Al Assisted Coal Interpretation Techniques

Geological evaluations of coal deposits have been traditionally undertaken in a somewhat manual manner. Information is collected downhole by chip sampling, coring and using downhole geophysical logging. This information is then interpreted by an experienced geologist to define the coal and noncoal lithological units. Coal units were subsequently correlated to provide data for structural modelling. In recent years a number of advancements in interpretation techniques have been made based on Artificial Intelligence. This paper describes an integrated geological interpretation system based on maximised use of Al techniques. The first part describes the lithological interpretation which uses a number of boreholes with both logged lithology and downhole geophysical logs. This information provides a learning set of data to the neural network. The second part concentrates on the correlation of both coal and noncoal units from borehole to borehole. Problems in this area, in a manual sense, are interpretation of correlation across weathering zones and other geological anomolies. The technique is based on pattern recognition and dynamic programming techniques where a correlation matrix is developed relating all holes with their maximum correlations.