Predicting missing Energy Performance Certificates:Spatial interpolation of mixture distributions

Mass renovation goals aimed at energy savings on a national scale require a significant level of public financial commitment.To identify target buildings,decision-makers need a thorough understanding of energy performance.Energy Performance Certificates(EPC)provide information about areas of space,such as land plots or a building’s footprint,without specifying exact locations.They cover only a fraction of dwellings.This paper demonstrates that learning from observed EPCs to predict missing ones at the building level can be viewed as a spatial interpolation problem with uncertainty both on input and output variables.The Kriging methodology is applied to random fields observed at random locations to determine the Best Linear Unbiased Predictor(BLUP).Although the Gaussian setting is lost,conditional moments can still be derived.Covariates are admissible,even with missing observations.We present applications using both simulated and real data,with a specific case study of a city in France serving as an example.

Importance of Modeling Heterogeneities and Correlation in Reservoir Properties in Unconventional Formations: Examples of Tight Gas Reservoirs

We present lithofacies classifications for a tight gas sandstone reservoir by analyzing hierarchies of heterogeneities.We use principal component analysis(PCA)to overcome the two level of heterogeneities,which results in a better lithofacies classification than the traditional cutoff method.The classical volumetric method is used for estimating oil/gas in-place resources in the petroleum industry since its inception is not accurate because it ignores the heterogeneities of and correlation between the petrophysical properties.We present the importance and methods of accounting for the heterogeneities of and correlation between petrophysical properties for more accurate hydrocarbon volumetric estimations.We also demonstrate the impacts of modeling the heterogeneities and correlation in porosity and hydrocarbon saturation for hydrocarbon volumetric estimations with a tight sandstone gas reservoir.Furthermore,geoscientists have traditionally considered that small-scale heterogeneities only impact subsurface fluid flow,but not impact the hydrocarbon resource volumetric estimation.We show the importance of modeling small-scale heterogeneities using fine cell size in reservoir modeling of unconventional resources for accurate resource assessment.