Monte Carlo Risk Transfer Model for Drilling NPT Assessment
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Solution Overview
Problem
The oil and gas industry faces challenges in accurately assessing and managing non-productive time (NPT) and well completion risk, which affects drilling operators' performance metrics and profitability, with existing methods lacking precision and reliability.
Innovation Solution
A risk transfer model (RTM) is developed to quantify NPT risk using Monte Carlo trials and field parameters, such as drilling time, location, and downhole tools, to generate a non-productive time distribution and output risk transfer model results, enabling more accurate risk assessment and insurance structure pricing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to assess NPT risk, then the assessment process is simple, but the precision and reliability of the assessment is insufficient
Solution Approach 1:
The patent transforms the risk assessment by changing from qualitative parameters to quantitative parameters. It introduces specific measurable parameters such as NPT distribution, mean NPT, standard deviation, and variance, allowing for precise numerical assessment of drilling risk rather than relying on vague qualitative evaluations.
Solution Approach 2:
The patent replaces traditional manual or heuristic risk assessment methods with a computational statistical model. It uses probability distributions, Monte Carlo simulations, and mathematical calculations to substitute for conventional expert judgment and experience-based assessment, thereby improving precision and reliability.
2Reliability
If more comprehensive parameters are used to assess NPT risk, then the reliability improves, but the complexity of the assessment process increases
Solution Approach 1:
The patent segments the complex risk assessment into distinct manageable components: it separates NPT calculation from BRT (Below Rotary Table) hours, divides the risk assessment into different scenarios (with and without insurance), and breaks down the statistical analysis into separate steps (distribution generation, mean calculation, variance calculation). This segmentation reduces the perceived complexity while maintaining comprehensive coverage.
Solution Approach 2:
The patent creates a universal risk assessment framework that can be applied to various drilling scenarios and well completion types. The model handles multiple parameters (NPT, BRT, total hours) and can accommodate different insurance structures, making it a multi-functional tool that improves reliability across diverse applications without requiring separate assessment methods for each case.
3Measurement precision
If quantitative analysis is performed to improve risk assessment accuracy, then the precision improves, but the time required for analysis increases
Solution Approach 1:
The patent performs preliminary calculations of NPT distribution, mean, and standard deviation before the actual risk assessment. By pre-computing these statistical parameters and storing them in the model, the system eliminates the need for time-consuming real-time calculations during the risk assessment process, thereby improving precision without proportionally increasing analysis time.
Data Source
AI summary
A method, apparatus and system is provided for assessing risk for well completion, comprising: obtaining, using an input interface, a Below Rotary Table hours and a plurality of well-field parameters for one or more planned runs, determining, using at least one processor, one or more non-productive time values that correspond to the one or more planned runs based upon the well-field parameters, developing, using at least one processor, a non-productive time distribution and a Below Rotary Table distribution via one or more Monte Carlo trials; and outputting, using a graphic display, a risk transfer model results based on a total BRT hours from the Below Rotary Table and the non-productive time distribution produced from the one or more Monte Carlo trials.