USING ARTIFICIAL NEURAL NETS TO IDENTIFY THE WELL-TEST INTERPRETATION MODEL

被引：25

作者：

ALKAABI, AAU

LEE, WJ

机构：

来源：

SPE FORMATION EVALUATION | 1993年 / 8卷 / 03期

关键词：

D O I：

10.2118/20332-PA

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

This paper presents a new approach, based on artificial neural net technology, to identify a preliminary well-test interpretation model from derivative plot data. Artificial neural nets can identify patterns from incomplete and distorted data and also eliminate the need for elaborate data preparation, such as smoothing.

引用

页码：233 / 240

页数：8

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