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BrianMichellBrianMichell
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Merge branch 'main' into 624_prestack_schema
2 parents 9d8e0c8 + d6b8fd2 commit f220049

29 files changed

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-688
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‎docs/tutorials/quickstart.ipynb‎

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@@ -46,10 +46,10 @@
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]
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},
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{
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"\n",
@@ -75,6 +75,8 @@
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"\n",
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"MDIO uses [TGSAI/segy][segy-github] to parse the SEG-Y; the field names conform to its canonical keys defined in [SEGY Binary Header Keys][segy-binary-keys] and [SEGY Trace Header Keys][segy-trace-keys]. Since MDIO v1 we also introduced templates for common seismic data types. For instance, we will be using the `PostStack3DTime` template [here][mdio-template-poststack3dtime], which expects the same canonical keys.\n",
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"\n",
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"We will also specify the units for the time domain. The spatial units will be automatically parsed from SEG-Y binary header. However, there may be a case where it is corrupt in the file, for that see the [Fixing X/Y Units Issues](https://mdio-python.readthedocs.io/en/stable/tutorials/corrupt_files.html#fixing-x-y-units-issues) section.\n",
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"\n",
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"In summary, we will use the byte locations as defined for ingestion.\n",
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"\n",
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"[segy-github]: https://github.com/TGSAI/segy\n",
@@ -85,17 +87,20 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt\n",
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"from segy.schema import HeaderField\n",
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"from segy.standards import get_segy_standard\n",
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"\n",
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"from mdio import segy_to_mdio\n",
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"from mdio.builder.schemas.v1.units import TimeUnitModel\n",
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"from mdio.builder.template_registry import get_template\n",
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"\n",
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"teapot_trace_headers = [\n",
@@ -109,16 +114,17 @@
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"teapot_segy_spec = rev0_segy_spec.customize(trace_header_fields=teapot_trace_headers)\n",
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"\n",
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"mdio_template = get_template(\"PostStack3DTime\")\n",
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"unit_ms = TimeUnitModel(time=\"ms\")\n",
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"mdio_template.add_units({\"time\": unit_ms})\n",
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"\n",
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"segy_to_mdio(\n",
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" input_path=input_url,\n",
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" output_path=\"filt_mig.mdio\",\n",
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" segy_spec=teapot_segy_spec,\n",
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" mdio_template=mdio_template,\n",
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" overwrite=True,\n",
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")"
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],
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"outputs": [],
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"execution_count": null
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]
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},
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{
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"cell_type": "markdown",
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"from mdio import open_mdio\n",
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"\n",
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"dataset = open_mdio(\"filt_mig.mdio\")\n",
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"dataset"
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],
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"outputs": [],
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"execution_count": null
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]
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},
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{
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"cell_type": "markdown",
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"print(dataset[\"segy_file_header\"].attrs[\"textHeader\"])"
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],
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"outputs": [],
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"execution_count": null
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]
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},
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{
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"cell_type": "markdown",
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"dataset[\"segy_file_header\"].attrs[\"binaryHeader\"]"
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],
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"outputs": [],
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"execution_count": null
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]
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},
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"cell_type": "markdown",
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"dataset.sizes"
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],
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"outputs": [],
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"execution_count": null
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"dataset.inline"
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],
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"outputs": [],
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"execution_count": null
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"dataset.crossline"
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],
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"outputs": [],
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"execution_count": null
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]
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},
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"cell_type": "markdown",
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"from mdio.builder.schemas.v1.stats import SummaryStatistics\n",
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"\n",
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"il_dataset = dataset.sel(inline=278)\n",
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"il_amp = il_dataset[\"amplitude\"].T\n",
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"il_amp.plot(vmin=-2 * std, vmax=2 * std, cmap=\"gray_r\", yincrease=False);"
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],
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"outputs": [],
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]
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"twt_data = dataset[\"amplitude\"].sel(time=1000)\n",
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"twt_data.plot(vmin=-2 * std, vmax=2 * std, cmap=\"gray_r\", x=\"cdp_x\", y=\"cdp_y\");"
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],
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"outputs": [],
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"execution_count": null
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"name": "#%%\n"
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"outputs": [],
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"source": [
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"trace_mask = dataset.trace_mask[:]\n",
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"\n",
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"twt_data.plot(vmin=-2 * std, vmax=2 * std, cmap=\"gray_r\", x=\"cdp_x\", y=\"cdp_y\", alpha=0.5, figsize=(8, 5))\n",
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"trace_mask.plot(vmin=0, vmax=1, x=\"cdp_x\", y=\"cdp_y\", alpha=0.5);"
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],
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"outputs": [],
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"execution_count": null
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]
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},
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"cell_type": "code",
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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},
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"outputs": [],
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"source": [
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"dataset.headers[\"cdp_x\"].compute()"
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],
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]
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"name": "#%%\n"
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},
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"outputs": [],
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"source": [
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"dataset.headers[\"cdp_y\"].compute()"
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],
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"outputs": [],
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]
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"metadata": {
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"name": "#%%\n"
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"outputs": [],
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"source": [
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"xl_dataset = dataset.sel(crossline=100) # slices everything available in MDIO dataset!\n",
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"\n",
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"hdr_ax.set_xlabel(\"\")\n",
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"\n",
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"plt.tight_layout()"
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],
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"outputs": [],
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]
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"cell_type": "markdown",
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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"outputs": [],
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"source": [
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"from mdio import mdio_to_segy\n",
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"\n",
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" output_path=\"filt_mig_roundtrip.sgy\",\n",
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" segy_spec=teapot_segy_spec,\n",
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")"
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"from segy import SegyFile\n",
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" np.testing.assert_equal(original_segy.trace[idx], roundtrip_segy.trace[idx])\n",
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"\n",
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"print(\"Files identical!\")"
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"metadata": {
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"mystnb": {
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"execution_mode": "force"
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},
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"pygments_lexer": "ipython3",
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"version": "3.13.5"
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"mystnb": {
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"execution_mode": "force"
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},
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"widgets": {
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"application/vnd.jupyter.widget-state+json": {
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"state": {

‎pyproject.toml‎

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[project]
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name = "multidimio"
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version = "1.0.6"
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version = "1.0.7"
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description = "Cloud-native, scalable, and user-friendly multi dimensional energy data!"
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authors = [{ name = "Altay Sansal", email = "[email protected]" }]
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requires-python = ">=3.11,<3.14"
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warn_required_dynamic_aliases = true
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[tool.bumpversion]
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current_version = "1.0.6"
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current_version = "1.0.7"
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allow_dirty = true
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commit = false
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tag = false

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