Taggant Injection Control for Wellbore Depth Accuracy
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Solution Overview
Problem
Conventional mud logging methods face inaccuracies in determining the depth of rock cuttings due to depth uncertainties, especially in deviated and horizontal wells, where gravitational debris accumulation and hydraulics issues lead to delayed cuttings return, resulting in depth uncertainties of several feet.
Innovation Solution
A system comprising a taggant injection pump, IoT controller, and taggant detector, which uses machine learning to optimize taggant injection profiles, ensuring accurate detection and analysis of rock cuttings depth, with taggants like polymeric nanoparticles or metal microdots embedded in rock cuttings for precise depth determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional mud logging methods are used to determine rock cuttings depth, then the process is simple and cost-effective, but the depth determination accuracy deteriorates with uncertainties of several feet due to gravitational debris accumulation and hydraulics issues in deviated and horizontal wells
Solution Approach 1:
The patent introduces taggants (detectable markers) as intermediaries between the rock cuttings and the detection system. These taggants are injected into the wellbore, attach to rock cuttings, and provide a reliable detectable signal that bridges the gap between the physical cuttings and the depth determination system, enabling accurate tracking regardless of gravitational accumulation or hydraulic delays
Solution Approach 2:
The system implements a feedback mechanism where taggant detectors continuously monitor the presence and concentration of taggants in returned cuttings, and this information is fed back to adjust and optimize the taggant injection rate. This closed-loop feedback ensures accurate depth determination while adapting to varying well conditions and cuttings return rates
2Measurement precision
If taggant injection is increased to improve detection accuracy, then the rock cutting depth determination accuracy improves to within 1 foot, but the cost and complexity of the system increases
Solution Approach 1:
The system dynamically adjusts the taggant injection rate based on real-time feedback from taggant detectors and well conditions. The injection rate is not fixed but varies continuously to match the actual cuttings return rate and detection requirements, optimizing the balance between accuracy and taggant consumption
Solution Approach 2:
The system changes the concentration and injection parameters of taggants based on detected conditions. By monitoring taggant concentration in returned cuttings and adjusting injection parameters accordingly, the system maintains optimal detection accuracy while minimizing taggant usage through parameter optimization
Data Source
AI summary
A system for drilling a wellbore is disclosed. The injection pump releases the taggant into the mud stream traveling downhole. The taggant attaches to the rock cuttings and it is detected on the surface by the taggant detector. The taggant detector provides the data relating to the taggants detected in the drilling fluid. The data is analyzed by taggant analysis and control engine, which produces an injection profile. Based on the injection profile, the IoT Controller adapts the parameters of the taggant injection pump to achieve a real-time optimization of the taggant injection.