Significant risks faced by the oil and gas industry lead to the need of methodologies able to evaluate project and measure risk. Risk-mitigation strategies are most effective when the assessment of the risk includes an in-depth study of several uncertainties involved, with the aim of optimizing investment return. In this basket, petrophysical uncertainty acts a significant role in the risk assessment phase, especially in the computation of volumetrics.

The scope of this work is the presentation of a methodology coming up from a real case study, where the limited information available makes challenging, yet critical, the creation of a robust input dataset for petrophysical interpretation and the assessment of the relevant uncertainties.

The well log database is heterogeneous due to the complex data acquisition history of the field, and no information are available about tools and hole conditions. Thus, the use of neural networks allowed the prediction of missing log sections, and core data poor representativeness leaded to the need of integration from analogue wells from a regional database, making the uncertainty assessment quite complex.

The work proposes the use of Monte Carlo Simulations to assess and propagate petrophysical uncertainty information, and different solutions to integrate the results in the static geological model, ranging from building discrete petrophysical scenarios (conservative, expected and optimistic), to the use of full petrophysical output distribution. The petrophysical uncertainty shows a significant impact on the in-place volume distribution and therefore provide an important element for the subsequent risk analysis phase.


Many people faced the issue of quantifying the petrophysical uncertainty through years, resulting in the production of several approaches, but unfortunately not so many available "on the shelf" and, thus, rarely facing the problem of having poor database, with scarce information about the environment at the moment of the measure.

One of the first issues to approach is the following: a direct measure of the main petrophysical parameters does not exist, since there are not tools provided for their measure. We use so to call them indirect measures.

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