摘要
AVO正演模拟分析通常采用固定的岩石物理模型参数,而在实际勘探过程中不同岩石物理参数存在一定重叠,致使正演结果存在不确定性。以苏里格气田测井数据为基础,采用概率、信息熵等方法表征岩石物理参数的不确定性,基于典型的岩性反射界面,分析不同反射界面上下层介质纵波速度比、横波速度比、密度比对正演模拟结果的影响,通过马尔科夫链蒙特卡罗模拟方法(MCMC)开展不同岩性反射界面的反射系数和AVO属性响应特征的模拟,并采用信息熵估计AVO分析中的不确定性。结果表明:概率密度和信息熵在不同岩性的岩石物理参数上具有差异性,但是不同岩性之间存在交叉现象,增强了岩性识别结果的不确定性和多解性;AVO响应特征表明上下层介质岩石物理参数的变化和下层介质含气性的不同导致AVO反射系数具有不同的响应,且随着下层介质含气饱和度的增加,AVO属性表现"双负"特征,即负截距和负梯度。通过统计学手段解析AVO正演模拟过程中的不确定性,可以为储层预测提供有效的先验认识,从而降低致密砂岩气藏的开发风险。
Traditional AVO forward modeling usually uses constant parameters to construct the petrophysics model,however,these parameters have uncertainties in the exploration process,resulting in great uncertainty for the process of forward modeling. The petrophysical model was firstly established based on the wireline logs and the tools of probability density function(PDF)and information entropy(IE)were used to characterize the uncertainty of petrophysical parameters. Then based on the typical reflection interfaces,the parameters of AVO forward modeling,including the ratio of compressional wave velocity,shear wave velocity and density between the media above and below of reflection interfaces,are analyzed to the influence of AVO forward modeling. Finally,the Markov Chain Monte Carlo(MCMC)simulation method was used to model the reflection characteristics and AVO attribute response of different lithological interfaces. The IE was then used to analyze the uncertainty in AVO analysis. The results show that the PDF and IE indicate that petrophysical parameters are different in different lithologies,but there is a certain overlap for each other,which results in uncertain and multi-solution for the identification of lithology using petrophysical parameters. The AVO response indicates that the changes of the petrophysical parameters of the upper and lower media and the differences of lithology of the lower media result in different responses of AVO reflection coefficient. The attribute of AVO intercept(P)and the AVO gradient(G)shift to the type Ⅲ,as the gas saturation increases. The study effectively evaluates the uncertainty in the AVO forward modeling through statistical methods,which can provide a priori understanding for reservoir prediction and is helpful for the risk assessment and decision-making optimization of reservoir prediction.
作者
张艳
高世臣
孟婉莹
成育红
蒋思思
ZHANG Yan;GAO Shichen;MENGWanying;CHENG Yuhong;JIANG Sisi(School of Geophysics and Information Technology,China University of Geosciences(Beijing),Beijing 100083,China;School of Science,China University of Geosciences(Beijing),Beijing 100083,China;No.3 Gas Production Plant,PetroChina Changqing Oilfield Company,Xi'an 710016,China;No.5 Gas Production Plant,PetroChina Changqing Oilfield Company,Xi'an 710016,China)
出处
《岩性油气藏》
CSCD
北大核心
2020年第6期120-128,共9页
Lithologic Reservoirs
基金
国家科技重大专项“鄂尔多斯盆地大型岩性地层油气藏勘探开发示范工程”(编号:2016ZX05050)资助。
关键词
致密砂岩储层
AVO正演
岩石物理模型
不确定性
概率密度函数
信息熵
MCMC
tight sandstone reservoirs
AVO forward modeling
petrophysical model
uncertainty
probability density function
information entropy
Markov Chain Monte Carlo
