Understanding uncertainty in resource models is a significant requirement of ore deposit evaluation. Uncertainty analysis allows the modeller to explicitly quantify the risk around their estimate, along with provide high/low estimates for mine design, assess project up/down-side, model financial forecasts, and reconcile the deposit after mining. Geostatistical simulation is one method that can ...

Receivers for wireless local area networks based on the IEEE 802.11b standard are required to operate well in heavy multipath, as well as additive noise impairments. This paper discusses a practical approach to combined equalizing and decoding for IEEE 802.11b systems, based on the Fano sequential decoding algorithm. Simulation results are presented demonstrating the greatly improved performanc...

In this technical note, a geostatistical model was applied to explore the spatial distribution of source rock data in terms total organic carbon weight concentration. The median polish kriging method used approximate “row and column effect” generated array data, order for ordinary methodology be by means residuals. Moreover, sequential Gaussian simulation employed quantify uncertainty estimates...

The one dimension computational model of a sequential injection engine, which runs on compressed natural gas (CNG) with spark ignition, is developed for this study, to simulate the performance of gas flow pressure profile, under various speed conditions. The computational model is used to simulate and study of the steady state and transient processes of the intake manifold. The sequential injec...

The traditional approaches of modeling and estimation of highly skewed deposits have led to incorrect evaluations, creating challenges and risks in resource management. The low concentration of the rare earth element (REE) deposits, on one hand, and their strategic importance, on the other, enhances the necessity of multivariate modeling of these deposits. The wide variations of the grades and ...

Due to uncertain nature of grade in ore deposits, considering uncertainty is inevitable in geological modelling of resources and mine planning. In other words, uncertainty in grade of mineralized materials, is one of the most significant parameters need attention in mine planning. In this paper, a comparative procedure utilizing Sequential Gaussian Simulation (SGS) and traditional Ordinary Krig...

We have developed an efficient stochastic AVA inversion technique that works directly in a fine-scale stratigraphic grid, and is conditioned by well data and multiple seismic angle stacks. We use a Bayesian framework and a linearized, weak contrast approximation of the Zoeppritz equation to construct a joint log-Gaussian posterior distribution for Pand S-wave impedances. We apply a Sequential G...