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.

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

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.

Estimating the amount of gas hydrate and free gas from marine seismic data

Geophysics ◽  
2000 ◽  
Vol 65 (2) ◽  
pp. 565-573 ◽  
Author(s):  
Christine Ecker ◽  
Jack Dvorkin ◽  
Amos M. Nur
Keyword(s):  
Gas Hydrate ◽  
Seismic Data ◽  
Rock Physics ◽  
Free Gas ◽  
Interval Velocity ◽  
Blake Ridge ◽  
Hydrate Saturation ◽  
Physics Model ◽  
Rock Physics Model ◽  
Marine Seismic

Marine seismic data and well‐log measurements at the Blake Ridge offshore South Carolina show that prominent seismic bottom‐simulating reflectors (BSRs) are caused by sediment layers with gas hydrate overlying sediments with free gas. We apply a theoretical rock‐physics model to 2-D Blake Ridge marine seismic data to determine gas‐hydrate and free‐gas saturation. High‐porosity marine sediment is modeled as a granular system where the elastic wave velocities are linked to porosity; effective pressure; mineralogy; elastic properties of the pore‐filling material; and water, gas, and gas‐hydrate saturation of the pore space. To apply this model to seismic data, we first obtain interval velocity using stacking velocity analysis. Next, all input parameters to the rock‐physics model, except porosity and water, gas, and gas hydrate saturation, are estimated from geologic information. To estimate porosity and saturation from interval velocity, we first assume that the entire sediment does not contain gas hydrate or free gas. Then we use the rock‐physics model to calculate porosity directly from the interval velocity. Such porosity profiles appear to have anomalies where gas hydrate and free gas are present (as compared to typical profiles expected and obtained in sediment without gas hydrate or gas). Porosity is underestimated in the hydrate region and is overestimated in the free‐gas region. We calculate the porosity residuals by subtracting a typical porosity profile (without gas hydrate and gas) from that with anomalies. Next we use the rock‐physics model to eliminate these anomalies by introducing gas‐hydrate or gas saturation. As a result, we obtain the desired 2-D saturation map. The maximum gas‐hydrate saturation thus obtained is between 13% and 18% of the pore space (depending on the version of the model used). These saturation values are consistent with those measured in the Blake Ridge wells (away from the seismic line), which are about 12%. Free‐gas saturation varies between 1% and 2%. The saturation estimates are extremely sensitive to the input velocity values. Therefore, accurate velocity determination is crucial for correct 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

Seismic reflections of gas hydrate from perturbational forward modeling

Geophysics ◽  
2006 ◽  
Vol 71 (6) ◽  
pp. F165-F171 ◽  
Author(s):  
Ingrid Cordon ◽  
Jack Dvorkin ◽  
Gary Mavko
Keyword(s):  
Reservoir Characterization ◽  
Rock Physics ◽  
Clay Content ◽  
The Arctic ◽  
Seismic Amplitude ◽  
Hydrate Reservoir ◽  
Hydrate Saturation ◽  
Physics Model ◽  
Rock Physics Model ◽  
Seismic Reflections

We perturb the elastic properties and attenuation in the Arctic Mallik methane-hydrate reservoir to produce a set of plausible seismic signatures away from the existing well. These perturbations are driven by the changes we impose on porosity, clay content, hydrate saturation, and geometry. The key is a data-guided, theoretical, rock-physics model that we adopt to link velocity and attenuation to porosity, mineralogy, and amount of hydrate. We find that the seismic amplitude is very sensitive to the hydrate saturation in the host sand and its porosity as well as the porosity of the overburden shale. However, changes to the amount of clay in the sand only weakly alter the amplitude. Attenuation, which may be substantial, must be taken into account during hydrate reservoir characterization because it lowers the amplitude to an extent that may affect the hydrate-volume prediction. The spatial structure of the reservoir affects the seismic reflection: A thinly-layered reservoir produces a noticeably different amplitude than a massive reservoir with the same hydrate volume.

scholarly journals Rock Physics Model and Seismic Dispersion and Attenuation in Gas Hydrate-Bearing Sediments

2021 ◽  
Vol 9 ◽  
Author(s):  
Zhiqi Guo ◽  
Xueying Wang ◽  
Jian Jiao ◽  
Haifeng Chen
Keyword(s):  
Gas Hydrate ◽  
Rock Physics ◽  
P Wave ◽  
Pore Filling ◽  
P Wave Velocity ◽  
Hydrate Saturation ◽  
Physics Model ◽  
Rock Physics Model ◽  
Hydrate Bearing Sediments ◽  
Dispersion And Attenuation

A rock physics model was established to calculate the P-wave velocity dispersion and attenuation caused by the squirt flow of fluids in gas hydrate-bearing sediments. The critical hydrate saturation parameter was introduced to describe different ways of hydrate concentration, including the mode of pore filling and the co-existence mode of pore filling and particle cementation. Rock physical modeling results indicate that the P-wave velocity is insensitive to the increase in gas hydrate saturation for the mode of pore filling, while it increases rapidly with increasing gas hydrate saturation for the co-existence mode of pore filling and particle cementation. Meanwhile, seismic modeling results show that both the PP and mode-converted PS reflections are insensitive to the gas hydrate saturation that is lower than the critical value, while they tend to change obviously for the hydrate saturation that is higher than the critical value. These can be interpreted that only when gas hydrate begins to be part of solid matrix at high gas hydrate saturation, it represents observable impact on elastic properties of the gas hydrate-bearing sediments. Synthetic seismograms are calculated for a 2D heterogeneous model where the gas hydrate saturation varies vertically and layer thickness of the gas hydrate-bearing sediment varies laterally. Modeling results show that larger thickness of the gas hydrate-bearing layer generally corresponds to stronger reflection amplitudes from the bottom simulating reflector.

Breakthrough acquisition and technologies for subsalt imaging

Geophysics ◽  
2011 ◽  
Vol 76 (5) ◽  
pp. WB41-WB51 ◽  
Author(s):  
Denes Vigh ◽  
Jerry Kapoor ◽  
Nick Moldoveanu ◽  
Hongyan Li
Keyword(s):  
Velocity Field ◽  
Inversion Layer ◽  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
Reverse Time ◽  
Reverse Time Migration ◽  
Data Set ◽  
Low Frequencies ◽  
Full Waveform ◽  
Time Migration

The recently introduced method of wide-azimuth data acquisition offers better illumination, noise attenuation, and lower frequencies to more accurately determine a velocity field for imaging. For the field data experiment to demonstrate the technologies, we used a Gulf of Mexico (GOM) wide-azimuth data set that allows us to take advantage of possible low frequencies, relatively large crossline offsets, and increased illumination. The input data was processed through true 3D azimuthal surface-related multiple elimination (SRME) with zero-phasing and debubble. Eliminating the surface-related multiples aids the velocity determination and helps uncover the subsalt sediments at the final imaging stage. After the initial velocity derivation, which was constrained to wells and geology, full-waveform inversion (FWI) was used to further update the velocity field to achieve an enhanced image. The methodology used follows the top-down approach where suprasalt sediment model is developed followed by the top of salt, salt flanks, base of salt, and finished with a limited subsalt update. To approximate the observed data by using an acoustic inversion procedure, the propagator includes effects of attenuation, anisotropy, acquisition source, and receiver depth. The geological environment is salt related, which implies that the observed data is highly elastic, even though it is input to an acoustic full waveform inversion. To use the proper constraints for the inversion, layer-stripping method is used to develop the high-resolution velocity field. The inversion stages were carefully quality controlled through gather displays to ensure the kinematics were honored. We then demonstrated the benefit of the FWI velocity field by comparing the images derived with the traditional ray-based tomographic velocity field versus the velocity field derived by FWI performing reverse time migration to produce these images. Finally, the images were compared at key well locations to evaluate the robustness of the workflow.

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