Well Intervention Planning Using Predictive Success Models
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Solution Overview
Problem
Current well intervention planning systems require manual user input and expertise, leading to time-consuming and error-prone probability estimations of intervention success, which can result in increased failure risks and costs.
Innovation Solution
An automated well intervention planning system using a predictive model, such as a machine learning model, to predict the probability of success for intervention operations based on historical data and user inputs, generating optimized intervention plans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual planning is used, then user expertise and knowledge can be applied, but the process is time-consuming and error-prone
Solution Approach 1:
The patent replaces manual mechanical planning processes with an automated computer system that uses algorithms and data processing to generate intervention plans. The system automatically calculates probabilities of success, determines intervention sequences, and generates detailed operation plans without requiring manual computation, thereby reducing time consumption while maintaining reliability through systematic data-driven approaches
Solution Approach 2:
The system enables self-service by automatically generating intervention plans based on input well data and objectives. The computer system independently processes information, selects appropriate interventions, calculates success probabilities, and creates detailed operation plans without requiring continuous manual intervention or expert input for each decision point, thus reducing planning time while maintaining quality
2Reliability
If manual probability estimation is used, then user expertise is applied, but human error increases
Solution Approach 1:
The patent replaces manual probability estimation with automated computational algorithms that process well data, historical information, and intervention parameters to calculate success probabilities objectively. The system uses data processing and computational methods to determine probabilities without human intervention, eliminating human error while maintaining accuracy through systematic calculation based on input data and established models
Solution Approach 2:
The system incorporates feedback mechanisms by using historical well intervention data to validate and refine probability calculations. The computer system continuously references past performance data to adjust and verify its probability estimates, ensuring accuracy through data-driven feedback loops that compare predicted outcomes with actual results from historical interventions
3Productivity
If automated planning is used, then efficiency improves, but system complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the complex intervention planning process into distinct modular components: data input modules, intervention selection modules, probability calculation modules, and operation plan generation modules. Each module handles a specific aspect of planning independently, making the overall system more manageable and easier to implement while maintaining high automation efficiency
Solution Approach 2:
The system achieves universality by designing a multi-functional computer platform that can handle various planning scenarios, well types, and intervention methods through a single integrated software environment. The system adapts to different input data formats, well conditions, and intervention objectives using universal algorithms and data structures, reducing the need for multiple specialized systems while maintaining planning efficiency
Data Source
AI summary
Aspects of the disclosure provide for automated well intervention planning. An automated well intervention planning system includes one or more memories storing computer executable code. The system includes a user interface configured to receive inputs from a user, the input including at least one or more well intervention objectives and one or more well conditions. The system includes one or more processors configured to execute the computer executable code. The one or more processors are configured to search a database for one or more well intervention plans associated the one or more well intervention objectives and the one or more well conditions and generate a well intervention plan based on the one or more well intervention plans.