| 改进的贝叶斯迭代反演方法及其在白云岩致密储层识别的应用 |
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| 引用本文： | 马琦琦,孙赞东,杨柳鑫.改进的贝叶斯迭代反演方法及其在白云岩致密储层识别的应用[J].物探与化探,2019(2):234-243. |
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| 作者姓名： | 马琦琦 孙赞东 杨柳鑫 |
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| 作者单位： | 中国石油大学(北京)地球物理与信息工程学院 |
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| 基金项目： | 国家科技重大专项"大型油气田及煤层气开发"课题"致密气有效储层预测技术"之"致密储层地震响应模式研究"子课题(2016ZX05047-002-001) |
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| 摘 要： | 由于低孔隙度和低渗透率的白云岩致密油储集层的纵波阻抗与其围岩差异非常小,利用叠后反演技术难以有效预测储层,而可以提取丰富弹性信息的叠前反演是解决此问题的有效手段,但是由于噪声等问题,叠前反演方程有较强的不适定性,笔者在贝叶斯框架下引入了改进的多变量柯西分布和改进的低频约束因子,重新推导了反演方程,获得了新的目标函数,有效地减少了反演的不适定性,从而提高了反演的稳定性,并结合迭代的思想来不断更新反演求解过程中的背景纵横波速度比值,从而增加了反演结果的精度。模型数据测试和实际资料应用都证明了该方法的稳定性和适用性。统计表明,利用提出的反演方法,目的层段内优质储层厚度预测吻合率高达89.75%。因此,此方法对类似硅质致密储层的勘探有重要的借鉴意义。
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| 关 键 词： | 贝叶斯反演 致密油储集层 改进的约束 横波数据优化 储层识别 |
Modified Bayesian iterative inversion method and its application to dolomite tight oil reservoirs prediction |
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| MA Qi-Qi,SUN Zan-Dong,YANG Liu-Xin.Modified Bayesian iterative inversion method and its application to dolomite tight oil reservoirs prediction[J].Geophysical and Geochemical Exploration,2019(2):234-243. |
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| Authors: | MA Qi-Qi SUN Zan-Dong YANG Liu-Xin |
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| Institution: | (College of Geophysics and Information Engineering,China University of Petroleum(Beijing),Beijing 102246,China) |
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| Abstract: | It is difficult to accurately predict the dolomite tight oil reservoir which has the characteristics of low porosity and low permeability by using the post-stack inversion,due to the small difference in acoustic impedance between the reservoir and its surrounding rock.Therefore,more abundant elastic information is needed.AVO inversion is an effective means to extract elastic information from pre-stack data.However,due to the noise and other factors,the pre-stack inversion equation has a strong ill-posed problem.Bayesian theory allows the construction of a regularization term by introducing a priori information about the model parameters,thereby effectively reducing the ill-posed problem of the inversion.Therefore,the modified Trivariate Cauchy constraint and the modified low-frequency constraint factor is introduced into the objective function,which can improve the ill-posed problem of the inversion,thus upgrading the accuracy of the inversion results.The iterative idea is used to address the non-linear nature of the proposed inverse operator.The P and S-wave velocity is updated in the iterations,which leads to more reliable results when applied to real data.Both the model data tests and the field data applications prove the validity and stability of the proposed method.Statistics show that,by using the proposed inversion method,the prediction accuracy rate of the reservoir thickness is as high as 89.5%. Therefore,this method has important reference significance for the exploration of similar siliceous reservoirs. |
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| Keywords: | Bayesian inversion tight oil reservoir modified constraints S-wave data optimization reservoirs identification |
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