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.

Core logging relies on the subjective interpretation (or best guess!) of a geologist who may be rushed, stressed, tired, or inexperienced. Assay data is more objective but can still contain errors from a range of possible mishaps. Records might be manually transcribed from one format to another and errors introduced. If errors from any one of these sources are not identified and corrected, they can flow through the modelling process and result in models that, while internally consistent, do not reflect the real geology.

Errors in the data

Leapfrog identifies a range of data errors. These include duplicate hole IDs, missing collars, contradictory interval from and to values, interval depth exceeding maximum depth from collar, overlapping intervals, no intervals for a collar, missing survey information, duplicate drillholes, missing hole IDs, non-numeric values, and missing values. An error occurring in a table is shown by a red cross on the table in the project tree.

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You can open the error correction dialog by right clicking and choosing “Fix Errors”.

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Leapfrog will display the erroneous rows and either provide an automated correction method or allow you to manually correct or ignore the row.

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Let’s have a look at an example of a drillhole error. In this case the imported data has conflicting maximum depths in the collar table and the lithology table. A red cross is shown on the lithology table. Opening the fix errors dialogue box will display the type of error and the row in which it occurs.

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Often the actual depth reached by drillholes exceeds that planned and recorded in the drillhole survey table. This simple and common error can be automatically corrected in Leapfrog by clicking the “Fix Collar Maxdepths” button and then clicking “OK”.

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The maximum depth for the identified hole is increased automatically in the collar table so that it now matches that in the lithology table. Alternatively, you could manually edit the lithology table in the dialog above so that its maximum depth matches that in the collar table.

Assay and other numeric data may contain invalid values such as missing values, non-numeric values, and negative values. These could be accidentally introduced or reflect a conscious choice when creating the drillhole data. Leapfrog identifies these situations and displays them by adding a red cross to the interval table.

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You can also define rules for specific values. In the example below, when the non-numeric value “missed” occurs you may wish to replace it with a “0”. A rule to do so is shown below, and has been created by clicking the “Add Rule” button.

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Once you have reviewed how these special values are handled and made the necessary changes you must click the check box in the bottom left and then “OK”. The red cross will then be removed from the assay column. To remove the cross from the assay table all columns must be reviewed.

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Errors in the interpretation

These errors are more subjective than data errors. They are introduced when the person recording the data makes a judgment which may prove incorrect. As much as we would like it to, Leapfrog cannot second guess data interpretation just yet! However, what we do provide is the three dimensional environment in which to see the data and identify these dubious interpretations, and the ability for the modeller to easily make new interpretations. Leapfrog allows you to rapidly create new interval columns based on existing interval tables. You can view and select the imported intervals in 3D and assign them to new or existing lithologies using the Split, Group, and Interval Selection tools. These tools will be covered in the following blog articles.

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