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A type curve approach to estimatingp for ap-normal transformation

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Abstract

The p-normal transformation plays an important role in reservoir characterization for data sets that are neither normally nor log-normally distributed. The key step in the transformation is to estimate the value of pfor a given data set. Even though there are several ways to determine p,these are more inconvenient than the quicker and easier type curve approach to estimate pwe present in this paper. In addition, the method provides the p-normal transformation with a visual interpretation. We demonstrate the technique by analyzing reservoir permeability and porosity data from the East Velma West Block Sims Sand Unit, Oklahoma.

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Abbreviations

[=]:

means “has units of”

a :

Bottom truncation [=] percent

b :

Top truncation [=] percent

c :

A point betweena andb [=] percent

k :

Permeability [=]L 2

p :

Exponent of a power transformation

x :

Random variable

y :

Standard random variable

φ :

Porosity [=] percent

1:

Scaled from the original random variable

2:

Scaled from the truncations

a :

Bottom truncation

b :

Top truncation

c :

A point betweena andb

k :

Permeability

min:

Minimum of a random variable

max:

Maximum of a random variable

φ :

Porosity

(p):

Power transformation

^:

Estimate

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Li, D., Lake, L.W. A type curve approach to estimatingp for ap-normal transformation. Math Geol 27, 359–371 (1995). https://doi.org/10.1007/BF02084607

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  • DOI: https://doi.org/10.1007/BF02084607

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