Versatility in Application
It starts with the camera and we've got the best in the business. We are a developer partner with one of the world's largest suppliers of world class, explosion-proof, industrial cameras with NEC, CEC, ATEX, IECEx and INMETRO ratings.
Hole Cleaning Quantification
Did we mention hole cleaning is complicated? Actually what makes it difficult is knowing how to measure and manage it. CleanSight® fixes that. By streaming in real-time and accounting for lag depth, the cuttings' load, size, and shape characteristics are used to update the hydraulic and cuttings transport models using particle size distribution (PSD).
With CleanSight®, the rig team now has data for trend analysis that lets them monitor hole cleaning performance 24/7 and pick up anomalies. This awareness allows the team to drill faster and even reduce the bottoms up circulations before tripping.
Cuttings Volume Estimate
Using Image Classification, CleanSight® measures the cuttings load throughout the entire drilling and cementing process.
A qualitative estimate of the load is compared to ROP, flow rate, and other parameters to provide trend analysis and insights into hole cleaning efficiency.
You are looking at the Shaker Load Classification (SLC) Gen 1 version. Here is Gen 2 and Gen 3 is in development. Coming Soon!
Once the geomechanical team or consultant builds the wellbore stability model and gives the drilling engineer the mud weight windows and directional stresses, what then? What can the rig team use to monitor the well for CAVINGS, which is the primary stability indicators?
CleanSight® of course!
No more reliance on intermittent visits to the shakers, mud loggers, or expensive LWD to detect if the hole is becoming unstable.
Only CleanSight® can pick this up 24/7 and answer the question, "How Do the Shakers Look?"
Wellbore Stability Monitoring
Data Science Enabler
By now you may be asking, besides the cool camera, how do they do the computer vision? CleanSight® is a multi-tiered SaaS and the image on the right illustrates our plans.
As much as we'd like to nerd out and describe how and what we do in data science, our IP Advisor Marty has a say, so we will have to be content with:
DrillDocs uses deep learning techniques to build neural networks that detect, track and identify rock characteristics as they are being drilled. ‘Product as a Service’ is our revenue model. At the rig, we install and maintain a proprietary explosion-proof camera embedded with tiered CleanSight solutions that provide increasingly sophisticated deep learning detection and predictive software to fit the drilling application.
We Integrate With Your Ecosystem
CleanSight® operates as a standalone system sending time-based data via WITS or Cloud, which allows users to integrate the data into their own workflows. By providing the rig's EDR data, mud reports, and the client's daily time logs, DrillDocs' data science techniques deliver an exponentially improved solution for wellbore instability and poor hole cleaning mitigation.