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Case studies

Reduction of geotechnical risks through advanced data analysis at NTS

A single avoided incident, thanks to predictive analytical models, prevented the loss of hundreds of thousands of reais

The new analytical models reduced the time required to analyze potential incidents, resulting in decreased operational risks and mitigation of potential revenue losses.

The challenge

The Geotechnics Department at NTS analyzes, prevents, and addresses risks related to geotechnical occurrences. To achieve this, the team conducts continuous assessments along more than 2,000 kilometers, prioritizing actions based on the level of risk involved.

However, the department relied on multiple data sources and dispersed, unintegrated platforms to perform its analyses, which made decision-making slow and inefficient.

The challenge was to develop a solution where all data could be stored in a single location, enabling faster and more accurate analysis. Additionally, it was necessary to design a method to organize and structure the data in a way that would reduce the complexity of issues and contribute to crafting the final solution.

Company: Nova Transportadora do Sudeste - NTS

Industry: Oil and Gas

Size: large

Our method

Step 1 - Cloud solution

A cloud-based solution on Azure was designed to serve as the official repository for all data sources, including their collection and transformation processes. This solution consisted of a complete structure with two environments: staging and production. Additionally, our data squad developed an automation system for incident registration.

Step 2 - Data mapping and organization

All data flows were mapped in collaboration with the business department, from collection to the visualization of the analyzed data. This process resulted in two deliverables that served as the foundation for subsequent stages. The identified data was then structured and organized into different pillars, each with unique characteristics to be analyzed, as well as varying formats. Examples of identified file types include: xlsx, SHP, GeoJSON, KMZ, and PDF.

Step 3 - Time to automate

At this stage, the Azure cloud was structured with all configurations and deployments of resources corresponding to the mapped requirements. Additionally, our data squad developed automations to bring speed and greater reliability to the analysis process.

Step 4 - Data visualization and monitoring

After the entire structure was set up, the Data Hub began its initial operation by collecting and storing data, centralizing its operations in an Azure Blob Storage. Finally, a Data Visualization was created and delivered in Power BI, completing the project and enabling the NTS team to monitor risk indicators with greater accuracy and automation.

Technologies used in this project

Achieved results

Reduction in the time for identifying and analyzing geotechnical risks

The solution prevented incidents with risks amounting to hundreds of thousands of reais in a single occurrence

New capability for identifying smaller incidents that were previously unnoticed

Democratization of data access across the department for all analysts involved

With a Data Hub solution for the Geotechnical department, we helped NTS achieve immediate improvements in a critical process of its operation. Our Squad quickly identified the issues causing inefficient and slow analysis, and implemented a robust, scalable cloud solution with excellent cost-effectiveness, filling technical analysis gaps in just 3 months.

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