{ "cells": [ { "cell_type": "markdown", "id": "9dd6180e-0e1d-4503-b991-cd35ea1f0fc0", "metadata": {}, "source": [ "# Real case: Mannsworth - Tomo2D \n", "\n", "This notebook implements the Tomography-like approach on data from [Barone et al. (2021)](https://doi.org/10.1007/s10712-021-09631-x)" ] }, { "cell_type": "code", "execution_count": 1, "id": "512a492a-6f40-400d-ab5b-8368dc60d1fb", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/alberto/anaconda3/envs/pyswapp/lib/python3.9/site-packages/obspy/core/util/base.py:26: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n", " import pkg_resources\n" ] } ], "source": [ "from pyswapp import *" ] }, { "cell_type": "code", "execution_count": 2, "id": "19f263e8-a0ec-4dd7-a69b-f68f44447b1c", "metadata": {}, "outputs": [], "source": [ "# directories\n", "prj_dir = '../../data/real_data' # project directory\n", "path2raw = os.path.join(prj_dir,'raw') # path to raw data\n", "path2geom = f'{prj_dir}/Geometry_mannsworth.csv' # path to the geometry file" ] }, { "cell_type": "code", "execution_count": 3, "id": "f0b656ab-caaf-498f-85b4-65a6986cdad3", "metadata": {}, "outputs": [], "source": [ "# processing and plotting settings\n", "settings = create_settings(fmin=5, fmax=30, # frequency range\n", " vmin=10, vmax=500, velstep=1) # testing phase velocity range and step" ] }, { "cell_type": "code", "execution_count": 4, "id": "1750ee9f-c04e-48b5-887b-28238a2b648e", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Warning: Ignoring XDG_SESSION_TYPE=wayland on Gnome. Use QT_QPA_PLATFORM=wayland to run on Wayland anyway.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Loading project:\n", "Reading seismic shot files ..... 10.33 s\n", "Read 82 files and applied geometry and settings.\n", "Active procset label: tomo2D\n", "\n", "Existing procsets: raw proc1 tomo2D\n", "Loading amplitude data from \"tomo2D\" ..... 0.25 s\n", "\n" ] } ], "source": [ "swam = Tomo2DManager(f'{prj_dir}/proc/tomo2D', # project directory path\n", " path2raw=path2raw, # optional, copy & per default rename data from path (outside project directory)\n", " path2geom=path2geom, # optional, copy geom from path (outside project directory)\n", " settings=settings, # optional, define settings for visualisations and processing\n", " rename = False, # optional, rename copied raw data to preferred filename format (Shotfile_), default value is False!\n", " overwrite = False, # optional, overwrite database .db file if it already exists --> create new project data base\n", " )" ] }, { "cell_type": "code", "execution_count": 5, "id": "9378d703-44f8-4990-b897-2b9feed48e54", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Active procset label: tomo2D\n" ] } ], "source": [ "# set a new procset label\n", "procset = 'tomo2D'\n", "swam.set_procset_label(procset)" ] }, { "cell_type": "code", "execution_count": 6, "id": "7d057b77-bb7e-4a3e-ad3d-e7a6601625b0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Trimming data based on offset (SIN,REP) = (43, 2) ..... 9.67 s\n" ] } ], "source": [ "# Retrieve subsets from data corresponding to forward and reverse shots\n", "swam.prepare_streams(min_offset=5, #max_offset=1e6,\n", " min_rec =12, #max_rec=None\n", " )" ] }, { "cell_type": "markdown", "id": "52bf402e-2ea9-41dc-9880-365d3b639fbd", "metadata": {}, "source": [ "### A. Pick interactively the FK filter" ] }, { "cell_type": "code", "execution_count": 7, "id": "94fc615e-c078-4a6b-9dea-1f54daf5bd55", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Loading the GUI ..... 2.32 s\n", "Applying FK filter to (SIN,REP,WID) = (1, 1, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (1, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (2, 1, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (2, 2, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (3, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (3, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (4, 1, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (4, 2, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (5, 1, 0) and writing to database..... 0.09 s\n", "Applying FK filter to (SIN,REP,WID) = (5, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (6, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (6, 2, 0) and writing to database..... 0.09 s\n", "Applying FK filter to (SIN,REP,WID) = (6, 2, 1) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (7, 2, 0) and writing to database..... 0.09 s\n", "Applying FK filter to (SIN,REP,WID) = (8, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (9, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (9, 2, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (10, 1, 0) and writing to database..... 0.09 s\n", "Applying FK filter to (SIN,REP,WID) = (10, 2, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (11, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (11, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (12, 1, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (12, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (13, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (14, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (15, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (16, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (17, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (17, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (18, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (18, 2, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (19, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (19, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (20, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (20, 2, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (21, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (21, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (22, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (22, 2, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (23, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (23, 2, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (24, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (24, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (25, 1, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (25, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (26, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (26, 2, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (27, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (27, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (28, 1, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (28, 2, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (29, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (29, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (30, 1, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (30, 2, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (31, 1, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (31, 2, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (32, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (32, 2, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (33, 1, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (33, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (34, 1, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (34, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (35, 1, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (35, 2, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (36, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (36, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (37, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (37, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (38, 1, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (38, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (39, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (39, 2, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (40, 1, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (40, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (41, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (41, 2, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (42, 1, 0) and writing to database..... 0.08 s\n", "Applying FK filter to (SIN,REP,WID) = (42, 2, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (43, 1, 0) and writing to database..... 0.07 s\n", "Applying FK filter to (SIN,REP,WID) = (43, 2, 0) and writing to database..... 0.07 s\n" ] } ], "source": [ "# Isolate the fundamental mode in FK domain\n", "swam.gui_interact('filter','FK')" ] }, { "cell_type": "code", "execution_count": 8, "id": "10b97132-ca32-490b-adf3-6010ed5a48e1", "metadata": {}, "outputs": [], "source": [ "# save picked filter from database to disk for whole procset\n", "swam.save_filter(fname = f'{prj_dir}/proc/FKfilter.txt', ftype='FK')" ] }, { "cell_type": "markdown", "id": "508f7b45-daeb-4882-85b2-91590a020ee7", "metadata": {}, "source": [ "### B. Apply an existing FK filter" ] }, { "cell_type": "code", "execution_count": 7, "id": "7c61e791-0e2d-4497-82b2-35821bb5bfb3", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Applying FK filter to (SIN,REP) = (43, 2) ..... 76.61 s\n" ] } ], "source": [ "# Filter in FK based on a file containing the filter (points along line to mute data abov or below)\n", "path2fk = f'{prj_dir}/proc/FKfilter.txt' # path to the geometry file\n", "\n", "swam.import_filter(fname = path2fk)\n", "swam.apply_filter(ftype = 'FK')" ] }, { "cell_type": "markdown", "id": "b9a8c6a0-3335-4971-9fd1-92066bacaeee", "metadata": {}, "source": [ "## Phase diff and run tomo" ] }, { "cell_type": "code", "execution_count": 8, "id": "f8c111da-06e7-4b10-b516-af2719b48618", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Calculating phase differences for (SIN,REP) = (43,2) ..... 6.15 s\n", "Calculating mean and std of phase differences for (SIN) = (43) ..... 2.01 s\n" ] } ], "source": [ "# compute phase differences\n", "swam.compute_phasediff()" ] }, { "cell_type": "code", "execution_count": 9, "id": "9c671dc4-9dce-4c01-be16-af43e8e778a2", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Running tomographic-like approach\n", " 5.00 Hz | Cost = 1.517\n", " 5.50 Hz | Cost = 1.137\n", " 6.00 Hz | Cost = 1.586\n", " 6.50 Hz | Cost = 0.953\n", " 7.00 Hz | Cost = 1.065\n", " 7.50 Hz | Cost = 0.901\n", " 8.00 Hz | Cost = 0.832\n", " 8.50 Hz | Cost = 0.823\n", " 9.00 Hz | Cost = 0.819\n", " 9.50 Hz | Cost = 0.723\n", " 10.00 Hz | Cost = 0.766\n", " 10.50 Hz | Cost = 0.817\n", " 11.00 Hz | Cost = 0.602\n", " 11.50 Hz | Cost = 0.677\n", " 12.00 Hz | Cost = 0.773\n", " 12.50 Hz | Cost = 0.856\n", " 13.00 Hz | Cost = 1.033\n", " 13.50 Hz | Cost = 1.024\n", " 14.00 Hz | Cost = 0.871\n", " 14.50 Hz | Cost = 0.822\n", " 15.00 Hz | Cost = 0.885\n", " 15.50 Hz | Cost = 1.046\n", " 16.00 Hz | Cost = 1.154\n", " 16.50 Hz | Cost = 1.021\n", " 17.00 Hz | Cost = 1.081\n", " 17.50 Hz | Cost = 1.375\n", " 18.00 Hz | Cost = 3.241\n", " 18.50 Hz | Cost = 1.782\n", " 19.00 Hz | Cost = 1.081\n", " 19.50 Hz | Cost = 1.162\n", " 20.00 Hz | Cost = 2.098\n", " 20.50 Hz | Cost = 1.533\n", " 21.00 Hz | Cost = 1.747\n", " 21.50 Hz | Cost = 1.660\n", " 22.00 Hz | Cost = 1.398\n", " 22.50 Hz | Cost = 2.765\n", " 23.00 Hz | Cost = 1.369\n", " 23.50 Hz | Cost = 1.615\n", " 24.00 Hz | Cost = 3.270\n", " 24.50 Hz | Cost = 4.931\n", " 25.00 Hz | Cost = 1.553\n", " 25.50 Hz | Cost = 4.242\n", " 26.00 Hz | Cost = 1.867\n", " 26.50 Hz | Cost = 4.787\n", " 27.00 Hz | Cost = 6.094\n", " 27.50 Hz | Cost = 4.801\n", " 28.00 Hz | Cost = 5.673\n", " 28.50 Hz | Cost = 7.087\n", " 29.00 Hz | Cost = 5.376\n", " 29.50 Hz | Cost = 6.181\n", " 30.00 Hz | Cost = 4.324\n", "Finished tomographic-like approach ..... 125.91 s\n" ] } ], "source": [ "# offset in meters\n", "min_offset = 10 \n", "max_offset = 12\n", "err_r = 2/100\n", "lam = 20\n", "\n", "typ = 'tomo2D'\n", "\n", "# Run the tomo2D\n", "swam.run(lam = lam, min_offset = min_offset, max_offset = max_offset, rel_err = err_r)\n", "#swam.run(min_offset = min_offset, max_offset = max_offset, rel_err = err_r, opt_lam=True)" ] }, { "cell_type": "code", "execution_count": 10, "id": "71c97869-8152-4273-9ab7-6fae2ea63b27", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# plot pseudosection\n", "c_map = 'jet'\n", "\n", "fig,ax = plt.subplots(figsize=(8,3))\n", "swam.plot('pseudosection', method = typ, cmap = c_map, axes = ax,\n", " vmin = 120, vmax = 270,\n", " fmin = 10, fmax = 25\n", " )\n", "fig.suptitle(f'lam = {lam}, min_offset = {min_offset}, max_offset = {max_offset}, rel_err = {err_r}', fontsize=10)\n", "fig.tight_layout(rect=[0, 0, 1, 0.95])\n", "\n", "fig.savefig(f'{prj_dir}/proc/tomo2D/04_figs/pseudo_tomo2d_raw.png', dpi=200)" ] }, { "cell_type": "code", "execution_count": 11, "id": "86d7a102-5933-434a-812e-dc879eb0c96e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Applying smooth to dispersion curves ..... 3.56 s\n" ] } ], "source": [ "# Process the dispersion curves\n", "swam.process_curves(type = 'smooth', method = typ)" ] }, { "cell_type": "code", "execution_count": 12, "id": "7b24f8a3-1636-4fb4-a4f3-11431555134a", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "c_map = 'jet'\n", "\n", "fig,ax = plt.subplots(figsize=(8,3))\n", "swam.plot('pseudosection', method = typ, cmap = c_map, axes = ax,\n", " vmin = 120, vmax = 280,\n", " fmin = 10, fmax = 25\n", " )\n", "fig.suptitle(f'lam = {lam}, min_offset = {min_offset}, max_offset = {max_offset}, rel_err = {err_r}', fontsize=10)\n", "fig.tight_layout(rect=[0, 0, 1, 0.95])\n", "\n", "fig.savefig(f'{prj_dir}/proc/tomo2D/04_figs/pseudo_tomo2d_smooth.png', dpi=200)" ] }, { "cell_type": "code", "execution_count": 13, "id": "50dc0138-59ba-4e40-9c38-7f8768ed9a6b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Saving disperion curves to \"../../data/real_data/proc/tomo2D/03_proc/tomo2D_tomo2D/Mode0\" ..... 0.47 s\n" ] } ], "source": [ "# Save the dispersion curves\n", "swam.save(procset=procset, method=typ, dc_mode=0, format = 'csv')" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.23" } }, "nbformat": 4, "nbformat_minor": 5 }