b'AEGC 2021Short abstractsdimensions can substantially reduce the risk and uncertaintyNoise, particularly distortion of signal, is often the dominant involved in modelling and interpreting shale- and tight-gasproblem with land seismic data and much data redundancy reservoirs, including traps associated with Coal Bed Methaneand expense is incurred during acquisition to address noise (CBM). Anisotropy, Poissons ratio and Youngs modulusissues. Acquisition must sample the subsurface sufficiently that properties corroborate the interpretation of stress images fromnoise can be effectively handled during processing, particularly the 3D acoustic characterization of shale reservoirs. The statisticalwhen using powerful new noise removal algorithms that take analysis of data-views, their correlations and patterns furtheradvantage of noise sparsity. This is especially important for facilitate us to visualize and interpret geoscientific metadatashallow scattering noise, being difficult to sample unaliased. meticulously. Data geo-science guided integrated methodologyNew algorithms, using the same principals as compressive can be applied in any basin, including frontier basins. sensing, utilize sparsity to handle aliased noise, so optimizing acquisition for these algorithms is, effectively, compressive 64: Big Data guided digital petroleum ecosystems forsensing for the noise.visual analytics and knowledge management Modern dense acquisition helps with noise removal, but alone does not solve the whole problem because the noise can have Dr Shastri Nimmagadda 1, Mr Andrew Ochan2, Dr Neel Mani3very short wavelengths, tight sampling doesnt solve signal and Dr Dengya Zhu1 distortion, some noise doesnt require ultra-dense sampling and the gain from signal-to-noise ratio diminishes as we increase 1 Curtin University fold. However, this dense acquisition does provide flexibility to 2 PAU optimize seismic acquisition to aid processing.3 Amity ITIn terms of handling noise issues inherent in seismic data, the The North West Shelf (NWS) interpreted as a Total Petroleumsuccess of any acquisition-processing combination is based on System (TPS), is Super Westralian Basin with active onshoreseveral factors - the amplitude of the noise relative to signal, the and offshore basins through which shelf, -slope and deep- types of noise observed, the multi-dimensional sampling of the oceanic geological events are construed. In addition to theirnoise, the ability of processing algorithms to address the noise data associativity, TPS emerges with geographic connectivityand the seismic objective (frequency, inversion, AVO, subtle through phenomena of digital petroleum ecosystem. The superfaults, complex structure).basin has a multitude of sub-basins, each basin is associatedSeismic noise and energy transmission vary dramatically by with several petroleum systems and each system comprisedfrequency. At low and high frequencies , data are often more of multiple oil and gas fields with either known or unknownthan 10 times noisier than in the prime frequency range. areal extents. Such hierarchical ontologies make connectionsMoreover, the noise at different frequencies can have vastly between attribute relationships of diverse petroleum systems.different characteristics. Low frequencies are often affected Besides, NWS has a scope of storing volumes of instances inby trapped surface waves and macro-scattering while higher a data-warehousing environment to analyse and motivatefrequencies are affected by guided waves and micro-scattering. to create new business opportunities. Furthermore, theWe cannot eliminate this noise in acquisition, but we can record big exploration data, characterized as heterogeneous andthe data sufficiently well to aid removing it in processing.multidimensional, can complicate the data integration process, precluding interpretation of data views, drawn from TPS metadata in new knowledge domains. The research objective66: Interpretation of magnetotelluric and airborne is to develop an integrated framework that can unify the exploration and other interrelated multidisciplinary data into aelectromagnetic inversions from the Proterozoic basins holistic TPS metadata for visualization and valued interpretation.of the Capricorn Orogen, WAPetroleum digital ecosystem is prototyped as a digital oilDr Sasha Banaszczyk , Prof Mike Dentith, Dr Perla Pia-Varasfield solution, with multitude of big data tools. Big data1,2 3,4,1,2associated with elements and processes of petroleum systemsand Dr David Annetts5are examined using prototype solutions. With conceptual1 Centre for Exploration Targetingframework of Digital Petroleum Ecosystems and Technologies2 The University of Western Australia(DPEST), we manage the interconnectivity between diverse3 Dinmica de la Terra i dels Oceanspetroleum systems and their linked basins. The ontology- 4 Universitat de Barcelonabased data warehousing and mining articulations ascertain the5 CSIRO Mineral Resourcescollaboration through data artefacts, the coexistence between different petroleum systems and their linked oil and gas fieldsThe Bryah and Yerrida Basins of the Capricorn Orogen, WA, that benefit the explorers. The connectivity between systemscomprise sedimentary sequences that are prospective for further facilitates us with presentable exploration data views,base metals and which can be mapped using airborne improvising visualization and interpretation. The metadataelectromagnetic (AEM) and magnetotelluric (MT) techniques. with meta-knowledge in diverse knowledge domains ofA regional MT survey (50 km100 km station-spacing) and a digital petroleum ecosystems ensures the quality of untappedregional AEM survey (5 km line-spacing) have been acquired reservoirs and their associativity between Westralian basins. across the Capricorn Orogen for this purpose. Unfortunately, the AEM and MT surveys provide information at vastly different scales 65: Optimizing land seismic acquisition for modern(local-basin versus orogen, respectively), which, in addition to noise suppression in processing the paucity of MT data, complicates comparisons between the two datasets. Indeed, few studies compare AEM and MT results Mr Graeme Eastwood 1 and Mr Christof Stork1 and interpretations thereof, particularly within prospective sedimentary basin terrains. Two newly acquired MT survey lines 1 Land Seismic Noise Specialists proximal to several Capricorn Orogen AEM survey lines over the AUGUST 2021 PREVIEW 72'