Publication History: This article is based on Chapter 7 of "The Log Analysis Handbook" by E. R. Crain, P.Eng., published by Pennwell Books 1986  Updated 2004. This webpage version is the copyrighted intellectual property of the author.

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Selection of Porosity MethodS
The answers for all the porosity solutions will vary, and in some cases be unreasonable or impossible to calculate due to lack of data. In order of preference, we would choose:

1. Density neutron crossplot (if hole is good and if both logs are available).

2. Sonic density crossplot if neutron is unavailable and no gas is present.

3. Sonic neutron crossplot in carbonates or in bad hole where density is not acceptable.

4. Density log corrected for shale (in good hole only).

5. Sonic log corrected for shale (in bad hole or if nothing else is available).

6. Neutron log corrected for shale (in bad hole or if nothing else is available).

7. Microresistivity, shallow or deep resistivity as a last resort.

8. Apply maximum porosity and material balance constraints to selected method.

9. Apply non-porous lithology triggers as needed.

Discard unreasonable answers, and/or revise shale or matrix assumptions and re-compute if difference between methods is too large.

Normally you will settle upon a method that suits you and the zone under consideration. You will not have time to compute results from all methods. Use the above list as a guide to reduce your effort and to gain a better chance for success on the first pass. Log analysis is seldom satisfactory on the first pass in new areas, so do not be bashful about trying several methods. Then keep a record of which methods worked best in which areas.

Porosity is usually reported to the nearest 1/10 of one percent (or 0.001 fractional) but this can be reduced to the nearest percent (or 0.01 fractional) for hand calculations or for porosity greater than 0.25.

Computed Results for Mixed Lithology Example from six different porosity models, compared
to core analysis porosity.

All porosity calculations need to be calibrated to core data at some point, usually at an early stage in an analysis project. Log analysis in isolation from other data is pointless and dangerous.

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