利用Kohonen 神经网络划分二维地震相———以柴达木盆地E区风险勘探为例

doi:10.3969/j.issn.1673-8926.2011.04.021

Lithologic Reservoirs ›› 2011, Vol. 23 ›› Issue (4): 115-118.doi: 10.3969/j.issn.1673-8926.2011.04.021

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Application of Kohonen neural network to 2D seismic facies division in E area of Qaidam Basin

LIU Xiaohong¹， FENG Mingyou¹， YANG Wuyang²， SUN Hui²， WEI Xinjian²， LIU Zhe³

1. School of Resources and Environment， Southwest Petroleum University， Chengdu 610500， China； 2. Research Institute of Petroleum Exploration & Development-Northwest， PetroChina， Lanzhou 730020， China； 3. Department of Exploration， Changqing Oilfield Company， PetroChina， Xi’an 710018， China

Online:2011-08-20 Published:2011-08-20

Abstract

Abstract:

The situation ofE area is hard to proceed deep research and risk assessment by the absent of prospecting well data. Based on seismic mis-tie calibration, adjacent well calibration and fine horizon interpretation, Kohonen neural network method is applied to carry out two-dimensional seismic facies classification of target zone.Microfacies of delta front such as distributary channel, interdistributary bay and sand bar are recognized. The paleocurrent direction is suspected from southeast to northwest. Reservoir sand bodies developed well in the middle of the study area, preliminary prospecting well is located in favorable sedimentary facies. Sedimentary facies division are supplied and refined by the result of seismic facies，which can supply significant foundation for geometric arrangement of risk wells and regional breakthrough.

Key words: Chang4+5 reservior, ultra-lowpermeability, fracture, Jiyuan Oilfield

LIU Xiaohong， FENG Mingyou， YANG Wuyang， SUN Hui， WEI Xinjian， LIU Zhe. Application of Kohonen neural network to 2D seismic facies division in E area of Qaidam Basin[J].Lithologic Reservoirs, 2011, 23(4): 115-118.

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