Innova Drilling & Intervention are proud to introduce an innovative new dull bit grading feature, in partnership with ZerdaLab, where users can automate the dull bit grading process with the power of AI via the Innova Web Portal and Mobile App.
Bit Dull Grading Explained
A critical component of drilling oil wells is drilling efficiency, which is impacted by the performance of the drill bit used. In a similar way that geological and seismic data inform operators of the best spots to drill for maximum reserve deposits; information gathered from a drill bit can be used to optimize drilling efficiency and performance.
Bit dull grading is the standard method of classifying drill bits for wear characteristics. Gathering bit grade data provides valuable insight for selecting the most suitable bits for future runs and upcoming operations in the same area.
Why It’s Important
Historical data gathered from bits graded on previous runs is vital to making an informed selection of the correct bit to suit the geological conditions of the formation. Correct bit selection ensures the best rate of penetration (ROP) is achieved, reducing the cost by shortening the time to well completion.
Inconsistencies in Current Process
Manually grading drill bits hinders the grading criteria to be subjective and relies on the individual expertise and experience of assessors, as well as assessment conditions that can vary drastically.
Consider a drilling services company that is drilling 20 wells across a region with a different team independently grading bits in tandem. Even when using shared grading criteria, each bit across the portfolio requires grading that is naturally subjective to the eye of the personnel.
In practice this means there is no objective grading scale for the company to take a holistic view of bits graded between different projects, creating a serious detriment to employing an informed decision-making process for bit selection.
This issue can be alleviated with the introduction of an AI-based grading system, as it implements a consistent and unbiased methodology wherever it is employed across the company.
Deliver Consistent Results with AI-based Bit Grading
Automation of the bit grading function ensures that a consistent grading criteria and methodology is applied across all projects regardless of the job or personnel involved.
AI-based grading systems analyze a wide range of data on the condition of a drill bit allowing them to be catalogued more quickly and in far greater detail than is possible with a manual grading system. This approach enables an objective and consistent assessment of wear characteristics and drilling performance that is highly accurate.
Bit Grading with Innova
Implementation of bit grading on the Innova platform provides a detailed record of consistent and objective bit grade results.
The functionality comes as a simple integration within the software whereby users can upload images directly from their phone to the Innova platform. In the background ZerdaLab’s advanced machine learning models determine the type and severity of damage to each individual cutter from the images, making dull grades as accurate as possible. Reports utilize consistent and repeatable outputs to users that help identification of drilling disfunctions that contributed wear to the bit.
All grading information is pulled directly into BHA results and is accessible for distribution on the Innova portal.
Innova D&I are available if you require additional support for diagnosing a drilling disfunction or to provide reporting on your grading result to provide further context on request.
You can find further information about ZerdaLab technology on their website.