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Understanding and predicting reservoir presence and characteristics at regional to basin scales is important for evaluating risk and uncertainty in hydrocarbon exploration. Simulating reservoir distribution within a basin by a stratigraphic forward model enables the integration of available prior information with fundamental geologic processes embedded in the numerical model. Stratigraphic forward model predictions can be significantly improved by calibrating the models to independent constraints, such as thicknesses from seismic or well data. A three-dimensional basin-scale stratigraphic forward-modeling tool is coupled with an inversion algorithm. The inversion algorithm is a modification of the neighborhood algorithm (a type of genetic algorithm), which is designed to sample complex multimodal objective functions and is parallelized on computer clusters to accelerate convergence. The process generates a set of representative geological models that are consistent with prior ranges for uncertain parameters, calibration constraints, and associated tolerance thresholds. The workflow is first demonstrated on two data sets: a synthetic example based on a clastic passive margin and a real hydrocarbon exploration example for slope and basin-floor stratigraphic traps in the Neocomian (Lower Cretaceous) of the West Siberian Basin. The analysis of calibrated models provides constraints on stratigraphic controls, and allows prediction of locations with higher potential to develop stratigraphic traps. These locations are related to complex interactions between paleobathymetry, subsidence, eustatic fluctuations, characteristics of sediment-input sources, and sediment-transport parameters. Results show the potential of stratigraphic forward modeling combined with inverse methods as an additional tool to support conventional play-based exploration and reservoir-presence prediction.

Forecasting coal resources and reserves is critical for coal mine development. Thickness maps are commonly used for assessing coal resources and reserves; however they are limited for capturing coal splitting effects in thick and heterogeneous coal zones. As an alternative, three-dimensional geostatistical methods are used to populate facies distribution within a densely drilled heterogeneous coal zone in the As Pontes Basin (NW Spain). Coal distribution in this zone is mainly characterized by coal-dominated areas in the central parts of the basin interfingering with terrigenous-dominated alluvial fan zones at the margins. The three-dimensional models obtained are applied to forecast coal resources and reserves. Predictions using subsets of the entire dataset are also generated to understand the performance of methods under limited data constraints. Three-dimensional facies interpolation methods tend to overestimate coal resources and reserves due to interpolation smoothing. Facies simulation methods yield similar resource predictions than conventional thickness map approximations. Reserves predicted by facies simulation methods are mainly influenced by: a) the specific coal proportion threshold used to determine if a block can be recovered or not, and b) the capability of the modelling strategy to reproduce areal trends in coal proportions and splitting between coal-dominated and terrigenous-dominated areas of the basin. Reserves predictions differ between the simulation methods, even with dense conditioning datasets. Simulation methods can be ranked according to the correlation of their outputs with predictions from the directly interpolated coal proportion maps: a) with low-density datasets sequential indicator simulation with trends yields the best correlation, b) with high-density datasets sequential indicator simulation with post-processing yields the best correlation, because the areal trends are provided implicitly by the dense conditioning data.

Sedimentary facies is a key control on petrophysical properties within subsurface reservoirs and facies modelling is a critical aspect of reservoir modelling. Several modelling methods exist and selecting the best approach for a specific case is challenging and time-consuming. Outcrop analogues provide detailed information on architecture, geometry and facies connectivity that is not directly available in the subsurface. By modelling outcrop data it is possible to test and compare different modelling strategies systematically in a case where the geology is well constrained. The Eocene aged, Sant Llorenc del Munt fan-delta complex (NE Spain) is a well exposed, transgressive–regressive fan-delta. Outcrop data were used to test a variety of modelling strategies in which the density of conditioning wells, stratigraphic subdivision, modelling algorithm and trends were all varied. The results of these modelling exercises were compared against themselves and against a close-to-deterministically built Base Case reconstruction using a series of static measures including the distribution of fan-delta front reservoir facies, directional connectivity and reservoir-to-well connectivity. The results highlight the following: (a) the impact of the conditioning well density on improving the stratigraphic architecture reproduction in the different modelling approaches; (b) that surface-based modelling subdivisions including the maximum flooding surface to separate independent grids for modelling the transgressive and regressive sequence sets can be detrimental when compared to using only the top and base of the composite sequence unless additional constraints are included; (c) that an algorithm combining a linear trend and a Gaussian field is the most suitable algorithm for reproducing this type of architecture, but requires defining a 3D trend; and (d) the need for using trends to reproduce the architecture when well data are sparse. These results provide guidelines for modelling analogue fan-delta reservoirs in the subsurface.

This study uses one-dimensional convolution seismic models to better understand which features of slope turbidite systems can (or cannot) be observed on real seismic data, aiming to improve subsurface seismic interpretation. Synthetic seismic sections and cubes were built from reservoir-scale three-dimensional facies models of the outcropping Ainsa turbidite system. This turbidite system developed in a foredeep and wedge-top depositional setting within a slope system. The turbidite system consists of laterally and vertically stacked sandstone- and debrite-dominated channel fills, grading into heterolithic and mudstone units, with intercalations of slump-deformed mudstone-rich units. Typical petrophysical values for subsurface Cenozoic sediments were assumed for the seismic models, which are presented at 25-, 50-, and 75-Hz resolution. Seismic models enabled the comparison between architectural and facies distributions observed in the outcrops and the geological models to their possible seismic expression in the subsurface. Comparisons show how seismic expression degrades when seismic resolution decreases. By using models at different geological scales, the effects of each heterogeneity scale are identified. Precise delineation of the internal architecture and facies distribution within channel complexes is beyond the reach of all seismic frequencies. The position of channel complex tops and margins is uncertain because of their gradual character. Differentiating between sandstone- and debrite-filled channels is not straightforward, and bed-scale heterogeneities within the sandstone-dominated channels are barely distinguishable in the seismic data. The net-to-gross predictive capability of root-mean-square amplitude extractions varies depending on the seismic frequency and unit thickness

Using data from an outcrop characterization of a sandstone-rich turbidite channel fill (the so-called Quarry outcrop in the Ainsa basin), several stochastic facies models were constructed at bed-scale resolution (cells 2.5 m [8 ft] wide and 0.05 m [2 in.] thick). Several industry-standard reservoir-modeling algorithms were employed: truncated Gaussian simulation, sequential indicator simulation, multiple-point geostatistics, and object-based methods with varying degrees of complexity. The degree of similarity (i.e., realism) between realizations and the outcrop characterization was quantified through the use of several responses: (1) static connectivity, (2) effective permeability, and (3) recovery efficiency from waterflood simulations. Differences in the responses measured from the outcrop and facies models were observed: these are mostly algorithm related, instead of caused by soft data or different stochastic realizations. Differences increase greatly when the permeability of the heterolithic packages and mudstone beds (Ht-M) decreases and reflect the methods' ability to model the inclined and undulating Ht-M packages and beds that occur in the outcrop. These packages and beds can drape scours and sandstone beds with depositional topography and pinch-outs, producing sandstone thinning and dead ends. Object-based methods capable of introducing highly undulating Ht-M beds provided the most realistic models. Variogram-based and simple object-based methods failed to capture and reproduce the whole length of undulating beds. Multiple-point geostatistics provided realizations with responses intermediate between variogram-based and simple object-based methods and the more successful advanced object-based methods. The conditioning-to-hard-data capabilities of multiple-point geostatistics are higher than those of the object-based methods, which give them an added advantage.

The external and internal geometry of four turbidite systems outcropping around the Buil syncline (Ainsa basin, Spanish Pyrenees) has been reconstructed with reservoir-scale resolution in three dimensions (3-D). The irregular geometry of the syncline and the resolution required for the reconstruction cannot be resolved with cross sections. Therefore, reconstruction has been carried out with a new methodology that applies a 3-D dip-domain geometrical model and 3-D restoration techniques to achieve reservoir-scale resolution in kilometric-scale reconstructions. This methodology is aimed at resolving 3-D geometries in folded areas and regions with variable thickness stratigraphy.The 3-D reconstruction of the Buil syncline reveals the synsedimentary growth of an intrabasinal anticline and the foreland lithospheric flexure associated with tectonic loading north of the Ainsa basin.

Coal exploration and mining in extensively drilled and sampled coal zones can benefit from 3D statistical facies interpolation. Starting from closely spaced core descriptions, and using interpolation methods, a 3D optimum and robust facies distribution model was obtained for a thick, heterogeneous coal zone deposited in the non-marine As Pontes basin (Oligocene-Early Miocene, NW Spain). Several grid layering styles, interpolation methods (truncated inverse squared distance weighting, truncated kriging, truncated kriging with an areal trend, indicator inverse squared distance weighting, indicator kriging, and indicator kriging with an areal trend) and searching conditions were compared. Facies interpolation strategies were evaluated using visual comparison and cross validation. Moreover, robustness of the resultant facies distribution with respect to variations in interpolation method input parameters was verified by taking into account several scenarios of uncertainty. The resultant 3D facies reconstruction improves the understanding of the distribution and geometry of the coal facies. Furthermore, since some coal quality properties (e.g. calorific value or sulphur percentage) display a good statistical correspondence with facies, predicting the distribution of these properties using the reconstructed facies distribution as a template proved to be a powerful approach, yielding more accurate and realistic reconstructions of these properties in the coal zone.