惠州凹陷古近系优质烃源岩评价方法研究

2015年 35卷 第2期
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Evaluation Methods for Paleogene Source Rocks in Huizhou Sag
李扬帆 程超 何贤科 张年念 秦德文
LI Yangfan CHENG Chao HE Xianke ZHANG Niannian QIN Dewen
中海石油(中国)有限公司上海分公司, 上海 200030
Shanghai Branch of CNOOC Ltd., Shanghai 200030, China
近海盆地勘探受到钻探成本限制,实际收获的烃源岩样品相对有限,难以对单井进行烃源岩整体评价。目前烃源岩评价研究中,常利用测井资料建立与有机碳含量之间的关系,对烃源岩进行评价。但是单一测井评价方法难以定量评价烃源岩有机碳含量,需要多种方法互相结合。此文建立了烃源岩测井响应特征模型,并依据电阻率法、自然伽马能谱法、聚类分析和人工神经网络方法原理,对惠州凹陷古近系井点进行优质烃源岩识别与评价,并将测井资料评价处理成果与岩心的有机地化、地质录井资料相互检验,得出了适合该地区烃源岩评价的方法。
In offshore basin exploration,the actual hydrocarbon source rock samples are relatively limited due to the high drilling cost.It is difficult to make the overall evaluation on hydrocarbon source rock by single well.At present,during evaluation on hydrocarbon source rocks,logging data is often used to establish the relationship with the content of organic carbon.But it is difficult to quantitatively evaluate the content of organic carbon in hydrocarbon source rock only with logging evaluation method.Therefore,it is necessary to combine many methods together.In this study,we have established logging response model for the source rock.In addition,identification and evaluation on Paleogene excellent source rocks at well points in Huizhou Sag have been conducted based on resistivity method,natural gamma ray spectrometry,cluster analysis and artificial neural network theory.The evaluation results from the logging data have been verified with the organic geochemical data and geological logging data,and the suitable evaluation methods for the study area have been obtained.
惠州凹陷; 优质烃源岩; 有机碳含量; 聚类分析; 神经网络; 测井评价;
Huizhou Sag; excellent source rocks; total organic carbon; cluster analysis; neural network; logging evaluation;
https://doi.org/10.3969/j.issn.1008-2336.2015.02.040