Computer modeling of nuclear logging tools is making a growing contribution to an understanding of tool behaviour and log interpretation. While simple analytical computations have provided useful information in the past, the last few years have seen an increasing use of more advanced computational techniques employing both statistical (Monte Carlo) and non-statistical (deterministic) programs. The main features of these two approaches are described and examples are presented of their capabilities. It is shown that Monte Carlo and deterministic computations should not be considered as competitors but as complementary aids to tool design and log interpretation. These complementary roles are identified and related to operational features, such as execution time and cost, and to the presence, or otherwise, of statistical variations.

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