Quantitative interpretation for gas hydrate accumulation in the eastern Green Canyon Area, Gulf of Mexico using seismic inversion and rock physics transform

Geophysics ◽  
2011 ◽  
Vol 76 (4) ◽  
pp. B139-B150 ◽  
Author(s):  
Zijian Zhang ◽  
De-hua Han ◽  
Qiuliang Yao
Keyword(s):  
Gulf Of Mexico ◽  
Gas Hydrate ◽  
Pore Space ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Bright Spot ◽  
Quantitative Interpretation ◽  
Free Gas ◽  
Qualitative And Quantitative ◽  
Amplitude Data

Gas hydrate can be interpreted from seismic data through observation of bottom simulating reflector (BSR). It is a challenge to interpret gas hydrate without BSR. Three-dimensional qualitative and quantitative seismic interpretations were used to characterize gas hydrate distribution and concentration in the eastern Green Canyon area of the Gulf of Mexico, where BSR is absent. The combination of qualitative and quantitative interpretation reduces ambiguities in the estimation and identification of gas hydrate. Sandy deposition and faults are qualitatively interpreted from amplitude data. The 3D acoustic impedance volume was interpreted in terms of high P-impedance hydrate zones and low P-impedance free gas zones. Gas hydrate saturation derived from P-impedance is estimated by a rock physics transform. We interpreted gas hydrate in the sand-prone sediments with a maximum saturation of approximately 50% of the pore space. Sheet-like and some bright spot gas hydrate accumulations are interpreted. The interpretation of sheet-like gas hydrate within sand-prone sediments around faults suggests that fluid moves into the sand zones laterally by conduits. Variations in depths of interpreted gas hydrate zones imply nonequilibrium conditions. Low P-impedance free gas zones within high P-impedance gas hydrate zones imply possible coexistence of hydrate and free gas within the hydrate stability zone. We propose that gas hydrate distribution and concentration are associated with structures, buried sedimentary bodies, sources of gas, and fluid flux.

Combined seismic inversion and gravity modeling of a shallow anomaly in the southern Barents Sea

Geophysics ◽  
2003 ◽  
Vol 68 (4) ◽  
pp. 1140-1149 ◽  
Author(s):  
Bjørn Ursin ◽  
Christian Bauer ◽  
Huasheng Zhao ◽  
Christine Fichler
Keyword(s):  
Gas Hydrate ◽  
Barents Sea ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Gravity Modeling ◽  
Generation Process ◽  
Unknown Parameters ◽  
Water Contact ◽  
Free Gas ◽  
Seismic Anomaly

A combination of prestack elastic inversion with gravity modeling has been applied to a shallow seismic anomaly in the southern Barents Sea. The anomaly is crosscutting dipping layers of late Paleocene age. Earlier seismic interpretations indicate a possible origin in gas‐hydrated sediments trapping underlying free gas. Our interpretation includes seismic inversion of a seismic model which consists of a stack of isotropic, homogeneous, and anelastic layers. The unknown parameters are the P‐ and S‐wave velocities, density, and thickness for each layer. As densities are poorly determined by this method, we included gravity modeling, which improved the density estimates. The resulting parameters have been integrated by rock physics calculations and the knowledge of typical attributes of gas hydrate occurrences. The top of the seismic anomaly is interpreted as a reflection from the base of a gas‐hydrated sediment trapping underlying free gas. The base of the anomaly is the gas‐water contact, which deviates from a flat spot due to capillary pressure differences related to lithology and the generation process of gas hydrate. The estimated density has been interpreted together with well results and indicates a significant amount of gas filling the pore volume.

Characterization of elastic properties of near-surface and subsurface deepwater hydrate-bearing sediments

Geophysics ◽  
2013 ◽  
Vol 78 (3) ◽  
pp. D169-D179 ◽  
Author(s):  
Zijian Zhang ◽  
De-hua Han ◽  
Daniel R. McConnell
Keyword(s):  
Wave Velocity ◽  
Elastic Constants ◽  
Gas Hydrate ◽  
Effective Medium Theory ◽  
Pore Space ◽  
Seismic Interpretation ◽  
P Wave ◽  
Near Surface ◽  
Free Gas ◽  
Hydrate Bearing Sediments

Hydrate-bearing sands and shallow nodular hydrate are potential energy resources and geohazards, and they both need to be better understood and identified. Therefore, it is useful to develop methodologies for modeling and simulating elastic constants of these hydrate-bearing sediments. A gas-hydrate rock-physics model based on the effective medium theory was successfully applied to dry rock, water-saturated rock, and hydrate-bearing rock. The model was used to investigate the seismic interpretation capability of hydrate-bearing sediments in the Gulf of Mexico by computing elastic constants, also known as seismic attributes, in terms of seismic interpretation, including the normal incident reflectivity (NI), Poisson’s ratio (PR), P-wave velocity ([Formula: see text]), S-wave velocity ([Formula: see text]), and density. The study of the model was concerned with the formation of gas hydrate, and, therefore, hydrate-bearing sediments were divided into hydrate-bearing sands, hydrate-bearing sands with free gas in the pore space, and shallow nodular hydrate. Although relations of hydrate saturation versus [Formula: see text] and [Formula: see text] are different between structures I and II gas hydrates, highly concentrated hydrate-bearing sands may be interpreted on poststack seismic amplitude sections because of the high NI present. The computations of elastic constant implied that hydrate-bearing sands with free gas could be detected with the crossplot of NI and PR from prestack amplitude analysis, and density may be a good hydrate indicator for shallow nodular hydrate, if it can be accurately estimated by seismic methods.

Assessment of gas hydrate using pre-stack seismic inversion in Mahanadi Basin, offshore eastern India

2021 ◽  
pp. 1-42
Author(s):  
Maheswar Ojha ◽  
Ranjana Ghosh
Keyword(s):  
Gas Hydrate ◽  
Rock Physics ◽  
Type Equation ◽  
Seismic Inversion ◽  
Log Analysis ◽  
Well Log ◽  
Seismic Section ◽  
Bottom Simulating Reflector ◽  
Hydrate Saturation ◽  
Well Log Analysis

The Indian National Gas Hydrate Program Expedition-01 in 2006 has discovered gas hydrate in Mahanadi offshore basin along the eastern Indian margin. However, well log analysis, pressure core measurements and Infra-Red (IR) anomalies reveal that gas hydrates are distributed as disseminated within the fine-grained sediment, unlike massive gas hydrate deposits in the Krishna-Godavari basin. 2D multi-channel seismic section, which crosses the Holes NGHP-01-9A and 19B located at about 24 km apart shows a continuous bottom-simulating reflector (BSR) along it. We aim to investigate the prospect of gas hydrate accumulation in this area by integrating well log analysis and seismic methods with rock physics modeling. First, we estimate gas hydrate saturation at these two Holes from the observed impedance using the three-phase Biot-type equation (TPBE). Then we establish a linear relationship between gas hydrate saturation and impedance contrast with respect to the water-saturated sediment. Using this established relation and impedance obtained from pre-stack inversion of seismic data, we produce a 2D gas hydrate-distribution image over the entire seismic section. Gas hydrate saturation estimated from resistivity and sonic data at well locations varies within 0-15%, which agrees well with the available pressure core measurements at Hole 19. However, the 2D map of gas hydrate distribution obtained from our method shows maximum gas hydrate saturation is about 40% just above the BSR between the CDP (common depth point) 1450 and 2850. The presence of gas-charged sediments below the BSR is one of the reasons for the strong BSR observed in the seismic section, which is depicted as low impedance in the inverted impedance section. Closed sedimentary structures above the BSR are probably obstructing the movements of free-gas upslope, for which we do not see the presence of gas hydrate throughout the seismic section above the BSR.

Recent advances in rock physics

Geophysics ◽  
1985 ◽  
Vol 50 (12) ◽  
pp. 2480-2491 ◽  
Author(s):  
David P. Yale
Keyword(s):  
Electrical Properties ◽  
Seismic Waves ◽  
Seismic Velocity ◽  
Pore Space ◽  
Rock Physics ◽  
Rock Properties ◽  
Bright Spot ◽  
Geometrical Parameters ◽  
S Wave ◽  
Velocity Models

The need to extract more information about the subsurface from geophysical and petrophysical measurements has led to a great interest in the study of the effect of rock and fluid properties on geophysical and petrophysical measurements. Rock physics research in the last few years has been concerned with studying the effect of lithology, fluids, pore geometry, and fractures on velocity; the mechanisms of attenuation of seismic waves; the effect of anisotropy; and the electrical and dielectric properties of rocks. Understanding the interrelationships between rock properties and their expression in geophysical and petrophysical data is necessary to integrate geophysical, petrophysical, and engineering data for the enhanced exploration and characterization of petroleum reservoirs. The use of amplitude offsets, S‐wave seismic data, and full‐waveform sonic data will help in the discrimination of lithology. The effect of in situ temperatures and pressures must be taken into account, especially in fractured and unconsolidated reservoirs. Fluids have a strong effect on seismic velocities, through their compressibility, density, and chemical effects on grain and clay surfaces. S‐wave measurements should help in bright spot analysis for gas reservoirs, but theoretical considerations still show that a deep, consolidated reservoir will not have any appreciable impedance contrast due to gas. The attenuation of seismic waves has received a great deal of attention recently. The idea that Q is independent of frequency has been challenged by experimental and theoretical findings of large peaks in attenuation in the low kHz and hundreds of kHz regions. The attenuation is thought to be due to fluid‐flow mechanisms and theories suggest that there may be large attenuation due to small amounts of gas in the pore space even at seismic frequencies. Models of the effect of pores, cracks, and fractures on seismic velocity have also been studied. The thin‐crack velocity models appear to be better suited for representing fractures than pores. The anisotropy of seismic waves, especially the splitting of polarized S‐waves, may be diagnostic of sets of oriented fractures in the crust. The electrical properties of rocks are strongly dependent upon the frequency of the energy and logging is presently being done at various frequencies. The effects of frequency, fluid salinity, clays, and pore‐grain geometry on electrical properties have been studied. Models of porous media have been used extensively to study the electrical and elastic properties of rocks. There has been great interest in extracting geometrical parameters about the rock and pore space directly from microscopic observation. Other models have focused on modeling several different properties to find relationships between rock properties.

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.

Identification of gas hydrate dissociation from wireline-log data in the Shenhu area, South China Sea

Geophysics ◽  
2012 ◽  
Vol 77 (3) ◽  
pp. B125-B134 ◽  
Author(s):  
Xiujuan Wang ◽  
Myung Lee ◽  
Shiguo Wu ◽  
Shengxiong Yang
Keyword(s):  
Wave Velocity ◽  
Gas Hydrate ◽  
Seismic Data ◽  
Pore Space ◽  
P Wave ◽  
Well Log ◽  
Hydrate Dissociation ◽  
Free Gas ◽  
P Wave Velocity

Wireline logs were acquired in eight wells during China’s first gas hydrate drilling expedition (GMGS-1) in April–June of 2007. Well logs obtained from site SH3 indicated gas hydrate was present in the depth range of 195–206 m below seafloor with a maximum pore-space gas hydrate saturation, calculated from pore water freshening, of about 26%. Assuming gas hydrate is uniformly distributed in the sediments, resistivity calculations using Archie’s equation yielded hydrate-saturation trends similar to those from chloride concentrations. However, the measured compressional (P-wave) velocities decreased sharply at the depth between 194 and 199 mbsf, dropping as low as [Formula: see text], indicating the presence of free gas in the pore space, possibly caused by the dissociation of gas hydrate during drilling. Because surface seismic data acquired prior to drilling were not influenced by the in situ gas hydrate dissociation, surface seismic data could be used to identify the cause of the low P-wave velocity observed in the well log. To determine whether the low well-log P-wave velocity was caused by in situ free gas or by gas hydrate dissociation, synthetic seismograms were generated using the measured well-log P-wave velocity along with velocities calculated assuming both gas hydrate and free gas in the pore space. Comparing the surface seismic data with various synthetic seismograms suggested that low P-wave velocities were likely caused by the dissociation of in situ gas hydrate during drilling.

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.

Seismic Quantitative Interpretation for Uncertainty Reduction of Subsurface Modeling of the Deep Visean Reservoirs

2021 ◽  
Author(s):  
Pavlo Kuzmenko ◽  
Rustem Valiakhmetov ◽  
Francesco Gerecitano ◽  
Viktor Maliar ◽  
Grigori Kashuba ◽  
...  
Keyword(s):  
Elastic Properties ◽  
Seismic Data ◽  
Seismic Anisotropy ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Well Logs ◽  
Quantitative Interpretation ◽  
Structural Interpretation ◽  
Elastic Inversion ◽  
Subsurface Modeling

Abstract The seismic data have historically been utilized to perform structural interpretation of the geological subsurface. Modern approaches of Quantitative Interpretation are intended to extract geologically valuable information from the seismic data. This work demonstrates how rock physics enables optimal prediction of reservoir properties from seismic derived attributes. Using a seismic-driven approach with incorporated prior geological knowledge into a probabilistic subsurface model allowed capturing uncertainty and quantifying the risk for targeting new wells in the unexplored areas. Elastic properties estimated from the acquired seismic data are influenced by the depositional environment, fluid content, and local geological trends. By applying the rock physics model, we were able to predict the elastic properties of a potential lithology away from the well control points in the subsurface whether or not it has been penetrated. Seismic amplitude variation with incident angle (AVO) and azimuth (AVAZ) jointly with rock-derived petrophysical interpretations were used for stochastical modeling to capture the reservoir distribution over the deep Visean formation. The seismic inversion was calibrated by available well log data and by traditional structural interpretation. Seismic elastic inversion results in a deep Lower Carboniferous target in the central part of the DDB are described. The fluid has minimal effect on the density and Vp. Well logs with cross-dipole acoustics are used together with wide-azimuth seismic data, processed with amplitude control. It is determined that seismic anisotropy increases in carbonate deposits. The result covers a set of lithoclasses and related probabilities: clay minerals, tight sandstones, porous sandstones, and carbonates. We analyzed the influence of maximum angles determination for elastic inversion that varied from 32.5 to 38.5 degrees. The greatest influence of the far angles selection is on the density. AI does not change significantly. Probably the 38,5 degrees provides a superior response above the carbonates. It does not seem to damage the overall AVA behavior, which result in a good density outcome, as higher angles of incidence are included. It gives a better tie to the wells for the high density layers over the interval of interest. Sand probability cube must always considered in the interpretation of the lithological classification that in many cases may be misleading (i.e. when sand and shale probabilities are very close to each other, because of small changes in elastic parameters). The authors provide an integrated holistic approach for quantitative interpretation, subsurface modeling, uncertainty evaluation, and characterization of reservoir distribution using pre-existing well logs and recently acquired seismic data. This paper underpins the previous efforts and encourages the work yet to be fulfilled on this subject. We will describe how quantitative interpretation was used for describing the reservoir, highlight values and uncertainties, and point a way forward for further improvement of the process for effective subsurface modeling.

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