In any geoscience survey, each survey technique must be effectively applied, and many techniques are often combined optimally. An important task is to get necessary and sufficient information to meet the requirement of the survey. A prize-penalty function quantifies effectiveness of the survey, and hence can be used to determine the best survey technique. For example, when the function is applied to classification of alteration types in a gold mineralization area, it suggests that a chemical technique is advantageous compared with a mineralogical technique based on XRD in the case that penalty defined as the refund for prize is low, and that the accuracy of the classification is high. On the other hand, information-cost function can be used to determine the optimal combination of survey techniques on the basis of geoinformation obtained. To realize the optimal alteration between techniques, however, it is necessary for us to able to evaluate obtained geoinformation. Entropy and variance have a possibility for the evaluation of geoinformation as shown in a simple model where both variables decrease with progressing geological survey.