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An AVO method toward direct detection of lithologies combining P-P and P-S reflection data

机译:结合P-P和P-S反射数据的直接检测岩性的AVO方法

摘要

I here present a combined AVO analysis of P-P and P-S reflection data whose objective is to improve the identification of lithology by estimating the specific values of Poisson's ratio, [sigma], for each rock formation in a given geological model, rather than a contrast between formations. Limited knowledge on the elastic parameters of a given rock formation and difficulty regarding the availability and processing of P-S data constitute hindrances of lithology identification. Considering that ocean bottom seismology (OBS) has aided in solving the problem of P-S data availability, limited information on elastic parameters is still a challenge, and the focus of this thesis. The present analysis is based on Zoeppritz' solution for the P-P and P-S reflection coefficients, RPP and RPS, with a slight modification. We used the normalized P-S reflection coefficient; i.e.,R'PS = RPS / sin [theta] for [theta] > 0,instead of RPS, where [theta] is the incident angle. By normalizing RPS, we avoid dealing with the absence of converted S-waves at small incident angles and enhance the similar linear behavior of the P-P and normalized P-S reflection coefficients at small angles of incidence. We have used the linearity of RPP and R'PS at angles smaller than 35 degrees to simultaneously estimate the average VP/VS ratio, the contrasts of P- and S-wave velocities, and the contrast of density. Using this information, we solve for Poisson's ratio of each formation, which may enable lithology discrimination. The feasibility of this analysis was demonstrated using nonlinear synthetic data (i.e., finite-difference data). The results in estimating Poisson's ratio yielded less than 5 percent error. We generalize this new combined P-P and P-S AVO analysis for dipping interfaces. Similarly to the nondipping interface case, our derivations show that the amplitude variation with offset (AVO) of P-P and P-S for a dipping interface can be cast into intercepts and gradients. However, these intercepts and gradients depend on the angle of the dipping interface. Therefore, we further generalize our analysis by including a migration step that allows us to find the dipping angle. Because seismic data is not available in terms of RPP and R'PS, this process includes recovery of reflection coefficients after migrating the data and correcting for geometrical spreading, as done by Ikelle et al. (1986 and 1988). The combination of all of these steps, namely geometrical-spreading correction, migration, and AVO analysis, is another novelty of this thesis, which leads to finding the specific values of Poisson's ratio of each rock formation directly from the seismic data.
机译:我在这里介绍了PP和PS反射数据的组合AVO分析,其目的是通过估算给定地质模型中每种岩层的泊松比σ的特定值来改善岩性识别,而不是通过对比编队。对给定岩层的弹性参数的了解有限,以及对P-S数据的获取和处理的困难,构成了岩性识别的障碍。考虑到海底地震学(OBS)有助于解决P-S数据的可用性问题,关于弹性参数的有限信息仍然是一个挑战,因此,本文的重点是。本分析基于Zoeppritz's解决方案,对P-P和P-S反射系数RPP和RPS进行了一些修改。我们使用归一化的P-S反射系数;即,对于θ> 0,R′PS = RPS /sinθ,而不是RPS,其中θ是入射角。通过对RPS进行归一化,我们避免了在小入射角处不存在转换S波的情况,并增强了在小入射角处P-P和归一化P-S反射系数的相似线性行为。我们使用RPP和R'PS在小于35度角时的线性度来同时估计平均VP / VS比,P波和S波速度的对比度以及密度的对比度。利用这些信息,我们可以求出每个岩层的泊松比,从而可以进行岩性判别。使用非线性综合数据(即有限差分数据)证明了这种分析的可行性。估计泊松比的结果产生的误差小于5%。我们将这种新的组合的P-P和P-S AVO分析归纳为浸渍接口。与非浸入式界面情况相似,我们的推导表明,浸入式界面的P-P和P-S的具有偏移的幅度变化(AVO)可以转换为截距和梯度。但是,这些截距和梯度取决于浸入界面的角度。因此,我们通过包括允许我们找到倾角的迁移步骤来进一步概括我们的分析。由于无法获得RPP和R'PS方面的地震数据,因此该过程包括在迁移数据并校正几何扩展之后恢复反射系数,如Ikelle等人所做的那样。 (1986年和1988年)。所有这些步骤的组合,即几何扩展校正,偏移和AVO分析,是本论文的另一个新颖之处,它可以直接从地震数据中找到每个岩层的泊松比的特定值。

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