Trends and Technologies in Drilling Management - Core Case

Trends and Technologies in Drilling Management

The search for innovations to enhance geoscience data acquisition and management is a reality in mining companies. Therefore, we have selected five trends and technologies in drilling technology.

Among these trends, the following are highlighted:

  • automation and robotics
  • data optimization and analysis
  • implementation of artificial intelligence
  • adoption of technologies and good practices aimed at ESG preservation
  • digital transformation technologies aimed at obtaining data directly from the drilling source with production logs

Drilling is an Essential Process

Currently, drilling is an essential process for the geological understanding of a mine or mineral exploration project. Mining companies invest substantial resources in drilling programs every year. Thus, core samples comprise one of the few certainty resources on subsurface geology.

Geologists are able to describe, analyze and extract chemical, physical and lithological features from there and can have an estimate on mineral resources and several other geologies, mine and mining site routines. Therefore, any deviations taking place during the drilling stage can have an impact on various process throughout the mining chain.

In summary, the importance of drilling is such that new management trends and technologies are emerging more and more. Here are some of them.

Automation, Robotics, Scanners and Sensors

The use of automated machines, sensors and scanners that record high quality images is a growing trend in warehouses.

This equipment enables geology teams to extract more information from samples. They promote efficiency gains, decrease manual inputs, organization and data standardization.

This hardware can be equipped with a number of sensors. In addition to traditional RGB, spectral, hyper-spectral and laser band sensors to scan 3D core samples.

Solutions include from image recording and processing to software with artificial intelligence based on computational vision. This brings several insights that would otherwise be difficult for geologists’ eyes (and magnifiers).

Moreover, the use of automated robots in combination with rolling system workbenches enable case handling in warehouses.

Efficiency is key. This includes the adoption of practices and technologies to enable digital and direct recording of drilling information. For instance, core sample cases can be identified with QR CODES and RFID in addition to header physical engravings. This enables machines and software to later identify cases without the need of operator inputs.

Artificial Intelligence

Another major trend is the use of artificial intelligence algorithms to acquire drilling core samples. The use of machine learning is already a reality. It brings numerous use opportunities within the mining value chain, especially for geology teams.

From sample images it is possible to train computational vision models to partition and classify several parameters. For instance, identification of flaws, cracks, texture and lithological classification.

However, computational vision can be used in many other geological or geotechnical classifications. It is possible to optimize several processes such as extracting the size of core samples in the case to check for development and recovery.

These algorithms use background data and descriptions and can be retrofitted from new geologist inputs. However, in order for artificial intelligence models to be effective, it is essential to acquire images in a uniform and high quality manner.

A common scenario in several projects is the progression of geologic interpretation. Over time there are changes to the terms used, acronyms and description format. Moreover, new important geologic markers can be discovered and become the basis to outline mineralized bodies in current interpretation.

Geologists often need to endeavor to gather legacy and new descriptions in building and updating geologic models.  This process frequently needs trips to the warehouse, looking for old drilling cases to reinterpret or reassess.

Artificial intelligence models can help in this scenario. Old core sample images can be used in AI models to extract geological indicators that weren’t noted in the past.

However, every technology has its limit. Old pictures may not have the required quality for good algorithm response. A spectral sensor would be needed to obtain the required data.

This trend is not about replacing geologists by algorithms, but to expand their capabilities and possibilities. By exploring AI resources, they can achieve more assertive results and optimize them.

Sustainability, Governance and ESG

The mining industry is ever more committed to conservation, employee safety and ESG matters. This includes the implementation of practices to assess the environmental impact of value chain activities and to measure their implications.

Mining companies have adopted the use of ESG Analytics solutions to identify opportunities for improvement in drilling operational chains. And by complying with such guidelines, they propose actions to reduce waste, environmental and social impacts.

An innovation example in this regard is the adoption of Core Case sample packages. This product has revolutionized the industry by replacing old wood cases by recycled plastic cases. This replacement reduces wood use as a drilling input and contributes to plastic decrease and removal from nature.

Moreover, the recycled plastic cases manufactured by Core Case are more resistant and durable than wooden cases. This eliminates future waste by replacing cases, which have systems to ensure better worker safety and comfort. Such as stacking, pallet and handling protections.


A common occurrence in mining companies is the lack of sufficient warehouse space to store drill core. This makes them use warehouse external space which is constantly surrounded by case and pallet piles. This causes deterioration of identification and loss of core sample information.

Thus, a significant effort is being made by handling and transport personnel to manage storage rooms and absorb case streams. Frequent handling to reorganize storage rooms can result in the loss of core samples and valuable geologic information.

The trend in large mining companies is the creation of large central storage warehouses. Large enough to accommodate and store several projects or mines. These structures include solutions and technologies to facilitate and optimize core sample use and handling. Work benches with rolling systems, pallet holders, robotization and automatic, etc.

In this context, the implementation of tools to manage warehouse inventories and document case transfers and handling is essential.

Digital transformation, integrated systems and real-time data management

Drilling is a key method to acquire geologic information required for the exploitation, planning and operation of any mining enterprise.

However, it is characterized by its high costs and a complex activity chain. It includes sample extraction and case identification, transport, warehouse handling, description, sawing, sampling activities, analyses and storage.

In most companies, these activities are performed by several teams, both internal and external. Many of these processes are managed by sorted tools, whether physical or digital. However, this approach fragments and hinders integrated management of drilling operations.

In this sense, there are growing investments in integrated management systems that enable full process visibility throughout the chain.

The implementation of 4.0 industry technologies, IoT devices, Business Intelligence, analytics and management and control solutions is a reality.

Real-time data analysis tools enable timely problem identification for decision-making and correction purposes.

Core Case Tech’s CORE MANAGER allows users to track core sample cases from the moment they are stored to their final storage location. It optimizes inventory management, handling and drilling warehouse activities by using QR CODE and RFID technologies embedded in the cases.

Digital data collection and integrated management aim at increasing the efficiency of drilling operations. They reduce losses, waste, deviations and data errors from drilling by digitizing the controls.

A New Drilling Era

The drilling status quo is changing. It can be concluded that these five trends and technologies in drilling management show that the process can be understood differently. Large mining companies are aware of the trends that promise to revolutionize management, eliminating old, rudimentary practices.

Author: Marcéu Barreto
Review: Rochelle Kazap
Layout: Débora Souza
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