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  • What we do
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    iRun
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  1. LTIMindtree is now LTM | It’s time to Outcreate
  2. Industries we serve
  3. Energy & Utilities Solutions | Renewable Energy & Sustainability
  4. Intelligent Rig Operations

Intelligent Rig Operations

Driving Drilling Efficiency Through Edge-Based Real-Time Analytics

About the Client

The client is a global leader in oilfield services, delivering advanced technologies and integrated solutions to support upstream energy operations. Operating in over 70 countries, the company specializes in drilling, evaluation, completion, and production services that optimize reservoir performance and enhance efficiency. Its offerings include cementing, stimulation, well intervention, and digital platforms for real-time insights. 

Need for Change

To keep pace with the demands of modern drilling operations, it became essential to move beyond traditional, manual monitoring and delayed decision-making. The transition toward edge-based, real-time data analytics was driven by the need to empower rig crews with immediate, actionable insights. This shift would enable optimization of drilling parameters, proactive response to operational risks, and streamline workflows. The organization wanted to leverage advanced data analysis and visualization directly at the rig site to foster a culture of data-driven decision-making, reduce reliance on centralized cloud resources, and accelerate the transformation of raw data into operational value.

Challenges

The client faces several operational challenges in managing rig sites and drilling activities. These challenges stemmed from limitations in connectivity, real-time monitoring, equipment reliability, and the need for timely, data-driven decision-making, all of which impacted safety, efficiency, and overall performance. A range of stakeholders including field operators, drilling engineers and operations managers were impacted by these challenges.

Overcoming Remote Monitoring Limitations at Rig Sites

Restricted internet connectivity and bandwidth at rig sites hindered timely access to operational data.

Mitigating Real-Time Monitoring Risks in Drilling Operations

The client struggled to detect and respond quickly to critical drilling incidents, such as well kicks, interference, or collisions due to limited real-time monitoring at rig sites. This created safety risks and operational hazards for on-site teams.

Addressing Equipment Reliability and Human Error

Equipment failures and human errors sometimes led to operational delays and increased costs, ultimately reducing overall project efficiency and profitability.

Sub-Optimal Operational Efficiency due to Manual Monitoring

Non-optimized drilling processes and reliance on manual monitoring led to increased non-productive time (NPT) and delayed decision-making.

Slow Responses due to Reliance on Manual Expertise in Drilling Operations

Depending on individual expertise to interpret real-time rig data slowed response times and made consistent decision-making challenging.

LTIMindtree’s Solution

To address the operational challenges faced at rig sites, an edge-based, real-time drilling data analysis solution was implemented to optimize oil and gas drilling operations. This approach leveraged advanced engineering models, visualization, and monitoring tools to transform raw drilling data into actionable insights, driving efficiency and informed decision-making.
Key features of the solution included:
Real-Time Data Analysis
Applied business logic to real-time drilling data streams, transforming raw data into actionable operational insights for immediate decision-making.
Operational Insights
Utilized detailed analytics to clarify drilling efficiency improvements and cost reductions through real-time well monitoring.
Data-Driven Analytical Models
Leveraged advanced dashboards like torque-drag, anti-collision monitoring, bit wear prediction, and kick/loss detection to identify drilling irregularities and trigger timely warnings.
Visualization Tools
Employed interactive charts and graphs to enhance the visualization of drilling data, supporting better operational understanding and faster decision-making.
Microservices-based Architecture
Adopting a microservices-based architecture and ensuring compatibility with various communication protocols enabled support for diverse rig environments and operational needs.
Multiple Test Iterations
Conducting multiple test iterations with varied datasets significantly enhanced the reliability and effectiveness of the software solution.
The solution comprised several specialized modules, each targeting critical aspects of well engineering. A few of the important modules were:
Torque and Drag (T&D)
This module enabled real-time friction factor calibration, generated broomstick plots, and applied Bayesian optimization for subsurface friction factors. It supported advanced analysis of hook load, torque and drag trends. It enabled continuous monitoring and adjustment of wellbore conditions for safer and more cost-effective operations.
Anti-Collision Monitoring
This module provided real-time 3D visualization and analysis to prevent wellbore collisions during directional drilling. It integrated survey data and planned trajectories, enabling early detection of potential collision risks with offset wells for safer drilling operations.
Bit Wear Prediction
Real-time monitoring and forecasting of bit wear, integrating mechanical specific energy, gamma ray, and formation data to optimize bit life and reduce unnecessary trips. It helped operators make informed decisions about bit replacement and avoid unnecessary trips. By analyzing drilling parameters and formation data, it reduced costs and improved drilling efficiency.
Kick/Loss Prediction
Analyzed real-time drilling and tripping data to detect early signs of well control risks such as kicks and fluid losses. It provided automated risk indices and alerts, enabling proactive intervention to enhance safety and prevent costly incidents.
Experience-Centric Offerings
1
Alert System
It enabled users to configure automated notifications for critical drilling parameters, operational risks, and custom conditions across all modules. It supported real-time alerts creation and customization, helping teams respond quickly to potential issues and maintain safe, efficient operations.
Unit Conversion
Flexible unit system across all modules for global usability.

                       

                        Architecture Diagram

Figure 1: System Architecture Diagram

Tech Stack

CategoryKey Technology/Services
Programming LanguagePython, NodeJS
Framework.NET, AngularJS
ContainerizationDocker
OrchestrationKubernetes
Message BrokerRabbitMQ
CI/CD ToolJenkins
API Testing ToolPostman
DatabaseMongoDB

Benefits

The implementation of an edge-based, rig-installable application for drilling optimization and hazard prevention has delivered measurable benefits for the client. These benefits include operational efficiency, safety improvements, cost savings, and accelerated data-driven decision-making for well construction projects.

Optimized Drilling Parameters
Optimized Drilling Parameters
Optimized Drilling Parameters

Optimized Drilling Parameters

Our solution enabled rig crews to optimize drilling parameters such as rate of penetration (ROP), bit replacement, and tripping speeds, improving both operational efficiency and safety.

Faster Turnaround Times
Faster Turnaround Times
Faster Turnaround Times

Faster Turnaround Times

Leveraged predictive algorithms to accelerate decision-making and reduce turnaround times, helping operators minimize non-productive time (NPT).

Proactive Approach to Issue Management
Proactive Approach to Issue Management
Proactive Approach to Issue Management

Proactive Approach to Issue Management

Provided smart alerts and 3D visualizations to predict and prevent issues like kicks, stuck pipes, and loss circulation.

Lowered Operational Costs
Lowered Operational Costs
Lowered Operational Costs

Lowered Operational Costs

Our solution reduced costs associated with data transmission and cloud storage and this led to lower operational costs.

Swifter Data Analysis in Minutes
Swifter Data Analysis in Minutes
Swifter Data Analysis in Minutes

Swifter Data Analysis in Minutes

Reduced data analysis time from multiple days to just a few minutes, supporting faster and more informed decisions.

Ultra-low Latency
Ultra-low Latency
Ultra-low Latency

Ultra-low Latency

Less than 10 milliseconds, which is critical for drilling safety and non-productive time (NPT) reduction. Compared to cloud-based solutions that take 100–300 milliseconds.

Significant Bandwidth Savings
Significant Bandwidth Savings
Significant Bandwidth Savings

Significant Bandwidth Savings

60–80% reduction in bandwidth usage. Essential because raw sensor data transmission requires high bandwidth.

Reduced Downtime
Reduced Downtime
Reduced Downtime

Reduced Downtime

Predictive maintenance at the edge can save up to $25 million per day on offshore rigs by preventing failures.

Improved Efficiency
Improved Efficiency
Improved Efficiency

Improved Efficiency

25% improvement in drilling efficiency by using edge-based solutions.

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Conclusion

The deployment of LTIMindtree’s edge-based, real-time drilling data analytics solution has empowered the customer to overcome operational challenges at rig sites, driving significant improvements in efficiency, safety, and cost savings. By transforming raw drilling data into actionable insights and enabling rapid, data-driven decision-making, the solution, powered by predictive analytics for drilling, has set a new benchmark for drilling optimization and hazard prevention.

                                                  Internal Quote

“The successful deployment of LTIMindtree’s edge-based, real-time drilling analytics solution is a testament to our unwavering commitment to innovation and operational excellence. By harnessing advanced analytics at the rig site, we have empowered our clients to achieve safer, faster, and more cost-effective drilling operations. This solution not only delivers measurable improvements in efficiency and safety but also sets a new benchmark for data-driven decision-making in the energy sector. We are proud to partner with our clients on their digital transformation journey and look forward to driving even greater value together.” 

— Associate Vice President, LTIMindtree

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