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A Practical Framework to Characterize Non-Stationary Regionalized Variables
- Author / Creator
- Qu, Jianan
Geostatistics aims at applying statistics to quantitatively describe geological deposits and assess the uncertainty due to incomplete sampling. Strong assumptions are required regarding the location-independence of statistical parameters to construct numerical models with geostatistical tools. Most geological data often exhibit trends or non-stationary location-dependent features. Such location-dependence in the average grade violates common geostatistical assumptions and the results may be suboptimal. Non-stationary geostatistical techniques have been developed; however, there are concerns with all current approaches of dealing with location-dependent mean values. Developing a practical framework that accounts for location-dependent features would improve geostatistical models in these situations.
This dissertation develops a practical geostatistical modeling workflow to account for the deterministic and stochastic features of continuous regionalized grade variables. The main contributions of the thesis include: (1) the construction of a deterministic trend model that realistically represents the primary features of the geological process. A mathematical form for the trend is established; (2) the development of an objective function to optimize the calculation of the large-scale trend features. The objective function is established with a synthetic example to minimize the mean squared error values between the modeled trend and the true trend for cases when the true trend is known; (3) the incorporation of the non-stationary features into geostatistical modeling. A parametric stepwise conditional transformation is considered to provide a stable and artifact-free numerical model. The complex features of the regionalized variable in the presence of a trend are removed in the forward transformation and restored in the back transformation; (4) the demonstration of the proposed techniques with real data. The trend is modeled with corrected parameters in an objective manner, and further, considered in subsequent geostatistical modeling for a more robust and reliable result.
The importance of the trend for improving performance in resource estimates is demonstrated in this thesis. The ultimate goal of this research is to improve resource management in the presence of a deterministic trend.
- Graduation date
- Fall 2018
- Type of Item
- Doctor of Philosophy
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