Elastic full-waveform inversion with probabilistic petrophysical model constraints
Elastic full-waveform inversion with probabilistic petrophysical model constraints
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DOI：
10.1190/geo2019-0285.1
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发表时间：
2020-03
期刊：
影响因子：
3.3
通讯作者：
O. Aragao;P. Sava
中科院分区：
文献类型：
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作者：
O. Aragao;P. Sava
基于数据残差最小化的全波形反演（FWI）可能不会增强我们对地下的了解，并且有时会导致误导性的地下模型。此外，无约束的多参数 FWI 还可能导致模型无法代表独立导出的参数的实际岩性。我们开发了一种弹性 FWI 方法，该方法明确施加岩石物理限制，以指导模型走向现实可行的岩性，即与地震数据和底层岩石物理一致的地下模型。我们利用岩石物理信息（例如测井记录提供的信息）来限制反演并避免不可信的模型。我们通过将反演模型限制在由概率密度函数定义的可行区域而不是将岩性相作为位置的函数来实现这一目标。在这个可行的岩石物理体系内，反演模型不需要服从特定的趋势，也就是说，我们不将参数与明确的和可能不准确的岩石物理关系联系起来。相反，我们定义了一个岩石物理吸引力盆地，将模型限制在经区域岩性和岩石物理信息验证的可行区域内。我们通过弹性模型发现，将概率岩石物理约束纳入反演目标函数会产生优于无约束或有近似解析约束所获得的模型的模型。此外，我们发现这些约束可以帮助缓解影响弹性 FWI 的常见问题，例如参数间串扰和有限的采集覆盖范围产生的伪影。
Full-waveform inversion (FWI) based on the minimization of data residuals may not enhance our understanding of the subsurface and can at times lead to misleading subsurface models. Additionally, unconstrained multiparameter FWI may also lead to models that do not represent realistic lithology for independently derived parameters. We have developed a method for elastic FWI that explicitly imposes petrophysical restrictions to guide models toward realistic and feasible lithology, that is, to subsurface models consistent with the seismic data and with the underlying petrophysics. We exploit petrophysical information, such as that provided by well logs, to constrain the inversion and to avoid implausible models. We achieve this goal by confining the inverted models to a feasible region defined by a probability density function instead of imposing lithologic facies as a function of position. Inside this feasible petrophysical regime, the inverted models do not need to obey a specific trend, that is, we do not link the parameters with explicit and potentially inaccurate petrophysical relations. Instead, we define a petrophysical basin of attraction that confines models to a feasible region validated by regional lithologic and petrophysical information. We find through elastic models that incorporating probabilistic petrophysical constraints into the inversion objective function leads to models that are superior to models obtained either without constraints or with approximate analytic constraints. In addition, we discover that these constraints can help in mitigating common issues affecting elastic FWI, such as the artifacts produced by interparameter crosstalk and limited acquisition coverage.