Syntactic Pattern Recognition for Seismic Oil Exploration by Kou-Yuan Huang

By Kou-Yuan Huang

Using trend reputation has develop into progressively more very important in seismic oil exploration. studying a wide quantity of seismic info is a demanding challenge. Seismic mirrored image info within the one-shot seismogram and stacked seismogram might comprise a few structural details from the reaction of the subsurface. Syntactic/structural development popularity innovations can realize the structural seismic styles and increase seismic interpretations. The syntactic research tools comprise: (1) the error-correcting finite-state parsing; (2) the converted error-correcting Earley's parsing; (3) the parsing utilizing the fit primitive degree; (4) the Levenshtein distance computation; (5) the possibility ratio try out; (6) the error-correcting tree automata; and (7) a hierarchical method. Syntactic seismic development popularity might be one of many milestones of a geophysical clever interpretation approach. The syntactic equipment during this publication should be utilized to different parts, corresponding to the scientific analysis method. The paintings might be of curiosity to geophysicists, machine scientists and electric engineers.

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7) Output Min which is the minimum cost from node 1 to node n following the terminal sequence of the input string S. Then stop. S(h) is the hth terminal symbol of S. \S\ is the number of terminal symbols in S. This algorithm is a minimum-cost error-correcting finite-state parsing when insertion, deletion, and substitution error transformations are con­ sidered. The cost function Cij(a) denotes the cost of moving from state i to state j when the input symbol is "a". It is noted that Cij(a) = maxint, a large number, if there is no direct path from state i to state j under the symbol "a".

That is, each pattern primitive, a, can be represented by a two-tuple, a = (s: y), where s is a syntactic symbol denoting the basic segment, and y represents the length of a. For example, a pattern string is aaadgggggeeaaagg. It can be simplified by merging the identical symbols. Thus, the above string becomes (a,3)(d,l){g,5)(e,2)(a,3)(g,2) as the attributed string where each number represents the number of du­ plications for that symbol. This idea leads to some storage improvement in string representation.

The parsing technique is called minimum-distance errorcorrecting parser (MDECP) (1, 41]. We use MDECP in the finite-state parsing, attributed string parsing and tree automaton. 1. SUMMARY Syntactic pattern recognition techniques are applied to the analysis of onedimensional seismic traces for classification of Ricker wavelets. Seismic Ricker wavelets have structural information in the shape. Each Ricker wavelet can be represented by a string of symbols. In order to recognize the strings, we use the finite-state automaton for recognition of each string.

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