Got a question today about the Well Log visualization that I thought I would work through here. We haven’t done much write up on the tool so I thought I would take a moment and sketch out this use case.
A point is a spot in space. In the world of geologic mapping, or mapping in general, it is represented by co-ordinates: X, Y on a plane; and X, Y, Z in 3-dimensions.
Using Ruths.ai 3D Subsurface Visualization, it is easy to identify/add a point in a spatial environment for reservoir management or geologic applications – marking a pick location of interest. A point can be marked along a wellbore, on a surface, in a seismic imagery, or in an empty space. What defines the positioning of a point is its X, Y, Z co-ordinates.
It is quite easy to include formation tops in the Ruths.ai Well Log Visualization. The neatest way to do that is to have a data table that contains the formation top depth for each well contained in the data table that has the well log data. In its most basic form, the formation tops data table should contain at least 3 columns: Formation Name, Top Depth and Well Name. Here is a video of how to add formation tops to Ruths.ai Well Log Visualization:
If you are a petroleum engineer and you have Spotfire installed on your computer, you’re further ahead than you realize. Sound strange? Here’s the hint:
Spotfire can be your tool for:
- visualizing and analyzing 3D subsurface map and
- diagramming well trajectory
And you can do all that in one environment.
Now, I’m guessing you thought that those analyses could only be done with some high-end expensive software from say Schlumberger, Halliburton, IHS, or Baker Hughes; not anymore.
Out of the box, Spotfire does not naturally load or represent seismic data. In this post, we will cover how we have extended the Spotfire platform with the Segy data source (available as part of the 3D Subsurface Visualization) which allows the loading, representation and visualization of seismic data in Spotfire.
In this post, we will extract the seismic binary data into a vanilla Spotfire table which we can visualize using a heatmap. In the next post, we will actually do some interpretation on the seismic, but for now we wanted to show how you can manipulate seismic data in TERR. We will add some dynamic interaction so the user can select different cross line or inline indices to extract and view in a heatmap. Once the data is extracted and visualized, we can color it, mark it, and build histograms with it. Ok let’s get started.