The primary controls on subsurface reservoir heterogeneities and fluid flow characteristics are sedimentary facies architecture and petrophysical rock fabric distribution in clastic reservoirs and in carbonate reservoirs, respectively. Facies models are critical and fundamental for summarizing facies and facies architecture in data-rich areas. Facies models also assist in predicting the spatial architectural trend of sedimentary facies in other areas where subsurface information is lacking. The method for transferring geological information from different facies models into digital data and then generating associated numerical models is called facies modeling or geological modeling. Facies modeling is also vital to reservoir simulation and reservoir characterization analysis. By extensively studying and reviewing the relevant research in the published literature, this report identifies and analyzes the best and most detailed geologic data that can be used in facies modeling, and the most current geostatistical and stochastic methods applicable to facies modeling. Through intensive study of recent literature, the author (1) summarizes the basic concepts and their applications to facies and facies models, and discusses a variety of numerical modeling methods, including geostatistics and stochastic facies modeling, such as variogram-based geostatistics modeling, object-based stochastic modeling, and multiple-point geostatistics modeling; and (2) recognizes that the most effective way to characterize reservoir is to integrate data from multiple sources, such as well data, outcrop data, modern analogs, and seismic interpretation. Detailed and more accurate parameters using in facies modeling, including grain size, grain type, grain sorting, sedimentary structures, and diagenesis, are gained through this multidisciplinary analysis. The report concludes that facies and facies models are scale dependent, and that attention should be paid to scale-related issues in order to choose appropriate methods and parameters to meet facies modeling requirements. / text

Despite increasing computer power, the requirement to upscale 3D geological models for dynamic reservoir simulation purposes is likely to remain in many commercial environments. This study established that there is a relationship between sandbody size, cell size and changes to predictions of reservoir production as grids are upscaled. The concept of a cell width to sandbody width ratio (CSWR) was developed to allow the comparison of changes in reservoir performance as grids are upscaled. A case study of the Flounder Field in the Gippsland Basin resulted in the interpretation of three depositional environments in the intra-Latrobe reservoir interval. The sandbody dimensions associated with these depositional environments were used to build a series of 3D geological models. These were upscaled vertically and horizontally to numerous grid cell sizes. Results from over 1400 dynamic models indicate that if the CSWR is kept below 0.3 there will be a strong correlation between the average production from the upscaled grids compared to those of a much finer grid, and there will be less than 10% variation in average total field production. If the CSWR is between 0.3 and 1, there could be up to 30% difference, and once the CSWR exceeds 1.0 there is only a weak relationship between the results from upscaled grids and those of finer grids. As grids are upscaled the morphology of bodies in facies models changes, the distribution of petrophysical properties is attenuated and the structure is smoothed. All these factors result in a simplification of the fluid flow pathways through a model. Significant loss of morphology occurs when cells are upscaled to more than a half the width of the reservoir body being modelled. A simple rule of thumb is established — if the geological features of a model cannot be recognised when looking at a layer in the upscaled grid, the properties of the upscaled grid are unlikely to be similar to those of the original grid and the predictions of dynamic models may vary significantly from those of a finer grid. This understanding of the influence of sandbody size on the behaviour of upscaled dynamic models can be used in the planning stages of a reservoir modelling project. Two simple charts have been created. The first chart is for calculating the approximate number of cells in a model before it is built. The second chart is for comparing the proposed cell size against the CWSR, so that the predicted discrepancy between the ultimate production from the upscaled grid and one with much smaller cells can be assessed. These two charts enhance discussion between all interested disciplines regarding the potential dimensions of both static and upscaled dynamic models during the planning stage of a modelling project, and how that may influence the results of dynamic modelling. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1375309 / Thesis (Ph.D.) - University of Adelaide, Australian School of Petroleum, 2009

Despite increasing computer power, the requirement to upscale 3D geological models for dynamic reservoir simulation purposes is likely to remain in many commercial environments. This study established that there is a relationship between sandbody size, cell size and changes to predictions of reservoir production as grids are upscaled. The concept of a cell width to sandbody width ratio (CSWR) was developed to allow the comparison of changes in reservoir performance as grids are upscaled. A case study of the Flounder Field in the Gippsland Basin resulted in the interpretation of three depositional environments in the intra-Latrobe reservoir interval. The sandbody dimensions associated with these depositional environments were used to build a series of 3D geological models. These were upscaled vertically and horizontally to numerous grid cell sizes. Results from over 1400 dynamic models indicate that if the CSWR is kept below 0.3 there will be a strong correlation between the average production from the upscaled grids compared to those of a much finer grid, and there will be less than 10% variation in average total field production. If the CSWR is between 0.3 and 1, there could be up to 30% difference, and once the CSWR exceeds 1.0 there is only a weak relationship between the results from upscaled grids and those of finer grids. As grids are upscaled the morphology of bodies in facies models changes, the distribution of petrophysical properties is attenuated and the structure is smoothed. All these factors result in a simplification of the fluid flow pathways through a model. Significant loss of morphology occurs when cells are upscaled to more than a half the width of the reservoir body being modelled. A simple rule of thumb is established — if the geological features of a model cannot be recognised when looking at a layer in the upscaled grid, the properties of the upscaled grid are unlikely to be similar to those of the original grid and the predictions of dynamic models may vary significantly from those of a finer grid. This understanding of the influence of sandbody size on the behaviour of upscaled dynamic models can be used in the planning stages of a reservoir modelling project. Two simple charts have been created. The first chart is for calculating the approximate number of cells in a model before it is built. The second chart is for comparing the proposed cell size against the CWSR, so that the predicted discrepancy between the ultimate production from the upscaled grid and one with much smaller cells can be assessed. These two charts enhance discussion between all interested disciplines regarding the potential dimensions of both static and upscaled dynamic models during the planning stage of a modelling project, and how that may influence the results of dynamic modelling. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1375309 / Thesis (Ph.D.) - University of Adelaide, Australian School of Petroleum, 2009

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The Frontier Formation in the Green River Basin of southwestern Wyoming consists of Late Cretaceous (Cenomanian-Turonian) marine and non-marine sandstones, siltstones, mudstones and coals deposited on the western margin of the Cretaceous Interior Seaway. Tight gas reservoirs exist in subsurface fluviodeltaic sandstones in the upper Frontier Formation (Dry Hollow Member) on the north-south trending Moxa Arch within the basin. These strata crop out in hogback ridges of the Utah-Idaho-Wyoming Thrust Belt approximately 40 km west of the crest of the Moxa Arch. Detailed, quantitative outcrop descriptions were constructed using emerging photogrammetric techniques along with field observations and measured sections at five key outcrop localities along the thrust belt. Understanding the architectural style of this low net-to-gross fluvial system allows for improved reservoir prediction in this and other comparable basins. The architectural style of the Dry Hollow Member fluvial deposits varies vertically as the result of a relative shoreline transgression during Dry Hollow deposition. Amalgamated conglomerates and associated fine to coarse sandstones near the base of the section and much thinner, isolated sandstones near the top of the Dry Hollow occur in laterally extensive units that can be identified over tens of kilometers. These units also provide means to relate outcrop and subsurface stratigraphic architecture. Combined with available subsurface data, fully-realized 3D static reservoir models for use as analogs in subsurface reservoir characterization may be constructed. Grain size, reservoir thickness and connectivity of fluvial sandstones is generally greatest near the base of this member and decreases upward overall. Despite relative isolation of some channel bodies, geocellular facies modeling indicates good lateral and vertical connectivity of most channel sandstones. The Kemmerer Coal Zone, with little sandstone, divides lower and upper well-connected sandy units.

Intra-archipelago waterways, including tidal strait networks, present a complex set of barriers to, and conduits for sediment transport between marine basins. Tidal straits may also be the least well understood tide-dominated sedimentary environment. To address these issues, currents, sediment transport pathways, and seabed sedimentology & geomorphology were studied in the central Salish Sea (Gulf and San Juan Islands region) of British Columbia, Canada and Washington State, USA. A variety of data types were integrated: 3D & 2D tidal models, multibeam bathymetry & backscatter, seabed video, grab samples, cores and seismic reflection. This dissertation included the first regional sediment transport modelling study of the central Salish Sea. Lagrangian particle dispersal simulations were driven by 2D tidal hydrodynamics (~59-days). It was found that flood-tide dominance through narrow intra-archipelago connecting straits resulted in the transfer of sediment into the inland Strait of Georgia, an apparent sediment sink. The formative/maintenance processes at a variety of seabed landforms, including a banner bank with giant dunes, were explained with modelled tides and sediment transport. Deglacial history and modern lateral sedimentological and morphological transitions were also considered. Based on this modern environment, adjustments to the tidal strait facies model were identified. In addition, erosion and deposition patterns across the banner bank (dune complex) were monitored with 8-repeat multibeam sonar surveys (~10 years). With these data, spatially variable bathymetric change detection techniques were explored: A) a cell-by-cell probabilistic depth uncertainty-based threshold (t-test); and B) coherent clusters of change pixels identified with the local Moran's Ii spatial autocorrelation statistic. Uncertainty about volumetric change is a considerable challenge in seabed change research, compared to terrestrial studies. Consideration of volumetric change confidence intervals tempers interpretations and communicates metadata. Techniques A & B may both be used to restrict volumetric change calculations in area, to exclude low relative bathymetric change signal areas. / Graduate / 2018-12-07