Mark Lindsay

Inversion and Geodiversity: Searching Model Space for the Answers

Geophysical inversion employs various methods to minimize the misfit between geophysical datasets and three-dimensional petrophysical distributions. Inversion techniques rely on many subjective inputs to provide a solution to a non-unique underdetermined problem, including the use of a priori model elements (i.e. a contiguous volume of the same litho-stratigraphic package), the a priori input model itself or inversion constraints. In some cases, inversion may produce a result that perfectly matches the observed geophysical data, but can still misrepresent the geological system. A workflow is presented here that offers objective methods to provide inputs to inversion: (1) simulations are performed to create a model suite that contains a range of geologically possible models; (2) stratigraphic variability is determined via uncertainty analysis to identify low certainty model regions and elements; (3) geodiversity analysis is then conducted to determine geometrical and geophysical extremes and commonalities within the model space; (4) geodiversity metrics are simultaneously analysed using principal component analysis to identify the contribution of different model elements toward overall model suite uncertainty; (5) principal component analysis also determines which models exhibit diverse or common geological and geophysical characteristics which (6) facilitate the selection of models as inputs to geophysical inversion. This workflow is applied to a three-dimensional model of the Ashanti Greenstone Belt, southwestern Ghana in West Africa in order to reduce the subjectivity incurred during decision making, explore the range of geologically possible models and provide geological constraints to the inversion process to produce geologically and geophysically robust suites of models. Results further suggest that three-dimensional uncertainty grids can optimize inversion processes and assist in finding geologically reasonable solutions.

An irregular triangle mesh buffer analysis method for boundary representation geological object in three-dimension

Three-dimensional (3D) buffer analysis is a basic function of spatial analysis used widely in 3D Geographic Information Systems (3DGIS). Current buffer analysis methods for spatial points and curves generally function well. One exception is buffer zone of surface. Previous researchers in this field have used voxel models to overcome this limitation; however, defects with voxel model buffer analysis include redundancies, approximations, and poor visualization characteristics. In this contribution, a surface buffer analysis method is presented for the boundary representation of geological objects. Exact geometric representation is achieved via the construction of irregular triangle meshes in 3D. The results can be used for 3D structural modeling and then form the basis for spatial analysis or model-based quantitative assessment in mineral potential mapping and resource evaluation. Three comparisons between existing voxel methods and our new method, evaluating visualization, precision and redundancy, are conducted. The comparisons show that our proposed method is robust and provides a higher quality output than voxel modeling. Finally, uncertainty analysis of buffer distance in different geological objects was discussed.

Improving assessment of geological structure interpretation of magnetic data

Geological structures are recognisable as discontinuities within magnetic geophysical surveys, typically as linear features. However, their interpretation is a challenging task in a dataset with abundant complex geophysical signatures representing subsurface geology, leading to significant variations in interpretation outcomes amongst, and within, individual interpreters. Previously, numerous computational methods were developed to enhance and delineate lineaments as indicators for geological structures. While these methods provide rapid and objective analysis, selection and geological classification of the detected lineaments for structure mapping is in the hands of interpreters through a time consuming process. This paper presents new ways of assisting magnetic data interpretation, with a specific aim to improve the confidence of structural interpretation through feature evidence provided by automated lineament detection. The proposed methods produce quantitative measures of feature evidence on interpreted structures and interactive visualisation to quickly assess and modify structural mapping. Automated lineament detection algorithms find the feature strengths of ridges, valleys and edges within data by analysing their local frequencies. Ridges and valleys are positive and negative line-like features detected by the phase symmetry algorithm which finds locations where local frequency components are at their extremum, the most symmetric point in their cycle. Edge features are detected by the phase congruency algorithm which finds locations where local frequency components are in phase. Their outputs are used as feature evidence through interactive visualisation to drive data evidenced interpretation.Our experiment uses magnetic data and structural interpretation from the west Kimberley region in northern Western Australia to demonstrate the use of automated analysis outputs to provide: quantitative measures of data evidence on interpreted structures, and graphical evaluation of interpretation quality.

Visual saliency and potential field data enhancements:Where is your attention drawn?

Interpretation of gravity and magnetic data for exploration applications may be based on pattern recognition in which geophysical signatures of geologic features associated with localized characteristics are sought within data. A crucial control on what comprises noticeable and comparable characteristics in a data set is how images displaying those data are enhanced. Interpreters are provided with various image enhancement and display tools to assist their interpretation, although the effectiveness of these tools to improve geologic feature detection is difficult to measure. We addressed this challenge by analyzing how image enhancement methods impact the interpreter’s visual attention when interpreting the data because features that are more salient to the human visual system are more likely to be noticed. We used geologic target-spotting exercises within images generated from magnetic data to assess commonly used magnetic data visualization methods for their visual saliency. Our aim was achieved in two stages. In the first stage, we identified a suitable saliency detection algorithm that can computationally predict visual attention of magnetic data interpreters. The computer vision community has developed various image saliency detection algorithms, and we assessed which algorithm best matches the interpreter’s data observation patterns for magnetic target-spotting exercises. In the second stage, we applied this saliency detection algorithm to understand potential visual biases for commonly used magnetic data enhancement methods. We developed a guide to choosing image enhancement methods, based on saliency maps that minimize unintended visual biases in magnetic data interpretation, and some recommendations for identifying exploration targets in different types of magnetic data.

Identifying mineral prospectivity using 3D magnetotelluric, potential field and geological data in the east Kimberley, Australia

Abstract An integrated interpretation of the east Kimberley, northern Western Australia was completed to determine mineral prospectivity, and was centred on a portion of a magnetotelluric (MT) survey conducted across the entire Kimberley Craton and surrounding orogens. A structural geophysical interpretation used potential field data, and was constrained by geological field observations, petrophysics, remote sensing and understanding of the tectonic history of the region. Potential field forward modelling located along the same survey traverse as the MT data allowed comparison between the two datasets and their interpretations revealing interesting features suggesting the presence of large-scale structures, the presence of mineralization deep in the crust, and where mineralization may be at or near the surface. The King River Fault is shown from both the MT inversion and potential field modelling as a crustal-scale, west-dipping structure, the footwall of which bounds the western side of a large resistive body. A conductive anomaly is also located on the hanging wall of the King River Fault. Our assessment suggests that graphitic rocks, most likely with some sulphide content, contribute to the strength of this anomaly, and highlights the potential of the east Kimberley to host graphite and base metal deposits.

A Major Geophysical Experiment in the Capricorn Orogeny, Western Australia

A major geophysical experiment has begun in the Capricorn Orogen in Western Australia. Orogen-scale passive seismic and magnetotelluric surveys are on-going and preliminary results suggest have successfully delineated the base of the crust and major structures and tectonic boundaries. Airborne electromagnetic data have successfully mapped features in the near-surface such as palaeovalleys. The integration of the different geophysical datasets with each other and with parallel geological studies are intended to lead to a better understanding the Capricorn Orogen and develop exploration approaches and appropriate toolkits that significantly improve our ability to prospect under cover.

Integration of geological uncertainty into geophysical inversion by means of local gradient regularization

We introduce a workflow integrating geological uncertainty information in order to constrain gravity inversions. We test and apply this approach to data from the Yerrida Basin (Western Australia), where we focus on prospective greenstone belts beneath sedimentary cover. Geological uncertainty information is extracted from the results of a probabilistic geological modelling process using geological field data and their uncertainty as input. It is utilized to locally adjust the weights of a 15 minimum-structure gradient-based regularization function constraining geophysical inversion. Our results demonstrate that this technique allows geophysical inversion to update the model preferentially in geologically less certain areas. It also indicates that inverted models are consistent with both the probabilistic geological model and geophysical data of the area, reducing interpretation uncertainty. The interpretation of inverted models finally reveals that the recovered greenstone belts may be shallower and thinner than previously thought. 20

Atmospheric sulfur is recycled to the crystalline continental crust during supercontinent formation

The sulfur cycle across the lithosphere and the role of this volatile element in the metasomatism of the mantle at ancient cratonic boundaries are poorly constrained. We address these knowledge gaps by tracking the journey of sulfur in the assembly of a Proterozoic supercontinent using mass independent isotope fractionation (MIF-S) as an indelible tracer. MIF-S is a signature that was imparted to supracrustal sulfur reservoirs before the ~2.4 Ga Great Oxidation Event. The spatial representation of multiple sulfur isotope data indicates that successive Proterozoic granitoid suites preserve Δ33S up to +0.8‰ in areas adjacent to Archean cratons. These results indicate that suturing of cratons began with devolatilisation of slab-derived sediments deep in the lithosphere. This process transferred atmospheric sulfur to a mantle source reservoir, which was tapped intermittently for over 300 million years of magmatism. Our work tracks pathways and storage of sulfur in the lithosphere at craton margins.The long-term evolution of the sulfur budget in the lithosphere is poorly constrained. Here, using mass independent isotope fractionation as an indelible tracer, the authors track the pathway of sulfur from the Earth’s surface to punctuated episodes of granitoid magmatism during collisional orogenesis.