Integration of digital rock physics and full waveform inversion for unconventional exploration

2015 ◽  
Author(s):  
Wenhui Yu* ◽  
Aifei Bian ◽  
Wei Zhu
Keyword(s):  
Waveform Inversion ◽  
Rock Physics ◽  
Full Waveform Inversion ◽  
Digital Rock Physics ◽  
Digital Rock ◽  
Full Waveform

Full-waveform inversion with borehole constraints for elastic VTI media

Geophysics ◽  
2020 ◽  
Vol 85 (6) ◽  
pp. R553-R563
Author(s):  
Sagar Singh ◽  
Ilya Tsvankin ◽  
Ehsan Zabihi Naeini
Keyword(s):  
Objective Function ◽  
Reservoir Characterization ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Rock Physics ◽  
Anisotropic Media ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Trade Offs ◽  
Vti Media

The nonlinearity of full-waveform inversion (FWI) and parameter trade-offs can prevent convergence toward the actual model, especially for elastic anisotropic media. The problems with parameter updating become particularly severe if ultra-low-frequency seismic data are unavailable, and the initial model is not sufficiently accurate. We introduce a robust way to constrain the inversion workflow using borehole information obtained from well logs. These constraints are included in the form of rock-physics relationships for different geologic facies (e.g., shale, sand, salt, and limestone). We develop a multiscale FWI algorithm for transversely isotropic media with a vertical symmetry axis (VTI media) that incorporates facies information through a regularization term in the objective function. That term is updated during the inversion by using the models obtained at the previous inversion stage. To account for lateral heterogeneity between sparse borehole locations, we use an image-guided smoothing algorithm. Numerical testing for structurally complex anisotropic media demonstrates that the facies-based constraints may ensure the convergence of the objective function towards the global minimum in the absence of ultra-low-frequency data and for simple (even 1D) initial models. We test the algorithm on clean data and on surface records contaminated by Gaussian noise. The algorithm also produces a high-resolution facies model, which should be instrumental in reservoir characterization.

Direct elastic full-waveform inversion of rock physics properties

2020 ◽  
Author(s):  
Qi Hu ◽  
Scott Keating ◽  
Kristopher Innanen ◽  
Huaizhen Chen
Keyword(s):  
Waveform Inversion ◽  
Rock Physics ◽  
Full Waveform Inversion ◽  
Full Waveform

Direct updating of rock physics properties using elastic full-waveform inversion

Geophysics ◽  
2021 ◽  
pp. 1-64
Author(s):  
Qi Hu ◽  
Scott Keating ◽  
Kristopher A. Innanen ◽  
Huaizhen Chen
Keyword(s):  
Reservoir Characterization ◽  
Seismic Velocity ◽  
Water Saturation ◽  
Quantitative Estimation ◽  
Waveform Inversion ◽  
Rock Physics ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Physics Model ◽  
Rock Physics Model

Quantitative estimation of rock physics properties is an important part of reservoir characterization. Most current seismic workflows in this field are based on amplitude variation with offset. Building on recent work on high resolution multi-parameter inversion for reservoir characterization, we construct a rock-physics parameterized elastic full-waveform inversion (EFWI) scheme. Within a suitably-formed multi-parameter EFWI, in this case a 2D frequency-domain isotropic-elastic FWI with a truncated Gauss-Newton optimization, any rock physics model with a well-defined mapping between its parameters and seismic velocity/density can be examined. We select a three-parameter porosity, clay content, and water saturation (PCS) parameterization, and link them to elastic properties using three representative rock physics models: the Han empirical model, the Voigt-Reuss-Hill boundary model, and the Kuster and Toksöz inclusion model. Numerical examples suggest that conditioning issues, which make a sequential inversion (in which velocities and density are first determined through EFWI, followed by PCS parameters) unstable, are avoided in this direct approach. Significant variability in inversion fidelity is visible from one rock physics model to another. However, the response of the inversion to the range of possible numerical optimization and frequency selections, as well as acquisition geometries, varies widely. Water saturation tends to be the most difficult property to recover in all situations examined. This can be explained with radiation pattern analysis, where very low relative scattering amplitudes from saturation perturbations are observed. An investigation performed with a Bayesian approach illustrates that the introduction of prior information may increase the inversion sensitivity to water saturation

Hydrate quantification: Integrating full-waveform inversion, seismic attributes, and rock physics

2016 ◽  
Vol 4 (1) ◽  
pp. SA55-SA71 ◽  
Author(s):  
P. Jaiswal
Keyword(s):  
Velocity Field ◽  
Waveform Inversion ◽  
Rock Physics ◽  
Well Logs ◽  
Full Waveform Inversion ◽  
Secondary Porosity ◽  
Full Waveform ◽  
Hydrate Saturation ◽  
Physics Model ◽  
Rock Physics Model

Hydrate quantification from seismic data is a two-pronged challenge. The first is creating a velocity field with high enough resolution and accuracy such that it is a meaningful representation of hydrate variability in the host sediments. The second is constructing a rock-physics model that accounts for the appropriate growth of the hydrate and allows for the interpretation of the velocity field in terms of hydrate saturation. In this paper, both challenges are addressed in a quantification workflow that uses 2D seismic and colocated well logs. The study area is situated in the Krishna-Godavari Basin, offshore eastern Indian coast, where hydrate was discovered in the National Gas Hydrate Program Expedition 01 (NGHP-01). The workflow hinges on a rock-physics model that expresses total hydrate saturation in terms of primary (matrix) and secondary (fractures, faults, voids, etc.) porosities and their respective primary and secondary saturations and incorporates hydrate-filled secondary porosity into the rock as an additional grain type using the Hashin-Shtrikman bounds. The model is first applied to a set of well logs at a colocated site, NGHP-01-10, following which the application is extended into the seismic domain by (1) the incoherency attribute as a proxy for secondary porosity and (2) a full-waveform inversion-based P-wave velocity ([Formula: see text]) model as a proxy for primary saturation. The remaining — the primary porosity and secondary saturation — are assumed to remain the same across the seismic profile as at the site NGHP-01-10. The resulting, seismically estimated, hydrate saturation compares well with saturations from core depressurization at colocated sites NGHP-01-10 and NGHP-01-13. The quantification workflow presented here is potentially adaptable to other geographical areas with the caveat that empirical relations between porosity, saturation, and seismic attributes may have to be locally established.

Elastic Full Waveform Inversion With a Permanent Seismic Source ACROSS: Towards Hydrocarbon Reservoir Monitoring

2014 ◽  
Author(s):  
Mamoru Takanashi ◽  
Ayato Kato ◽  
Junzo Kasahara ◽  
Stefan Luth ◽  
Christopher Juhlin
Keyword(s):  
Waveform Inversion ◽  
Seismic Source ◽  
Full Waveform Inversion ◽  
Hydrocarbon Reservoir ◽  
Full Waveform ◽  
Reservoir Monitoring
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