No description available.

This study introduces a new methodology referred to as geoinformation synthesis for multivariate evaluation of mineral resources and integration of diverse geoscience data. The most critical component is the development of the notion of intrinsic samples and the methods for their delineation. Intrinsic samples replace grid cells which are conventionally employed as the basic information reference. Grid cell sampling has imposed several serious limitations on the geoscience and genetic information that can be objectively related to mineral endowment. Methods based upon intrinsic samples moderate to a certain extent these problems and bring the critical genetic information into the geoscience information system which forms the basis for the quantitative evaluation of mineral resources. The second major component in this new methodology is the integration of factors describing exploration effects with other geodata and mineral endowment estimation; this combination effectively reduces the possibilities of biases in the estimates of mineral endowment and recoverable resources due to the incomplete knowledge on the control area and imperfect analogy with the study areas. The third component is the use in the qualitative models of synthesized geoinformation, which is considerably enhanced, instead of using directly the original measurements (geodata). Several multivariate techniques are proposed and employed for synthesis of diverse information and estimation of mineral endowment, including a priori weighted multivariate criterion, optimum discretization, coherency analysis, multidimensional scaling method (p(ijk), filtering analysis, and geochemical transportation models. These methods were developed, tested, and demonstrated on an actual case study of the epithermal gold-silver deposits in the Walker Lake quadrangle of Nevada and California using various data sets available for this region: geochemical, structural, gravity and magnetic, lithology, and alteration. Finally, the estimation of endowment in terms of epithermal gold-silver mineral occurrences is given for some selected intrinsic samples or information zones identified in the Walker Lake region.

The depths to buried bodies, characterized by anomalous gravity and magnetic properties, are determined by a combination of two numerical techniques. An upward continuation integral is solved by a method by Paul and Nagy using elemental squares and low order polynomials to describe the behavior of the gravity or magnetic data between observed data points. Downward continuation of the magnetic or gravity data is done by a finite difference technique as described by Bullard and Cooper. The applicability of the techniques are determined by comparison to depths determined by other means over the same anomalies and by comparison to various rule-of-thumb methods prevalent in the geophysical literature. The relative speed and cost of the particular computer system used is also considered in the applicability. The results show that although the initial costs of the computer program are high, the combined technique is as good as and at times better than the rule-of-thumb methods in determining the depth to the anomaly-causing body and is useful when more than just an approximate depth is of interest.

The shareholders of E&P companies evaluate the future performance of these companies in terms of multiple performance attributes. Hence, E&P decision makers have the task of allocating limited resources to available project proposals to deliver the best performance on these various attributes. Additionally, the performance of these proposals on these attributes is uncertain and the attributes of the various proposals are usually correlated. As a result of the above, the E&P portfolio optimisation decision setting is characterised by multiple attributes with uncertain future performance. Most recent contributions in the E&P portfolio optimisation arena seek to adapt modern financial portfolio theory concepts to the E&P project portfolio selection problem. These contributions generally focus on understanding the tradeoffs between risk and return for the attribute NPV while acknowledging the presence of correlation among the assets of the portfolio. The result is usually an efficient frontier where one objective is set over the expected value of the NPV and the other is set over a risk metric calculated from the same attribute where, typically, the risk metric has a closed form solution (e.g., variance, standard deviation, semi-standard deviation). However, this methodology fails to acknowledge the presence of multiple attributes in the E&P decision setting. To fill this gap, this thesis proposes a decision support model to optimise risk and return objectives extracted from the NPV attribute and from other financial and/or operational attributes simultaneously. The result of this approach is an approximate Pareto front that explicitly shows the tradeoffs among these objectives whilst honouring intra-project and inter-project correlations. Intra-project correlations are incorporated into the optimisation by integrating the single project models to the portfolio model to be optimised. Inter-project correlation is included by modelling of the oil price a global variable. Additionally, the model uses a multi-objective simulation-optimisation approach and hence it overcomes the need of using risk metrics with closed form solutions. The model is applied to a set of realistic hypothetical offshore E&P projects. The results show the presence of complex relationships among the objectives in the approximate Pareto set. The ability of the method to unveil these relationships hopes to bring more insight to the decision makers and hence promote better investment decisions in the E&P industry. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1320463 / Thesis (M.Eng.Sc.) -- University of Adelaide, Australian School of Petroleum, 2008