April 20, 2022

Customer story: Collecting 730 line-km of flight data to characterize the geological condition of a planned railway route in Mato Grosso

In 2021, EMerald Geomodelling was engaged by RUMO Logística, the largest railway company in South America, to accurately characterize the real geological conditions of the planned railway route. By using both geophysical data and existing data combined with EMerald Geomodellings proprietory machine learning software, EMerald could provide RUMO with suggestions of where to focus their follow-up investigations.

Background

In 2021, EMerald Geomodelling was engaged by RUMO Logística, the largest railway company in South America, to accurately characterize the real geological conditions of the planned railway route. This railway is important as it will help stimulate competition amongst the railway outlets, leading to increased competition to produce grain and in turn reduce costs for the producers. The aim of the project was threefold: use airborne geoscanning to understand large-scale trends in ground conditions; map different soil and rock types, both in terms of soil type and in terms of mechanical properties; and optimize upcoming drilling campaigns, with a focus on reducing the number of total drillings required.

RUMO was especially interested in mapping three different categories of earth materials, distinguished by their mechanical strength, more directly, their ease of excavation. The first category consisted of weaker sediments, that could be handled without too much planning and extra costs. The second category was a mix of lesser sediments and larger boulders. Generally, this material category poses a larger challenge and often result in additional costs. The third and final category was hard rock that will require blasting to excavate.

How it was done

The airborne geoscanning surveys were carried out in December 2021 by EMerald Geomodelling. The surveys covered portions of three different segments of the railway. During the data collection, EMerald Geomodelling monitored the operation ensuring that the data quality was sufficient for its detailed, geotechnical applications.

During these field surveys, a total of 170 km of railway alignment were covered, resulting in the collection of 730 line-km of flight data. As part of the initial phase of the project, the customer had already gathered certain geotechnical data, i.e., boreholes, which enabled the utilization of EMerald Geomodelling ́s machine learning algorithms. Geophysical models – specifically electrical resistivity models – were then generated and interpreted to create ground models.

Project timeline

Project timeline from november 2021 to march 2022

Deliveries to customer

Overview of recommended areas to prioritize
Model of depth and uncertainty models
Model of predicted and probobal material

Customer results and actions taken

By using both geophysical data and existing data combined with EMerald Geomodellings proprietory machine learning software, EMerald could provide RUMO with suggestions of where to focus their follow-up investigations. This proved to be very valuable, and the customer estimated that it saved them about 33% of the drillings they would otherwise have done.

3D volumetric models of different materials were also performed, and predictions of the sediment type along the length of the railway sections were presented as a result. This aided, among other things, RUMO in planning their excavation methods.

"The partnership with EMerald was a must to overcome the huge deadline challenges we faced in the project, which is currently the largest project in our portfolio. In addition, this innovative technique of geomodelling brought key values such as the increase of the project’s executive plan capability". Jose Carlos Filho, Executive Manager of Expansion Projects at RUMO
“By applying EMerald’s technology, the project was able to start faster and with less risk. The geological models delivered by EMerald provided us with the opportunity to create a more efficient drilling plan, and it also reduced the geological risk overall of the project”, Filho says.

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