Other approaches to review incidents that were mentioned were case reviews (10 units), significant event analysis (5 units), trend analysis (4 units), and one unit recommended choosing an approach from systems analysis with a contributory factor framework, brainstorming, the five whys, incident decision tree, fishbone diagram and gap analysis.
To the southeast, where the parallel to subparallel ranges become lower and form isolated, compact units trending north-south, the flat valleys between are called bolsones (basins).
Our in silico analysis revealed a positive relationship between SSR polymorphism and the number of repeat units, a trend previously reported in other organisms.
Partitioning the scattered samples of a unit slope trend line into sub-flow units leads to permeability prediction improvement, and the use of (FZI) arithmetic average for each sub-flow units for permeability prediction equation is recommended.
It is noticed that (Table 3) the arithmetic averages of (FZI) values for sub-flow unit samples that lie on the unit slope trend line using Amaefuleʼs approach are very close to (FZI) values at (ϕ Z) = 1, (units 1-B and 3-B), so they have the lowest error percent in predicted permeability using Amaefuleʼs approach, and the reverse is right for rest of the samples.
Improvement is done through the new additional processing of Amaefuleʼs approach by differentiation or redistribution of scattered samples of unit slop trend line of (ϕ Z-RQI) relation into three sub-flow units as follows: 1. Unit includes the scattered samples that lie above the trend line.
This is simply done through differentiation of all samples that lie on the unit slope trend line and those lie scattered on both sides of it, into three sub-flow units regardless their slopes and the use of (FZI) arithmetic average for each sub-unit instead of that at (ϕ Z) = 1.
Concerning scattered samples (FZI) of a unit slope trend line at (ϕ Z) = 1 differ greatly from the (FZI) arithmetic average of those samples.
It was found out that the normal application of Amaefuleʼs hydraulic flow unit approach using the relation of normalized porosity index (ϕ Z) versus reservoir quality index (RQI and FZII values at (ϕ Z) = 1 leads to deviation of predicted permeability from the measured one in case of scattered data of (ϕ Z-RQI) relation having a unit slope trend line.
For non-scattered samples, it is found that (FZI) value of a unit slope trend line at (ϕ Z) = 1 equals or nearly equals the (FZI) arithmetic average of those samples to a great extent, so FZI that produced at (ϕ Z) = 1 is recommended for non or very low scattered samples of (ϕ Z-RQI) relation for permeability prediction.
On the other hand, if all or majority of samples are scattered around the unit slope trend line, then (FZI) value from the intercept differs greatly from (FZI) arithmetic average of these sample, and predicted permeability is far from measured one, and the error between them is great.
