Invention Grant
US07792766B2 Design of reconnaissance surveys using controlled source electromagnetic fields via probabilistic neural network 有权
通过概率神经网络设计使用受控源电磁场的侦察调查

Design of reconnaissance surveys using controlled source electromagnetic fields via probabilistic neural network
Abstract:
Method for determining an expected value for a proposed reconnaissance electromagnetic (or any other type of geophysical) survey using a user-controlled source. The method requires only available geologic and economic information about the survey region. A series of calibration surveys are simulated with an assortment of resistive targets consistent with the known information. The calibration surveys are used to train pattern recognition software to assess the economic potential from anomalous resistivity maps. The calibrated classifier is then used on further simulated surveys of the area to generate probabilities that can be used in Value of Information theory to predict an expected value of a survey of the same design as the simulated surveys. The calibrated classifier technique can also be used to interpret actual CSEM survey results for economic potential.
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