The Gippsland Basin of southeastern Australia is the most energy-rich basin of Australia producing petroleum, gas and brown coal. Three-quarters of the Basin lies offshore and the rest onshore. The basin was initiated as a rift valley, caused by the separation of the Australian continent from the Antarctic followed by a number of tectonic events throughout the basin history. Early Cretaceous sedimentary rocks form the basement, which is in turn covered with Late Cretaceous to Recent sediment of sand, clay, limestone, and brown coal seams. The total thickness of the in-filling sediments offshore attains up to 6000 m, but onshore is up to 1200 m. There are three main acquifer systems, the Hydrostratigraphic Units 2, 4, and 7, all of which are confined. The two lower aquifer systems, Units 4 and 7, contain high temperature groundwater. It is generally agreed that the hydrocarbons offshore have been derived from terrestrial matters including brown coal and ligneous clay offshore. In the present study, the author has developed a case that hydrocarbons offshore being derived not only from the offshore source but also from onshore brown coals and coaly matter and in this hydrocarbon forming processes, groundwater has played a significant role. The Central Deep, in particular, provides favourable conditions for hydrocarbon maturation. Throughout the basin history, the Central Deep has experienced the oil window temperatures. In supporting this hypothesis, geochemical studies on groundwater, brown coal, and hydrocarbons as well as hydrodynamics are presented.

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

The carbon-isotope and palynological record through 580 m thick almost continuous brown coal in southeast Australia's Gippsland Basin is a relatively comprehensive southern hemisphere Middle Eocene to Middle Miocene record for terrestrial change. The carbon isotope δ13Ccoal values of these coals range from - 27.7‰ to - 23.2. This isotopic variability follows gymnosperm/angiosperm fluctuations, where higher ratios coincide with heavier δ13C values. There is also long-term variability in carbon isotopes through time. From the Eocene greenhouse world of high gymnosperm-heavier δ13Ccoal values, there is a progressive shift to lighter δ13Ccoal values that follows the earliest (Oi1?) glacial events around 33 Ma (Early Oligocene). The overlying Oligocene-Early Miocene brown coals have lower gymnosperm abundance, associated with increased %Nothofagus (angiosperm), and lightening of isotopes during Oligocene cooler conditions. The Miocene palynological and carbon-isotope record supports a continuation to the Oligocene trends until around the late Early Miocene (circa 19 Ma) when a warming commenced, followed by an even stronger isotope shift around 16 Ma that peaked in the Middle Miocene when higher gymnosperm abundance and heavier isotopes prevailed. The cycle between the two major warm peaks of Middle Eocene and Middle Miocene was circa 30 Ma long. This change corresponds to a fall in inferred pCO2 levels for the same period. The Gippsland data suggest a link between gymnosperm abundance, long-term plant δ13C composition, climatic change, and atmospheric pCO2. Climatic deterioration in the Late Miocene terminated peat accumulation in the Gippsland Basin and no further significant coals formed in southeast Australia. The poor correspondence between this terrestrial isotope data and the marine isotope record is explained by the dominant control on δ13C by the gymnosperm/angiosperm abundance, although in turn this poor correspondence may reflect palaeoclimate control. From the brown coal seam dating, the coal appears to have accumulated during a considerable part of the allocated 30 Ma Cenozoic time period. These brown coal carbon isotope and palynological data appear to record a more gradual atmospheric carbon isotope change compared to the marine record.