Inversion of Fracture Parameters by Using the Artificial Neural Network
نویسندگان
چکیده
A BPNN approach is developed to invert the fracture parameters from Thomsen parameters. A BPNN is trained by pairs of fracture parameters and Thomsen parameters which are calculated by a complex relationship. After training, the BPNN can emulate the inverted relationship between them and then to invert fracture parameters from Thomsen parameters. The results are encouraging. This BPNN approach can invert the fracture parameter with high accuracy. It shows that this BPNN approach can be used as a general simulation tool to resolve complicated relationship between sets of input and output. Although this work only applied to the theoretical relationship, it also shows the potential of applying BPNN to inversion problem with experiment data so that a comprehensive solution can be obtained by combining them.
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