In Danomics Petrophysics Insights users are guided through a workflow that walks them through a number of modules. These modules are located via a dropdown menu at the top center of the window. The modules are listed in the order in which a user should ideally proceed through a project. However, this order is not strictly enforced and the user can start at any module and can seamlessly move both forward and back through the modules. This help article will focus on the Curve Normalization module.
The curve normalization module is activated by selecting “Curve Normalization” from the module selection dropdown located in the top middle area of the page.
Danomics performs curve normalizations by using the data distribution from the Stats Window (see Setup Module) range in the key well for its reference. There are three normalization methods available:
- Simple Shift
- Simple Scale
- Advanced Scale
Note that when you click to normalize you will not see any change in the key well. This is because normalizations are done relative to the key well. You will see the changes occur if you navigate to non-key wells.
The simple shift option requires the user to enter the percentile value in the data distribution that they wish to align (e.g., the P50). This will then shift the values in the non-key wells so that they match the values in the key well. For example, if the selected percentile has a value of 75 in the key well and a value of 80 in the non-key well for a curve, the values at all depth steps in the non-key well will be shifted 5 units lower.
The simple scale option performs a stretch/squeeze operation between the two values entered. For example, if you use the default values (P10 and P90) all non-key wells will have their distribution stretched/squeezed using a linear interpolation in order to make the values in the non-key wells match those of the key well.
The advanced scale option performs a two-sided stretch squeeze. It will stretch/squeeze the data asymmetrically between the low/mid/high percentile values given by the user. Although this option can work well if data is highly skewed, the user should thoroughly QC outputs and check for intended behavior.
QC’ing Curve Normalization Results
Understanding how normalization has affected your data set is quite important, and as such, Danomics has built in several curve normalization QC cross-sections and maps. In an active cross-section tab there are options to show a “Normalization QC” template for all of the relevant curves. Below is an example of the GR Normalization QC plot, with some wells being shifted to lower values (red shading) and some shifted to higher values (blue shading).
In the example above the leftmost well has been shifted entirely to higher values. In the next well, the low values have been shifted higher and the high values have shifted lower (a squeezed distribution). On the rightmost well, the values have been shifted entirely to lower values.
There are also maps that can be displayed that show the RMS (root mean squared) values for each of the curves on a zone-by-zone basis. These can be helpful for recognizing when spatially dependent features such as facies changes may have implications for curve normalization.
Key Well and Normalization
Inasmuch as all of the normalization are made relative to a key well, it is exceedingly important that you select a key well that has a representative data range. A poor selection of the key well will result in challenged results. Furthermore, normalization (and parameter re-mapping) are based only on the distribution set for the Stats Window Range, as dictated in the Setup module. Therefore, it is important that the user carefully select the desired log interval to use.
Note that normalizations can be performed on a well-by-well basis, so users have flexibility on how to control results.
Auto-Eval (Parameter Remapping)
Danomics parameter re-mapping (auto-eval) can be used in place of or in tandem with curve normalization. Whereas normalization affects the curve values so that more consistent parameter values can be selected for an analysis, parameter remapping adjusts petrophysical parameters automatically to best match how parameters were selected in the key well.
In a simple example, let’s say in the key well the GR clean parameter was selected to be 15, while in a non-key well the distribution is wider with low values typically lower and high values typically higher. In this case, the non-key well would have it’s GR clean parameter mapped to something lower, such as 10 (the methodology is similar to what happens with the Advanced Scaling option in the curve normalization). Both methods have their pros and cons. Curve normalization is less dependent on interpreter choices in the key well, and is therefore more stable. However, the parameter re-mapping can be more finely tuned.
LAS and Curve Outputs
Once you have selected to use/not use compositing and to use/not use normalizations the final curves representing your choices are as follows:
|Curve Data Type||Final Output Curve Name|
|Bulk Density or Density Porosity||density_final|