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《Fault-block Oil & Gas Field》 2005-04
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Application of Artificial Nerve Network Method to Evaluating & Choosing Target Layer/Well in Hydraulic Fracturing Treatment

Wei Yunsheng (Southwest Petroleum Institute,Chengdu 610500,China), Hu Yongquan and Zhao Jinzhou et al.  
The factors affecting choosing wells and commenting layers in hydraulic fracturing are generally analyzed; with the general and independent principles, main factors are selected; economy law as the criterion of choosing wells and commenting layers put forward clearly in this paper. With artificial nerve network method to forecast the ratio of cost and earning on hydraulic fracturing treatment under the condition of multi-factors and non-linear, the lack of blurry judgment method, such as subjectivity, dependence and relativity, is conquered. Consequently, artificial nerve network model is set up for choosing wells and commenting layers to fracture, then with the model, power value of each factor is gained. Thereby, the ratio of cost and earning on hydraulic fracturing treatment and the probability of payoff or lose of each well or layer is obtained finally. So artificial nerve network method is better than blurry judgement method in theory obviously. Calculating an actual oil field example, the result has proved that the adaptability and precision of artificial nerve network method in the sample " data limited " ( a little sample ) is better compared to others, so artificial nerve network method has a wide prospect in hydraulic fracturing treatment. Its science, rationality and correctness is also proved. This paper provides a new and novel method for evaluating and choosing a suitable target layer/well in stimulation.
【CateGory Index】: TE357.1
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