Release 2.9
10x faster analysis. Greater scale. Smarter operational decisions.
A new backend for smarter well delivery and scalable real-time insight
Release #: Release 2.9
Date: July 1, 2025
Energy operators and their drilling and wells teams are continuously striving to improve well construction and reduce operational risk. Every well plan aims to optimize performance, minimize nonproductive time (NPT), and ensure the well delivers—whether for production or data collection.
Yet outdated software tools, slow data processing, legacy “best practices”, and rising costs hold engineers back from learning effectively from past operations.
Exebenus Spotter Release 2.9 overcomes these challenges with 10x faster processing, streamlining WITSML integration, and powerful ML-driven insight. It transforms historical data into actionable intelligent for smarter planning and real-time decision-making.
With Release 2.9, historical analysis becomes a real-time advantage, helping teams improve decisions before and during well constructions. Engineers can quickly identify stuck pipe risks and uncover rate of penetration (ROP) optimization opportunities using real-world performance data.
Exebenus Spotter now processes 30 days of 1Hz real-time data in just 37 minutes – delivering speed and scale previously out of reach.
The enhanced ROP Agent unlocks untapped potential to reduce time on bottom by quantifying improvements opportunities, enabling smarter tool selection and challenging overly conservative constraints. NPT events, like stuck pipe in offset wells, can be quickly analyzed, with insights directly applied to ongoing operations.
Why
Release 2.9
matters
10X faster data processing
Processes 24 hours of 1 Hz data – 87,241 data points – in 74 seconds*
25% reduction in WITSML read requests
Monitor 100+ wells on a small CPU footprint
* Machine details: 4 VCPUs, 16GB memory
Built for scale: Monitor over 100 wells with less infrastructure strain
Release 2.9 brings a major leap in scalability. Exebenus Spotter now supports over 100 concurrent operations on a lightweight infrastructure footprint, delivering real-time insight across your entire well portfolio. A faster, more efficient backend reduces WITSML traffic and processing time, providing engineers consistent, high-quality visibility across assets, and time to act on issues as they arise.
Tim Robinson, Chief Data Scientist
Release 2.9 gives drilling engineers a stronger foundation for operational intelligence with 10X faster data processing, efficient integration to WITSML store, and the ability to oversee more rigs at once. It’s about turning high-volume data into high-value decisions, across the well delivery.
Harnessing the power of past wells
Historical analysis is a key tool for learning and improving future operations.
With Exebenus Spotter Release 2.9, engineers can uncover insights from past wells, such as ROP parameters, vibration effects, and stuck pipe risks, faster and more efficiently.
The following real-world case stories show how these insights lead to better planning, reduced risk, and smarter drilling decisions.
Oman case study: Historical ROP optimization analysis
How historical data unlocked 25%+ ROP gains
As part of this historical well analysis, Exebenus Spotter was used to evaluate ROP optimization potential in a 12 ¼” section. The drilling program included:
- Weight on Bit (WOB): Up to 35 klbs
- RPM: Target of 100 RPM (pre-set), operational limit later adjusted to 80 RPM
- Flow rate: 500–650 gallons per minute
The goal was to assess how well drilling operations adhered to optimal drilling parameters and identify opportunity for improving ROP performance.
Key findings and recommendations
- WOB: The ROP Agent recommended alternating between lower, stable, and higher WOB settings to better match formation changes. With WOB staying within program limits, historical analysis estimated that adjusting WOB in line with the agent’s guidance could have delivered a 10–25% increase in ROP. This highlights the value of real-time adaptation to subsurface variability.
- RPM: Although the plan initially allowed up to 100 RPM, this was reduced to 80 RPM in practice, but frequently remaied lower. The ROP Agent consistently recommended higher RPM within the safe range. Following these recommendations was estimated to have improved ROP by over 30% during specific intervals, underscoring a missed opportunity for enhanced drilling efficiency..
- Flow rate: The agent’s recommended flow rates closely matched actual values, except during sliding intervals where ROP was not a key concern. As a result, any deviations had minimal impact on overall performance.
The screenshot illustrates how the Exebenus Spotter ROP Agent provided recommendations for optimizing WOB and RPM. Due to the chosen bottomhole assembly (BHA), the agent was configured to limit RPM increase recommendations to a maximum of 20%. Despite this constraint, analysis indicates that moving closer to the agent’s unrestricted upper range could have delivered up to a 50% improvement in ROP.
Conclusion
This historical analysis demonstrates how Exebenus Spotter can provide clear, actionable opportunities for improving ROP, using existing equipment and operational constraints.
If the ROP Agent’s recommendations had been followed during the operation, the section could have been drilled faster and more efficiently, reducing cost and time without compromising safety or requiring new tools.
For drilling teams striving to improve performance well over well, Exebenus Spotter delivers the real-world data needed to drill smarter. Based on this analysis, the operator built a business case for selecting a higher-performance drilling motor on the next well. This upgrade was projected to save 1.2 days of time on bottom.
Built for drilling managers and engineers, Release 2.9 makes historical analysis practical and powerful by directly supporting better planning, performance and decision-making
Indonesia case story: Historical stuck pipe risk analysis
Mitigate stuck pipe risk through data-driven insight
Exebenus Spotter was used to investigate a stuck pipe incident that caused 25 days of NPT and a sidetrack. Release 2.9 enabled engineers to efficiently analyze 68 days of real-time WITSML providing a detailed understanding of the conditions leading up to the event, and how those learnings helped prevent a similar issue in the sidetrack.
Key findings and observations
- Pre-event risk identification: The Stuck Pipe Agent issued multiple warnings up to 12 hours before the pipe became stuck during tripping out. Alerts for mechanical drag, static friction, and breakover torque clearly marked the depth interval where risk was escalating.
- Operational insight: While drilling, the agent detected poor hole cleaning symptoms and pointed to debris buildup in the wellbore. Although pipe rotation and high flow rates helped mitigate risk, Exebenus Spotter revealed increasing pack-off conditions. As the team began tripping out, warning frequency rose, indicating accumulating debris around the BHA and mounting drag resulting in the stuck pipe event. The analysis showed how risk developed gradually and where earlier mitigating actions could have made a difference.
The Stuck Pipe Agent flagged a sequence of risks warnings starting 12 hours prior to the stuck pipe event: breakover torque risk (A), fluid friction (B), numerous escalating mechanical drag (C), and finally static friction warnings (D). Together, these offered a clear progression toward the final pack-off, giving the rig team a window for intervention, had the system been running live.
- Post-incident learning: The sidetrack, drilled at similar inclinations, reflected a much more cautious approach. Extended reaming at each stand and four hours of reaming at section TD helped avoid a repeat event. These adjustments confirmed the value of the risk zone identified in the original operation.
Conclusion
This case illustrates how Exebenus Spotter enables fast, focused analysis of complex drilling data to uncover critical operational insights. Using historical data, engineers can clearly identify failure patterns and apply lessons learned to future wells.
This case illustrates how Exebenus Spotter enables fast, focused analysis of complex drilling data to uncover critical operational insights. Using historical data, engineers can clearly identify failure patterns and apply lessons learned to future wells.
Exebenus Spotter’s early warnings, issued up to 12 hours before the event, could have helped mitigate risk and avoid the costly sidetrack altogether.
Release 2.9 empowers engineers to monitor multiple operations concurrently, turning data into actions more consistently and without added complexity
Smarter oversight across every rig – scaled and in real time
Today’s drilling engineer often monitors 2-6 wells at once. Exebenus Spotter Release 2.9 scales effortlessly to support over 100 concurrent wells without overloading or slowing down the infrastructure.
Build on the same architectural principles as leading cloud platforms, Exebenus Spotter delivers real-time, high-frequency insight across your rig fleet of wells, ensuring consistent performance and shared learnings across assets.
Always-on monitoring, consistent insight
Exebenus Spotter’s machine learning agents run continuously in the background, analyzing every data stream and highlight only what matters, delivering:
Objective interpretation of real-time data
Consistent, automatic insight across rigs and teams
Early warnings and alarms triggered by developing risks
Scalable monitoring, from single well to an entire rig portfolio
It’s
Plug & Play
Time
Want to see how Exebenus Spotter Release 2.9 can help reduce risk and optimize performance in your next well? Contact our team to schedule a walkthrough.