| To justify the large investments for developing a newly discovered reservoir, it is crucial to know early on the uncertainty about the total hydrocarbon reserves available. This thesis addresses the uncertainty about reservoir net-to-gross, which is an important parameter in reserves computation. Net-to-gross is the ratio of volume of pay rock to the gross reservoir volume; pay rock is the local reservoir interval that contains economically producible hydrocarbons.; Assessing uncertainty about a global attribute, such as rock proportions or net-to-gross, is difficult because by definition such an attribute has no replicate over the reservoir. At appraisal stage quantifying global uncertainty is also more difficult due to sparse wells which tend to be preferentially located in high-pay zones. Traditional statistical approaches typically assume data independence, a situation rarely met. In addition, these approaches cannot easily account for the contribution of seismic data and, most critically, geological interpretation.; We propose a framework to assess global uncertainty while accounting for the alternative geological scenarios resulting from different geological interpretations. The framework utilizes company expertise and historical data through a prior probability distribution of the global attribute under study and addresses the potential bias induced by the preferential location of appraisal wells in high-pay zones. Tests on a large synthetic reservoir show that the proposed methodology works. Application to an actual offshore turbidite reservoir shows its practical feasibility. |
