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《Progress in Geophysics》 2015-02
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Fluid type identification of sandstone based on support vector machine

SONG Chao;GUO Zhi-qi;LU Qi;FENG Xuan;JIANG Yu-hang;LIU Cai;College of Georexploration Science and Technology,Jilin University;  
Pore fluid identification in sandstone reservoir has always been a important step in the process of petroleum exploration and development,conventional methods depend on the logging data.Generally speaking,it is hard to get accurate fluid identification result under the condition of lack of logging data.In this paper,we present a new fluid identification method based on Support Vector Machine.This new method can achieve the fluid identification with only seismic data.We set geophysical parameters σ,ρλ and ρμ which can be observed or rectifiable by geophysical methods as fluid identification factor,then do model experiments.First,set up typical fluid states and do the fluid substitution with Gassmann equation,then set the fluid identification factors we get as training data for support vector machine.After that,we set up random fluid states,using Gassmann equation to calculate fluid identification factors,the results will be set as test data for support vector machine.Model experiments indicate that support vector machine method can determine the major fluid properties in the sandstone porosity.
【Fund】: 国家“973”计划项目(2013CB429805);; 国家自然科学基金项目(41340039 41174080)联合资助
【CateGory Index】: P618.13
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