OVERVIEW OF NEW MONTE CARLO SOFTWARE FOR QUANTITATIVE MINERAL RESOURCE ESTIMATION

The third step of the US Geological Survey (USGS) mineral assessment process is combining estimates of the types and numbers of deposits with historical grade and tonnage data to produce probability density functions of the quantities of contained mineral commodities in undiscovered deposits. This poster presentation focuses on developing a new software application used in this step of the assessment process. Initial objectives met by the new software application include:

a) Produce software that is easy to support, maintain, and modify.

b) Develop an application that interfaces with a relational database containing grade and tonnage models that can be updated, compared, and reviewed on a regular basis.

c) The software application needs to be intuitive and easy to use, taking advantage of a Graphical User Interface (GUI) and graphical output.

d) The software needs to interface with modern desktop publishing and analysis programs for creating consistent and easy to interpret reports and graphs.

e) The software algorithms need to have been tested and proven in academia, government, and industry.

f) The simulation process needs to be transparent and reproducible by others.

g) The simulator needs to be able to act as a research tool in order to advance current USGS assessment methodology.

h) For unconventional or difficult to make assessments, the simulator needs to be flexible and expandable based upon user needs.

i) Aggregation of results and correlation among assumed probability density functions can be controlled by the user.

The prototype Monte Carlo simulator achieves these objectives by providing a GUI that wraps Microsoft (MS) Excel, MS Access, and Oracle Crystal Ball into a software application designed to estimate the probable amounts of contained metals in undiscovered deposits in support of the USGS Minerals Resource Program goals. Being developed in the MS Visual Studio.NET environment, it is fully compatible with current computer hardware and MS Windows operating systems. By taking advantage of MS Access, a grade-tonnage database has been developed that can be easily queried, updated, and interfaced with the simulator. Since the simulator rides atop MS Excel, the user environment is familiar to many who work with computers. Reports and charts can be automatically generated and output to MS Office applications or cut and pasted into other applications. By using Oracle Crystal Ball subroutines, there is the increased confidence of using tried and tested algorithms. Additionally, many of Crystal Ball’s standard library calls took teams of people years to develop, thereby greatly cutting down on development time and increasing both the visual appeal and utility of the application. Utilizing Crystal Ball’s advanced functionality and sophisticated statistical analysis routines allows the simulator to be used as a research tool in addition to a quantitative resource predictor.