Evaluating the geological properties of a mineral deposit is a fundamental task for mine planning and it requires an assessment of reserve parameters such as thickness and grade. This paper presents a linguistic model for estimating bauxite thickness within a deposit in a fuzzy environment using indicator geostatistics and fuzzy modeling. The proposed model consists of two main stages: determining the orebody boundary and estimating the thickness. In order to estimate the thickness, a rule-based fuzzy inference mechanism has been developed based on data statistics. Results and performance of the model have been compared with that of a well-known conventional technique, geostatistics (kriging), and it is shown that the proposed model has bigger estimation power. In addition, the fuzzy approach is more fl exible than the kriging approach. The fuzzy methodology used in the present paper is convenient for modeling reserve parameters.

No abstract

In this study, the rheological properties and performances of mud prepared with geothermal spring water to be used by geothermal drilling operators were examined at ambient and elevated temperatures. In this context, mud samples were prepared in the compositions detailed in the API specification by using five different geothermal spring water types and a distilled water type. Afterwards, density, apparent viscosity, plastic viscosity, yield point, gel strength, fluid loss, pH, and filter cake thickness of these samples were measured. The drilling muds were analyzed by means of rheological tests in accordance with the standards of the American Petroleum Institute (API). The experimental results have revealed that the mud prepared with geothermal water have lower viscosity and yield point compared to those prepared with freshwater at elevated temperatures. The stability of the muds decreases, especially at temperatures higher than 250°F, and they start to become flocculated. It was concluded that geothermal water-based muds have higher API fluid loss and cake thickness than the freshwater-based one. Therefore, it could be interpreted that the muds prepared with geothermal spring water will exhibit lower flow performance and lower ability of hole cleaning and rate of penetration compared to the freshwater muds. Hence, it is recommended that this kind of water should not be used to prepare drilling mud.

No abstract

Abstract:In this study, firstly, a practical and educational geostatistical program (JeoStat) was developed, and then example analysis of porosity parameter distribution, using oilfield data, was presented. With this program, two or three-dimensional variogram analysis can be performed by using normal, log-normal or indicator transformed data. In these analyses, JeoStat offers seven commonly used theoretical variogram models (Spherical, Gaussian, Exponential, Linear, Generalized Linear, Hole Effect and Paddington Mix) to the users. These theoretical models can be easily and quickly fitted to experimental models using a mouse. JeoStat uses ordinary kriging interpolation technique for computation of point or block estimate, and also uses cross-validation test techniques for validation of the fitted theoretical model. All the results obtained by the analysis as well as all the graphics such as histogram, variogram and kriging estimation maps can be saved to the hard drive, including digitised graphics and maps. As such, the numerical values of any point in the map can be monitored using a mouse and text boxes. This program is available to students, researchers, consultants and corporations of any size free of charge. The JeoStat software package and source codes available at: http://www.jeostat.com/JeoStat_2017.0.rar