Coiled Tubing String Optimization for Mission-Driven Well Design
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Solution Overview
Problem
Conventional optimization techniques for coiled tubing string design are inadequate, relying on educated guesses with limited validation, and do not account for the evolving complexity of well environments and operational considerations, leading to a wide variety of non-standardized designs with inefficiencies.
Innovation Solution
An automated system utilizing a Mission Profile Generator and CT String Design and Optimization Tool to generate optimized coiled tubing string designs based on operational parameters, historical data, and predicted life cycle, incorporating factors like downhole conditions, wellbore geometry, and logistical constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional optimization techniques are used for coiled tubing string design, then design process is simple and quick, but design quality is poor and lacks validation
Solution Approach 1:
The patent replaces manual mechanical design processes with an automated computer-based optimization system. The system uses computational algorithms to automatically generate, evaluate, and optimize coiled tubing string designs based on multiple constraints and operational parameters, eliminating the need for manual trial-and-error design while improving design quality and consistency.
Solution Approach 2:
The optimization system performs self-validation and self-optimization by automatically evaluating design proposals against mission profiles, operational constraints, and performance criteria. The system iteratively adjusts design parameters without requiring external validation, generating optimal designs that satisfy all constraints while minimizing costs and maximizing performance.
2Stability of the object's composition
If standardized design processes are implemented, then design consistency is improved, but adaptability to unique well conditions decreases
Solution Approach 1:
The patent implements a dynamic optimization system that automatically adapts design parameters to match specific well conditions, mission profiles, and operational requirements. Rather than using static standardized designs, the system dynamically generates customized designs for each application while maintaining consistent design principles and validation processes, achieving both standardization and adaptability.
Solution Approach 2:
The system changes key design parameters such as tubing outer diameter, wall thickness, material grade, and length based on input mission profiles and well conditions. The optimization algorithm automatically adjusts these parameters to create customized designs that fit specific operational requirements while maintaining overall design consistency through standardized optimization methodology.
3Manufacturing precision
If multiple design options are explored manually, then design optimization is improved, but time consumption increases
Solution Approach 1:
The optimization system continuously iterates through design options, automatically evaluating each proposal against all constraints and objectives. The system maintains continuous improvement by repeatedly generating, evaluating, and refining design proposals until optimality is achieved, eliminating the need for manual iteration while reducing overall design time through automated continuous optimization.
Solution Approach 2:
The system incorporates feedback mechanisms where design evaluations and performance assessments automatically feed back into the optimization process. The system uses feedback from mission profile compliance, operational constraint satisfaction, and performance metrics to continuously refine design proposals, accelerating the optimization process compared to manual evaluation methods.
4Reliability
If detailed validation is performed for each design, then reliability is improved, but design complexity increases
Solution Approach 1:
The system performs preliminary validation by automatically checking design proposals against mission profiles and operational constraints before finalization. The optimization process includes built-in validation steps that pre-screen designs for compliance with all requirements, ensuring reliable designs are generated from the outset rather than requiring separate validation phases.
Solution Approach 2:
The optimization system integrates multiple validation functions into a single unified platform that simultaneously evaluates design compliance, operational feasibility, and performance optimization. This multi-functional approach consolidates what would otherwise be separate validation processes into one integrated system, improving reliability without proportionally increasing complexity.
Data Source
AI summary
Systems and methods presented herein are configured to optimize the design and validation of coiled tubing strings. For example, a processing workflow may include generating a mission profile for a coiled tubing (CT) string for deployment in a well based on CT analytics. The processing workflow may also include creating a CT string design for the CT string based at least in part on a plurality of operational parameters of the well. The CT string design of the CT string defines a plurality a physical characteristics of the CT string. The processing workflow may further include adjusting one or more of the plurality of physical characteristics of the CT string design of the CT string based at least in part on the generated mission profile for the CT string and a predicted life cycle of the CT string.