Tag: data

Predictions at locations where there are no measurements

By Richard Lane

A key feature problem in geological modelling is how to take scattered measurements and use these to make predictions at locations where there are no measurements. The data may be measurements on the surface, or samples taken from drilling, or channel samples taken while excavating. Figure 1 shows the basic problem. Solving this problem is fundamental to how Leapfrog software works, and it underpins the geological and mineralization models that are produced.

Figure 1: A simple scattered data problem. Estimate the value at the red cross from the blue samples.

Figure 1: A simple scattered data problem. Estimate the value at the red cross from the blue samples.

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Modifying your drillhole data: Interval Selections

By Sam Bain

The “Interval Selection” tool in Leapfrog combines most of the abilities of Grouping and Splitting (as discussed in previous blogs) with fewer restrictions. The Grouping and Splitting tools provide workflows for combining or splitting existing lithologies exclusively. The intervals selection is ideal when elements of both the grouping and splitting workflows need to be combined. For example, perhaps assay data indicates some intervals have been incorrectly logged and need to be assigned to a new lithology. If these intervals have been logged as several different lithologies then they need to be split from their old lithologies and then grouped to a single new lithology. The interval selection tool allows you to do this.

Figure 1: Right click the interval table and select the "Interval Selection" option

Figure 1: Right click the interval table and select the “Interval Selection” option

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Modifying your drillhole data: Splitting lithologies

By Sam Bain

The “Split Lithology” tool (available in Leapfrog Geo, Geothermal, and Hydro) creates a new lithology column by sub-dividing lithologies in an imported column. Often simple logging will result in repeating intervals on each drillhole and these will need to be separated for modelling purposes. As an example, perhaps three unique limestone units at different depths are encountered by exploratory drilling. These might all be logged simply as “Limestone”. In this case the splitting tool could be used to divide the “Limestone” intervals into “Upper”, “Middle”, and “Lower” units. Then each unit can be modelled separately. It is important to note that the original logged intervals are preserved, and the new splits are made in a new interval column. The modeller can correct or re-interpret the logging without altering the original field data.

This blog explains how the “Split Lithology” tool works by walking through a simple example.

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Drillhole Data Errors: Acknowledging a reality and dealing with it

By Sam Bain

Introduction

Everyone would like accurate and correct data. A lot of money is spent on trying to ensure the accuracy of data, whether it is from core logging, field mapping, or geophysical surveys. However, the reality is that mistakes and accidents will happen and some data will be wrong. Accepting that errors are always going to get in somehow, it makes sense to create systems and software that identify these errors, and then provide the tools to fix them. Good software packages help deal with data quality by identifying common errors on import of data and providing automated correction of these problems. Ideally there should be a person in the loop to ensure the identified data is an error and to decide how they should be dealt with.

Leapfrog software automatically highlights recognised data errors and in most cases provides automated or semi-automated correction tools for you. The principle source of errors is drillhole information and the drillhole interface prominently highlights recognised issues and offers you the ability to correct errors. Leapfrog software will also recognise errors and potential errors in imported locations and prompt user input to fix them.

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