• 期刊
• OpenAccess

Hybrid ANFIS with ant colony optimization algorithm for prediction of shear wave velocity from a carbonate reservoir in Iran

Shear wave velocity (V_s) data are key information for petro-physical, geophysical and geomechanical studies. Although compressional wave velocity (V_p) measurements are available in almost every well, shear wave velocity is usually not recorded for most of old wells due to the technological limitations. Furthermore, measurement of shear wave velocity comparatively costly. This study proposes a novel methodology to tackle these problems by taking advantage of Hybrid Adaptive Neuro Fuzzy Inference System (ANFIS) with Ant Colony Optimization algorithm (ACO) based on Fuzzy C-Means Clustering (FCM) and Subtractive Clustering Method (SCM). The ACO is combined with two ANFIS models for determination of the optimal value of its user-defined parameters. The optimization implementation by the ACO significantly improves the generalization ability of the ANFIS models. These models are used in this study to formulate conventional well log data into Vs in a swift, economical, and accurate manner. A total of 3030 data points were used for model construction and 833 data points were employed for assessment of ANFIS models. Finally, a comparison among ANFIS models, and six well–known empirical correlations proved that ANFIS models can outperform the other methods. This strategy was successfully applied in the Marun reservoir, Iran.

• 期刊
• OpenAccess

Tire demand planning based on reliability and operating environment

Tires are of critical spare parts in mines. There is a shortage of medium and large tires. In addition, since the mining activities and opening new mines has increased, the demand for tires has increased significantly as well. Thus, it is very important for mining engineers to identify the tire characteristics and properly manage the spare part inventory. Spare parts management is critical from an operational perspective, especially in intensive industries assets, such as mining, as well as in organizations that own and operate costly assets. A knowledge of the tires’ behavior (historical data) must be taken into account along with the operating environment conditions (covariates). This study uses Cox multiple regression model to incorporate machine operating environment information into systems reliability analysis for estimation of spare parts. It considers a proportional hazard model and a stratified Cox regression model for time independent and dependent covariates. Based on the results, the study develops a mathematical model for spare parts estimation at the component level for non-repairable parts (tires). It validates the outcomes using a case study of loader tires in the Sungun mine in Iran. There is a significant difference in the results of spare parts forecasting and inventory management when considering and dismissing the covariates.

• 期刊
• OpenAccess

A new method for determination of frothability of frothers using water recovery measurement

A new method was introduced for frothing characterization of flotation frothers. The method uses water recovery to develop a new frothability index named water recovery index (WRI). This index was determined for some commercial frothers and the results were compared with dynamic frothability index (DFI). The results show that the water recovery index values follows the order of A-65 13016 s/mol ＞ DF-250 6292.4 s/m ＞ MIBC 1240 s/mol ＞ Isoamyl alcohol 343.2 s/mol ＞ Butanol 144.87 s/mol. It also shows that the DFI order is A-65 437,080 s.dm3/mol ＞ DF-250 197,271 s.dm^3/mol ＞ MIBC 39,427 s.dm3/mol ＞ Isoamyl alcohol 10,517 s.dm^3/mol ＞ Butanol 1977.3 s.dm^3/mol. The new method offers many advantages over conventional froth height measurement; the experimental set-up developed for water recovery measurement is more compact and is easy to use. Moreover, the special design of the set-up on the other hand, eliminates the wall effect of flotation container and increases the reproducibility of measurements.