematical algorithms and decision analysis methods. The system substitutes human manual trajectory design with automated computational optimization that processes geologic, mechanical, and hydraulic constraints to generate optimal well paths, thereby reducing time consumption while maintaining decision quality through systematic analysis
Solution Approach 2:
The optimization model enables the system to self-generate well trajectories and drilling plans by automatically processing input data, evaluating constraints, and producing optimized solutions without requiring manual intervention at each step. The computer-based system serves itself by autonomously performing the planning functions that previously required human operators, thereby reducing time loss while preserving flexibility through programmable decision frameworks
2Device complexity
If conventional manual trajectory planning is used, then simplicity of the process is maintained, but optimization of well paths is insufficient
Solution Approach 1:
The patent segments the well trajectory planning process into distinct computational modules that handle different aspects independently: geologic constraint analysis, mechanical constraint analysis, hydraulic constraint analysis, and optimization algorithm execution. This segmentation allows the complex optimization task to be broken down into manageable components while achieving superior well path optimization compared to manual methods
Solution Approach 2:
The system dynamically adjusts trajectory parameters based on multiple constraints and objectives by using optimization algorithms that continuously evaluate and refine well path solutions. The planning process transitions from static manual design to dynamic computational optimization that adapts to varying constraints and produces optimized trajectories, thereby improving manufacturing precision without overwhelming complexity
3Ease of manufacture
If traditional well trajectory planning is used, then ease of implementation is maintained, but consideration of geologic, mechanical, and hydraulic constraints is inadequate
Solution Approach 1:
The patent merges multiple constraint considerations (geologic, mechanical, hydraulic) into a unified computer-based optimization model that simultaneously evaluates all constraints together. The system combines these previously separate planning concerns into an integrated framework that generates trajectories satisfying all constraints, thereby improving reliability without significantly increasing implementation difficulty through the use of standardized software tools
4Use of energy by moving object
If manual planning methods are used, then low computational requirements are maintained, but the probability of success is reduced
Solution Approach 1:
The patent replaces manual planning with computer-based optimization that uses computational algorithms to systematically evaluate trajectories and maximize probability of success. The system substitutes human judgment with computational analysis that processes multiple constraints and objectives, thereby improving reliability through more rigorous analysis while keeping computational requirements manageable through efficient algorithm design
Data Source
AI summary
A robust well trajectory planning and drilling or completion planning system that integrates well trajectory optimization and well development planning optimization so that optimized solutions are generated simultaneously. The optimization model can consider unknown parameters having uncertainties directly within the optimization model. The model can systematically address uncertain data and well trajectory, for example, comprehensively or even taking all uncertain data into account. Accordingly, the optimization model can provide flexible optimization solutions that remain feasible over an uncertainty space. Once the well trajectory and drilling or completion plan are optimized, final development plans may be generated. Additionally, the optimization model may generate and implement modified well development planning and modified well trajectory in real-time.