Heterogeneity-preserving property models of subsurface regions are commonly constructed by means of sequential simulations. Sequential Gaussian simulation (SGS) and direct sequential simulation (DSS) draw values from a local probability density function that is described by the simple kriging estimate and the local simple kriging variance at unsampled locations. The local simple kriging variance, however, does not necessarily reflect the geological variability being present at subsets of the target domain. In order to address that issue, we propose a new workflow that implements two modified versions of the popular SGS and DSS algorithms. Both modifications, namely, LVM-DSS and LVM-SGS, aim at simulating values by means of introducing a local variance model (LVM). The LVM is a measurement-constrained and geology-driven global representation of the locally observable variance of a property. The proposed modified algorithms construct the local probability density function with the LVM instead of using the simple kriging variance, while still using the simple kriging estimate as the best linear unbiased estimator. In an outcrop analog study, we can demonstrate that the local simple kriging variance in sequential simulations tends to underestimate the locally observed geological variability in the target domain and certainly does not account for the spatial distribution of the geological heterogeneity. The proposed simulation algorithms reproduce the global histogram, the global heterogeneity, and the considered variogram model in the range of ergodic fluctuations. LVM-SGS outperforms the other algorithms regarding the reproduction of the variogram model. While DSS and SGS generate a randomly distributed heterogeneity, the modified algorithms reproduce a geologically reasonable spatial distribution of heterogeneity instead. The new workflow allows for the integration of continuous geological trends into sequential simulations rather than using class-based approaches such as the indicator simulation technique.

Abstract. The prediction of physicochemical rock properties in subsurface models regularly suffers from uncertainty observed at the sub-meter scale. Although at this scale – which is commonly termed the lithofacies scale – the physicochemical variability plays a critical role for various types of subsurface utilization, its dependence on syn- and post-depositional processes is still subject to investigation. The impact of syn- and post-depositional geological processes, including depositional dynamics, diagenetical compaction and chemical mass transfer, onto the spatial distribution of physicochemical properties in siliciclastic media at the lithofacies scale is investigated in this study. We propose a new workflow using two cubic rock samples where eight representative geochemical, thermophysical, elastic and hydraulic properties are measured on the cubes' faces and on samples taken from the inside. The scalar fields of the properties are then constructed by means of spatial interpolation. The rock cubes represent the structurally most homogeneous and most heterogeneous lithofacies types observed in a Permian lacustrine delta formation that deposited in an intermontane basin. The spatio-temporal controlling factors are identified by exploratory data analysis and geostatistical modeling in combination with thin section and environmental scanning electron microscopy analyses. Sedimentary structures are well preserved in the spatial patterns of the negatively correlated permeability and mass fraction of Fe2O3. The Fe-rich mud fraction, which builds large amounts of the intergranular rock matrix and of the pseudomatrix, has a degrading effect onto the hydraulic properties. This relationship is underlined by a zonal anisotropy that is connected to the observed stratification. Feldspar alteration produced secondary pore space that is filled with authigenic products including illite, kaolinite and opaque phases. The local enrichment of clay minerals implies a non-pervasive alteration process that is expressed by network-like spatial patterns of the positively correlated mass fractions of Al2O3 and K2O. Those patterns are spatially decoupled from primary sedimentary structures. The elastic properties, namely p- and s-wave velocity, indicate a weak anisotropy that is not inevitably oriented perpendicularly to the sedimentary structures. The multifarious patterns observed in this study emphasize the importance of high-resolution sampling in order to properly model the variability present in a lithofacies-scale system. In fact, the physicochemical variability observed at the lithofacies scale might nearly cover the global variability in a formation. Hence, if the local variability is not considered in full-field projects – where the sampling density is usually low – statistical correlations and thus conclusions about causal relationships among physicochemical properties might be feigned inadvertently.

Abstract. The prediction of physicochemical rock properties in subsurface models regularly suffers from uncertainty observed at the submeter scale. Although at this scale – which is commonly termed the lithofacies scale – the physicochemical variability plays a critical role for various types of subsurface utilization, its dependence on syndepositional and postdepositional processes is still subject to investigation. The impact of syndepositional and postdepositional geological processes, including depositional dynamics, diagenetic compaction and chemical mass transfer, onto the spatial distribution of physicochemical properties in siliciclastic media at the lithofacies scale is investigated in this study. We propose a new workflow using two cubic rock samples where eight representative geochemical, thermophysical, elastic and hydraulic properties are measured on the cubes' faces and on samples taken from the inside. The scalar fields of the properties are then constructed by means of spatial interpolation. The rock cubes represent the structurally most homogeneous and most heterogeneous lithofacies types observed in a Permian lacustrine-deltaic formation that deposited in an intermontane basin. The spatiotemporal controlling factors are identified by exploratory data analysis and geostatistical modeling in combination with thin section and environmental scanning electron microscopy analyses. Sedimentary structures are well preserved in the spatial patterns of the negatively correlated permeability and mass fraction of Fe2O3. The Fe-rich mud fraction, which builds large amounts of the intergranular rock matrix and of the pseudomatrix, has a degrading effect on the hydraulic properties. This relationship is underlined by a zonal anisotropy that is connected to the observed stratification. Feldspar alteration produced secondary pore space that is filled with authigenic products, including illite, kaolinite and opaque phases. The local enrichment of clay minerals implies a nonpervasive alteration process that is expressed by the network-like spatial patterns of the positively correlated mass fractions of Al2O3 and K2O. Those patterns are spatially decoupled from primary sedimentary structures. The elastic properties, namely P-wave and S-wave velocity, indicate a weak anisotropy that is not strictly perpendicularly oriented to the sedimentary structures. The multifarious patterns observed in this study emphasize the importance of high-resolution sampling in order to properly model the variability present in a lithofacies-scale system. Following this, the physicochemical variability observed at the lithofacies scale might nearly cover the global variability in a formation. Hence, if the local variability is not considered in full-field projects – where the sampling density is usually low – statistical correlations and, thus, conclusions about causal relationships among physicochemical properties might be feigned inadvertently.