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.

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.

Porosity estimation based on rock skeleton general formula and comprehensive pore structure parameter – An application to a tight-sand reservoir

2021 ◽  
pp. 1-59
Author(s):  
Kai Lin ◽  
Xilei He ◽  
Bo Zhang ◽  
Xiaotao Wen ◽  
Zhenhua He ◽  
...  
Keyword(s):  
Aspect Ratio ◽  
Pore Structure ◽  
Seismic Data ◽  
Rock Physics ◽  
Structure Parameters ◽  
Pore Structure Parameter ◽  
Elastic Parameters ◽  
Physics Model ◽  
Rock Physics Model ◽  
Porosity Estimation

Most of current 3D reservoir’s porosity estimation methods are based on analyzing the elastic parameters inverted from seismic data. It is well-known that elastic parameters vary with pore structure parameters such as pore aspect ratio, consolidate coefficient, critical porosity, etc. Thus, we may obtain inaccurate 3D porosity estimation if the chosen rock physics model fails properly address the effects of pore structure parameters on the elastic parameters. However, most of current rock physics models only consider one pore structure parameter such as pore aspect ratio or consolidation coefficient. To consider the effect of multiple pore structure parameters on the elastic parameters, we propose a comprehensive pore structure (CPS) parameter set that is generalized from the current popular rock physics models. The new CPS set is based on the first order approximation of current rock physics models that consider the effect of pore aspect ratio on elastic parameters. The new CPS set can accurately simulate the behavior of current rock physics models that consider the effect of pore structure parameters on elastic parameters. To demonstrate the effectiveness of proposed parameters in porosity estimation, we use a theoretical model to demonstrate that the proposed CPS parameter set properly addresses the effect of pore aspect ratio on elastic parameters such as velocity and porosity. Then, we obtain a 3D porosity estimation for a tight sand reservoir by applying it seismic data. We also predict the porosity of the tight sand reservoir by using neural network algorithm and a rock physics model that is commonly used in porosity estimation. The comparison demonstrates that predicted porosity has higher correlation with the porosity logs at the blind well locations.

scholarly journals Assessment of gas-hydrate saturations in the Makran accretionary prism using the offset dependence of seismic amplitudes

Geophysics ◽  
2010 ◽  
Vol 75 (2) ◽  
pp. C1-C6 ◽  
Author(s):  
Maheswar Ojha ◽  
Kalachand Sain ◽  
Timothy A. Minshull
Keyword(s):  
Gas Hydrate ◽  
Seismic Velocity ◽  
Rock Physics ◽  
Accretionary Prism ◽  
Seismic Line ◽  
Amplitude Variation With Offset ◽  
Free Gas ◽  
Bottom Simulating Reflector ◽  
Physics Modeling ◽  
Physics Model

We estimate the saturations of gas hydrate and free gas based on measurements of seismic-reflection amplitude variation with offset (AVO) for a bottom-simulating reflector coupled with rock-physics modeling. When we apply the approach to data from a seismic line in the Makran accretionary prism in the Arabian Sea, the results reveal lateral variations of gas-hydrate and free-gas saturations of 4–29% and 1–7.5%, respectively, depending on the rock-physics model used to relate seismic velocity to saturation. Our approach is simple and easy to implement.

Prediction of porosity and gas saturation for deep-buried sandstone reservoirs from seismic data using an improved rock-physics model

2019 ◽  
Vol 67 (2) ◽  
pp. 557-575 ◽  
Author(s):  
Yaneng Luo ◽  
Handong Huang ◽  
Morten Jakobsen ◽  
Yadi Yang ◽  
Jinwei Zhang ◽  
...  
Keyword(s):  
Seismic Data ◽  
Rock Physics ◽  
Gas Saturation ◽  
Sandstone Reservoirs ◽  
Physics Model ◽  
Rock Physics Model

Two-parameter prestack seismic inversion of porosity and pore structure parameter of fractured carbonate reservoirs: Part 1 — Methods

2018 ◽  
Vol 6 (4) ◽  
pp. SM1-SM8 ◽  
Author(s):  
Tingting Zhang ◽  
Yuefeng Sun
Keyword(s):  
Pore Structure ◽  
Seismic Data ◽  
Rock Physics ◽  
Seismic Inversion ◽  
High Porosity ◽  
Structure Parameter ◽  
Pore Structure Parameter ◽  
Fractured Zones ◽  
Physics Model ◽  
Rock Physics Model

Fractured zones in deeply buried carbonate hills are important because they often have better permeability resulting in prolific production than similar low-porosity rocks. Nevertheless, their detection poses great challenge to conventional seismic inversion methods because they are mostly low in acoustic impedance and bulk modulus, hardly distinguishable from high-porosity zones or mudstones. A proxy parameter of pore structure defined in a rock-physics model, the so-called Sun model, has been used for delineating fractured zones in which the pore structure parameter is relatively high, whereas the porosity is low in general. Simultaneous seismic inversion of the pore structure parameter and porosity proves to be difficult and nontrivial in practice. Although the pore structure parameter is well-defined at locations where density, P-, and S-velocity are known from logs, estimation of P- and S-velocity information, especially density information from prestack seismic data is rather challenging. A three-step iterative inversion method, which uses acoustic, gradient, and elastic impedance from angle-stacked seismic data as input to the rock-physics model for calculating porosity and bulk and shear pore structure parameters simultaneously, is proposed and implemented to solve this problem. The methodology is successfully tested with well logs and seismic data from a deeply buried carbonate hill in the Bohai Bay Basin, China.

Rock-physics diagnostics of a turbidite oil reservoir offshore northwest Australia

Geophysics ◽  
2017 ◽  
Vol 82 (1) ◽  
pp. MR1-MR13 ◽  
Author(s):  
Humberto S. Arévalo-López ◽  
Jack P. Dvorkin
Keyword(s):  
Seismic Data ◽  
Rock Physics ◽  
Rock Properties ◽  
Oil Reservoir ◽  
Controlled Experiments ◽  
Seismic Modeling ◽  
Physics Model ◽  
Rock Physics Model ◽  
Offshore Oil ◽  
Northwest Australia

Interpreting seismic data for petrophysical rock properties requires a rock-physics model that links the petrophysical rock properties to the elastic properties, such as velocity and impedance. Such a model can only be established from controlled experiments in which both groups of rock properties are measured on the same samples. A prolific source of such data is wellbore measurements. We use data from four wells drilled through a clastic offshore oil reservoir to perform rock-physics diagnostics, i.e., to find a theoretical rock-physics model that quantitatively explains the measurements. Using the model, we correct questionable well curves. Moreover, a crucial purpose of rock-physics diagnostics is to go beyond the settings represented in the wells and understand the seismic signatures of rock properties varying in a wider range via forward seismic modeling. With this goal in mind, we use our model to generate synthetic seismic gathers from perturbational modeling to address “what-if” scenarios not present in the wells.

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.

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.

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