砂岩敏感识别因子的建立及直接提取方法

大量文献证明敏感识别因子已成功用于储层的岩性、流体、岩石脆性等的预测，但研究砂岩敏感识别因子的建立及直接提取方法相对较少。为此，根据黄珏地区浅层砂岩纵、横波速度相对较高、密度较低情况，设计砂岩敏感识别因子SF₄，避免了大部分常规岩性识别因子（速度与密度乘积形式）预测的砂、泥岩数值重叠现象；为避免二次计算产生的累计误差，推导了包含砂岩敏感识别因子的AVO近似式，引入低频软约束项补偿反演的低频信息，结合Downton的参数协方差矩阵特征分解去相关思路，利用贝叶斯参数反演方法直接估算该因子。数值试验与实际应用均证明了砂岩敏感识别因子建立与直接提取方法效果较好。

A method for establishing and directly extracting sensitive identification factors of unconsolidated sandstones

Many literatures prove that sensitive identification factors are successfully used to predict reservoir lithology,fluids,and rock brittleness.However,very few researches focus on the establishment of sensitive identification factors of reservoir and its direct extraction methods.We demonstrate this kind of research in shallow-sandstone reservoirs in Huangjue area.Firstly,a sensitive identification factor in sand reservoirs is designed for SF4 based on high P-wave velocity (v_P),high S-wave velocity (v_S),and low density (ρ),which effectively avoids numerical overlaps of conventional sand and mud identification factors (velocity multiplied by density).Then the AVO approximation containing the sensitive sand identification factor is derived which decreases accumulative errors caused by indirect calculations.Finally,the sensitive sand identification factor is directly extracted using the Bayesian-based elastic parameter inversion and the low frequency component of the inversion can be compensated by introducing the soft low-frequency constraint.Numerical tests and real data examples prove the validity and practicability of the proposed method.