DocumentCode :
3399423
Title :
A new method for detecting real-time geopressure from drilling-logging parameters
Author :
Li Gongquan ; Wang Zhizhan
Author_Institution :
Sch. of Geosci., Yangtze Univ., Jinzhou, China
fYear :
2011
fDate :
19-22 Aug. 2011
Firstpage :
2502
Lastpage :
2506
Abstract :
Real-Time detecting abnormal formation pressure can not only prevent the happening of drilling hazard, but also effective protect the pollution of reservoir. A detective model can be made from some drilling-logging parameters because these parameters collected by comprehensive logging instrument can indicate the abnormal pressure information existing in the formation. First, a PCA method is used to process six wells from Dongying Depression, China in order to reduce the cross-correlation among parameters and the count. Then a neural net model is trained by the result in the first step. Finally, thirty wells are detected by the model. The correspondence between real data and predicted results is about 84.6%.So this method can be used in the real case.
Keywords :
drilling (geotechnical); neural nets; principal component analysis; well logging; Dongying; PCA method; drilling hazard; drilling-logging parameters; neural net model; real-time geopressure detection; Artificial neural networks; Correlation; Hydrocarbons; Predictive models; Principal component analysis; Real time systems; Training; Abnormal formation pressure; Neural net; PCA; Real-Time detecting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronic Science, Electric Engineering and Computer (MEC), 2011 International Conference on
Conference_Location :
Jilin
Print_ISBN :
978-1-61284-719-1
Type :
conf
DOI :
10.1109/MEC.2011.6026001
Filename :
6026001
Link To Document :
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