Realistic uncertainty quantification in geostatistical seismic reservoir characterization

Making informed field development decisions requires taking uncertainty into account. Geostatistical inversion is a key technology for quantifying uncertainties using available seismic and well data. However, the common practice, consisting of choosing the "best possible" parameters, results in unrealistically small uncertainty estimates. In this paper, we propose a multi-scenario approach to geostatistical inversion. By considering various alternative scenarios, a more realistic picture of the overall uncertainty can be built. This is illustrated on a case study, where the traditional single-scenario practice and the proposed multi-scenario approach are compared.