I want to calculate the Moving RMS on first break pics for seismic data.

Hello. So I need to calculate the moving RMS for first break pics. I have already made a code to display the first break picks which is:

% Define the file name

file_name = 'RL7000SL8000.prn';

% Import data from the .prn file

data = importdata(file_name);

% Extract the three columns: source x, receiver x, and First Break Picks

source_x = data(:, 1);

receiver_x = data(:, 2);

first_break_picks = data(:, 3);

% Replace negative or zero values in first break picks with NaN

first_break_picks(first_break_picks <= 0) = NaN;

% Get unique source x locations

unique_source_x = unique(source_x);

num_sources = numel(unique_source_x);

% Define a colormap with enough colors for the unique source x locations

color_map = lines(num_sources);

% Create a new figure for the plot

figure;

% Plot lines for each unique source x location with a unique color

for i = 1:num_sources

source_x_location = unique_source_x(i);

idx = source_x == source_x_location;

% Plot the data with a unique color and label

plot(receiver_x(idx), first_break_picks(idx), 'Color', color_map(i, :), 'DisplayName', ['Source X = ', num2str(source_x_location)]);

hold on;

end

% Add axis labels and title

xlabel('Receiver X');

ylabel('First Break Picks');

title('First Break Picks vs. Receiver X for Different Source X Locations');

% Reverse the Y-axis so that 0 is at the top

set(gca, 'YDir', 'reverse');

% Add a legend to distinguish the source x locations

legend('Location', 'Best');

grid on;

% Customize the colors and line styles as needed

% Display the plot

hold off;

I have read the instructions on Moving RMS, but I have no clue how to utilize it on my code.

[Mathieu NOE]

hi

would be helpful to have your data file as well - otherwise no one is going to work on your problem

[Lucas Spriggs]

Hi, sorry thanks for the heads up. I edited and attached my data. However I had to change it back to an excel file, as I could not upload a .prn file.

[Star Strider]

If you want to upload a .prn (or any other extension), use the zip function to enclose it in a .zip file, and then upload that. So long as it meets the file size limits, that should work. (It always helps for us to know what the file actually is, for example .txt, .csv, or something else.)

Answer 1

[Mathieu NOE]

hello again

see below , now you have the RMS values displayed in the legend (or you wanted to make a separate plot ? )

% Define the file name
file_name = 'RL7000SL8000.xlsx';
% Import data from the .prn file
data = importdata(file_name);
% Extract the three columns: source x, receiver x, and First Break Picks
source_x = data(:, 1);
receiver_x = data(:, 2);
first_break_picks = data(:, 3);
% Replace negative or zero values in first break picks with NaN
first_break_picks(first_break_picks <= 0) = NaN;
% Get unique source x locations
unique_source_x = unique(source_x);
num_sources = numel(unique_source_x);
% Define a colormap with enough colors for the unique source x locations
color_map = lines(num_sources);
% Create a new figure for the plot
figure;
% Plot lines for each unique source x location with a unique color
for k = 1:num_sources
    source_x_location = unique_source_x(k);
    idx = source_x == source_x_location;
    
    % Plot the data with a unique color and label
    x = receiver_x(idx);
    y = first_break_picks(idx);
    y_rms = sqrt(mean(y.^2));
    plot(x, y, 'Color', color_map(k, :), 'DisplayName', ['Source X = ', num2str(source_x_location), ' / RMS = ', num2str(y_rms)]);
    
    hold on;
end
% Add axis labels and title
xlabel('Receiver X');
ylabel('First Break Picks');
title('First Break Picks vs. Receiver X for Different Source X Locations');
% Reverse the Y-axis so that 0 is at the top
set(gca, 'YDir', 'reverse');
% Add a legend to distinguish the source x locations
legend('Location', 'Best');
grid on;
% Customize the colors and line styles as needed
% Display the plot
hold off;

[Lucas Spriggs]

Awesome thank you. The RMS on each source is very useful.

[Mathieu NOE]

as always, my pleasure !