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地层模量分解及在流体识别中的应用
引用本文:石玉梅, 曹宏, 孙夕平, 李凌高, 宋建勇, 孙虎生. 地层模量分解及在流体识别中的应用[J]. 地球物理学报, 2016, 59(11): 4278-4286, doi: 10.6038/cjg20161128
作者姓名:石玉梅  曹宏  孙夕平  李凌高  宋建勇  孙虎生
作者单位:中国石油勘探开发研究院, 北京 100083
基金项目:国家重大科技专项(2016ZX05001)和国家自然科学基金(41504110)资助.
摘    要:储层流体识别是确定油气水分布,合理布设井位,提高钻井成功率的关键之一.本文基于流体饱和孔隙介质岩石物理模型,对地震反演的地层体积模量进行分解,获得孔隙流体体积模量,并依据油、气、水(尤其是气-油、气-水)模量的显著差异进行识别.文中简要分析了Gassmann模型和Kuster-Toksöz模型的特征,详细讨论了孔隙形态和饱和度对弹性模量的影响,提出了联合Kuster-Toksöz方程和Gassmann方程的体积模量分解方法.该方法通过Kuster-Toksöz方程从测井数据中反演地层骨架固体和干骨架的弹性模量,再利用Gassmann方程对地层体积模量进行分解,既考虑了孔隙形态,又充分利用了Gassmann方程的易用性.理论模型结果表明方法是可行的.方法应用于西部地区某气田,流体识别与地层含气性预测结果与钻井基本一致,进一步证实了方法的有效性.

关 键 词:油气地层   岩石物理   模量分解   流体识别
收稿时间:2015-04-24
修稿时间:2016-09-28

Formation modulus decomposition and its application to discrimination of pore fluid
SHI Yu-Mei, CAO Hong, SUN Xi-Ping, LI Ling-Gao, SONG Jian-Yong, SUN Hu-Sheng. Formation modulus decomposition and its application to discrimination of pore fluid[J]. Chinese Journal of Geophysics (in Chinese), 2016, 59(11): 4278-4286, doi: 10.6038/cjg20161128
Authors:SHI Yu-Mei  CAO Hong  SUN Xi-Ping  LI Ling-Gao  SONG Jian-Yong  SUN Hu-Sheng
Affiliation:Research Institute of Exploration and Development, PetroChina, Beijing 100083, China
Abstract:Fluid discrimination is important for predicting the distribution of oil/gas/water and the arrangement of wells. It is also one of the keys to improve the success ratio of drilling. In this paper, we briefly analyze the Gassmann equation and Kuster-Toksöz equation which are used to describe the elastic characteristics of the fluid saturated porous medium and discuss the formation elastic characteristics for various pore morphology and saturation. A method based on the both equations is presented to decompose the formation bulk modulus which is derived from seismic inversion, and then to identify the pore fluid according to the differential bulk modulus between oil, gas and water. This method has been tested successfully by a theoretical model and field data from western China. The drilling results demonstrate that this method is effective in fluid discrimination and prediction of gas reservoirs.
Keywords:Hydrocarbon formation  Rock physics  Modulus decomposition  Fluid identification
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