Drilling System Risk Assessment via Probabilistic Modeling
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Solution Overview
Problem
The oil well drilling industry faces challenges in efficiently selecting and optimizing drilling systems due to unpredictable drilling conditions and high risks of failure, leading to increased costs and non-productive time, as existing methods rely heavily on past performance data and do not account for real-time variations in formation characteristics and system robustness.
Innovation Solution
A method is developed to assess the risk of drilling system failure by using a probabilistic model to determine the instantaneous and section-wise risk of triggering failure modes, defining critical control parameters, and identifying operating windows to optimize drilling system performance and reduce failure risks, allowing for real-time adjustments and selection of robust drilling configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If trial-and-error approach based on past performance data is used for drilling system selection, then system selection can be made using available historical data, but the reliability assessment does not account for real-time variations in formation characteristics and drilling conditions
Solution Approach 1:
The patent implements dynamic risk assessment by continuously updating failure probability calculations as drilling progresses through different formation sections. The system adapts to real-time variations in drilling conditions by recalculating risk parameters based on actual formation characteristics encountered, rather than relying solely on static historical data from offset locations.
Solution Approach 2:
The patent performs preliminary risk assessment before drilling operations begin by modeling expected formation characteristics and identifying high-risk sections in advance. This allows drilling systems to be selected and configured proactively to mitigate identified risks before encountering problematic formation zones, rather than reacting to failures after they occur.
2Productivity
If drilling is performed as quickly as possible with highest rate of penetration, then productivity is improved, but the risk of BHA failure increases leading to more frequent trips and fishing operations
Solution Approach 1:
The patent applies partial action by using aggressive drilling parameters (high ROP) in low-risk formation sections where the probability of BHA failure is minimal, while transitioning to more conservative parameters in high-risk sections identified by the probabilistic model. This allows maximizing productivity where safe and reducing risk where necessary.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor actual drilling performance and formation characteristics in real-time, comparing them against predicted parameters. When deviations indicate increased failure risk, the system provides feedback to adjust drilling parameters or alert operators to potential BHA issues before catastrophic failure occurs.
3Productivity
If BHA is changed frequently to optimize performance in different rock types, then drilling performance is optimized for each formation, but the number of trips out increases leading to higher costs and non-productive time
Solution Approach 1:
The patent segments the wellbore into distinct formation sections with characteristic rock types and failure risks. By identifying transition points between formation types in advance, the system allows planned BHA changes at optimal locations rather than reactive changes after failure, reducing unnecessary trips while maintaining performance optimization.
Solution Approach 2:
Instead of changing the physical BHA configuration frequently, the patent optimizes drilling performance by changing operational parameters (weight on bit, rotary speed, feed rate) based on the probabilistic risk model's recommendations for different formation sections. This maintains performance optimization while avoiding the time loss associated with physical BHA changes.
Data Source
AI summary
There is disclosed a method for assessing risk associated with drilling a section of a wellbore in a formation using a drilling system, including the steps of: providing a probabilistic model for the risk of the drilling system triggering a failure mode during drilling; and assessing the risk of the drilling system triggering one of the failure modes during drilling of the section based on the probabilistic model. A further such method includes the steps of defining the critical control parameters for the drilling system; and identifying one or more failure modes of the drilling system associated with each critical control parameter which may arise during drilling the section of the formation.