Recognition and prediction of fracture by using antcolony algorithm analysis in carbonate reservoir
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    Abstract:

    A fracture-developed carbonate oil field in the east has a complicate oil and gas distribution in facture network at late development stage, which leads to multiplicity of favorable reservoir estimation. In view of problems above, ant colony algorithm is adapted to recognition and predict facture in this field. The ant parameters are optimized on the basis of core and image log data, and the spatial distribution feature of fracture is described, as a reticulate structure with three dominant clusters of fracture (NW, NNE & NE). Drilling leakage, production data and image log are then used for reliability analysis of fracture predict, which presents that ant colony algorithm is a practicable methodology to recognition fracture and provides a support for remaining oil distribution analysis. As a booming bionic algorithm, ant colony algorithm has great potential for quantitative fracture predict with seismic materials.

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吴斌,唐洪,王素荣,王兴志,徐立明,徐正华.利用蚁群算法识别及预测碳酸盐岩裂缝的方法探讨[J].重庆大学学报,2012,35(9):131~138

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  • Online: October 11,2012
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