Amplitude Variation With Offset Response Research Articles

Evaluation of seismic responses from well-associated gas producing sands using integrated approaches for optimal field production in Zamzama gas field, Pakistan

The producing fields often observe early decline due to many misapprehended factors concerning structural interpretation, facies identification, and proper estimation of geological properties. The accuracy of the estimation of these characteristics is critical for enhanced recovery. An integrated approach based on well identified potential lithofacies distribution in relation to seismic trace responses and accurate fluid estimation is vital. In the present study, gas-bearing sands are appraised for their reservoir characteristics within a complex anticline structure. The faulted anticline's hanging wall provided suitable locations for optimum gas entrapment; however, its connection with the footwall through lateral ramps allows the aquifer's early encroachment into the reservoir. For enhanced recovery, the combination of well-derived petrophysical parameters with seismic extracted responses provided insight into the producing facies with quantitative fluids identification using fluid replacement modeling (FRM) and their amplitude variation with offset (AVO) responses. The reliable AVO responses of substituted fluids comprising 85% gas with 15% brine are observed for identified potential sands, classifying sands as class-II. Similarly, the intercept (A), gradient (B), and product (A*B) of angle dependent seismic traces were mapped within the Pab Formation and showed amplitude anomalies for porous channelized gas-bearing sands. Finally, crossplotting intercept-gradient volumes differentiated the gas-bearing sands and precisely demarcated the identified gas sands throughout the field, with confirmation at producing well locations. Hence, the integrated assessment of the outcomes resulting from structural interpretation, petrophysical evaluation, and seismic trace valuation can be readily employed for distinguishing the producing sand facies in complex structures and demarcating risk-efficient zones.

AVO analysis for high amplitude anomalies using 2D pre-stack seismic data

Amplitude variation with offset (AVO) analysis is an 1 efficient tool for hydrocarbon detection and identification of elastic rock properties and fluid types. It has been applied in the present study using reprocessed pre-stack 2D seismic data (1992, Caulerpa) from north-west of the Bonaparte Basin, Australia. The AVO response along the 2D pre-stack seismic data in the Laminaria High NW shelf of Australia was also investigated. Three hypotheses were suggested to investigate the AVO behaviour of the amplitude anomalies in which three different factors; fluid substitution, porosity and thickness (Wedge model) were tested. The AVO models with the synthetic gathers were analysed using log information to find which of these is the controlling parameter on the AVO analysis. AVO cross plots from the real pre-stack seismic data reveal AVO class IV (showing a negative intercept decreasing with offset). This result matches our modelled result of fluid substitution for the seismic synthetics. It is concluded that fluid substitution is the controlling parameter on the AVO analysis and therefore, the high amplitude anomaly on the seabed and the target horizon 9 is the result of changing the fluid content and the lithology along the target horizons. While changing the porosity has little effect on the amplitude variation with offset within the AVO cross plot. Finally, results from the wedge models show that a small change of thickness causes a change in the amplitude; however, this change in thickness gives a different AVO characteristic and a mismatch with the AVO result of the real 2D pre-stack seismic data. Therefore, a constant thin layer with changing fluids is more likely to be the cause of the high amplitude anomalies.

Model-based approach to improve class 1 AVO attributes

We propose a model-based Amplitude Variation with Offset (AVO) approach to address the assumption of weak elastic contrast in the linearized approximations of Aki-Richard equation. Existing approximations, especially for the Class 1 AVO response, which indicates the positive elastic contrast, deviate significantly from the Zoeppritz equation in presence of large elastic contrast. Results of the proposed approach show that it can minimize the deviation from the Zoeppritz equation, improve AVO attributes, and is capable of providing the desired attribute for characterizing a reservoir. The method starts with two matrices. One matrix is of the simulated rock properties termed as the rock-property-matrix and the other of the Zoeppritz AVO responses for those rock properties termed as the response-matrix. A model-based AVO equation or the basis-function-matrix is computed utilizing the rock-property-matrix and the response-matrix. The inverse of the basis-function-matrix is applied to the real data to get the AVO attributes from this approach. The conventional AVO (Aki-Richards) and model-based AVO attributes are compared in a class 1 AVO environment from the offshore east coast of India. The curvature attribute based on model-based AVO shows significant improvement. The synthetic-seismic correlation of the curvature attribute improves from −0.03 to 0.9 while synthetic-seismic correlation of the gradient attribute improves from 0.5 to 0.77. The improved AVO attribute volumes add significant values in the reservoir characterization.

Near Surface Velocity Estimation Using GPR Data: Investigations by Numerical Simulation, and Experimental Approach with AVO Response

The velocity of near-surface materials is one of the most important for Ground-Penetrating Radar (GPR). In the study, we evaluate the options for determining the GPR velocity to measure the accuracy of velocity approximations from the acquired GPR data at an experimental site in Hangzhou, China. A vertical profile of interval velocities can be estimated from each common mid-point (CMP) gather using velocity spectrum analysis. Firstly, GPR data are acquired and analyzed using the popular method of hyperbola fitting which generated surprisingly high subsurface signal velocity estimates while, for the same profile, the Amplitude variation with offset (AVO) analysis of the GPR data (using the same hyperbola fitting method) generate a more reasonable subsurface signal velocity estimate. Several necessary processing steps are applied both for CMP and AVO analysis. Furthermore, experimental analysis is conducted on the same test site to get velocities of samples based on dielectric constant measurement during the drilling process. Synthetic velocities generated by AVO analysis are validated by the experimental velocities which confirmed the suitability of velocity interpretations.

AVO inversion using pseudoisotropic elastic properties

Amplitude variation with offset (AVO) inversion of an anisotropic data set is a challenging task. Nonnegligible differences in the anisotropy parameters between the various lithologies make the seismic data AVO response completely different from the isotropic synthetic seismogram. In this case, it is difficult to invert for VP/VSand density consistent with well-log data. AVO inversion using pseudoisotropic elastic properties is a practical solution to this problem. Verification of this method was performed using data from an offshore Western Australia field. It was found that wavelet extraction and density inversion are improved significantly by replacing the isotropic elastic properties with the pseudoisotropic properties. Inverted density shows reasonable quality and therefore can be included in the reservoir characterization study. Postinversion analyses can be performed effectively on the pseudoisotropic elastic properties because crossplot analysis shows the increased separation of different lithofacies due to contrasts in anisotropy parameters. This result could have significant implications for other fields, as shale constitutes most of the overburden in conventional oil and gas fields and often shows strong elastic anisotropy.

Seismic petrophysics workflow applied to Delaware Basin

Petrophysical analysis of unconventional plays that are comprised of organic mudrock needs detailed data QC and preparation to optimize the results of quantitative interpretation. This includes accurate computation of mineral volumes, total organic carbon (TOC), porosity, and saturations. We used TOC estimation to aid the process of determining the best pay zones for development of such reservoirs. TOC was calculated as a weighted average of Passey’s (empirical) and the bulk density-based (theoretical) methods. In organic mudrock reservoirs, the computed TOC log was used as an input to compute porosity and calibrate rock-physics models (RPMs), which are needed for understanding the potential of source rocks or finding sweet spots and their contribution to the amplitude variation with offset (AVO) changes in the seismic data. Using calibrated RPM templates, we found that TOC is driving the elastic property variations in the Avalon Formation. We determined the layering and rock fabric anisotropy using empirical relationships or modeled in the rock property characterization process because reflectivity effects are often seen in the observed seismic used for well tie and wavelet estimation. A Class IV AVO response was seen at the top of the Avalon Formation, which is typical of an unconventional reservoir. We then performed solid organic matter (TOC) substitution to account for variability of elastic properties and their contrasts as expressed in seismic amplitudes. To complete the characterization of the intervals of interest, we used conventional seismic petrophysical methods in the workflow and found that the main driver modifying the elastic properties for the Avalon shales was TOC; this conclusion serves as a foundation in integrated seismic inversion that may target lithofacies, TOC, and geomechanical properties. Seismic reservoir characterization results are critical in constraining landing zones and trajectories of the horizontal wells. The final interpretation may be used to rank targets, optimize drilling campaigns, and ultimately improve production.

Seafloor elastic-parameter estimation based on a regularized AVO inversion method

Seafloor properties play important roles in both the civilian and the military domains. In this paper, we propose to use a regularization-based AVO (amplitude variation with offset) inversion method to estimate the elastic parameters of seafloor sediment along a seismic survey line. Conventional AVO research focuses mainly on the strata beneath seafloor sediment; accordingly, the AVO response of the interface between the seawater and seafloor sediment is typically ignored. Several studies on the estimation of seafloor elastic parameters have been published based on AVO theory. However, these earlier studies only consider one CRP (common reflection point) gather in the inversion process. When dealing with a long seismic survey with many CRPs, earlier methods involve clear random inversion errors along the survey line. To suppress the inversion errors, we try to regularize each of the elastic parameters along the seismic survey by a total-variation method. Synthetic tests demonstrate that the regularization-based method can effectively suppress the inversion errors along the seismic survey and yield much cleaner inversion results. Finally, we apply the regularization-based method to a real two-dimensional marine seismic survey and obtain satisfactory results, which further proves the efficacy of the method.

Application of AVO attributes for gas channels identification, West offshore Nile Delta, Egypt

The offshore part of the Nile Delta is considered one of the most prolific provinces for gas production and for future petroleum exploration. Amplitude Variation with Offset (AVO) analysis supported by composite logs considered as one of the best-advanced techniques enables the interpreter to understand the seismic data. It is used to generate a new view of the output results, especially for the identification of gas zones as gas channels by using pre-stack AVO attributes that based on the intercept product gradient (A*B) and the Scaled Poisson’s Ratio Change. Free gas, regardless of the percentage show obvious AVO anomaly. Well log data, including gamma-ray, resistivity, and Vp sonic logs are used in the seismic data to well tie and in the generation of the synthetic seismogram. Seismic data conditioning processes with check-shot correction is performed to improve the resolution of the reflection events and signal to noise ratio. AVO attributes technique, as a direct hydrocarbon indicator, including AVO gradient analysis and AVO crossplot separate the gas levels in the sand-shale sequences. The identified gas-bearing zones consistent with well log data responses. As the main conclusion, we show the visual evidence for the gas-bearing zones by interpreting different AVO responses due to the changes in fluid and rock types.

A physical modelling study of the reservoir scale effect on amplitude variation with incidence angle

Abstract The 3D pre-stack seismic data from a physical modeling experiment were employed to investigate the effect of reservoir scales on AVO (amplitude variation with offset or incidence angle). Eight cuboid samples simulating cavernous reservoirs with different widths and the same thickness and elastic parameters were set within a 3D model. 3D seismic data acquisition and processing were conducted. To get the AVO responses of the samples with different widths, trough amplitudes corresponding to the sample tops at different incidence angles were extracted from the pre-stack angle gathers. Amplitude calibration for transducer radiation patterns was conducted on the extracted amplitudes at different angles. AVO analysis was conducted to quantitatively demonstrate the effect of sample scales on AVO characteristics. The effect of sample width was weak when the width was less than 60 m, which was 3/5 of the wavelength. When the width was larger than 60 m, both AVO intercept and gradient gradually increased with the sample width. The AVO gradient peaked at 150 m, which was 1.5 times the wavelength. Cross-plot analysis of AVO intercept and gradient showed the samples were aligned in a straight line when the sample width was less than twice the seismic wavelength. The result in this study partially verified the conclusions of reservoir scale effect on AVO responses drawn from previous numerical modelling studies. For a heterogeneous rectangular reservoir, the effect of reservoir scales on AVO responses could potentially be used to quantitatively estimate reservoir scale.

Numerical simulation of AVO response characteristics from pore-filling gas hydrate in Qilian mountain permafrost, China

The seismic reflection wave amplitude variation with offset (AVO) technique can effectively extract the lithology and fluid parameters that are hidden in the seismic record, and thus can be applied to gas hydrate prospecting and assessments in the permafrost region. Based on the geological conditions of pore-filling gas hydrate reservoir in Qilian mountain permafrost, the forward simulation velocity model of gas hydrate, by the rock physics model of the equivalent medium theory, was established. The AVO response characteristics of the gas hydrate reservoir with different properties by the forward modeling velocity model and the ray tracing theory were studied. The sensitivity of elastic parameters, for gas hydrate reservoir identification and formation lithology, was also studied. The AVO attribute partition changing with the porosity is quite well; the AVO attribute partition changing with the saturation presents continuous transition and could not be distinguished easily, and the AVO attribute partition changing with the thickness of the gas hydrate reservoir is linear. The μ and E are the most sensitive parameters to the properties of the gas hydrate reservoir, the crossplot of μ and E can effectively identify the gas hydrate reservoir, and the crossplot of μ and λ/μ could identify the lithology of the gas hydrate reservoir.

The Shuey-Radon transform

The traditional hyperbolic Radon transform (RT) decomposes seismic data into a sum of constant amplitude basis functions. This limits the performance of the transform when dealing with real data in which the reflection amplitudes include the amplitude variation with offset (AVO) variations. We adopted the Shuey-Radon transform as a combination of the RT and Shuey’s approximation of reflectivity to accurately model reflections including AVO effects. The new transform splits the seismic gather into three Radon panels: The first models the reflections at zero offset, and the other two panels add capability to model the AVO gradient and curvature. There are two main advantages of the Shuey-Radon transform over similar algorithms, which are based on a polynomial expansion of the AVO response. (1) It is able to model reflections more accurately. This leads to more focused coefficients in the transform domain and hence provides more accurate processing results. (2) Unlike polynomial-based approaches, the coefficients of the Shuey-Radon transform are directly connected to the classic AVO parameters (intercept, gradient, and curvature). Therefore, the resulting coefficients can further be used for interpretation purposes. The solution of the new transform is defined via an underdetermined linear system of equations. It is formulated as a sparsity-promoting optimization, and it is solved efficiently using an orthogonal matching pursuit algorithm. Applications to different numerical experiments indicate that the Shuey-Radon transform outperforms the polynomial and conventional RTs.

Anisotropic AVO: Implications for reservoir characterization

Routinely applied methods in seismic reservoir characterization such as forward modeling, wavelet extraction, amplitude-variation-with-offset (AVO) analysis, AVO inversion, and interpretation of seismic data usually assume that the earth can be modeled by a stack of isotropic layers. This assumption may cause significant problems where there are nonnegligible differences in the anisotropic parameters between the various lithologies that cause vertical profiles of VP/VSand the anisotropy parameters to be dissimilar. In this case, a significant mismatch between the seismic data and the isotropic synthetic seismogram AVO response will occur, making far-angle stack interpretation difficult. In some cases, the mismatch might be misinterpreted as a data quality issue. In an offshore Western Australia field, three lithofacies (volcanic rock, sandstone, and shale) need to be correctly identified for detailed reservoir characterization. Here, the AVO response of the actual seismic data is significantly affected by velocity anisotropy. Originally, it was thought that the far-angle stack could be used to detect volcanic rock in the field; however, after accounting for the velocity anisotropy effect, it was found that the far-angle stack enables us to identify sandstone. A proper understanding of the anisotropy effect allows the interpreter to use seismic data more effectively, which leads to a more robust estimation of the distribution of lithofacies in the target area.

On the effectiveness of using quantitative avo analysis in fluid and lithology discrimination in an offshore Niger Delta Field, Nigeria

Quantitative Amplitude Variation with Offset (AVO) analysis of “Jay” Field, offshore Niger Delta, was carried out with a view to properly discriminating fluid and lithology using near, mid and far offset seismic and well data. Seismic and well data were interpreted and analyzed. Synthetic seismogram was generated using density (r) and sonic logs. AVO modeling, seismic AVO attribute analysis and AVO inversion were carried out and the results from well log interpretation using 70-API gamma-ray cut-off, neutron-density over lay and resistivity logs revealed that the field consists of intercalation of sand and shale with typical deltaic depositional environment log signatures. Four identified sand reservoirs (a, b, c and d) with high resistivity values and negative separation in the neutron-density overlay suggested that the field was hydrocarbon bearing probably containing gas or condensate. Two sand reservoirs showed good rock physics results, 'Sand a' at 11,632 ft TVD with 18% porosity (ϕ), 0.25 water saturation (Sw), decreasing ratio of compressional wave velocity to shear wave velocity (Vp/Vs) and Poisson's ratio () relative to the background shale signified AVO response typical of a hydrocarbon bearing sand. 'Sand e' at 5,925 ft TVD, with 30% ϕ, Sw of 1, no change in V /V and relative to the background shale p S implied that an AVO response was unlikely. Gradient analysis result for the synthetic seismic at the top and base of the two sands agreed with Rutherford's classification scheme for class IV AVO for 'Sand a' and no AVO response for 'Sand e'. AVO attribute analysis and impedance inversion of the seismic volumes confirmed AVO result for the two sands. The study established that AVO technique could be effectively used for fluid and lithology discrimination in the “Jay” Field, Niger Delta.Keywords: Amplitude Variation with Offset (AVO), Seismic and Well data, Rock Physics, Reservoir Sands

Effect of VS predictors on amplitude variation with offset response

We have posed a question whether the differences between various [Formula: see text] predictors affect one of the ultimate goals of [Formula: see text] prediction, generating synthetic amplitude variation with offset (AVO) gathers to serve as a calibration tool for interpreting the seismic amplitude for rock properties and conditions. We address this question by evaluating examples in which we test several such predictors at an interface between two elastic layers, at pseudowells, and at a real well with poor-quality S-wave velocity data. The answer based on the examples presented is that no matter which [Formula: see text] predictor is used, the seismic responses at a reservoir are qualitatively identical. The choice of a [Formula: see text] predictor does not affect our ability (or inability) to forecast the presence of hydrocarbons from seismic data. We also find that the amplitude versus angle responses due to different predictors consistently vary along the same pattern, no matter which predictor is used. Because our analysis uses a “by-example” approach, the conclusions are not entirely general. However, the method of comparing the AVO responses due to different [Formula: see text] predictors discussed here is. Hence, in a site-specific situation, we recommend using several relevant predictors to ascertain whether the choice significantly affects the synthetic AVO response and if this response is consistent with veritable seismic data.

Source wavelet and local wave propagation effects on the amplitude-variation-with-offset response of thin-layer models: A physical modeling study

In target layers with thicknesses below the vertical seismic resolution as thin layers, the tuning effect/interference between the wave propagation modes may increase the challenge of doing amplitude-variation-with-offset (AVO) analysis because it is difficult to recover the primary PP amplitudes embedded in the data by further seismic data processing. Thus, we have investigated the importance of the primary PP reflections, locally P-SV converted waves, and internal multiple reflections in the amplitude response of two thin-layer seismic physical models. One model consists of a thin water layer embedded between two nylon plates, and another model with a thin acrylic layer surrounded by water. Numerical modeling using the reflectivity method was applied to analyze each wave propagation mode and the source waveform role in the experimental data. Before the experimental reflection data acquisition, we characterized two source and receiver piezoelectric transducer (PET) pairs: one with a circular plane face and the other with a semispherical face. We measured the source wavelet, its dominant frequency, and the PETs’ directivity pattern. Semispherical PETs were chosen to acquire common midpoint reflection data. Thereafter, a processing workflow was applied to remove linear events interfering with the target reflections and to correct amplitudes due to transmission losses, source/receiver directivity, and geometric spreading effects. Finally, we investigated the thin-layer targets near incidence angle amplitude and the AVO response. The results showed that the interference between the primary PP reflections and the locally converted shear waves may considerably affect the observed amplitude response. The source wavelet bandwidth appeared as a second-order effect, and the internal multiple reflections were practically negligible. These results suggested that in real data sets, it is important to investigate the wave propagation modes and source wavelet role in the amplitudes observed, before deciding the AVO analysis/inversion workflow that should be adopted.

Azimuthal AVO signatures of fractured poroelastic sandstone layers

Azimuthal P-wave amplitude variation with offset (AVO) offers a method for the characterisation of a naturally fractured system in a reservoir. This information is important for the analysis of fluid flow during production of, for example, oil, petroleum and natural gas. This paper provides a modelling scheme by incorporating the squirt-flow model for the prediction of velocity dispersion and attenuation with azimuthal reflectivity method for the calculation of frequency-dependent seismic responses. Azimuthal AVO responses from a fractured poroelastic sandstone layer encased within shale are investigated based on the proposed method. Azimuthal reflections are a combination of the dynamic information including the contrast in anisotropic properties, anisotropic propagation and attenuation within the layer, as well as tuning and interferences. Modelling results indicate that seismic responses from the top of the sandstone layer are dominated by reflection coefficients, and show azimuthal variations at far offset which is consistent with conventional azimuthal AVO theory. Reflections from the base, however, demonstrate complex azimuthal variations due to anisotropic propagation and attenuation of transmission waves within the layer. Tuning and interferences further complicate the azimuthal AVO responses for thinner layer thickness. The AVO responses of top reflections show no azimuthal variations for lower fluid mobility, while those of base reflections show visible and stable azimuthal variations even at near and moderate offsets for different fluid mobility. Results also reveal that it would be practical to investigate wavetrains reflected from the fractured layers that are regarded as integrated units, especially for thinner layers where reflections from the top and base are indistinguishable. In addition, near-offset stacked amplitudes of the reflected wavetrains show detectable azimuthal variations, which may offer an initial look at fracture orientations before AVO analysis.

Amplitude variation with offset analysis of time-lapse land seismic data in a gas field, Thrace Basin, Turkey

The Thrace Basin that is located in northwestern Turkey contains sandstone and carbonate reservoirs of Eocene and Oligocene age. Production and exploration activities are still underway. Mapping undrained sweet spots from seismic data is currently a challenge, so time lapse (4D) seismic is used to reduce the risk for new production and development drilling. We have evaluated the normalization and amplitude variation with offset (AVO) analysis of 3D-4D land seismic data in a gas producing field from which baseline and monitor surveys were acquired in 2002 and 2011, respectively. Through AVO analysis, intercept (A) and gradient (B) analysis was conducted, and fluid factor (FF) attribute maps were generated for the assessment of the remaining potential areas. Synthetic gathers were created for simulation of the AVO response, drained and undrained stages and compared with the corresponding 4D seismic data. The drainage of gas from the reservoir interval is evident from the difference maps between 2002 and 2011 seismic data. Both data sets were processed using an amplitude friendly processing sequence. This parallel processing was followed a mild data conditioning and crossequalization for reliable 4D interpretation. The 4D seismic data, especially land data, has low repeatability and requires conditioning to reduce the 4D noise. The 4D noise can be described as nonrepeatable noise, and any difference outside the reservoir zone is not related to production. A so-called crossequalization was applied to the base and the monitor data to bring out similarities so that they cancel out when differences of seismic data and its attributes indicated only the production results over the reservoir zones. As the available 4D data crossequalization software was implemented for stack data only, we created angle band stacks and crossequalized each angle band stack from the base and the monitor data cubes. Five angle band stacks from the base and the monitor prestack data cubes 0°–55° (0°–15°, 15°–25°, 25°–35°, 35°–45°, and 45°–55°) were crossequalized individually. The crossequalized angle band stacks were used in AVO analysis and AVO inversion to generate pore fill identifiers such as FF to map possible undrained zones after 10 years of production.

Determination of subsurface rock properties from AVO analysis in Konga oil field of the Niger Delta, Southeastern Nigeria

Amplitude variation with offset (AVO) analysis was carried out on Konga oil field, an onshore oil field in the Niger Delta, Southeastern Nigeria. The study consisted of forward modeling from rock parameters measured from well logs and AVO analysis of events on pre-stack time migrated 3D seismic gathers. Forward modeling predicted specific AVO behaviour of anomalous reservoir sands in the field. Density, compressional and shear wave velocity logs, combined with a wavelet extracted from recorded seismic gathers were used to generate synthetic seismic gathers and Gassmann fluid substitution models. These synthetics supported key observations made of the AVO response in the field data. AVO attributes (intercept and gradient) were derived from analysis of common depth point (CDP) gathers obtained from a 3D pre-stack seismic survey. The attributes were cross-plotted to establish trends against which anomalous amplitude behaviour were identified. Reflections related to shales and brine sands exhibit a relatively small range of orientations creating a dominant “background trend” against which anomalous events related to hydrocarbon-saturated reservoirs show clear deviations. On the basis of crossplot analyses (reflectivity versus offset/angle and intercept versus gradient) and modeled acoustic impedance, Class 1 type AVO anomalies observed are associated with non-hydrocarbon bearing clastic rocks that are most probably brine saturated in the field. Evidence from these results show that drilling in this field in search of hydrocarbon reservoirs poses a risky venture.

셰일 저류층에서 케로젠, GOR 변화에 따른 속도 변화 및 AVO 반응 분석

Recently, the studies about rock physics model (RPM) in shale reservoir are widely performed. In shale reservoir, the degree of the maturity can be estimated by kerogen and GOR (Gas-Oil Ratio). The researches on the rock physics model of shale reservoir with the amount of kerogen have been actively carried out but not with GOR. Thus, in this study, we analyzed the changes in seismic velocity and density, and AVO (Amplitude Variation with Offset) response depending on changes in GOR and the amount of kerogen. Since the shale consists of plate-like particles, it has vertical transverse isotropy (VTI). Therefore we estimated the seismic velocity and density by using Backus averaging method and analyzed AVO responses based on these estimated properties. The results of analysis showed that the changes in the velocity with the GOR variation are small but the velocity changes with the variation in kerogen amount are relatively larger. In case, GOR 180 (Litre/Litre) which is boundary between heavy oil and light oil, when volume fraction of kerogen increased from 5% to 35%, the P-wave velocity normal to the layering increased 51%. That is, it helps estimating maturity of kerogen through the velocity. Meanwhile, when rates of oil-gas mixture are large, the effect of GOR variation on the velocity change became larger. In case volume fraction of kerogen is 5%, the P-wave velocity normal to the layering was estimated in heavy oil (GOR 40) but in light oil (GOR 300). The AVO responses analysis showed class 4 regardless of the GOR and amount of kerogen because variation of poisson`s ratio is small. Therefore, shale reservoir has possibility to have class 4.

Feasibility of time-lapse AVO and AVOA analysis to monitor compaction-induced seismic anisotropy

Hydrocarbon reservoir production generally results in observable time-lapse physical property changes, such as velocity increases within a compacting reservoir. However, the physical property changes that lead to velocity changes can be difficult to isolate uniquely. Thus, integrated hydro-mechanical simulation, stress-sensitive rock physics models and time-lapse seismic modelling workflows can be employed to study the influence of velocity changes and induced seismic anisotropy due to reservoir compaction. We study the influence of reservoir compaction and compartmentalization on time-lapse seismic signatures for reflection amplitude variation with offset (AVO) and azimuth (AVOA). Specifically, the time-lapse AVO and AVOA responses are predicted for two models: a laterally homogeneous four-layer dipping model and a laterally heterogeneous graben structure reservoir model. Seismic reflection coefficients for different offsets and azimuths are calculated for compressional (P–P) and converted shear (P–S) waves using an anisotropic ray tracer as well as using approximate equations for AVO and AVOA. The simulations help assess the feasibility of using time-lapse AVO and AVOA signatures to monitor reservoir compartmentalization as well as evaluate induced stress anisotropy due to changes in the effective stress field. The results of this study indicate that time-lapse AVO and AVOA analysis can be applied as a potential means for qualitatively and semi-quantitatively linking azimuthal anisotropy changes caused by reservoir production to pressure/stress changes.