技术方法

基于模型的叠前数据多参数非线性反演

  • 李书恒 ,
  • 赵继勇 ,
  • 崔攀峰 ,
  • 杨金龙 ,
  • 陈文龙
展开
  • 中国地质大学( 武汉) 地球物理与空间信息学院
王辉, 1983 年生, 男,中国地质大学地球探测与信息技术专业硕士研究生, 主要从事地球物理反演理论及储层预测技术等方面的 研究。地址: ( 430074) 中国地质大学( 武汉) 地球物理与空间信息学院。电话: ( 027) 87580070。E-mail: wh55255@sina.com

网络出版日期: 2008-06-15

Model-based multi-par ameter s non-linear inver sion method in pr estack domain

  • LI Shuheng ,
  • ZHAO Jiyong ,
  • CUI Panfeng ,
  • YANG Jinlong ,
  • Chen Wenlong
Expand
  • College of Geophysics & Geomatics, China University of Geosciences, Wuhan 430074, China

Online published: 2008-06-15

摘要

该文提出了一种基于模型的叠前数据多参数反演方法。通过测井资料建立井旁处地层模型, 其模型参数包括每层的层位信息及纵波速度、横波速度与密度。以Gassmann 流体置换理论为指导, 区分模型中的渗透性地层与非渗透性地层, 并根据研究区实际特点建立模型中每一地层相应的岩石物理回归关系及各层模型参数的先验函数。在贝叶斯原理的基础上, 通过Zoeppritz 方程简化公式及褶积模型建立反演参数的后验概率模型。用Marmousi2 模型来检验所提出的反演算法, 结果表明该方法不仅可以获得较准确的反演结果, 还可以获得各参数对指示油气与否的敏感性及反演结果的多解性信息, 从而降低最终决策的风险。

本文引用格式

李书恒 , 赵继勇 , 崔攀峰 , 杨金龙 , 陈文龙 . 基于模型的叠前数据多参数非线性反演[J]. 岩性油气藏, 2008 , 20(2) : 108 -113 . DOI: 10.3969/j.issn.1673-8926.2008.02.019

Abstract

A multi-parameters inversion method in prestack domain is proposed. A lithology model near well is established, of which the parameters include layers time, P-wave velocity, S-wave velocity and density. Under the guidance of Gassmann fluid substitution theory, the permeable layers could be distinguished from impermeable layers. According to the characteristics of the study area, the rock-physics regression relation and prior model of each layer are established. In the basis of Bayes principle, the linearized Zoeppritz equation and convolution model are applied to obtain the posterior probability density of the lithologymodel. The results of the testing byMarmousi2 model show that we could obtain not only accurate inversion result, but also the sensitivity information indicating the existence of oil and gas of each parameter, which could reduce the risk of final exploration.

参考文献

[ 1] 贾承造, 赵文智, 邹才能, 等.岩性地层油气勘探研究的两项核心技术[ J] .石油勘探与开发, 2004, 31( 3) : 3- 9.
[ 2] Rose P R. Measuring what we think we have found: Advantages of probabilistic over deterministic methods for estimating oil and gas reserves and resources in exploration and production[ J] . AAPG Bulletin, 2007, 91( 1) : 21- 29.
[ 3] 林承焰, 谭丽娟, 于翠玲.论油气分布的不均一性(Ⅰ)———非均质控油理论的由来[ J] .岩性油气藏, 2007, 19( 2) : 16- 21.
[ 4] 林承焰, 谭丽娟, 于翠玲.论油气分布的不均一性(Ⅱ)———非均质控油理论的由来[ J] .岩性油气藏, 2007, 19( 3) : 14- 22.
[ 5] Martin GS,Wiley R, Marfurt KJ. Marmousi2: An elastic upgrade for Marmousi[ J] . The Leading Edge, 2006, 25( 2) : 156- 166.
[ 6] Gunning J, Glinsky ME. Delivery: An open-source model-based Bayesian seismic inversion program[ J] . Computers &Geosciences,2004, 30( 6) : 619- 636.
[ 7] Buland A, Omre H. Bayesian wavelet estimation from seismic and well data[ J] . Geophysics, 2003, 68( 6) : 2 000- 2 009.
[ 8] Gunning J, GlinskyME.Wavelet extractor: ABayesian well-tie and wavelet extraction program[ J] . Computers & Geosciences, 2006,32( 5) : 681- 695.
[ 9] Buland A, Omre H. Joint AVO inversion, wavelet estimation and noise-level estimation using a spatially coupled hierarchical Bayesian model[ J] . Geophysical Prospecting, 2003, 51( 6) : 531- 550.
[ 10] Gunning J, Glinsky ME, White C. Delivery massager: A tool for propagating seismic inversion information into reservoir models [ J] . Computers &Geosciences, 2007, 33( 5) : 630- 648.
[ 11] Tarantola A. Inverse problemtheory[M] . Paris: SiamPress, 2005:10- 12.
[ 12] Mosegaard K, Tarantola A. Monte Carlo sampling of solutions to inverse problems[ J] . Journal of Geophysical Research, 1995, 100(B7) : 12 431- 12 447.
[ 13] Papoulis A. Probability, randomvariables and stochastic processes[M] . NewYork:McGraw-Hill Press. 2002: 591- 592.
[ 14] Liu J S.Monte Carlo strategies in scientific computing[M] . Berlin:Springer, 2001: 112- 114.
[ 15] Mukerji T, Avseth P,MarkoG. Statistical rock physics: Combining rock physics, information theory, and geostatistics to reduce uncertainty in seismic reservoir characterization[ J] . The Leading Edge,2001, 20( 3) : 313- 319.
[ 16] 史松群, 王宇超.有关岩性地震勘探的讨论与思考[ J] .岩性油气藏, 2007, 19( 3) : 131- 134.
文章导航

/