Predicting CO2 occurrence on a regional scale:: Southeast Asia example

被引:31
作者
Imbus, SW [1 ]
Katz, BJ
Urwongse, T
机构
[1] Texaco E&P Technol, Houston, TX 77042 USA
[2] Texaco Informat Technol, Bellaire, TX 77401 USA
关键词
Southeast Asia; carbon dioxide (CO2) prediction; neural network; basin classification; reservoir conditions; gas composition;
D O I
10.1016/S0146-6380(98)00156-9
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Prediction of CO2 occurrence in natural gases is difficult owing to the interplay among basinal sources (e.g. volcanic emanations, carbonate hydrolysis and metamorphism, organic diagenesis and maturation), reservoir processes (e.g. mineralogical transformations), and poorly understood physicochemical phenomena (e.g. differential solubility of gas components, carbonate buffering, phase segregation). Published approaches to assessing CO2 risk are based either on circumstantial evidence of basinal influences or statistical analysis of reservoir attributes. The present study presents the results of empirical, statistical and neural network analysis of CO2 abundance in natural gas and discusses potentially influential basinal and reservoir attributes to quantify risk factors for anomalous CO2 occurrences in Southeast Asia. The results of this study indicate that tectonic setting (including basement crustal age), basement fault density, reservoir temperature and reservoir pressure are key elements controlling CO2 abundance. Assignment of CO2 risk at the basin level can be roughly approximated using the results of this study. More accurate assessments of CO2 risk at the basin, play, field and reservoir levels require more comprehensive geological and geochemical data as well as consideration of potentially influential physico-chemical processes. (C) 1998 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:325 / 345
页数:21
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