ASEG Extended Abstracts - 2nd Australasian Exploration Geoscience Conference: Data to Discovery, 2019

2.5D (2D geology, 3D source) inversion of airborne electromagnetic (AEM) data has evolved into a routine and established practice on datasets from an array of applications. Large datasets may be inverted in days using conventional PC’s, or cloud computing for faster results.

The 2.5D inversions in this study were carried out using a highly modified adaptation of the ArjunAir program originally developed by the CSIRO and subsequently by AMIRA project P223F. The new program is called Moksha.

Results are presented from a continental scale AEM regional mapping survey carried out by Geoscience Australia. 2.5D inversions performed in a study area in the Mammoth Mines mineral district of Queensland defined discrete conductivity anomalies on a line over the Mount Gordon Fault Zone, and imaged a series of steeply-dipping conductors on a nearby regional traverse.

The study demonstrated the ability of 2.5D inversions to image steeply-dipping and folded geology, and present possible exploration targets, in a mineralised deformed terrane.

Giant quartz reefs can develop as part of a larger scale ‘mineral factory’ within a specific space and time, due to a series of interlinking processes and mechanisms. Ascertaining the criteria for giant quartz reef formation is based on data obtained from multidisciplinary, multi-scale analysis. The results show that a ‘quartz reef window’ is met when the following conditions are optimal (i) accommodation space; (ii) permeability; (iii) significant fluid supply; (iv) considerable Time Integrated Fluid Fluxes; (v) temperature conditions; (vi) SiO2 oversaturation; and (vii) cap rock/seal is present. These elements are key to understanding the evolution of giant quartz reef formations, as well as identifying and targeting these mineral lodes.

We present results of 18 magnetotelluric (MT) stations from the Link East transect adjacent to the 03GA-CU1 Curnamona deep crustal seismic reflection line in the southern Curnamona Province, South Australia. The transect was designed to provide resistivity information on the crustal architecture to complement existing datasets and cross the Flinders Conductivity Anomaly (FCA), now known as separate conductors from AusLAMP 3D resistivity models. On the eastern third of the profile, the 10 km site spacing of the profile has allowed us to image two upper crustal conductors (1 Ωm) to the east and west of the Kalkaroo anticline. The eastern conductor (1-4 km depth) is situated in the southern limb of the Mooleulooloo syncline containing Bimba Formation and Strathearn Group sediments, while the western conductor (1-2 km depth) is situated in a small graben comprising Neoproterozoic sediments. On the eastern half, at midcrustal depths (~15-30 km) a broad conductor (> 20 Ωm) is identified as the southern extension of the Curnamona Conductor with conductive fluid pathways connecting to the upper crustal conductors.

Exploration and mining companies in Australia are faced with the challenge of locating deep ore deposits potentially buried under hundreds of metres of cover sequence materials. This research aims to investigate how the integration of hyperspectral remote sensing and surface geochemistry can be used to recognise signatures of alteration potentially associated with buried mineralisation. While each of these methods are individually mature, their combination for the purpose of mineral exploration is novel. Integration of methods including classification of spatial data and radiometric imagery, hyperspectral alteration mineral mapping and lithogeochemical analysis has produced results that might benefit exploration within the study area of the Central Gawler Gold Province. Further, the methods developed have the potential to be applied in other areas and therefore benefit the wider Australian and international minerals industry, especially in areas where there is no obvious expression of alteration at the surface.

Existing 3D geological modelling methods do not incorporate fault kinematics and do not have any way of modelling interacting fault networks, e.g. duplex systems, flower structures and listric fault systems. It is difficult to build models that honour both geological observations and fault kinematics because fault kinematics are not used to constrain the resulting geometries. In this study we introduce a new method for modelling faults within implicit 3D geological modelling systems where the fault kinematics are incorporated by restoring the model domain. Our approach is capable of building models that honour both structural geological data and fault kinematics. Because our approach uses the kinematics of the faults it is also possible to model interactions between co-eval faults where the resulting geometry is the result of combining the fault displacements. We demonstrate this with two synthetic examples: a normal fault system and a duplex system.

The Cooper Basin of Australia is a world-class unconventional gas resource with estimated gas resources of 29.8 trillion cubic feet. However, the production of this gas is challenging as the significant gas resources are located in deep coal seams, which are poorly cleated and characterised by extremely low matrix permeability. Feasibility of gas production from the Cooper Basin Deep Coal Gas (CBDCG) play was demonstrated by Santos; however, its commercial viability is yet to be proven.

Recent studies provided a new insight into the gas generation ability of Cooper Basin coal seams and showed that multiple environmental features affect gas concentration and flow capacity. Fortunately, a large historical dataset exists and includes wireline and mud log data from wells drilled in the Cooper Basin. Up to 10,000 individual coal seams were identified in 1400 wells and various parameters of individual reservoir intersections, which include gas in place, thermal maturity, temperature and other petrophysical readings, completed the Cooper Basin Deep Coal Reservoir (CBDCR) database. Such a database is suitable for assessing the potential of the ultradeep Permian coal gas reservoirs of the Cooper Basin using machine learning.

In this study, we explore the data using traditional statistical methods and propose a hierarchical clustering procedure to identify various coal seam families. The quality of the identified coal seams families (clusters) is then examined by domain experts. The gas in place, geomechanical parameters, pore pressure and other important for successful production parameters can be further assessed for all confirmed clusters.

CO2 injection in oil reservoirs has been widely accepted as an effective EOR and CO2 storage technique. While oil recovery and CO2 storage potential of this technique at the core scale has been widely studied, complex fluids flow and fluid-fluid interactions at the pore-scale during nearmiscible CO2 injection require further study. For this aim, a unique high-pressure and high-temperature microfluidic system was used to conduct experiments at 2,500 psi and 40°C using live reservoir crude oil.

According to results, during tertiary CO2 injection, due to the positive value of spreading coefficient, CO2 flowed only inside the oil and oil spread over CO2 and prevented CO2 contact the water. Due to unfavourable mobility ratios and permeability heterogeneities, displacement during tertiary CO2 flooding was unstable and viscous fingering occurred which led to an early breakthrough of CO2 and bypassing of a large amount of oil. However, after CO2 breakthrough, CO2 gradually started to flow inside the bypassed oil zones in the transverse/backward directions which is a characteristic of capillary fingering. Due to the gradual diffusion of CO2 into the bypassed oil, IFT between oil and CO2 decreased which led to a reduction of threshold capillary pressure, thus CO2 (non-wetting phase) entered the bypassed oil-filled pores. As a result of this unique mechanism, oil recovery after CO2 breakthrough significantly increased and almost all the bypassed oil was produced. The extent of this oil recovery mechanism depends on the extent of CO2-oil IFT reduction which depends on injection pressure.

During CO2 flow in pores, CO2 displaced the water through multiple displacement mechanism. CO2 displaced the oil in the open-end pores thorough bulk flow, and the spreading oil layers were gradually produced by film flow. Uniquely, CO2 produced the oil in dead-end pores through a mix of bulk flow and film flow.

The outcomes of this study provide an in-depth understanding of fluids flow and fluid-fluid interactions during near-miscible CO2 EOR-storage.

Integration of geology and geophysics thinking requires a common earth model, that accommodates, with errors, all the features from the geophysics interpretation products, topological rules from geology, field mapping and drill logs, and the link between the two via physical rock property estimates. Automation of intelligent search, inference engines to this problem involves 200+ individual processes, to yield a family of plausible models. The true limiting factor is managing technical complexity and communicating to the geoscience team, not compute power.

All models are wrong and are destined to be replaced as further data or insights are gleaned. So, taking too much time trying to create the ultimate “correct” interpretation is wasteful, hence the need for automation.

An example of a simple pattern recognition technique to locate kimberlite pipes that have a magnetic and/or gravity response is given. This uses a range of pipe diameters, depths, topography, density and susceptibility, and variable directions of remanent magnetization vectors, in an automated manner.

Most regional scale magnetic maps are dominated by the magnetic characteristics of steeply dipping basement units truncated by an unconformity surface. It is easy to demonstrate that 80 to 90% of each total field magnetic anomaly is contributed by this intersecting surface. We approach this problem by mapping the boundaries between contrasting magnetic units along each line in the magnetic survey using the full precision of the line data and 3D information from the magnetic gradient tensor. Additionally, we derive the azimuth of each boundary, depth to the unconformity and magnetic properties of the anomalous units. The segments are overlain on any image such as existing geological maps, satellite imagery, gravity or magnetic imagery to provide a new geological interpretation concept. This method provides a new way to interpret new and old magnetic surveys.

Eigenvector analysis of the magnetic tensor and normalised source strength (NSS) are combined with an artificial intelligence (AI) approach to estimate the basement properties. The method is applied to full tensor magnetic survey data or a grid of the total magnetic intensity data is processed using FFT transformations to derive the magnetic gradient tensor. These data are used as input to the pre-trained AI process for calculation of depth, width, azimuth, magnetic susceptibility and magnetisation direction. The rock properties and depth information can be used for 3D visualisation of the unconformity and 2D mapping of the magnetic lithology of the unconformity surface.

Magnetotellurics is a versatile exploration technique that can be used for imaging across scale lengths of tens to hundreds of metres, down to tens to hundreds of kilometres. Only in recent years has the potential of MT as an exploration tool been fully realised across varying depth scales. The optimum design of an MT survey for imaging the full mineral system has not yet been studied in detail, leaving questions such as, could the famous ‘Fingers of God’ conductivity anomalies that point to Olympic Dam, Wirrda Well and Vulcan deposits be resolved with larger site spacing or with a narrower period range? What about with an array instead of a transect? These questions are addressed using synthetic studies that take known conductivity anomalies that lead to mineral deposits, and trialling different survey layouts, period ranges and cover thickness to determine the ideal survey layout to make sure these features are not missed, whilst keeping survey acquisition expenditure and time to a minimum.

Eigenvector analysis of the magnetic gradient tensor is combined with an artificial intelligence (AI) approach to rapid, interactive estimation of depth to magnetic source for a variety of geological target shapes. The method uses the flight line data for maximum depth resolution and grids of the magnetic gradient tensor and other parameters for 2D spatial attributes. The magnetic gradient tensor and related parameters are computed using FFT processing of the original total magnetic intensity grid. These data are then used as input to the pre-trained AI process for preliminary calculation of depth, width and magnetic susceptibility.

The eigenvectors are used to compute the normalised source strength (NSS) which peaks over the centre of magnetisation of the magnetic target. The tensor is used to compute the dimensionality of the target which is then used to infer if it is pipe-like or linear. If the target is linear or elongate, the eigenvector analysis provides a direct method for calculating the azimuth of the target at the centre of magnetisation. The azimuth is then used to correct the apparent depth, width and susceptibility estimates. If the target is pipe-like or an ellipsoid in shape, then the eigenvector is used to compute the azimuth and dip of the magnetisation vector. The NSS results also provide a useful tool for estimating the level of interference between adjacent magnetic anomalies, a factor that decreases the accuracy of any magnetic depth estimate. The AI algorithm uses this information to assign a quality estimate to the depth result.

At this point, the AI algorithm has derived a lot of information about the target shape, orientation and approximate depth. This information is then used to constrain some classic depth interpretation techniques that include the tensor, Euler 2D, Euler 3D, Peters Length, Werner Deconvolution and Tilt methods. The numerical complexity of each of these methods is greatly simplified because the origin of the target is the centre of magnetisation. Each method has strengths and weaknesses and the AI algorithm attempts to select the best method and most probable geological shape. Interpreters can override both the method and target shape if they are not satisfied with the AI selection because the shape selection has a large influence on the depth estimation precision.

The Exmouth Sub-basin forms one of several Jurassic depocentres in the greater Carnarvon Basin and has been prolific in terms of hydrocarbon production with approximately 1 Bbbls of oil and over 1 Tcf of gas discovered/produced to date.

The sub-basin was recently covered for the first time with a contiguous, high quality, deep-record 3D seismic survey that has enabled detailed structural and stratigraphic mapping over its full extent, providing new insights into the tectono-stratigraphic history of the area.

These interpretations along with those incorporating the sub-basins thermal history and gross depositional environments were used to constrain an integrated petroleum systems model with the ultimate aim of representing hydrocarbon distribution and future exploration potential.

Zircon and xenotime U-Pb SHRIMP geochronology was conducted on samples from the South Nicholson Basin, and western Mount Isa Orogen. These samples were collected from outcrop and core from the Northern Territory and Queensland. The age data indicate the South Nicholson Basin was deposited after ca. 1483 Ma but deposition most likely had ceased by ca. 1266 Ma; the latter age likely represents post-diagenetic fluid flow in the area, based on U-Pb xenotime data. Geochronology presented here provides the first direct age data confirming the South Nicholson Group is broadly contemporaneous with the Roper Group of the McArthur Basin, which has identified facies with high hydrocarbon prospectivity. In addition, geochronology on the Paleoproterozoic McNamara Group provides new age constraints that have implications for the regional stratigraphy. The data obtained in this geochronological study allow for a comprehensive revision of the existing stratigraphic framework, new correlations and enhances commodity prospectivity in central northern Australia.

Seismic physical modelling is a powerful method for verification of different algorithms and also for better understanding wave propagation phenomenon. In this paper, we design a physical model made out of Plexiglas to investigate the effect of fluid substitution on Amplitude Variation with offset (AVO) by designing a physical model in a way that remove the influence of other factors that can impact the AVO behavior. We record the seismic response of two scenarios, one that is representative of dry/gas saturated medium and another one is the representative of water saturated medium. After processing of recorded seismic data and picking the reflection amplitude, we implement some corrections over the reflection amplitude to represent true reflectivity. The corrected amplitude of both cases were used to extract Intercept (R0) and Gradient (G) AVO attributes based on the Shuey equation. The extracted values are mapped on R0 − G cross-plot. From the cross-plot, it is clear that the substitution of water with gas is resulted in shifting the position of point toward the center of the cross-plot.

Exploring for the Future is a four-year $100.5 million initiative by the Australian Government conducted in partnership with state and Northern Territory government agencies and universities that aims to boost northern Australia's attractiveness as a destination for investment in resource exploration. The acquisition of deep crustal seismic reflection data in the Kidson Sub-basin (Canning Basin) between the Kiwirrkurra community and Marble Bar in northern Western Australia was a major EFTF objective, and was completed in August 2018. This paper presents the preliminary geological interpretation of the sedimentary succession imaged by the Kidson Sub-basin seismic line.

The direct current electrical resistivity and induced polarization (DCIP) method has received another significant upgrade through the introduction of common voltage referencing (CVR) in a fully-distributed array system. An array of single-channel receivers with a CVR wire allows for the extraction of an unprecedented volume of dipole data for the number of receivers deployed. In 3D implementation, this new method reduces noise levels and allows for the derivation of multi-scale and multi-azimuth receiver dipoles.

Operational efficiencies in the CVR method include lower overall wire lengths, less equipment weight and less crew fatigue when compared with conventional and other distributed array methods. Cable-free mesh network capability in each receiver allows for real-time assessment of data quality metrics, safety information, location data, and system health data. These operational efficiencies translate directly to improvements in safety.

With several hundred active receivers, data volume can reach 10s of millions of data records. Careful processing and selection of an optimised data subset with multi-scale and multi-azimuth information will inform highly accurate inversion imaging.

Predicting the interconnectivity and permeability of fractures at any scale remains a fundamental challenge in structural geology. Models which predict the likelihood of fracture opening based on their relation to the stress field can be applied at scales of 100s of metres to kilometres. Increasingly however, an understanding of how networks of the smallest-scale (sub-seismic to mm) natural fractures permit fluid flow in the subsurface appears key to predicting and exploiting these pathways. Here, we apply the nascent method of network topology to natural fracture networks to a fossilised fault damage zone in the Otway Basin. Network connectivity and the potential to percolate fluids has been shown to be directly related to the topology, and intensity of fracturing. This technique is relatively straightforward, provides a range of parameters to define various aspects of a fracture network (e.g. intensity, connectivity), and is independent of the scale and geometry of the structures of interest. We integrate this technique with traditional structural analysis to illustrate the scale of fracturing around a region-scale fault and constrain spatial variation in permeability associated with the fracture network. We also illustrate how elements of this technique might be applied to existing sub-surface data.

In order to understand the nature of reflections imaged by reflection seismic data in hard-rock environment and to investigate the seismic anisotropy across the Karari gold deposit, ultrasonic velocity measurement and seismic anisotropy studies were conducted on 18 representative samples of different alteration zones of the deposit.

The preliminary results indicate a remarkable contrast of acoustic impedance between the volcaniclastic host rock and the slightly altered zone, making this seismic interface a good guide to delimitate the mineralised zone. Furthermore, the foliated unaltered host rocks possess high values of seismic anisotropy, which must not be ignored during the seismic processing and interpretation. The anisotropy of the altered rocks is much smaller – this change in anisotropy could be potentially used as an additional parameter for seismic identification and characterisation of the altered zones.

The offshore Northeast Java Basin is one of the largest basins in Indonesia and one that contains complete hydrocarbon systems from Middle Miocene Tuban formations to Pre Tertiary basement formations. The offshore East Java Basin is located on the southeast margin of Sundaland and is dominated by a series of Northeast trending basement highs and intervening half – grabens that formed during Late Cretaceous to Tertiary times along the Southeast margin of the Sunda Plate (Manur and Barraclough, 1994).

In Pangkah Field, Carbonaete Oligo-Miocene has a diversity property of reservoir. Challenges to identified characterisation resevoir using stochastic inversion method. Within this method enhance our detail in classification distribution of carbonate facies. East Java projects using deterministic seismic inversion has been successfully executed, but need additional data and analysis for better visualization of reservoir, caused by heteregeneous reservoir due to various property and thickness. Some of the benefits of these methods are inverted impedances rock properties calibrates with well data, seismic inversion process reduces the wavelet and tuning effects estimating the thickness of a thin bed to improving the understanding of the reservoir geology for exploration strategy and development. We used a stochastic inversion methodology, which simulates many possible realizations, to better discriminate the thickness and real extent of the carbonate/shale layers, and estimate the uncertainties of carbonate volumes (P10, P50 and P90) in the Kujung I play and CD Carbonate Play of the Pangkah PSC.