Publication History: This article is based on Chapter 8 of "The Log Analysis Handbook" by E. R. Crain, P.Eng., published by Pennwell Books 1986  Updated 2004, 2021. This webpage version is the copyrighted intellectual property of the author. Do not copy or distribute in any form without explicit permission.

Crain's Usage Rules for SelectinG WATER SATURATION Method
The answers for all the water saturation solutions will vary, and in some cases will be unreasonable or impossible to calculate due to lack of data. In order of preference, we would choose:

BEST MODEL
1. Simandoux Model
Use whenever possible. Rreverts to Archie Model when Vsh = 0.
Works reliably in conventional and unconventional reservoirs.

OTHER SATURATION MODELS
Use only within  limitations

2. Archie Model
Use in clean sands or carbonates. Use Simandoux to handle both clean and shaly rocks.

3. Rwa Model
Use in clean sands or carbonates.

4. Dual Water Model
Eeverts to Archie Model when Vsh = 0. Czn create negative  saturation answers.

5 Waxmzn - Smits Model
Requires CEC and Qv data  which is hard to find.

6. Buckles Model
Use when resistivity is missing.Also used to find irreducible water saturation SWir in water zones.

7. Resistivity Ratio Model.
Use when porosity is missing.

8. TDT / PDK / RST / Pulsed Neutron Models
Use in cased hole for reservoir monitoring.

9. Sppecial Cases
Pyrite corrections, laminated reservoirs, fractured reservoirs.

10. Many alternate models are covered in this Handbook.

Triming Water Saturation RESULTS
Trim shale volume and porosity before using them in water saturation equations.

Water saturation results must be constrained by the following:

1: IF Sw < 0
2: THEN Sw = 0
3: IF Sw > 1.0
4: THEN Sw = 1.0

Where:
Sw = water saturation from any method (fractional)

Only the bulk volume water (dual water) method could create a negative water saturation.

All methods can create values greater than 1.0 (100%). If too many points are over 1.0, water resistivity, shale resistivity, porosity, and shale volume parameters should be reviewed.

Water Saturation Smoothing
Schlumberger proposed a smoothing function to reduce statistical noise in saturation data at both the high and low ends of the spectrum.

1: IF Sw > 0.75
2: THEN Sw = (1 - ((16 / 3) (1 - Sw) ^ 3) * (5 - 128 * (1 - Sw) ^ 3))
3: IF Sw < 0.25
4: THEN Sw = Sw + 0.04 * (1 - 4 * Sw) / (1 + 21 * Sw)

Otherwise Sw is unchanged.

Where:
Sw = water saturation from any method (fractional)