Publications

Innovative processing of high-resolution aerial geophysical survey data (gravity, magnetic and gravity gradiometery) combined with minimal geological data can constrain and validate realistic 3D geology models. In this way, exploration programmes in pre-3D seismic survey phases can access relatively low cost data acquisition and interpretation methods to facilitate detailed geological and structural interpretation, and thus elucidate spatial locations of source rocks, reservoirs, and potential sites for hydrocarbon traps. Our case study focuses on the Merlinleigh Sub-basin, part of the southern Carnavon Basin in Western Australia (Figure 1). For this project we built an initial 3D geology model constrained by minimal geological mapping and just two interpreted regional seismic sections. (Alternatively, a couple of deep stratigraphic wells could have been used.) Next we refined and validated the model using enhanced processing workflows applied to potential field data, including multi-scale edge detection, and depth to basement determination. Finally, we applied a stochastic geophysical inversion to explore for all valid alternative models which can honour the independent datasets (geology, gravity and magnetics) and determined the most probable geological and rock-property models, via a Markov Chain Monte Carlo approach. Model validation prompted the following key geological findings: (i) Multi-scale edge detection outcomes supported the geological modelling, and were particularly useful for mapping of the Wandagee and Kennedy Faults in 3D, (ii) Depth to basement processing concurred with the available seismic section data, and enabled extension of the top of basement mapping in 3D away from the limited seismic lines available. (iii) Property optimisation revealed a high density dyke-like formation aligned with the Wandagee Fault and within basement, and (iv) The most-probable geological model from the post-inversion outcomes indicated small refinements to the geology-geometry mainly to the top of basement horizon compared with the advanced starting model. Our study demonstrates it is possible to accurately characterise 3D geology in greenfields exploration areas by acquiring relatively low cost potential field data, and applying innovative processing and 3D modelling techniques. Keywords: 3D geology, airborne magnetics and gravity, multi-scale edge enhancement (worming), spectral depth determination, Murthy and Roa depth to basement, litho-constrained stochastic inversion.