The Neoproterozoic–Paleozoic Officer Basin, located in South Australia and Western Australia, remains a frontier basin for energy exploration with significant uncertainty due to a paucity of data. As part of Geoscience Australia’s Exploring for the Future (EFTF) program, the objective of this study is to derive the petrophysical properties and characterise potential reservoirs in the Neoproterozoic–Cambrian sedimentary succession in the Officer Basin through laboratory testing, and well log interpretation using both conventional and neural network methods. Laboratory measurements of forty-one legacy core samples provide the relationships between gas permeability, Klinkenberg corrected permeability, and nano-scale permeability, as well as grain density, effective and total porosity for various rock types. Conventional log interpretation generates the volume fraction of shale, effective and total porosity from gamma ray and lithology logs. Self-organising map (SOM) was used to cluster the well log data to generate petrophysical group/class index and probability profiles for different classes. Neural network technology was employed to approximate porosity and permeability from logs, conventional interpretation results and class index from SOM modelling. The Neoproterozoic-Cambrian successions have the potential to host both conventional and tight hydrocarbon reservoirs. Neoproterozoic successions are demonstrated to host mainly tight reservoirs with the range in average porosity and geometric mean permeability of 4.77%-6.39% and 0.00087-0.01307 mD, respectively, in the different sequences. The range in average porosity and geometric mean permeability of the potential Cambrian conventional reservoirs is 14.54%-26.38% and 0.341-103.68 mD, respectively. The Neoproterozoic shales have favourable sealing capacities. This work updates the knowledge of rock properties to further the evaluation of the resource potential of the Officer Basin. Published in The APPEA Journal 2022 <b>Citation:</b> Wang Liuqi, Bailey Adam H. E., Carr Lidena K., Edwards Dianne S., Khider Kamal, Anderson Jade, Boreham Christopher J., Southby Chris, Dewhurst David N., Esteban Lionel, Munday Stuart, Henson Paul A. (2022) Petrophysical characterisation of the Neoproterozoic and Cambrian successions in the Officer Basin. <i>The APPEA Journal</i><b> 62</b>, 381-399. https://doi.org/10.1071/AJ21076

Barnicarndy 1 is a stratigraphic well drilled in the southern part of the Canning Basin’s Barnicarndy Graben under Geoscience Australia’s Exploring for the Future program in collaboration with the Geological Survey of Western Australia to provide stratigraphic data for this poorly understood tectonic component. The well intersects a thin Cenozoic section, Permian–Carboniferous fluvial clastics and glacial diamictites and a thick pre-Carboniferous succession (855–2585 mRT) unconformably overlying Neoproterozoic metasedimentary rocks. Three informal siliciclastic intervals were defined based on core lithology, well logs, chemical and mineral compositions: the Upper Sandstone (855–1348.1 mRT), Middle Interval (1348.1–2443.4 mRT) and Lower Sandstone (2443.4–2585 mRT). The Middle Interval was further divided into six internal zones. Both conventional methods and artificial neural network technology were applied to well logs to interpret petrophysical and elastic properties, total organic carbon (TOC) content, pyrolysis products from the cracking of organic matter (S2) and mineral compositions. Average sandstone porosity and reservoir permeability are 17.9% and 464.5 mD in the Upper Sandstone and 6.75% and 10 mD in the Lower Sandstone. The Middle Interval claystone has an average porosity and permeability of 4.17% and 0.006 mD, and average TOC content and S2 value of 0.17 wt% and 0.047 mg HC/g rock, with maximum values of 0.66 wt% and 0.46 mg HC/g rock, respectively. Correlations of mineral compositions and petrophysical, geomechanical and organic geochemical properties of the Middle Interval have been conducted and demonstrate that these sediments are organically lean and lie within the oil and gas window. Published in The APPEA Journal 2021 <b>Citation:</b> Wang Liuqi, Edwards Dianne S., Bailey Adam, Carr Lidena K., Boreham Chris J., Grosjean Emmanuelle, Normore Leon, Anderson Jade, Jarrett Amber J. M., MacFarlane Susannah, Southby Chris, Carson Chris, Khider Kamal, Henson Paul, Haines Peter, Walker Mike (2021) Petrophysical and geochemical interpretations of well logs from the pre-Carboniferous succession in Barnicarndy 1, Canning Basin, Western Australia. <i>The APPEA Journal</i><b> 61</b>, 253-270. https://doi.org/10.1071/AJ20038

Cloud coverage remains a key issue for researchers working with satellite data. Accurate reconstruction of measurements obstructed by cloud can enhance the usefulness of satellite databases for identifying trends and changes in various environments. In this work, we develop, train and test a bidirectional long short-term memory (BiLSTM) model with a custom temporal penalty layer for filling gaps in sea surface temperature (SST) images acquired by the Himawari- 8 satellite. The proposed model showed strong performance, achieving a per-image MAE of 0.1193◦C and per-image RMSE of 0.0985◦C. Our model is also shown to outperform previous state-of-the-art literature. Overall, this work shows that our BiLSTM algorithm is an effective tool for gapfilling cloud-affected SST data. <b>Citation: </b>S. Baker, Z. Huang and B. Philippa, "Lightweight Neural Network for Spatiotemporal Filling of Data Gaps in Sea Surface Temperature Images," in <i>IEEE Transactions on Geoscience and Remote Sensing</i>, vol. 61, pp. 1-10, 2023, Art no. 4204310, doi: 10.1109/TGRS.2023.3273575