Nicholas Harvey
Feb 22, 20172 min
One of the fundamentals in designing LogScope was ease of use. The next release of LogScope will have the ability to import and store what we call discrete data. Discrete data can be defined as data that comes from a discrete point or interval that is generally sampled irregularly.
HRP will be releasing the discrete data module in the next major revision of LogScope, sometime around April 2017. For those interested in beta testing the module contact us here
An example of discrete data is core porosity and permeability samples. These are generally picked at the points along the core to help calibrate porosity, permeability, matrix density and saturation computations from other measurements (usually indirect wireline or logging while drilling measurements that need to have the level of uncertainty reduced.
Typically the data comes in a variety of different formats depending on age, analytical lab and technique that is used to collect the data. An example of the information supplied is shown in the figure below. Spreadsheet
Comparing this information with continuous measurements usually requires a one to one reference correspondence where the reference is typically depth. So whilst the display of data in a plot for comparison is intriguing the user is left with a lot of work to massage the data to meet the one to one correspondence. Depth indexed plot
LogScope is designed to allow direct comparison of continuous and discrete data by using some smart logic that finds the closest sample point and compares the data. This allows the points to be compared quickly and efficiently without the need for steps such as ensuring the data is on depth. The example below shows the use of regression to identify the equation for log computed versus core porosity
A video showing the simplicity of loading data is here.