qaqc_tools⚓︎

Quality Assurance of the forecast (QA) and analysis (QC) step.

`QAQC` ⚓︎

Perform Quality Assurance of the forecast (QA) and analysis (QC) step. Available functions: 1) calc_coverage: check forecast data coverage 2) calc_mahalanobis: evaluate "higher-order" data coverage 3) calc_kg: check/write individual gain for parameters; flag data which have conflicting updates 4) calc_da_stat: compute statistics for updated parameters

`calc_coverage(line=None, field_dim=None)` ⚓︎

Calculate the Data coverage for production and seismic data. For seismic data the plotting is based on the importance-scaled coverage developed by Espen O. Lie from GeoCore.

Input: line: if not None, plot 1d coverage field_dim: if None, must import utm coordinates. Else give the grid

`calc_da_stat(options=None)` ⚓︎

Calculate statistics for the updated parameters. The persentage of parameters that have updates larger than one, two and three standard deviations (calculated from the initial ensemble) are flagged.

Input: options: Settings for statistics - write_to_file: write results to .grdecl file (default False)

`calc_kg(options=None)` ⚓︎

Check/write individual gain for parameters. Note form ES gain with an identity Cd... This can be improved

Visualization of the many of these parameters is problem-specific. In reservoir simulation cases, it is necessary to write this to the simulation grid. While for other applications, one might want other visualization. Hence, the method also depends on a simulator specific writer.

Input: options: Settings for the kalman gain computations - num_store: number of elements to store (default 10) - unique_time: calculate for each time instance (default False) - plot_all_kg: plot all the kalman gains for the field parameters, if not plot the num_store (default False) - only_log: only write to logger; no plotting (default True) - auto_ada_loc: use localization in computations (default True) - write_to_resinsight: pipe results to ResInsight (default False) (Note: this requires that ResInsight is open on the computer)

`calc_mahalanobis(combi_list=(1, None))` ⚓︎

Calculate the mahalanobis distance as described in "Oliver, D. S. (2020). Diagnosing reservoir model deficiency for model improvement. Journal of Petroleum Science and Engineering, 193(February). https://doi.org/10.1016/j.petrol.2020.107367"

Input: combi_list: list of levels and possible combination of datatypes. The list must be given as a tuple with pairs: level int: defines which level. default = 1 combi_typ: defines how data are combined: Default is no combine.

qaqc_tools⚓︎

QAQC ⚓︎

calc_coverage(line=None, field_dim=None) ⚓︎

calc_da_stat(options=None) ⚓︎

calc_kg(options=None) ⚓︎

calc_mahalanobis(combi_list=(1, None)) ⚓︎

`QAQC` ⚓︎

`calc_coverage(line=None, field_dim=None)` ⚓︎

`calc_da_stat(options=None)` ⚓︎

`calc_kg(options=None)` ⚓︎

`calc_mahalanobis(combi_list=(1, None))` ⚓︎