Search Results (3)

Groundwater levels were monitored before, during and after groundwater pumping to understand the impacts of groundwater extraction on Abercorn Spring, a recharge spring in the Great Artesian Basin (GAB) in southeast Queensland, Australia. We measured the wetted area of the spring during this time to understand if changes in hydrology affected the water available for vegetation communities. Sustained groundwater extraction >20 km upgradient of the spring resulted in (1) rapid drawdown of the source aquifer, causing a reduction in aquifer pressure; (2) a small decline (0.35 m) in water level at the spring; and (3) a significant change (p = 0.0001) in wetted area in winter. Recovery of water levels and wetted area of the mound spring took over three years after pumping ceased. Our study demonstrated that significant changes to the wetted area occurred with only a minimal drawdown at the springs. Abercorn Springs have a natural low variability in water level (<0.2 m), implying a stable and predictable biological community. This natural range is less than half the water level change that is currently considered for impact assessment in artesian springs in the Queensland section of the GAB, highlighting the need to incorporate updated information to inform future management of both recharge and discharge springs. In the case of Abercorn Springs, long-term monitoring and research have led to refinement of license conditions for groundwater extraction, thereby mitigating further impacts to the springs and demonstrating adaptive management. Full article

This paper presents the results of a research project which investigated permeability prediction for the Precipice Sandstone of the Surat Basin. Machine learning techniques were used for permeability estimation based on multiple wireline logs. This information improves the prediction of CO₂ injectivity in this formation. Well logs and core data were collected from 5 boreholes in the Surat Basin, where extensive core data and complete sets of conventional well logs exist for the Precipice Sandstone. Four different machine learning (ML) techniques, including Random Forest (RF), Artificial neural network (ANN), Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR), were independently trained with a wide range of hyper-parameters to ensure that not only is the best model selected, but also the right combination of model parameters is selected. Cross-validation for 20 different combinations of the seven available input logs was used for this study. Based on the performances in the validation and blind testing phases, the ANN with all seven logs used as input was found to give the best performance in predicting permeability for the Precipice Sandstone with the coefficient of determination (R²) of about 0.93 and 0.87 for the training and blind data sets respectively. Multi-regression analysis also appears to be a successful approach to calculate reservoir permeability for the Precipice Sandstone. Models with a complete set of well logs can generate reservoir permeability with R² of more than 90%. Full article

Carbon dioxide geological storage involves injecting captured CO₂ streams into a suitable reservoir. Subsequent mineral trapping of the CO₂ as carbonate minerals is one of the most secure forms of trapping. Injection of CO₂ dissolved in water or co-injection of CO₂ with water may enhance trapping mechanisms. Produced waters are already re-injected into reservoirs worldwide, and their co-injection with CO₂ could enhance mineral trapping in low reactivity rock by providing a source of cations. Sandstone drill core from a reservoir proposed for CO₂ storage was experimentally reacted with supercritical CO₂ and a synthetic produced water. Micro computed tomography (CT), QEMSCAN, and SEM were performed before and after the reaction. The sandstone sample was predominantly quartz with minor illite/muscovite and kaolinite. The sandstone sub-plug micro-CT porosity was 11.1% and 11.4% after the reaction. Dissolved Ca, Mg, and Sr decreased during the reaction. After the reaction with CO₂ and synthetic produced water, precipitation of crystalline carbonate minerals calcite and dolomite was observed in the pore space and on the rock surface. In addition, the movement of pore filling and bridging clays, as well as grains was observed. Co-injection of CO₂ with produced waters into suitable reservoirs has the potential to encourage CO₂ mineral trapping. Full article