3D Geosteering Using Segment-Based Well Performance Prediction
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Solution Overview
Problem
Current geosteering techniques are limited in accurately predicting well performance and optimizing well trajectories due to their inability to account for complex three-dimensional variations in wellbore trajectory and orientation, leading to suboptimal well placement and reduced production efficiency.
Innovation Solution
A system and method for automated well planning and control using an analytical well performance model that predicts well productivity by segmenting complex trajectories into straight-line segments, accounting for inclination and azimuth variations, and optimizing well placement based on real-time logging data and geological survey data to maximize production and minimize drilling difficulties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current geosteering techniques are used, then wellbore planning can be performed based on geoscience constraints, but accurate prediction of well performance and optimization of well trajectories cannot be achieved due to inability to account for complex three-dimensional variations
Solution Approach 1:
The complex three-dimensional wellbore trajectory is divided into multiple straight-line segments. Each segment is characterized by its length, inclination angle, and azimuth angle. This segmentation allows the system to accurately model complex trajectories while maintaining computational efficiency, as each segment can be independently analyzed and combined to predict overall well performance.
2Productivity
If complex three-dimensional trajectory variations are accounted for, then accurate well performance prediction can be achieved, but the complexity of the geosteering system increases
Solution Approach 1:
The model assigns specific local characteristics to each trajectory segment, including its own inclination angle, azimuth angle, and length. This allows the system to capture local variations in wellbore orientation and their impact on productivity, while maintaining overall system manageability through modular segment-based analysis.
Solution Approach 2:
The system transitions from two-dimensional wellbore planning to three-dimensional trajectory modeling by incorporating inclination angles and azimuth angles for each segment. This dimensional expansion enables accurate prediction of well performance by accounting for the spatial orientation of the wellbore relative to formation dip and strike directions.
3Manufacturing precision
If real-time logging data is used for automated geosteering, then well placement can be optimized, but the computational requirements and system complexity increase
Solution Approach 1:
The system incorporates real-time logging data from the wellbore into the performance prediction model, creating a feedback loop that continuously updates trajectory optimization recommendations. This allows automated geosteering to adjust well placement based on actual formation properties encountered during drilling, improving precision while managing computational complexity through efficient algorithms.
Data Source
AI summary
Systems and methods for automated planning and/or control of a drilling operation are implemented to be based at least in part on automated prediction of well performance using an analytical well performance model. Substantially real-time determination of one or more drilling parameters and/or well trajectory parameters is based on measurements received from a drill tool together with the well performance model. The described techniques thus provide for automated, analytically determined well performance measures (e.g., well productivity and/or revenue) to a geosteering process. The well performance model accounts for variations of well trajectory both in inclination and in azimuth angle.