Volume 12 Issue 4
Dec.  2006
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SUN Dong-sheng, WANG Hong-cai, HOU Mo, et al., 2006. FACTORS INFLUENCING THE EFFECTS OF HYDROFRACTURING IN A LOW-PERMEABILITY OILFIELD AND POTENTIAL EVALUATION USING ARTIFICIAL NEURAL NETWORK. Journal of Geomechanics, 12 (4): 485-491.
Citation: SUN Dong-sheng, WANG Hong-cai, HOU Mo, et al., 2006. FACTORS INFLUENCING THE EFFECTS OF HYDROFRACTURING IN A LOW-PERMEABILITY OILFIELD AND POTENTIAL EVALUATION USING ARTIFICIAL NEURAL NETWORK. Journal of Geomechanics, 12 (4): 485-491.

FACTORS INFLUENCING THE EFFECTS OF HYDROFRACTURING IN A LOW-PERMEABILITY OILFIELD AND POTENTIAL EVALUATION USING ARTIFICIAL NEURAL NETWORK

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  • Received: 2006-05-10
  • Published: 2006-12-28
  • Hydrofracturing is one of the main technical means for improving the recovery efficiency in low-permeability oil/gas fields.However,there are many factors that influence the hydrofracturing effects,including geological characteristics,physical properties of reservoirs and energy of strata.In order to obtain ideal hydrofracturing results,it is necessary to give a comprehensive consideration of the relationships between various influence factors and find out the main factors that influence the hydrofracturing effects.The authors constructed a mathematic evaluation model by using the artificial neural network method and performed net training and method check and verification of a wealth of available production data.The results prove that the constructed potential evaluation model using hydrofracturing wells has good stability and a high precision of prediction.It has certain guiding significance for choosing wells and evaluating layers for hydrofracturing and forecasting of the production capacity.

     

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