b'AEGC 2021Short abstracts253: Microbial methane production in the Surat Basin,Distributed fibre-optic sensing is being actively used in Queensland various exploration and reservoir monitoring applications. Understanding of how exactly distributed acoustic (DAS) Ms Bronwyn Campbell 1, Dr Se Gong2, Dr Paul Greenfield2,measurements can be affected by changing of the temperature DrDavid Midgley2, Prof Ian Paulsen1 and Prof Simon George1 conditions is paramount to avoid or/and eliminate noise related to these temperature variations. This can be particularly critical 1 Macquarie University for the DAS time-lapse seismic and passive monitoring.2 CSIROA large proportion of the methane found in coal seams isFor this study we utilised the Curtin University Geolab (NGL) produced by microbial communities. Despite coal seam methaneresearch facility and Rock-Physics Laboratory to estimate being a valuable resource for human energy security, little istemperatures effect on three various DAS cables. Two fibres known about the microbial communities responsible for muchwere tested in the laboratory and one cable (installed in the of its production. Previous literature has identified many of theNGL well) was examined at the site. We showed that DAS microbes present in coal seams internationally and which broadis sensitive to long-period temperature changes and its coal characteristics lead to greater methane production, howeverresponse is proportional to a time derivative of temperature. our understanding of the interactions between these microbialWe also estimated strain-temperature dependencies (thermal communities and coal is mainly speculative. The present studycoefficients) in all three tests. Our study shows that by using aims to determine which microbes are performing the final stepDAS and temperature data together, it is possible to estimate in coal degradation to methane within the Walloon Subgroupstraintemperature change dependency (coefficientin the Surat Basin, Queensland. Two datasets of coal seammicrostrain/C) for a particular cable. Coefficients estimated in microbial community DNA were processed in order to identify athree tests indicate that cable design can affect DAS response specific region of a gene (known as mcrA) required for methaneto temperature changes. Temperature change can have a production. Closest known relatives and probable methanogenicsignificant effect on DAS measurements and must be taken pathways of the detected mcrA genes were then determinedinto account in time-lapse DAS seismic monitoring applications and compared across both datasets. Increased understanding ofand especially for passive monitoring with the utilisation of low coal seam microbial community structure and function has thefrequencies.potential to enhance gas production at existing wells, and also to assist in the exploration stage of coal seam gas extraction by256: Next-generation velocity model of the Australian providing a clearer guide of which aspects of the coal or whichcrust from synchronous and asynchronous ambient microbes are most important to have present. noise imaging254: Closing the gap between ground and airborne IPDr Yunfeng Chen 1 and Dr Erdinc Saygin1data modelling 1 Deep Earth Imaging, Future Science Platform, CSIRODrandreaviezzoli 1 and Prof Gianluca Fiandaca2 The proliferation of seismic networks in Australia has laid the 1 Aarhus Geophysics groundwork for improved probing of the continental crust. 2 Department of Earth Sciences, Universit di Milano Despite ever-growing seismic instrumentation across the country, the last major effort of mapping continental-scale Modelling of Induced Polarization in AEM data (AIP) has recentlystructures with ambient noise was conducted more than a been used more often in exploration. Which demands fordecade ago. In this study, we develop a new crustal model using more research to address the fundamental question how doesa large dataset that consists of nearly three decades (1994-AIP compare to ground IP?. Beside some of the well-known2019) of continuous seismic recordings from over 1600 stations. differences in terms of, e.g., frequencies deployed and expectedThis unprecedented dataset is further exploited with the to be recoverable or depth of investigation, one recurring issuerecently developed ambient noise imaging workflow of Chen hampering the comparison is the use of different modelling& Saygin (2020) that integrates results from temporary seismic approaches for ground versus IP. Reconciling them is the firstarrays deployed at different times. The new approach enables step to address the question above. To that effect, we use TEMextracting 1-3 times more noise correlation function (NCFs) than data together with full-decay time-domain ground IP data andavailable from the conventional method. As a result, we obtain we adopt the same Cole Cole modelling for both. We produce aover 200,000 high-quality NCFs to image the crustal structures, suite of simple synthetic examples that illustrate the sensitivitysignificantly improved upon the most recent model constructed of the two methods to the Cole-Cole spectral parameters andfrom 7500 measurements.their potential complementarity. The results suggest that groundThe final 3D shear velocity model reveals fine-scale structures and airborne IP data can be modelled with the same approach,in the Australian crust. The low velocities at shallow depths providing a much more robust IP model, based on their combined(10 km) are in excellent agreement with the distribution influence. Morevover, AIP can help designing more efficient (faster,of known sedimentary basins. On the other hand, the long cheaper, less risky) ground IP surveys, without compromising,period dispersion data enable resolving to the first time the often improving, the accuracy of the final output models lower crustal structures with ambient noise imaging. The 255: Laboratory study of temperature variation effectsMoho depths of our model agree well with the values from on Distributed Acoustic Sensing measurements AusMoho, a reference model complied with point-based Moho depth estimates. Our model also provides new information Mr Evgenii Sidenko 1, Prof Roman Pevzner1, Dr Konstantinfor the Moho depth in previously poorly sampled regions. For Tertyshnikov and Prof Maxim Lebedev1 example, our model shows a deeper Moho than previously reported near the northeastern edge of the Gawler craton in 1 Curtin University South Australia. In conclusion, this study provides significantly AUGUST 2021 PREVIEW 106'