Risk quantification combining geostatistical reali

Authors: Denis José Schiozer Guilherme Daniel Avansi Antonio Alberto de Souza dos Santos

Publish Date: 2016/06/04

Volume: 39, Issue: 2, Pages: 575-587

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Abstract

This work presents an alternative way to combine different types of uncertainty to quantify risk in petroleum field development Risk quantification is key in decision analysis Some areas need special attention namely 1 generating simulated scenarios compatible with geological models and 2 statistical techniques that address different types of uncertainty especially continuous and discrete attributes and realizations represented by geostatistical images using the fewest possible simulation runs Several statistical techniques address this but most present significant drawbacks potentially yielding incorrect risk quantification or demanding excessive time for simulation runs to reach good results This simple efficient methodology combines geostatistical realizations with other types of uncertainty eg reservoir structure fluid characterization and economic parameters using a Discretized Latin Hypercube sampling To verify the results we applied the methodology to the UNISIMID benchmark case showing that the method can be applied to a complex case yielding good results We found the methodology to meet our initial objectives to reliably and easily quantify risk within a minimal timeframe

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