Recognition of Reservoir Patterns with Grey Intelligence
The signal extracted by logging method that mirrors the stratigraphic information is considered gray signal, Pattern recognition and petroliferous analysis of reservoir based on logging data is a process of gray system analysis. A grey sliding-window correlation model based on two-dimensional wavelets is given, together with feasibility study. The reservoirs are classified into hydrocarbon and water reservoirs according to the given model, whose work involves the evaluation of reservoirs depth, thickness, type, etc. Study and experimentation that is targeted for identification of hydrocarbon and water reservoirs is conducted based on the logging data of oil well K in north Tarim. The result of the experiment is in perfect accordance with actual drilling explanation in the tested area.
Oil&gas reservoir Two-dimensional wavelets Grey sliding-window correlation model Intelligence Pattern Recognition
Guoping Wu Kun Zhou Fang Peng
the Institute of Information Engineering, China University of Geosciences, Wuhan, 430074, China the Institute of Mathematics and Physics, China University of Geosciences, Wuhan, 430074, China
国际会议
武汉
英文
2007-09-21（万方平台首次上网日期，不代表论文的发表时间）