番禺低隆起坡折带储层含气性综合预测技术
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摘要
PY气田位于番禺低隆起白云凹陷北坡断裂坡折带上,地质条件复杂,砂岩储层的含气性预测难度极大。为此,探究了由AVO技术、AFI流体成分反演技术及神经网络多属性反演技术组成的综合预测技术,以期有效摒除单一技术在含油气性预测过程中不尽客观的现象。首先是以AVO技术初步确定含气区,再结合AFI技术和神经网络多属性反演技术确定最终的有利含气区。该综合预测技术的应用有助于指导该区下一步天然气勘探,提高勘探成功率。
The PY gas field is situated on the fault slope breaks in the north slope of Baiyun Sag of Panyu low uplift,with complex geological conditions and extremely big difficulties in gas potential prediction of water-bearing sandstone reservoirs.Therefore,an in-depth investigation is made on an integrated prediction technology composed of the AVO technique,the AFI fluid component inversion,and neural network multi-attribute inversion,with the purpose of avoiding a single technique's bias and errors in hydrocarbon potential forecast.First,gas-bearing zones are determined by the AVO technique,then in combination with the AFI fluid component inversion and neural network multi-attribute inversion,the favorable gas areas are finally confirmed.The application of this integrated application technology will help guide the further gas exploration in this field and improve the exploration ratio.
The PY gas field is situated on the fault slope breaks in the north slope of Baiyun Sag of Panyu low uplift,with complex geological conditions and extremely big difficulties in gas potential prediction of water-bearing sandstone reservoirs.Therefore,an in-depth investigation is made on an integrated prediction technology composed of the AVO technique,the AFI fluid component inversion,and neural network multi-attribute inversion,with the purpose of avoiding a single technique's bias and errors in hydrocarbon potential forecast.First,gas-bearing zones are determined by the AVO technique,then in combination with the AFI fluid component inversion and neural network multi-attribute inversion,the favorable gas areas are finally confirmed.The application of this integrated application technology will help guide the further gas exploration in this field and improve the exploration ratio.
引文
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[2]殷八斤,曾灏,杨在岩.AVO技术的理论与实践[M].北京:石油工业出版社,1995.
[3]SHUEY R T.A simplification of the Zoeppritz equations[J].Geophysics,1985,50(4):609-634.
[4]FOURNIER F.Extraction of quantitative geologic informa-tionfromseismic data with multidimensional statistical ana-lyses:Part I,methodology,and PartⅡ:a case history[J].SEG Expanded Abstracts,1989(8):726-733.
[5]LUCET N,MAVKO G.Images of rock properties esti-mated froma cross-well tomogram[J].SEG Expanded Ab-stracts,1991(10):363-366.
[6]朱广生.地震资料储层预测方法[M].北京:石油工业出版社,1995.
[7]国庆鹏.济阳坳陷大芦家区块薄储集层预测研究[J].石油勘探与开发,2005,32(5):82-84.
[8]张喜,乔向阳,王玉艳,等.神经网络多属性分析技术[J].油气田地面工程,2007,26(8):1-3.
[9]丁峰,尹成,朱振宇,等.利用改进的自组织网络进行地震属性分析[J].西南石油大学学报:自然科学版,2009,31(4):47-51.
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