Calculate total shale thicknesses with sub-classification and uncertainty estimates

[fraserkeppie]

Brief Description:

Strip logs contain lithology descriptions by depth; stratigraphic logs contain horizon picks with depth; petrophysical logs contain numerical parameters characterizing different physical rock properties; and geochemistry logs contain numerical parameters characterizing different chemical rock properties. The use case should provide a way to sum the amount of shale in a given stratigraphic interval (bounded by either horizon picks or depth picks). Ideally, the sum will include intervals classified as all shale, as well as, portions of intervals where shale content is classified as having some percent of the whole. The intervals included in the sum should be able to be filtered on sub-classifications from petrophysical or geochemical cutoffs (for example, sum shale only where TOC > 2%, for example; only where kerogen type is 1, etc.). Gamma ray logs (or more fancy petrophysical algorithms) should provide a check for the verbal descriptions of shale; where gamma ray logs confirm or cast doubt on shale classification they should be used to provide an uncertainty estimate on the shale sums.

Actors:

users of this workflow want to classify the amount of hydrocarbon source rock that is in a basin; this specific use case is designed to extract source rock characterization from 1D well data.

Preconditions:

can assume that a strip log and companion stratigraphic, petrophysical, and geochemical logs all exist in a loadable format (e.g., LAS) with depth-data relationships specified.

Alternate Flows:

the use case should be adaptable to sum of sandstone or carbonate with sub-classification based on porosity logs, etc. to add the calculation of total reservoir thicknesses. Likewise, the use case should be adaptable to sum or any rock type with sub-classification based on other filter criteria from petrophysical and geochemical factors.

Exception Flows:

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Post-conditions:

the calculated sum(s) should be delivered along with a meta-data report that characterizes the source data and filters used to arrive at the sum.