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3D mapping and Artificial Intelligence through machine learning
offers an array of exciting opportunities for geotechnical
engineering.
MACHINE LEARNING
APPLICATIONS IN
GEOTECHNICAL
ENGINEERING
Digital innovation can improve mining productivity as profits are challenged, miners
must have focus on improving productivity. Digital innovation could provide a
breakthrough in this respect.
In the short term, falling commodity prices are squeezing cash flow.
Looking ahead, many existing mines are maturing, resulting in the extraction of
lower ore grades and longer haul distances from the mine face; ore-body-
replacement rates are in decline; and new-mine-development times are increasing.
On top of this, worldwide mining operations are as much as 28 percent less
productive today than a decade ago—and that’s after adjusting for declining ore
grades.
APPLICATIONS FOR USE
WITHIN MINING
• uGPS Rapid Mapper Data
• 3D Laser Mapping - Universal Mobile Mapping Systems & Monitoring Software
• 3D LiDAR Applications
• Terrasolid – Point Cloud Processing Software
• Mine Vision Systems - 3D vision and mapping software
• MVS Convergence Monitoring system
• Leapfrog Geo modelling software
• Surpac modelling software
TECHNOLOGIES IN
EXPLORATION, MINING,
AND PROCESSING
Modern mineral exploration has been driven largely by technology.
Many mineral discoveries since the 1950s can be attributed to geophysical and
geochemical technologies developed by both industry and government.
Even though industrial investment in in-house exploration research and
development in the U.S decreased during the 1990s, new technologies, such as
tomographic imaging (developed by the medical community) and GPS (developed
by the defense community), were newly applied to mineral exploration.
Research in basic geological sciences, geophysical and geochemical methods, and
drilling technologies could improve the effectiveness and productivity of mineral
exploration. These fields sometimes overlap, and developments in one area are
likely to cross-fertilize research and development in other areas.
GEOLOGICAL METHODS
The focus of research on geological ore deposits has changed with new mineral
discoveries and with swings in commodity prices.
Geoscientists have developed numerous models of ore deposits (Cox and
Singer, 1992). Models for ore deposits that, when mined, have minimal impacts
on the environment (such as deposits with no acid-generating capacity) and for
deposits that may be amenable to innovative in-situ extraction will be important
for the future.
Because the costs of reclamation, closure, postmining land use, and long-term
environmental monitoring must be integrated into mine feasibility studies, the
health and environmental aspects of an orebody must be well understood
during the exploration stage.
A wealth of geologic data has been collected for some mining regions, but the
data are not currently being used because much of the data is on paper and
would be costly to convert to digital format.
GEOCHEMICAL AND
GEOPHYSICAL METHODS
Surface geochemical prospecting involves analyzing soil, rock, water, vegetation,
and vapor (e.g., mercury and hydrocarbons in soil gas) for trace amounts of
metals or other elements that may indicate the presence of a buried ore deposit.
Geochemical techniques have played a key role in the discovery of numerous
mineral deposits, and they continue to be a standard method of exploration.
increasingly sophisticated analytical techniques and equipment developed in the
past 50 years, exploration geologists have been able to detect smaller and
smaller concentrations of the elements of interest. Available analytical tools are
sufficient for most types of analyses required by the industry. However, new
technologies, such as laser fluorescence scanning and portable X-ray
fluorescence, which can directly determine concentrations of elements in rocks,
and differential leaching techniques are also being developed and used for
exploration.

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Mining and artificial intelligence - a new paradigm growing!

  • 1. 3D mapping and Artificial Intelligence through machine learning offers an array of exciting opportunities for geotechnical engineering.
  • 2. MACHINE LEARNING APPLICATIONS IN GEOTECHNICAL ENGINEERING Digital innovation can improve mining productivity as profits are challenged, miners must have focus on improving productivity. Digital innovation could provide a breakthrough in this respect. In the short term, falling commodity prices are squeezing cash flow. Looking ahead, many existing mines are maturing, resulting in the extraction of lower ore grades and longer haul distances from the mine face; ore-body- replacement rates are in decline; and new-mine-development times are increasing. On top of this, worldwide mining operations are as much as 28 percent less productive today than a decade ago—and that’s after adjusting for declining ore grades.
  • 3. APPLICATIONS FOR USE WITHIN MINING • uGPS Rapid Mapper Data • 3D Laser Mapping - Universal Mobile Mapping Systems & Monitoring Software • 3D LiDAR Applications • Terrasolid – Point Cloud Processing Software • Mine Vision Systems - 3D vision and mapping software • MVS Convergence Monitoring system • Leapfrog Geo modelling software • Surpac modelling software
  • 4. TECHNOLOGIES IN EXPLORATION, MINING, AND PROCESSING Modern mineral exploration has been driven largely by technology. Many mineral discoveries since the 1950s can be attributed to geophysical and geochemical technologies developed by both industry and government. Even though industrial investment in in-house exploration research and development in the U.S decreased during the 1990s, new technologies, such as tomographic imaging (developed by the medical community) and GPS (developed by the defense community), were newly applied to mineral exploration. Research in basic geological sciences, geophysical and geochemical methods, and drilling technologies could improve the effectiveness and productivity of mineral exploration. These fields sometimes overlap, and developments in one area are likely to cross-fertilize research and development in other areas.
  • 5. GEOLOGICAL METHODS The focus of research on geological ore deposits has changed with new mineral discoveries and with swings in commodity prices. Geoscientists have developed numerous models of ore deposits (Cox and Singer, 1992). Models for ore deposits that, when mined, have minimal impacts on the environment (such as deposits with no acid-generating capacity) and for deposits that may be amenable to innovative in-situ extraction will be important for the future. Because the costs of reclamation, closure, postmining land use, and long-term environmental monitoring must be integrated into mine feasibility studies, the health and environmental aspects of an orebody must be well understood during the exploration stage. A wealth of geologic data has been collected for some mining regions, but the data are not currently being used because much of the data is on paper and would be costly to convert to digital format.
  • 6. GEOCHEMICAL AND GEOPHYSICAL METHODS Surface geochemical prospecting involves analyzing soil, rock, water, vegetation, and vapor (e.g., mercury and hydrocarbons in soil gas) for trace amounts of metals or other elements that may indicate the presence of a buried ore deposit. Geochemical techniques have played a key role in the discovery of numerous mineral deposits, and they continue to be a standard method of exploration. increasingly sophisticated analytical techniques and equipment developed in the past 50 years, exploration geologists have been able to detect smaller and smaller concentrations of the elements of interest. Available analytical tools are sufficient for most types of analyses required by the industry. However, new technologies, such as laser fluorescence scanning and portable X-ray fluorescence, which can directly determine concentrations of elements in rocks, and differential leaching techniques are also being developed and used for exploration.