基于稀疏自适应S变换的储层流体流度计算

反射地震数据中的低频信息包含了丰富的与流体流度相关的信息,据此可以从中提取相关储层的流体流度属性,从而可以利用地震数据的低频信息识别流体。因此,为了提高分辨率以及工作效率,将稀疏自适应S变换引入储层流体流度的计算,该方法开发了基于稀疏性的窗参数优化,以用于自适应地调控对不同频率分量的窗函数,应用该方法计算时频谱信息并求取流度可得到较高的分辨率和能量聚集性,此外也省去了参数调节的步骤。相较于常规的时频分析方法,该方法在具有较高分辨率的同时,克服了测不准原理对信号可分辨的限制。因其对不同的频率分量都自适应地获取最优窗参数,通过仿真信号,合成楔形记录试算,稀疏自适应S变换有更高的分辨率和能量聚集性。实际地震数据的试验表明,稀疏自适应S变换可有效地求取流体流度,并较常规时频方法所求流度有更高的分辨率。

Computation method for reservoir fluid mobility based on sparsity-based adaptive S-transform

The low-frequency signal of the reflected seismic data contains a wealth of information related to the fluid mobility attribute, from which the fluid mobility of the related reservoir can be extracted so that the fluid can be identified using the low-frequency information of the seismic data. Therefore, in order to improve the resolution and efficiency, the sparsity-based adaptive S-transform is introduced into the computation of the reservoir fluid mobility. The method has exploited window parameters optimization based on sparsity to adaptively control the shape of window against different frequency components, the method of calculating time-frequency representation(TFR) and obtaining the fluid attribute can be a higher-resolution and energy-concentration one, and it eliminate the need for parameter adjustment steps. Compared with the conventional time-frequency analysis method, this method overcomes the limitation of the uncertainty of the signal, at the same time, it obtains a higher resolution, because it adaptively obtains the optimal window parameters for different frequency components. The simulation and experiment of synthetic wedge model show that the sparsity-based adaptive S-transform performed better in resolution and energy concentration, and the application of real seismic data shows that sparsity-based adaptive S-transform can be used to calculate reservoir fluid mobility and obtain higher resolution than conventional one.