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Carbonated water injection (CWI) is described as a chemical-enhanced oil recovery method in which CO2-enriched water is injected into oil reservoirs as a displacing fluid. Although confirmed by many that a considerable amount of recovery improvement is attainable through CWI in both lab and field scales, the interaction of salinity on the performance of CWI and its potential fines migration is not very well understood. This study examines the efficiency of oil recovery improvement during low-salinity carbonated water injection (LSCWI) in a sandstone reservoir, while total dissolved salt concentration varies. To this end, a series of coreflooding experiments were performed on homogeneous sandstone cores at 80°C and 2000psi, and the amount of oil recovery was measured. From the experiments, it was observed that CWI could extract more crude oil than conventional water flooding in all salinities. In particular, the highest oil recovery was observed in the lowest salinity (61.2% in CWI and 42% during water flooding), indicating that by carbonating low-salinity water, oil recovery is enhanced by 20%. Moreover, the influence of salinity reduction on recovery enhancement was such that 9% of recovery improvement observed during conventional water flooding when salinity decreased from 40000 to 1000ppm. At the same time, this improvement was around 15% for CWI, suggesting that salinity reduction can be more effective in CWI rather than water flooding in recovery improvement. It was also found out that while recovery improvement and fines migration are both highly affected by water salinity, there is a synergy between the efficiency of CWI and onset of fines migration, which is one of the underlying mechanisms in oil recovery improvement during LSCWI into clay-containing sandstone reservoirs.

The petroleum industry uses high level dynamic simulations applied to geocellular models to guide forecasts of oil, gas and water production. Uncertainty in model choice and input variable selection is often addressed through large numbers of computationally slow Monte Carlo simulations designed around physics based models. Here, an alternate approach is proposed, which uses a relatively small amount of data and a reduced number of simulations of the high level physics model to train a fast (to evaluate) proxy or surrogate model based on a Polynomial Chaos Expansion. We give details of the theory and incorporated techniques, which significantly increase flexibility. Input variables (e.g. cell-by-cell variations in porosity and permeability) are sampled from unknown probability distributions and sensitivity analysis is based on low level proxy models. The theory is tested by developing proxy models to predict total gas production from a five-spot well configuration in the Hermitage area that taps into the Walloon Coal Measures of the Surat Basin in Queensland. Synthetic training data is simulated using commercial dynamic simulation software based on a high level physics model.

The stratigraphy of the Surat Basin, Queensland, has historically been sub-divided by formation and unit nomenclature with a few attempts by other authors to apply sequence stratigraphy to existing formation boundaries. At a local- to field-scale, lithostratigraphy may be able to represent stratigraphy well, but at regional-scale, lithostratigraphic units are likely to be diachronous. To date, this lithology-driven framework does not accurately reflect time relationships in the sub-surface. An entirely new integrated methodological approach, involving well tied seismic data and sequence stratigraphic well-to-well correlations compared with published zircon age dates, has been applied to hundreds of deep wells and shallower coal seam gas wells. This method sub-divides the Surat Basin stratigraphy into defendable 2nd order to 3rd order sequence stratigraphic cycles and has required the use of an alpha-numeric sequence stratigraphic nomenclature to adequately and systematically label potential time equivalent surfaces basin-wide. Correlation of wells is the first step in building models of aquifers and coal seam gas fields for numerical simulation of fluid flow, which is necessary for responsible resource management. Lithostratigraphic correlations will overestimate the extent and hydraulic connectedness of the strata of interest. The result may be fluid flow models that do not represent a realistic pressure footprint of the flow. The present sequence stratigraphic method more accurately reflects the disconnectedness of sub-surface coals and sandstones (aquifers) on a field-to-field scale, adjacent field-scale, and basin-wide scale. It forms the basis for improved and more representative modelling of the sub-surface.

A new sequence stratigraphic framework (SSF) for the Early–Late Jurassic Surat Basin, eastern Australia, is evolving. A second and third order framework based upon an integrated methodology of well-to-well correlations supported by well tied seismic data is being developed. The integration of an additional dataset (palynology) to test for regionally consistent sequence stratigraphic well correlations offers an improvement in defining sequence boundaries related to the geological timescale. The palynological data from 33 wells covering the north-east Surat Basin were extracted from the Queensland Digital Exploration (QDEX) open-file reports, some of which date back to the 1960s. These data were correlated and superposed on the SSF for age comparison. The dataset used in this study represents only a subset of all existing palynology information, as not all data are captured in QDEX. However, the palynology data in this exploratory study generally fits and supports the new SSF with only one exception, the reason for which is not understood at this stage. We recommend expanding this study to include more data because palynology can support stratigraphic interpretation, especially in wells that do not intercept, or have log data across, regional datums.

Effective geological storage of CO2 can be accomplished through a number of trapping mechanisms. Physical trapping is achieved through either CO2 being trapped under a structural closure or CO2 made immobile in the pore space, as residual saturation, by capillary action. Geochemical trapping, which might be regarded as a more secure mode of storage, is achieved through dissolution of CO2 in formation water and precipitation of carbonates. The dissolution rate depends on surface contact and is generally enhanced by greater CO2 plume movement. During site selection, a potential injection well location is commonly evaluated with respect to the proximity to potential leakage features. This paper investigates requirements for separation distance between CO2 injection location and potential leakage features in highly permeable steeply dipping brine reservoir settings. Reservoir models are simulated with a compositional code and sensitivity analyses performed with variations in reservoir permeability, hysteresis effects, and formation dip. Trapping mechanisms, over a timescale of several centuries, are illustrated as key indicators for containment and storage performance. Study results suggest that the amount of CO2 trapped by dissolution and residual saturation is enhanced by a dynamically flowing plume. The simulation results demonstrate that the separation distance requirement typically envisaged in a worst-case reservoir geometry setting is commonly overly conservative, representing opportunity for further optimisation. Numerical simulation is useful in addressing the complex reality of flow dynamics such as hysteresis in footprint prediction. Understanding CO2 plume migration scenarios relative to potential leakage risks, under various key reservoir key properties, is essential in storage containment and capacity assessments for storage site selection and development.