Tubular Running Torque-and-Drag Modelling for Downhole Load Estimation
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Solution Overview
Problem
Challenges in managing and optimizing tubular running operations in deviated wells due to complex forces and frictional impediments, leading to potential component damage without direct downhole load measurements.
Innovation Solution
A system comprising sensors, processors, and displays for real-time torque-and-drag analysis (TDA) to estimate downhole loads and provide damage indicators, enabling corrective actions to maintain acceptable stress levels and optimize tubular running duration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If real-time measurements and modelling are used to optimize tubular running operations, then productivity and operational efficiency are improved, but device complexity increases due to the need for sensors, processors, and real-time data systems
Solution Approach 1:
The system integrates multiple functions into a unified platform that combines real-time measurements, torque-and-drag analysis, load monitoring, and optimization algorithms. The processors perform multiple tasks including data acquisition, numerical modeling, friction factor estimation, and predictive analytics, allowing a single system to address various aspects of tubular running operations simultaneously.
Solution Approach 2:
The system introduces an intermediary computational layer that processes sensor data and translates it into actionable insights through numerical models. The processors act as intermediaries between the physical tubular running operations and the control decisions, using algorithms to estimate downhole loads, predict component damage, and optimize running parameters without requiring direct downhole measurements.
2Measurement precision
If downhole loads are directly measured, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The system replaces direct mechanical downhole load measurement devices with a computational approach using torque-and-drag analysis. Instead of installing complex sensors in the wellbore, the system uses surface measurements combined with numerical models to calculate downhole loads, substituting a mechanical measurement system with a field-based computational system.
Solution Approach 2:
The system creates a virtual model of the tubular string and wellbore environment that replicates the physical conditions. By running numerical simulations that mirror the actual tubular running process, the system estimates downhole loads without requiring physical sensors at depth, effectively copying the physical system in a computational environment.
3Productivity
If tubular running speed is increased to reduce operation duration, then productivity is improved, but the risk of component damage from excessive stresses and strains increases
Solution Approach 1:
The system continuously monitors tubular running operations in real-time and provides feedback on downhole loads and component stress levels. Based on this feedback, the system dynamically adjusts running parameters such as speed, weight on bit, and rotation rate to optimize productivity while maintaining component safety, allowing accelerated running when conditions permit and slowing down when risk increases.
Solution Approach 2:
The system transitions from static, pre-planned running procedures to dynamic, real-time optimization. The numerical models continuously update load predictions as the tubular string advances through the wellbore, allowing the running parameters to be dynamically adjusted based on actual downhole conditions, component characteristics, and changing stress states throughout the operation.
Data Source
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AI summary
A system for optimizing a tubular running operation (TRO) in which a running string is disposed in a wellbore includes sensors located at the wellsite, plus one or more processors, displays, and user-input devices, which may be at the wellsite or elsewhere. The sensors are configured to measure running string parameters including the running string's position within the well, the running and rotation rates, and loads acting at the top of the running string. Based on this information, the processor(s) perform torque-and-drag analysis (TDA) in the top-down direction to estimate downhole loads on user-selected running string components, accounting for measurement and modelling uncertainties. Based on the estimated loads, the processor(s) calculate one or more damage indicators, which are communicated to the user via the display(s), enabling the user to take corrective action to prevent or manage damage to the running string.