The northern Lawn Hill Platform (nLHP) is considered an emerging region with less than 15 wells drilled to date. With renewed interest in unconventional gas, new exploration opportunities exist in this early Proterozoic region. Petroleum systems analysis is presented here to improve the understanding of burial history, source rock richness and maturity of the nLHP of the Isa Superbasin, far NW Queensland. A pseudo-3D geological model was built and calibrated, in combination with 1-D burial and thermal history modelling of Desert Creek 1 and Egilabria 1. These were combined with source rock characteristics (e.g., Rock Eval and kerogen kinetics) which helped assess the hydrocarbon generation potential by source rock, allowing a broader assessment of petroleum prospectivity of the nLHP. The study focussed on two potential source rocks; the Lawn 4 Sequence and the River Supersequence. Maturity modelling of the Lawn 4 Sequence at Desert Creek 1 and Egilabria 1 predicted equivalent vitrinite reflectance (EqVR) of over 1.2% and 2%, respectively. The River Supersequence was modelled as overmature at both wells. Combining these results with the pseudo-3D model and source rock characteristics demonstrates that the highest maturities are encountered in the deepest depocentres to the east and gradually decrease in maturity to the west, indicating some potential for wet gas. Modelling results show generation of varying amounts of gas and oil from each potential source rock. Overall, due to the age of the sediments, maximum depth of burial and high paleotemperatures, the most likely hydrocarbon phase is gas from primary generation and supplemented by secondary gas from oil cracking. In spite of high maturities, encouraging gas shows from the Egilabria prospect support continued exploration interest in this region for unconventional hydrocarbons.

As part of the $225 million Exploring for the Future programme, Geoscience Australia have undertaken an investigation into the resource potential of the Officer-Musgrave-Birrindudu region. Part of this project focusses on characterising palaeovalley groundwater resources within the West Musgrave region of Australia. This record presents a three-dimensional palaeovalley model and describes the method used in its generation. Understanding the 3D architecture of palaeovalleys is an important component of conceptualising the shallow groundwater system. In this region groundwater is the only significant water resource, and is critical for supporting local communities, industries and the environment. The data products released alongside this record are a base of gridded Cenozoic surface, a grid of the thickness of the Cenozoic and polygons defining the spatial extent of palaeovalleys. The study area encompasses the upper reaches of several large palaeovalleys. These valleys incised mostly crystalline rocks of the Musgrave Province and sedimentary rocks of the adjoining basin during the late Cretaceous. Subsequently, valleys were filled by Cenozoic-aged sediments, which now form the aquifers and aquitards of the modern-day groundwater system. Palaeovalley architecture has been shaped by a complex interplay of climatic, tectonic, and geological factors over geological time. In some cases, tectonic deformation has caused tilting or disruption of palaeovalleys with implications for groundwater flow. We modelled the base of Cenozoic surface across the project area and used this geological surface to identify palaeovalleys. The modelling process used airborne electromagnetic conductivity models, borehole data and geological outcrop as model inputs. Using these data, we interpreted the base of Cenozoic along AEM flightlines, at borehole locations and at the surface where Pre-Cenozoic geology was cropping out. These data were gridded to generate the base of Cenozoic surface. This surface was then used as the basis for interpreting palaeovalley extents. The resulting model is adequate for its purpose of better understanding the groundwater system. However, the model has considerable uncertainty due to uncertainty in the model inputs and data sparsity. The model performed much better within the centre of the project area within the Musgrave Province compared to the adjoining basins.