Conference papers
Permanent URI for this collection
Browse
Recent Submissions
Item Open Access IMPLICIT MODELLING OF GEOLOGICAL DOMAINS BY SUPPORT VECTOR MACHINE: TUNING THE PARAMETERS BASED ON CONSISTENCY OF THE INDICATOR VARIOGRAM(APCOM 2021, 2021-09) Ongarbayev, Ilyas; Madani, Nasser; Musingwini, C; Woodhall, M3D modelling of geological domains is an essential part of orebody modelling and resource classification. Conventionally, one applies a wireframing technique, which, in practice, is quite laborious. An automatic approach for building an implicit geological model is the application of the Support Vector Machine (SVM) algorithm. However, in this machine learning problem, the accuracy of models significantly depends on the selected parameters. Here, the authors introduce another criterion for selecting optimum parameters, in which the indicator variogram is considered as an aid. The results can be used as an instruction for implicit geomodelling, based on the SVM algorithm where one is dealing with two categories. Keywords: SVM, Support Vector Machine, indicator variogram, geological modelling, implicit geomodelling.Item Open Access MINERAL RESOURCE MODELING OF VARIABLES WITH INEQUALITY CONSTRAINTS: A CASE STUDY OF AN IRON ORE DEPOSIT(APCOM 2021, 2021-09) Abulkhair, Sultan; Madani, Nasser; Musingwini, C; Woodhall, MIn multivariate geostatistics, it is common to have different types of complexities between variables of interest. In this context, an inequality constraint is an example of complex bivariate relationships. Unfortunately, traditional co-kriging and co-simulation algorithms cannot reproduce this type of bivariate complexity, leading to the overestimation of disturbing elements. This paper proposes a new algorithm based on a hierarchical sequential Gaussian co-simulation framework, integrated with inverse transform sampling, to model inequality constraints between variables. First, the proposed methodology's validity was evaluated by applying it to a real case study from an iron deposit, with an inequality constraint between iron and aluminum oxide. Then the simulated results were compared with a conventional hierarchical co-simulation algorithm to investigate the effect of inverse transform sampling on the quality of the co-simulation. The results showed that the proposed algorithm can reproduce an inequality constraint between variables.