document: Real-time quasi-2-D inversion of array resistivity logging data using neural network We present a quasi-2-D real-time inversion algorithm for a modern galvanic array tool via dimensional reduction and neural network simulation . Using reciprocity and superposition , we apply a numerical focusing technique to the unfocused data . The numerically focused data are much less subject to 2-D and layering effects and can be approximated as from a cylindrical 1-D Earth . We then perform 1-D inversion on the focused data to provide approximate information about the 2-D resistivity structure . A neural network is used to perform forward modeling in the 1-D inversion , which is several hundred times faster than conventional numerical forward solutions . Testing our inversion algorithm on both synthetic and field data shows that this fast inversion algorithm is useful for providing formation resistivity information at a well site
doc_bio_tags: O O O O B I I I O B I O O O O O O O O O O B I I O B I O B I O O O B O B O O O O B I I O O B I O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O B I O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O B I
extractive_keyphrases: array resistivity logging data neural network galvanic array tool dimensional reduction reciprocity superposition numerical focusing technique unfocused data focused data forward modeling formation resistivity well site
abstractive_keyphrases: real-time quasi-2-d inversion real-time inversion algorithm 1-d inversion