Probabilistic Drilling Path Adjustment Using Real-Time Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The challenge in subterranean drilling is the speculative nature of drill path trajectories between geological layers, which requires frequent updates based on new information, often leading to inaccurate modifications due to sparse or incorrect data, and assumes geological conformity that may not always be present.
Innovation Solution
A probabilistic approach using an earth model grid with cells/nodes containing various properties and a probability of success parameter to modify the drill path in real-time, allowing for optimal positioning within a target zone without assuming geological conformity, by updating the model with new data and adjusting the drill path based on real-time information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If frequent updates of drill path are made based on new information, then adaptability to geological variations is improved, but accuracy of path modification deteriorates due to sparse or incorrect data
Solution Approach 1:
The system performs preliminary actions by creating multiple probabilistic realizations of the geological model before drilling begins. These realizations represent different possible geological scenarios with assigned probabilities. During drilling, as new data becomes available, the system updates only the relevant portions of the model rather than completely re-evaluating all parameters, thereby maintaining accuracy while adapting to new information.
Solution Approach 2:
The system changes parameters by transitioning from deterministic single-value geological models to probabilistic multi-realization models. Each realization contains different geological property values (porosity, permeability, brittleness) with associated probabilities. This parameter transformation allows the system to quantify uncertainty and make more robust decisions about drill path adjustments despite data sparsity.
2Device complexity
If deterministic earth models are used for drill path planning, then computational simplicity is maintained, but reliability of drilling decisions deteriorates due to inability to handle uncertainty
Solution Approach 1:
The system segments the geological model into multiple discrete realizations, where each realization represents a possible geological scenario. Instead of attempting to model all uncertainties in a single deterministic framework (which would be computationally intractable), the system divides the problem into manageable segments (individual realizations) that can be evaluated separately and combined through probability weighting.
Solution Approach 2:
The system introduces probabilistic realizations as an intermediary between the deterministic drill path planning system and the uncertain geological reality. Rather than directly processing uncertain geological data, the system first transforms it into a set of probabilistic realizations, which then serve as the basis for deterministic path optimization. This intermediary layer enables reliable decision-making under uncertainty while maintaining computational tractability.
3Productivity
If speculative drill path trajectories are used between geological layers, then initial drilling can begin, but risk of incorrect trajectories increases leading to operational delays and cost overruns
Solution Approach 1:
The system performs preliminary probabilistic modeling and risk assessment before drilling begins. Multiple realizations of the geological model are created and evaluated in advance, allowing the system to identify high-risk trajectory segments before actual drilling occurs. This preliminary analysis enables operators to plan alternative paths or prepare contingency measures, reducing the likelihood of costly delays while maintaining aggressive drilling schedules.
Solution Approach 2:
The system implements continuous feedback by comparing actual drilling data against the probabilistic realizations in real-time. As the drill encounters actual geological conditions, the system updates the relevant realizations and re-evaluates the optimal path. This feedback loop allows the system to correct speculative trajectories early when changes are still feasible, minimizing operational delays and cost overruns while maintaining high drilling productivity.
Data Source
AI summary
The disclosed embodiments include a method, apparatus, and computer program product configured to provide a probabilistic approach for real time drilling. In particular, the disclosed embodiments are configured to obtain real-time data gathered during the drilling operation to update a probability model of a formation that is used in determining whether to alter a direction of a drill path. The disclosed embodiments may be configured to provide a notification to a user indicating or suggesting that certain adjustments be made to the drill path based on the updated probability model. Additionally, the disclosed embodiments may be configured to automatically make the adjustments to the drill path based on the updated probability model.