We present the results of a seismic interferometry experiment in a shallow cased borehole. The experiment is an initial study for subsequent borehole seismic surveys in an instrumented well site, where we plan to test other surface/borehole seismic techniques. The purpose of this application is to improve the knowledge of the reflectivity sequence and to verify the potential of the seismic interferometry approach to retrieve high‐frequency signals in the single well geometry, overcoming the loss and attenuation effects introduced by the overburden. We used a walkaway vertical seismic profile (VSP) geometry with a seismic vibrator to generate polarized vertical and horizontal components along a surface seismic line and an array of 3C geophones cemented outside the casing. The recorded traces are processed to obtain virtual sources in the borehole and to simulate single‐well gathers with a variable source‐receiver offset in the vertical array. We compare the results obtained by processing the field data with synthetic signals calculated by numerical simulation and analyse the signal bandwidth and amplitude versus offset to evaluate near‐field effects in the virtual signals. The application provides direct and reflected signals with improved bandwidth after vibrator signal deconvolution. Clear reflections are detected in the virtual seismic sections in agreement with the geology and other surface and borehole seismic data recorded with conventional seismic exploration techniques. 相似文献
作为一种典型的强阻抗差低阻抗薄层,煤层中孔隙含流体时是否会引起地震反射产生明显的异常是回答地震检测流体是否可行的根本.为此,本文针对强阻抗差薄层模型,基于Biot双相介质理论,通过弹性波有限差分法数值模拟,与各向同性单相介质假设的煤层反射对比,探讨了反射复合波受煤层孔隙度及流体性质变化的影响程度.模拟分析发现:由于薄层孔隙度和孔隙流体属性的变化在Biot理论中表现为纵波速度的变化,PP波反射AVO(Amplitude Versus Offset,振幅随偏移距变化)特征对薄层是否含流体相对敏感;综合使用PP与PS波对比有利于薄层中流体的预测;孔隙度一定时,PP波反射振幅随着含气饱和度的增加而增大;受薄层调谐作用的影响,孔隙和流体变化对煤层反射的频谱特征影响不大,近似于单相介质时的情况.
We present here a comparison between two statistical methods for facies classifications: Bayesian classification and expectation–maximization method. The classification can be performed using multiple seismic attributes and can be extended from well logs to three‐dimensional volumes. In this work, we propose, for both methods, a sensitivity study to investigate the impact of the choice of seismic attributes used to condition the classification. In the second part, we integrate the facies classification in a Bayesian inversion setting for the estimation of continuous rock properties, such as porosity and lithological fractions, from the same set of seismic attributes. The advantage of the expectation–maximization method is that this algorithm does not require a training dataset, which is instead required in a traditional Bayesian classifier and still provides similar results. We show the application, comparison, and analysis of these methods in a real case study in the North Sea, where eight sedimentological facies have been defined. The facies classification is computed at the well location and compared with the sedimentological profile and then extended to the 3D reservoir model using up to 14 seismic attributes. 相似文献