Heave Compensation via Changepoint Segmentation of Block Position Data
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Solution Overview
Problem
Floating drill rigs experience heave due to ocean swells, causing variability in bit depth measurements and making it difficult to maintain consistent drilling conditions, especially when compensators do not fully compensate for heave, leading to inaccurate bit depth and rate of penetration (ROP) calculations.
Innovation Solution
A position manager applies a changepoint model to time-based block position data from a block position sensor to segment the data and generate a de-sensitized block position, which helps determine the bit position without heave-induced variability, allowing for more accurate ROP calculations and identification of changes in drilling conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a floating drill rig operates in ocean swells, then drilling operations can be performed, but heave causes variability in bit depth measurements and inaccurate ROP calculations
Solution Approach 1:
The patent segments the bit depth measurement into two independent components: heave component (vertical position changes due to ocean swells) and drilling component (actual bit advancement). By separating these components through mathematical decomposition, the system can accurately measure only the drilling component while filtering out heave-induced variability, thus resolving the contradiction between maintaining continuous drilling operations and achieving precise bit depth measurements.
Solution Approach 2:
The patent introduces an intermediary calculation layer that processes raw bit depth measurements through mathematical operations (differentiation and integration) to eliminate heave effects. This intermediary processing layer acts as a mediator between the noisy raw measurements and the accurate drilling component extraction, enabling precise ROP calculations despite the presence of heave-induced measurement variability.
2Stability of the object's composition
If compensators are used to counteract heave, then bit depth consistency improves, but incomplete compensation leaves residual variability in measurements
Solution Approach 1:
The patent extracts the heave component from the total bit depth measurement through mathematical decomposition. By isolating and removing the heave component (which includes compensator effects and residual variability), the system obtains a purified drilling component that represents true bit advancement. This extraction approach resolves the contradiction by achieving measurement precision independent of compensator performance.
Solution Approach 2:
The patent transforms the measurement approach by changing from direct measurement of bit depth to measurement of rate of change of bit depth (ROP). This parameter transformation allows the system to measure drilling performance based on changes rather than absolute positions, making the measurements less sensitive to residual heave variability and compensator imperfections, thus achieving both stability and precision.
3Productivity
If real-time bit depth monitoring is implemented, then drilling efficiency improves, but heave-induced noise creates false indications of drilling condition changes
Solution Approach 1:
The patent segments the detected signal into heave component and drilling component, allowing real-time monitoring to focus only on the drilling component for identifying actual drilling condition changes. This segmentation eliminates false indications caused by heave noise while maintaining real-time monitoring capability, thus resolving the contradiction between drilling efficiency and detection accuracy.
Solution Approach 2:
The patent implements feedback through continuous mathematical processing of bit depth measurements to identify and correct heave effects in real-time. The system uses the processed drilling component feedback to trigger appropriate drilling operations only when genuine changes occur, filtering out false alarms from heave-induced noise. This feedback mechanism maintains real-time monitoring efficiency while ensuring reliable drilling condition detection.
Data Source
AI summary
A position manager may receive time-based block position data of a travelling block above a drill floor on a floating drill rig, wherein the time-based block position data is received from a block position sensor on the drill floor. A position manager may apply a changepoint model to the time-based block position data to separate the time-based block position data into a plurality of segments. A position manager may determine a best segment of the plurality of segments. A position manager may generate a de-sensitized block position using the best segment of the plurality of segments.