Category Archives: Tutorial

Visualization tips for geoscientists: Matlab, part II

Posted on by
4

Introduction

In my previous post on this topic I left two loose ends: one in the main text about shading in 3D, and one in the comment section to follow-up on a couple of points in Evan’s feedback. I finally managed to go back and spend some time on those and that is what I am posting about today.

Part 1 – apply shading with transparency in 3D with the surf command

I was trying to write some code to apply the shading with transparency and the surf command. In fact, I’ve been trying, and asking around in the Matlab community for more than one year. But to no avail. I think it is not possible to create the shading directly that way. But I did find a workaround. The breakthrough came when I asked myself this question: can I find a way to capture in a variable the color and the shading associated with each pixel in one of the final 2D maps from the previous post? If I could do that, then it would be possible to assign the colors and shading in that variable using this syntax for the surf command:

surf(data,c);

where data is the gravity matrix and c is the color and shading matrix. To do it in practice I started from a suggestion by Walter Robertson on the Matlab community in his answer to my question on this topic.

The full code to do that is below here, followed by an explanation including 3 figures. As for the other post, since the data set I use is from my unpublished thesis in Geology, I am not able to share it, and you will have to use your own data, but the Matlab code is simply adapted.

%% cell 1
figure;
shadedpcolor(x,y,data,(1-normalise(slope)),[-5.9834 2.9969],[0 1],0.45,cube1,0);
axis equal; axis off; axis tight
shadedcolorbar([-5.9834 2.9969],0.55,cube1);

In cell 1 using again shadedpcolor.m, normalise.m, and cube1 color palette I create the 2D shaded image, which I show here in Figure 1.

Figure 1



 Continue reading →

					

		
		
	


				
					
	

		

						
Visualization tips for geoscientists – Matlab

			
						

				Posted on   by  			

			
						

				9			

					


				

			
Introduction


In my last post I described how to create a powerful, nondirectional shading for a geophysical surface using the slope of the data to assign the shading intensity (i.e. areas of greater slope are assigned darker shading). Today I will show hot to create a similar effect in Matlab.


Since the data set I use is from my unpublished thesis in Geology, I am not able to share it, and you will have to use your own data, but the Matlab code is simply adapted. The code snippets below assume you have a geophysical surface already imported in the workspace and stored in a variable called “data”, as well as the derivative in a variable called “data_slope”.


Method 1 – with a slope mask and transparency


Some time ago I read this interesting Image Processing blog post by Steve Eddins at Mathworks on overlaying images using transparency. I encourage readers to take a look at this and other posts by Steve, he’s great! That particular blog post gave me the idea to use transparency and the slope to create my favorite shading in Matlab.


In addition to the code below you will need normalise.m from Peter Kovesi‘s website, and to import the color palette cube1.


%% alpha transparency code snippet
black = cat(3, zeros(size(data)), zeros(size(data)), ...
    zeros(size(data)));             % make a truecolor all-black image
gray=black+0.2;                     % make a truecolor all-gray image
alphaI=normalise(data_slope);       % create transparency weight matrix
                                    % using data_slope

imagesc(data);colormap(cube1);      % display data
hold on
h = imagesc(gray);                  % overlay gray image on data
hold off
set(h, 'AlphaData', alphaI);        % set transparency of gray layer using
axis equal;                         % weight matrix
axis tight;
axis off;


And here is the result in Figure 1 below – not bad!




Figure 1. Shaded using transparency


 Continue reading →

					

		
		
	


				
					
	

		

						
Compare lists from text files using Matlab – an application for resource exploration

			
						

				Posted on   by  			

			
						

				5			

					


				

			
INTRODUCTION


With today’s post I would like to share a Matlab script I used often to compare lists of ID numbers stored in separate text files. The ID numbers can be of anything: oil and gas wells, mining diamond drill hole locations, gravity or resistivity measurement stations, outcrop locations, you name it. And the script will handle any combination of ASCII characters (numbers, letters, etcetera).


I included below here some test files for you to try with the code, which is in the next section. Please refer to the comment section in the code for usage and file description. Have fun, and if you try it on your lists, let me know how it works for you.


TEST FILES


These files are in doc format; they need to be downloaded and saved as plain txt files. Test1 and Test2 contain 2 short lists of (fake) Canadian Oil and Gas wells; the former is the result of a search using a criterion (wells inside a polygonal area), the latter is a list of wells that have digital wireline logs. Test3 and Test4 are short lists of (fake) diamond drill holes.


*** Notice that script is setup to compare list in Test2.txt against list in Test1.txt and not the other way around. If using this on your own lists, you will have to decide in advance which subset of wells you are interested in.


Test1


Test2


Test3


Test4


THE SCRIPT


Here is the code:


 Continue reading →

					

		
		
	


				
					
	

		

						
Image processing tips for geoscientists – 1

			
						

				Posted on   by  			

			
						

				10			

					


				

			
Today I would like to show a way to quickly create a pseudo-3D display from this map:


Original image


The map is a screen capture of a meandering river near Galena, Alaska, taken in Google Earth. I love this image; it is one of my favorite maps for several reasons. First of all it is just plainly and simply a stunningly beautiful image. Secondly, and more practically, the meanders look not too dissimilar to what they would appear on a 3D seismic time slice displayed in grayscale density which is great because it is difficult to get good 3D seismic examples to work with. Finally, this is a good test image from the filtering standpoint as it has a number of linear and curved features of different sizes, scales, and orientation.The method I will use to enhance the display is the shift and subtract operation illustrated in The Scientist and Engineer’s Guide to Digital Signal Processing along with other 3×3 edge modification methods. The idea is quite simple, and yet extremely effective – we convolve the input image with a filter like this one:


0  0  0
0  1  0
0  0 -1


 Continue reading →