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碎屑岩储层预测技术适用性研究

Study on adaptability of clastic reservoir prediction technique

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【作者】 张以明康洪全沈华常建华

【Author】 Zhang Yi-ming1,Kang Hong-quan1,Shen Hua1 and Chang Jian-hua1.1.PetroChina Huabei Oilfield Company, Renqiu City, Hebei Province, 062550, China

【机构】 中国石油华北油田分公司

【摘要】 储层预测技术已成为岩性油藏勘探的常规技术。本文通过二连盆地三个岩性油藏勘探实例,对碎屑岩储层预测常用技术和软件的适用性进行了研究。其中实例1为巴音都兰凹陷的巴Ⅰ和巴Ⅱ号构造区,分别发育有扇三角洲砂体,由于地震资料分辨率偏低,扇体分布不清。在采用沿层属性提取及多元油气预测技术之后,确定了砂体有利分布区,并经钻探证实。实例2为乌里亚斯太凹陷的陡坡湖底扇砂砾岩体,主要应用沿层属性提取技术及ISIS和Jason反演软件确定砂砾岩体的展布特征,然后利用电阻率反演预测砂砾岩体的含油性,也获得了成功。实例3为赛汉塔拉凹陷陡坡带水下扇砂体,主要依据一口已知砂体的井预测相距2km的另一口井的砂体,结果预测失败,主要原因是对该区的沉积微相研究不够,预测方法选用不当。

【Abstract】 The reservoir prediction technique has become an ordinary technique of lithologic reservoir exploration. Through three cases of lithologic reservoir exploration in Erlian basin, the paper carried out the study on the adaptability of common techniques and software of clastic reservoir prediction, among which the case 1 is in Ba-1 and Ba-2 structural areas of Ba’yindulan sag, where the fan delta sand body is very development. Because of lower resolution of seismic data, distribution of fans is unclear. After using horizon-oriented attributes detecting technique and multi-element hydrocarbon prediction technique, the sand body-favorable distribution area has been determined and proved by drilling results. The case 2 is lake-floor fan sandy gravel body in steep slope of Wuliyastai sag, in which the horizon-oriented attributes detecting technique and ISIS and Jason inversion software are used to determine the distributing feature of sandy-gravel body, then resistivity inversion is used to predict the oil-bearing capacity of sandy-gravel body, achieving success. The case 3 is underwater fan sand body on steep slope of Saihantala sag, in which we mainly rely on a well with known sandy-gravel body to predict the sand body in another well with 2km interval to previous well, resulted in failure of prediction. The main raison is that the study of sedimentary micro-facies in this region is insufficient and inappropriate selection of predicted method.

  • 【文献出处】 石油地球物理勘探 ,Oil Geophysical Prospecting , 编辑部邮箱 ,2008年04期
  • 【分类号】P618.13
  • 【被引频次】9
  • 【下载频次】452
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