周林^1,,
廖建平¹,
李景叶^2,3,
陈小宏^2,3,
刘兴业⁴
1. 湖南科技大学页岩气资源利用湖南省重点实验室, 湘潭 411201
2. 中国石油大学(北京)油气资源与探测国家重点实验室, 北京 102249
3. 中国石油大学(北京)海洋石油勘探国家工程实验室, 北京 102249
4. 西安科技大学地质与环境学院, 西安 710054

基金项目: 国家自然科学基金项目（41904116，41874156，42074167）和湖南省自然科学基金项目（2020JJ5168）联合资助


详细信息

作者简介: 周林, 男, 1990年生, 2018年获得中国石油大学(北京)博士学位, 主要从事叠前AVO/AVA非线性反演方法研究.E-mail: linzhou6308@sina.com

中图分类号: P631

收稿日期:2021-02-07
修回日期:2021-06-22
上线日期:2021-10-10

Prediction method of reservoir oil-gas potential based on exact Zoeppritz equations

ZHOU Lin^1,,
LIAO JianPing¹,
LI JingYe^2,3,
CHEN XiaoHong^2,3,
LIU XingYe⁴
1. Hunan Provincial Key Laboratory of Shale Gas Resource Utilization, Hunan University of Science and Technology, Xiangtan 411201, China
2. State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing 102249, China
3. National Engineering Laboratory for Offshore Oil Exploration, China University of Petroleum, Beijing 102249, China
4. College of Geology and Environment, Xi'an University of Science and Technology, Xi'an 710054, China


MSC: P631

--> Received Date: 07 February 2021
Revised Date: 22 June 2021
Available Online: 10 October 2021


摘要
摘要:流体指示因子和泊松比作为重要的指标参数在储层含油气性预测中发挥着至关重要的作用，大量****开展了这两个参数的直接反演研究.然而，现有反演方法主要是以精确Zoeppritz方程的近似公式为正演方程，近似公式诸多的假设条件及较低的计算精度极大地限制了这类方法在复杂储层的应用效果.因此，为了提升储层含油气性预测精度，文中提出了一种新的基于精确Zoeppritz方程的流体因子和泊松比反演方法.首先，借助敏感流体因子定量分析法对现有流体指示因子进行优选，并将传统形式的精确Zoeppritz方程改写为包含该优选流体指示因子和泊松比的新形式.然后，基于新方程构建贝叶斯理论框架下的非线性反演目标函数.同时，为了进一步提升流体因子和泊松比对储层的刻画精度，在假设背景先验模型服从高斯分布的同时引入服从微分拉普拉斯分布的块约束项.最后，借助泰勒级数展开对上述非线性目标函数进行求解.合成数据和油田数据验证结果表明新方法能够稳定合理地估计流体指示因子和泊松比，且精度远高于基于近似公式的传统方法.此外，实际数据测试表明新方法能够有效提升储层含油气性预测精度，降低不确定性.
关键词: 精确Zoeppritz方程/
流体指示因子/
泊松比/
块约束/
含油气性预测

Abstract:The fluid indicator factor and Poisson's ratio are important index parameters, which play a vital role in prediction of reservoirs oil-gas potential. Many scholars have proposed a wide range of methods to invert these two parameters. However, the existing inversion methods mainly take the approximations of the exact Zoeppritz equations as the forward equations. The assumptions and low calculation accuracy of approximate formulas in these approaches greatly limit the application of the methods for complex reservoirs. To solve this problem, a new inversion method for the fluid factor and Poisson's ratio based on the exact Zoeppritz equations is proposed to improve the prediction accuracy of reservoir hydrocarbon potential. First, the existing fluid indicator factors are optimized by the sensitive fluid factor quantitative analysis, and the traditional form of exact Zoeppritz equations is rewritten into a new form that includes the optimized fluid indicator factors and Poisson's ratio. Then, a nonlinear inversion objective function based on the new equations is constructed in the Bayesian theory framework. Besides, to further improve the characterization accuracy of the fluid factor and Poisson's ratio for reservoirs, a differentiable Laplace distribution blocki constraint term is added to the background prior model that is assumed to obey Gaussian distribution. Finally, Taylor series expansion is used to solve the nonlinear objective function. Both synthetic and field data examples show that the new method can estimate the fluid indicator factor and Poisson's ratio stably and reasonably. The accuracy is much higher than the traditional method based on the approximate formula. Besides, the field data test shows that the proposed method can effectively improve the prediction accuracy of reservoir hydrocarbon potential and reduce uncertainty.
Key words:Exact Zoeppritz equations/
Fluid indicator factor/
Poisson's ratio/
Block constraint/
Hydrocarbon prediction



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