多种物理机制耦合作用下的储层介质参数反演研究

孔隙介质的黏弹性、孔隙流体的Biot流动和喷射流动是影响波传播的重要物理机制.本文分别基于弹性和黏弹性BISQ模型，利用自适应杂交遗传算法研究了多种物理机制耦合作用条件下储层介质参数反演.为了测试自适应杂交遗传算法的有效性，本文分别利用自适应杂交遗传算法和传统实数编码遗传算法对含有不同噪声的理论合成数据进行了反演试算.对比理论合成数据反演结果可知，自适应杂交遗传算法具有抗干扰能力强且收敛速度快的特点，是一种有效的储层介质参数反演方法.同时本文也利用不同频率尺度和不同温度条件下的P波和S波实测数据进行了联合反演.对比研究表明，黏弹性BISQ模型能够很好地解释不同频率尺度的波频散特征，不仅能够很好地预测P波速度，而且也能够很好地预测S波速度，从而证明了黏弹性BISQ模型能够准确地描述低频条件下的波频散.

A study on inversion of reservoir parameters under coupling interaction of multiple physical mechanisms

The viscoelasticity, Biot-flow mechanism and the Squirt-flow mechanism are the most important mechanisms affecting wave propagation in the porous medium. Based on the viscoelastic BISQ model and elastic BISQ model respectively, we use Self-adaptive Hybrid Genetic Algorithm to perform the inversions of reservoir parameters under the coupling interaction of these three mechanisms. First, in order to test the effectiveness of the algorithm, we invert the theoretical data with different noises by use of self-adaptive Hybrid Generic Algorithm and Traditional real code generic algorithm respectively. Theoretical results show that Self-adaptive Hybrid Genetic Algorithm has the properties of strong immunity of noise and fast convergence of objective function, thus it is an effective inversion method for the reservoir parameters. Finally, based on viscoelastic BISQ model and elastic BISQ model, we apply the Self-adaptive Hybrid Genetic algorithm to perform the joint-inversion of the observed multi-scale frequency data of P- and S- wave. Comparing the inversion results on basis of these two models, we discover that the viscoelastic BISQ model explains well the dispersion of the observed data, it fits very well not only the P-wave but also the S-wave. This confirms the validity in low frequencies of the viscoelastic BISQ model.