Heteroegenous media analysis workflows (darsia.presets.fluidflower)

Submodules

darsia.presets.fluidflower.benchmarkco2model module

Module containing presets for concentration analyses as used for analyzing the benchmark experiments.

benchmark_binary_cleaning_preset(base, options)

Cleaning methods also used in the benchmark_concentration_analysis_preset.

Parameters:

• base (darsia.Image) – baseline image

• options (dict) – options same as in benchmark_concentration_analysis_preset.

benchmark_concentration_analysis_preset(base, labels, options)

The strategy for identifying any phase is constructed as a pipeline of the following steps:

1. Use monochromatic signal reduction

2. Restoration (upscaling) of signal

3. Prior strategy providing a first detection.

   1. Thresholding.

   2. binary inpainting

   3. resizing and smoothing

   4. conversion to boolean data

4. Posterior strategy reviewing the first three steps.

Parameters:

• base (darsia.Image) – baseline image

• labels (np.ndarray) – labeling of domain in facies

• options (dict) – dictionary holding all tuning parameters

Returns:

concentration analysis for detecting CO2.

Return type:

darsia.ConcentrationAnalysis

darsia.presets.fluidflower.fluidflowerco2analysis module

Standardized FluidFlower analysis.

It will require further information for specific rigs to be obtained through multiple inheritance.

class FluidFlowerCO2Analysis(baseline, config, results, update_setup=False, verbosity=0)

Bases: CO2Analysis

Class for managing the FluidFlower CO2 images as those acquired in the benchmark analysis.

batch_analysis(images, **kwargs)

Standard batch analysis.

Parameters:

• images (list of Path) – paths to batch of images.

• kwargs – optional keyword arguments used in single_image_analysis.

define_co2_analysis()

FluidFlower Benchmark preset for detecting CO2.

Returns:

detector for CO2

Return type:

PriorPosteriorConcentrationAnalysis

define_co2_gas_analysis()

FluidFlower Benchmark preset for detecting CO2 gas.

Returns:

detector for CO2(g)

Return type:

PriorPosteriorConcentrationAnalysis

determine_co2()

Extract CO2 from currently loaded image, based on a reference image.

Returns:

binary image of spatial CO2 distribution.

Return type:

darsia.Image

determine_co2_gas()

Extract CO2(g) from currently loaded image, based on a reference image.

Returns:

binary image of spatial CO2(g) distribution.

Return type:

darsia.Image

determine_co2_gas_mask(co2)

Determine CO2.

Parameters:

co2 (darsia.Image) – boolean image detecting all co2.

Returns:

boolean image detecting CO2(g).

Return type:

darsia.Image

determine_co2_mask()

Determine CO2.

Returns:

boolean image detecting CO2.

Return type:

darsia.Image

load_and_process_image(path)

Load image for further analysis. Do all corrections and processing needed.

Parameters:

path (str or Path) – path to image

Returns:

processed image

Return type:

darsia.Image

single_image_analysis(img, **kwargs)

Standard workflow to analyze CO2 phases.

Parameters:

• image (Path or Image) – path to single image.

• kwargs –

  optional keyword arguments: plot_contours (bool): flag controlling whether the original image

  is plotted with contours of the two CO2 phases; default False.

  write_contours_to_file (bool): flag controlling whether the plot from

  plot_contours is written to file; default False.

  write_segmentation_to_file (bool): flag controlling whether the

  CO2 segmentation is written to file, where water, dissolved CO2 and CO2(g) get decoded 0, 1, 2, respectively; default False.

  write_coarse_segmentation_to_file (bool): flag controlling whether

  a coarse (280 x 150) representation of the CO2 segmentation from write_segmentation_to_file is written to file; default False.

color_correction

Color correction based on reference colors.

config

Config dict from file.

curvature_correction

Curvature correction.

deformation_correction

Local deformation correction wrt. baseline image.

drift_corrected_base

Baseline image corrected for drift only.

drift_correction

Drift correction wrt. baseline image.

height

Physical height of image.

origin

Physical origin of origin voxel.

processed_baseline_images

List of corrected baseline images.

reference_date

translation_correction

Translation correction based on fixed absolute translation.

uncorrected_base

Baseline image stored as physical image but without corrections.

width

Physical width of image.

darsia.presets.fluidflower.fluidflowerrig module

Module containing the general setup for a fluidflower rig with segmented geometry.

class FluidFlowerRig(baseline, config, update_setup=False)

Bases: AnalysisBase

batch_analysis(images, **kwargs)

Standard batch analysis.

Parameters:

• images (list of Path) – paths to batch of images.

• kwargs – optional keyword arguments used in single_image_analysis.

load_and_process_image(path)

Load image for further analysis. Do all corrections and processing needed.

Parameters:

path (str or Path) – path to image

Returns:

processed image

Return type:

darsia.Image

single_image_analysis(img, **kwargs)

Standard workflow to analyze CO2 phases.

Parameters:

• image (Path or Image) – path to single image.

• kwargs – optional keyword arguments

color_correction

Color correction based on reference colors.

config

Config dict from file.

curvature_correction

Curvature correction.

deformation_correction

Local deformation correction wrt. baseline image.

drift_corrected_base

Baseline image corrected for drift only.

drift_correction

Drift correction wrt. baseline image.

height

Physical height of image.

origin

Physical origin of origin voxel.

processed_baseline_images

List of corrected baseline images.

reference_date

translation_correction

Translation correction based on fixed absolute translation.

uncorrected_base

Baseline image stored as physical image but without corrections.

width

Physical width of image.

darsia.presets.fluidflower.fluidflowertraceranalysis module

Standardized tracer concentration analysis.

Applicable for the tracer experiments in the FluidFlower (and other similar assets), allowing for heterogeneous media.

class FluidFlowerTracerAnalysis(baseline, config, results, update_setup=False, verbosity=0)

Bases: TracerAnalysis

Class for managing the well test of the FluidFlower benchmark.

batch_analysis(images, **kwargs)

Standard batch analysis.

Parameters:

• images (list of Path) – paths to batch of images.

• kwargs – optional keyword arguments used in single_image_analysis.

calibrate_balancing(calibration_images, options)

Calibration routine aiming at decreasing the discontinuity modulus across interfaces of the labeling.

Parameters:

• calibration_images (list of Path) – calibration images.

• options (dict) – parameters for calibration.

calibrate_model(calibration_images, options)

Calibration routine aiming at matching the injection rate

NOTE: Calling this routine will require the definition of a geometry for data integration.

Parameters:

• calibration_images (list of Path) – calibration images.

• options (dict) – parameters for calibration.

define_tracer_analysis()

Identify tracer concentration using a reduction to the grayscale space.

determine_tracer(return_volume=False)

Extract tracer from currently loaded image, based on a reference image.

Parameters:

return_volume (bool) – flag controlling whether the volume of the fluid in the porous geometry is returned.

Returns:

image array of spatial concentration map float, optional: occupied volume by the fluid in porous geometry

Return type:

darsia.Image

load_and_process_image(path)

Load image for further analysis. Do all corrections and processing needed.

Parameters:

path (str or Path) – path to image

Returns:

processed image

Return type:

darsia.Image

single_image_analysis(img, **kwargs)

Standard workflow to analyze the tracer concentration.

Parameters:

• image (Path) – path to single image.

• kwargs – optional keyword arguments, see batch_analysis.

Returns:

tracer concentration map dict: dictinary with all stored results from the post-analysis.

Return type:

np.ndarray

color_correction

Color correction based on reference colors.

config

Config dict from file.

curvature_correction

Curvature correction.

deformation_correction

Local deformation correction wrt. baseline image.

drift_corrected_base

Baseline image corrected for drift only.

drift_correction

Drift correction wrt. baseline image.

height

Physical height of image.

origin

Physical origin of origin voxel.

processed_baseline_images

List of corrected baseline images.

reference_date

translation_correction

Translation correction based on fixed absolute translation.

uncorrected_base

Baseline image stored as physical image but without corrections.

width

Physical width of image.