Airborne Gravity 2010 - Geoscience Australia

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Airborne Gravity 2010 Figure 2. Snapshot of the IGMAS+ workspace that illustrates construction of realistic geological models and integration with FTG and magnetic forward calculation results. Figure 3. Snapshot of IGMAS+ screen showing multiple linked windows. In the control window (top left), the user can select the elements to be displayed. In the property editor (bottom, left), the display colours and model properties such as density, susceptibility, Koenigsberg ratio (Q value) can be changed. Geometry changes are made in the 2D View. Seismic sections can be displayed as overlays to guide the modelling. 93
Airborne Gravity 2010 Inversion for density and susceptibility is performed using a Minimum Mean Square Error (MMSE) method. A statistical approach is used with the MMSE inversion method to obtain the density or susceptibility models (Sæther, 1997; Haase, 2008). Every density or susceptibility value is treated as an ’expected value’ with its uncertainty as the ’variance’. In an MMSE inversion, the most probable densities and variances are derived such that the differences between observed and measured data are minimised. The advantage of this approach is that the inversion is well-behaved and has a unique solution. For future application, we are working on the implementation of evolutionary algorithms for three-dimensional inversion of potential fields and their derivatives (gradients). Evolutionary algorithms would be used to optimize objective functions for three-dimensional modelling of susceptibility, density, and conductivity distributions. Model construction The process of developing a 3D model with complicated topological structures is a laborious task and does not easily fit into modern work flows where users demand quick answers and decisions. IGMAS+ provides some special features to minimise this problem: � The geometry of a model is defined using parallel vertical planes. This configuration allows easy automatic triangulation as well as visualization in the form of cross sections. � Semi- or fully automated import of predefined models or information. An import option for predefined seismic horizons has recently been developed. � Use of standardized data exchange formats that allow integration of work carried out with IGMAS+ into complex workflow environments that require the use of several specialized computer software packages. Interpreted seismic horizons are generally defined using a large number of irregularly spaced points. In comparison, the modelling resolution of potential fields is quite modest. If not down sampled, these picked points will not only inflate the storage size of the model structure, but will place unnecessary demands on computational resources to perform potential field modelling calculations. Down sampling may be achieved through a variety of procedures. In IGMAS+, the “Binned Average Values” algorithm is used. The model space is subdivided into cells. An average value is calculated for all of the points within each gridded cell. The user can visually control the degree of generalization by adjusting the cell size of the filter. Since IGMAS+ needs a polygonal geometry on each of the cross sections of the 3D structure, each horizon surface has to be cut with vertical sections. The cutting algorithm is very fast and may be applied to a Delaunay-triangulated surface directly or after an intermediate step of gridding. This produces a more generalized and smoothed initial model geometry. Conclusions IGMAS+ is a software tool which can be used for integrated interpretation in today’s industrial oil and gas exploration projects. IGMAS+ allows interactive gravity and magnetic modelling to play an important role in the depth imaging workflows of these complex oil and gas projects (Figure 4). Integration of workflow and tools is important to meet the needs of today’s more interactive and interpretative depth imaging techniques. Current research activities focus on the use of natural language processing (NLP) techniques to extract semantic constraints from various texts such as reports, publications and books. The aim is to close the gap between data modelling and “intellectual summaries/descriptions” that are used in free text documents. 94
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Record Record 2010/23 2010/23 GeoCa
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