Uncertainty assessment in reservoir modeling using experimental designs

Reservoir Uncertainty Assessment Using Machine Learning Techniques

Petroleum exploration and production are associated with great risk because of the uncertainty on subsurface conditions. Understanding the impact of those uncertainties on the production performance is a crucial part in the decision making process.Traditionally, uncertainty assessment is performed using experimental design and response surface method, in which a number of training points are se...

Uncertainty Reduction in Reservoir Modeling

This paper presents a method by which uncertainty in reservoir modeling can be reduced by integrating observed data in the estimation of model parameters. The problem is inverse and ill-posed. Further, since the observed data and the reservoir properties are non-linearly related, reducing uncertainty becomes a non-trivial task. The methodology involves generating multiple reservoir descriptions...

Prediction under Uncertainty in Reservoir Modeling

Reservoir simulation is routinely employed in the prediction of reservoir performance under different depletion and operating scenarios. Usually, a single history matched model, conditioned to production data, is obtained. The model is then used to forecast future production profiles. Since the history match is non-unique, this is essentially an inverse problem. Hence the forecast production pr...

Risk Assessment for Reservoir Development Under Uncertainty

Decision analysis applied to petroleum field development is always strongly related to risk due to the uncertainties present in the process. Methodologies to quantify the impact of uncertainties are still not well established due to the amount of variables that have to be considered. The complete analysis usually depends on geological, economical and technological uncertainties that have differ...

Modeling Uncertainty in Seismic Imaging of Reservoir Structure