Amplitude Variation With Angle Research Articles

Novel approaches to uncertainty estimation in seismic subsurface characterization

Uncertainty estimation in subsurface characterization workflows is an important input to decision-making in earth science-related problems. We present three methods to characterize seismic-related uncertainty, each of which includes a real data case study. Two of these methods are designed to characterize depth uncertainty in positioning of migrated reflectors. Such estimates may be used in derisking well depth prognoses, analysis of well misties, and for estimating ranges on resource volume. The first method derives rapid and robust estimates of depth uncertainty around an existing velocity model using traditional velocity analysis to constrain the solution space while limiting a-priori constraints, consistent with a frequentist approach to uncertainty characterization. The second method characterizes depth uncertainty more rigorously in respect to the physics and prior information available by performing full-waveform inversion in a Bayesian framework. This method produces similar uncertainty estimates to the first in the case of simple velocity models but is more accurate where the overburden is complex; however, it requires significantly greater computational expense, thus limiting current practical applications. The third method is an amplitude variation with angle (AVA) inversion for reservoir properties designed to output uncertainty products for interpreters, utilizing the Bayesian framework and Zoeppritz equations to define the forward physics. Application to an offshore Egypt field demonstrates that it can generate reliable estimates of reservoir properties (e.g., lithofluid type or shale volume) including uncertainty, useful in various parts of subsurface characterization. These results also show that the method could provide improved point estimates of reservoir properties compared to conventional deterministic AVA inversion approaches. There is usually a trade-off between increasing the accuracy of subsurface characterization versus creating faster, less expensive, and more readily understood workflows for practitioners. We discuss how the relative importance of these competing factors should be considered within the context of how the outputs will be used.

Joint data-driven and physics-driven prestack amplitude-variation-with-angle elastic parameter inversion

Elastic parameters such as P-wave and S-wave velocity and density are of great significance for subsurface quantitative interpretation and reservoir prediction. Current prestack amplitude-variation-with-angle (AVA) inversion methods have been widely used in the industry to obtain subsurface elastic parameters. Conventional AVA inversion methods are theoretically based on a linearized amplitude-variation-with-offset model that formulates the relationship between prestack seismic reflection coefficients and the subsurface model of elastic parameters, which is called physical model-driven inversion. However, due to the linearized physical model, it is difficult to obtain high-accuracy and high-resolution inversion results using model-driven inversion when the incident angles are greater than 30°. In recent years, several neural network-based prestack AVA inversion methods, known as data-driven inversion, have been developed to address this issue. However, these methods typically require a large amount of labeled data for training networks, and there is no physical mechanism in the network training process. To solve this problem, a joint data-driven and physics-driven inversion of prestack AVA elastic parameters is proposed. Under the framework of semisupervised learning, a 2D convolutional neural network and a recurrent neural network are used to establish the mapping between several adjacent prestack AVA gathers and 1D elastic parameters in the time domain. The full Zoeppritz equation suitable for large incidence angles is used as a physical constraint for training the neural network. The loss functions of the network are constructed by combing well-log data and prestack AVA seismic data. This approach enables us to use fewer labeled data for training the network and increases the physical interpretability of the training process. To further improve the inversion results, the inverse distance weighted correlation coefficient of seismic data is applied to the loss function of seismic data and well-log data. Synthetic and field data examples demonstrate that the joint data-driven and physics-driven prestack AVA elastic parameter inversion improves accuracy and resolution compared with conventional model-driven inversion.

Rock physics and seismic reflectivity parameterization for amplitude-variation-with-angle inversion of low-maturity source rocks

Rock-physics inversion has been widely used in reservoir prediction. However, the prediction and evaluation of source rocks still predominantly rely on data-driven inversion methods. To directly incorporate the rock-physics relationship into the seismic inversion of source rocks, we first introduce a linearization approximation of the rock-physics model through the first-order approximation of the Taylor series. Model examples and well-logging tests substantiate the reliability of this linear approximation in establishing the connection between the elastic moduli and essential physical parameters (EPPs) of source rocks. Subsequently, we develop a novel equation for the P-wave reflection coefficient by combining the linear rock-physics relationship and Gray approximation. The newly developed reflectivity equation is a linear expression of differences in EPPs of source rocks. Model-simulating results demonstrate a favorable agreement between the novel P-wave reflectivity equation and the exact Zoeppritz equation until the incident angle reaches 60°. Furthermore, we explore the amplitude-variation-with-angle (AVA) effects of EPPs to validate their contributions meet the requirement of seismic inversion. Under the Bayesian scheme, we further develop an AVA inversion method, based on the novel P-wave reflectivity equation, to predict the EPPs of source rocks. Our AVA inversion method obtains satisfactory results under noise testing and demonstrates promising application potential in field examples. The predicted EPPs indicate a strong agreement with the actual well loggings. Comparative analysis against data-driven inversion results reveals that the EPPs predicted by our AVA inversion method possess enhanced rock-physics support and significance. Specifically, this study focuses on isotropic clay-rich source rocks with low maturity.

Seismic signatures of partial steam saturation in fractured geothermal reservoirs: Insights from poroelasticity

Detecting the presence of gaseous formation fluids, estimating the respective volumes, and characterizing their spatial distribution are important for a wide range of applications, notably for geothermal energy production. The ability to obtain such information from remote geophysical measurements constitutes a fundamental challenge, which needs to be overcome to address a wide range of problems, such as the estimation of the reservoir temperature and pressure conditions. With these motivations, we compute the body wave velocities of a fractured granitic geothermal reservoir formation with varying quantities of steam to analyze the seismic signatures in a partial saturation context. We use a poroelastic upscaling approach that accounts for mesoscale fluid pressure diffusion (FPD) effects induced by the seismic strain field, and, thus, describes the governing physical processes more accurately than standard representations. Changes in seismic velocities due to steam saturation are compared with changes associated with fracture density variations, as both are plausible results of pressure changes in geothermal reservoirs. We find that steam saturation has a significant impact on P-wave velocities while affecting S-wave velocities to a significantly lesser extent. This contrasting behavior allows us to discriminate between fracture density and steam saturation changes by means of P- and S-wave velocity ratio analyses. To evaluate the potential of seismic methods to provide this information, a canonical geothermal reservoir model is used to compute the Rayleigh wave velocity dispersion and seismic reflection amplitude variation with angle (AVA) curves. These studies reveal that AVA analyses allow differentiating changes in fracture density from changes in steam saturation. We also note that the Rayleigh-wave-based techniques are much less sensitive to steam content changes than to fracture density changes. Comparisons with elastic approaches indicate that including FPD effects through the use of a poroelastic model is crucial for the reliable detection and characterization of steam in fractured geothermal reservoirs.

AVA inversion for novel fluid indicator considering consolidation parameter

Abstract Geofluid identification from seismic data are crucial for understanding reservoir characteristics. However, fluid indicators based on elastic parameter combinations show strong ambiguity in terms of geofluid identification. Although the effective pore-fluid bulk modulus proves to be the superior fluid indicator in geofluid discrimination, it is limited to empirical models such as the critical porosity model. The consolidation parameter model can evaluate the consolidation and compaction of sediments and is widely used due to its better applicability. Therefore, a novel fluid indicator considering consolidation parameter is proposed and a boundary-constrained inversion strategy for geofluid identification is developed. First, the novel fluid indicator is defined based on the poroelasticity theory. Then, the linearized AVA (amplitude variation with angle) approximation equation related to the new fluid indicator is derived to directly link seismic data and properties of pore-filling materials. The model analysis verifies the accuracy of the derived approximation equation at moderate incident angles, which can be used for parameter prediction by pre-stack seismic inversion. Furthermore, the contribution of each attribute of the novel equation to the reflectivity is analyzed to validate the feasibility of new fluid indicator inversion. Finally, a boundary-constrained AVA pre-stack inversion method is presented to enhance the robustness of the inversion results of the model parameter. The reliability of the improved method is proved by accurate inversion results of synthetic seismic records. After determining the consolidation parameter using well-log data combined with BGT (Biot–Gassmann Theory), the field data further demonstrated that the proposed approach is accurate and effective.

Amplitude variation with angle analysis for deepening of a well planned as an infill opportunity: A case study of a mature oil field in the Niger Delta

A challenge in mature fields is the enhancement of field life to maximize investment. To meet this challenge, well-recovery optimization, robust geosteering for efficient well placement in terms of drainage and sweep, and the targeting of nearby undeveloped prospects or infill opportunities (IFOs) are routinely applied to prolong productivity. Quantitative interpretation schemes such as amplitude variation with angle (AVA) analysis and seismic inversion play important roles in targeting IFOs. We present the application of AVA analysis to an IFO located in a mature oil field in the Niger Delta. To mitigate a decline in oil production, an infill campaign was launched to identify IFOs in undrained areas of the field that could be combined as multilayer objectives for a well. One such IFO is the Zebra Miocene Z12 reservoir, an undeveloped reservoir that would serve as a secondary objective if a well proposed for drilling is deepened. The IFO was screened using an AVA characterization methodology that involved the integration of rock-physics analysis, comparative quality controls of the available seismic data vintages, AVA attribute analysis, and direct hydrocarbon indicator evaluation. Results from the AVA analysis indicated a high probability of finding hydrocarbons in the Z12 reservoir and thus resulted in a recommendation to extend the well into the secondary objective. The infill well was successful with results confirming hydrocarbons in the IFO, with oil production from the Z12 reservoir alone representing an increase of 17% in the field's production. The infill well has produced about 1.3 MMbbls of oil and 4.2 Bscf of gas from the Z12 IFO since startup three years ago. This has enhanced the life of the oil field, thus validating the robustness of AVA characterization in screening new IFOs.

Improving reservoir characterization and time-lapse seismic through joint inversion of PP- and PS-wave seismic data

Using synthetic and field data examples, we find that joint prestack amplitude variation with angle (AVA) inversion of PP- and PS-wave data can significantly improve estimation of P-impedance, S-impedance, and density. For reservoir characterization, improvements in these parameters can better identify reservoir rock and fluid properties. For reservoir monitoring, time-lapse (4D) changes in P-impedance, S-impedance, and density can lead to inversion of saturation and pressure changes. We see that in the joint inversion, 4D S-impedance is better estimated and not coupled to 4D P-impedance. These claims are first demonstrated on synthetic data, and then shown on an onshore unconventional play from Colorado and offshore 4-D-4C data set from the North Sea. Joint inversion of PP- and PS-wave data requires a higher level of care compared with PP-waves because the two wave modes need to be acquired, processed, and merged properly. This has diminished the use of converted waves in the past. However, modern acquisition and processing on land and offshore data make this technology quantitatively more accurate and realizable. As such, we also provide best practices for a successful project. We indicate that joint inversion can lead to a larger chance of success in placing exploration and development wells.

Ultralow-frequency amplitude variation with angle inversion of plane-wave primary reflection seismograms

An amplitude variation with angle (AVA) inversion method is presented for estimating density and velocities of a stratified elastic medium from reflection seismograms in the intercept time-horizontal slowness domain. The elastic medium parameters are assumed to vary continuously with depth. The seismograms are Green’s function precritical incidence primary P-wave reflections of time length [Formula: see text], assumed to obey differential equations of a model for elastic primary P-wave backscattering, similar to seismograms representing the first term in the well-known Bremmer series/Wentzel–Kramers–Brillouin–Jeffreys iterative solution model. A relation is found between the plane-wave Green’s function seismograms at each horizontal slowness and the medium properties in time. The Green’s function seismograms after normal-moveout correction are directly inverted for the medium parameters as a function of zero-offset traveltime. It is documented theoretically and verified numerically that the signal at the fundamental frequency [Formula: see text] must be present in the seismograms for the AVA method to provide the parameter trends of the elastic medium, implying that ultralow frequencies <1 Hz for [Formula: see text] s must be generated and recorded. Noise in the seismograms at ultralow frequencies is not considered because the theoretical AVA model does not handle microseisms that would be measured in real data. The main mathematical findings are illustrated by using simple model seismograms.

Joint PP, PS1, and PS2 AVA Inversion of HTI Media

Sedimentary strata formed by orientational vertical fractures are approximately equivalent to transversely isotropic media with a horizontal symmetry axis (HTI). Parameter inversion for the isotropic background and fracture parameters can provide valuable information for predicting fractured reservoirs. Following Bakulin’s modeling theory, we parameterized the HTI medium with the first- and second-order Lamé parameters of the isotropic background, host rock density, fracture density, and fracture azimuth. We calculated the fracture azimuth and separated split shear waves using the Alford rotation. Based on the exact reflection coefficients, we develop a joint P-to-P reflected wave (PP), PS1, and PS2 amplitude variation with angle (AVA) inversion method in the depth domain by using the second-order Levenberg–Marquardt (LM) algorithm to invert the remaining four parameters. Numerical model tests revealed that our method was more accurate compared to the traditional LM method and works for both weak/strong contrasts and anisotropy magnitudes. We used real data from the walkaway vertical seismic profiling (VSP) as an example to propose a set of strategies, thereby improving the practicality of our inversion method. To protect the fracture information contained in the wavefields, we adopted vector-feature-preserving data processing procedures to preprocess the field VSP data and separate PP, PS1, and PS2 reflections. We utilized P-wave first breaks to successfully discriminate and match these three wave modes from the same fractured formation in the depth domain; these were subsequently transformed to AVA gathers with ray tracing. We synthetically incorporated the time delays and layer velocities to build the initial models and to constrain the inversion process.

Overburden analysis and seal integrity study for CO2 sequestration in the North Sea (OASIS)

The Norwegian government recently launched a full-scale CCS project (Longship) in the North Sea that will store CO2 captured from Norway and other European countries. One of the proposed CO2 storage sites is “Smeaheia,” located east of the Troll oil and gas field, northern North Sea. Another neighboring prospective storage site, “Aurora” is located south of the Troll field. With a history of oil and gas exploration and production, Norway possesses all the necessary skills and technology to establish and run sub-surface CO2 storage. The geologic evaluation of an area for CO2 storage warrants detailed characterization of the reservoir, seal and overburden rocks. In the case of a hydrocarbon trap, the oil/gas accumulation manifests the caprock and the overburden integrity. However, in geological CO2 storage, a careful investigation of the reservoir, seal, and overburden rocks can avoid leakage risk. The Smeaheia area is bounded by a fault array separating the Troll field in the west and the Basement Complex in the east. The upper Jurassic Sognefjord Formation sandstone is the target CO2 storage reservoir in the Smeaheia area capped by Heather and Draupne Formations shales. In the Aurora prospect, the Johansen and Cook Formation sandstones of Early Jurassic age around the Troll field are potential storage units. The reservoir is enveloped by Amundsen shale, whereas in the southeast, where the Amundsen shale pinches out, the Drake Formation shale directly overlies the Johansen and Cook Formations. The OASIS project deals with various aspects of the seal and overburden rocks above a potential CO2 reservoir. This study aims to evaluate the viability of the seal and overburden rocks using seismic, well-log, and geological data to make sure the injected CO2 remains safely in the underground forever. The work investigated the seals overlying the potential CO2 reservoirs in the area using various techniques. This information will be used at the later stage of the OASIS project to generate and calibrate a field-scale 3D geomechanical model. To assess the integrity of seal rocks, the brittleness and ductility of shales are essential. If a rock is brittle, there is a risk of developing fractures once the pressure increases while injecting CO2. Conversely, a ductile rock preserves its integrity under high pressure. In the Aurora area, the Amundsen and Drake Formation shales’ brittleness relatively increases with depth and temperature; however, our analysis showed a low possibility of fracturing. The Johansen Formation reservoir sandstone quality is improving towards the south at shallower depths within the Aurora area. According to the rock physics analysis, some calcium-rich, thin baffles are found. In the Johansen Formation reservoir sandstone, at deeper levels, the material binding the sand grains is quartz cement, which decreases where the clay/shale percentage is relatively high. The presence of cement might reduce the void spaces between the sand grains, resulting in a reduction of space for CO2 storage. Using a 3D seismic GN1101 in the Smeaheia area, we decomposed the full frequency spectrum to 20 Hz, 40Hz, and 60 Hz frequency cubes. Draping horizons from the Lower Jurassic Drake Formation up to the seafloor on the RGB blend of the three frequencies enabled identifying various sedimentary features within the window below the respective surface. We also generated a dip-steered “Similarity” cube to identify faults intersecting a formation surface and detect associated fractured areas. Based on the seismic data, formations below Quaternary dip towards the west to south-west with several faults associated with the north-south running Vette fault system close to the western edge of the area. The attributes indicate a sedimentary environment ranging from coastal, shallow marine to open marine within the analyzed interval. Weak fault traces are identifiable on the base Quaternary surface; furthermore, we identified several pockmarks on the Draupne Formation sealing layer and the seafloor. The discontinuities/ faults do not extend from the reservoir to the seafloor. However, one linear impression was observed on the seafloor on the low-frequency spectrum, indicating possible palaeo-leakage of hydrocarbon gas from the underlying strata. The risk of CO2 leakage through the pockmarks and the said fault needs further investigation, though these features are not present above the potential storage structures. The Amplitude Variation with Angle (AVA) technique yields valuable information about the reservoir fluids. The AVA models confirmed that the changes in CO2 saturation and conversion to gaseous state within the reservoir are possible to monitor remotely using a time-lapse seismic or 4D survey. We also extracted mechanical properties from the Smeaheia 3D seismic using pre-stack Inversion. These property cubes will be used for making a geomechanical model that will be calibrated using the information obtained by the methods mentioned above.

Azimuthal P-P prestack amplitudes in the presence of oil-filled aligned porosity (fracture porosity)

A 3D P-P high-fold full-azimuth full-offset reflection survey was acquired and processed to characterize a naturally fractured carbonate reservoir. The reservoir is a thick carbonate, which will flow commercial oil with a sufficient fracture network. Extensive calibration data include (1) a horizontal borehole’s resistivity image log, (2) the first 24 months cumulative oil produced, by stage, as known from chemical frac tracer data, (3) pre- and postfrac job instantaneous shut-in pressures, (4) microseismic, and (5) wireline log data. We used the cumulative oil production to document the spatially varying amount of aligned vertical porosity (aligned compliance or fracture porosity) connected to the stage borehole location. The stages of high oil production exhibited, for the fracture-perpendicular azimuth, the more positive amplitude variation with angle (AVA) gradients, and dimmer near-angle (6°–15° angles of incidence) amplitudes, compared to the fracture-parallel azimuth. The azimuthal variation of the AVA gradient fit the cos 2θ curve well, indicating the presence of one set of vertical aligned fractures dominating the azimuthal amplitude signature. In a similar fashion, the azimuthal variation of the mathematical intercept, physically the near-angle amplitudes, also fit the cos 2θ curve well. We have constructed crossplots of the azimuthal near-angle amplitude versus the AVA gradient on a bin-by-bin basis: we observed a straight line at bins with elevated oil production (elevated fracture density). A straight line crossplot of the (AVA gradient, mathematical intercept) is the signature of change of the (sensed) porosity, as long as the lithology and pore fluid are held constant. In accord with industry knowledge, we found that porosity affects the P impedance and thus the near-angle amplitudes: the aligned porosity yields azimuthal P impedance (measured at the 6°–15° angles of incidence). Legacy high-fold 3D P-P surveys rich in the 6°–20° angles of incidence should be considered for reprocessing and reinterpretation using these techniques.

Characterization of fluvio-deltaic gas reservoirs through AVA deterministic, stochastic, and wave-equation-based seismic inversion: A case study from the Carnarvon Basin, Western Australia

Multiple state-of-the-art inversion methods have been implemented to integrate 3D seismic amplitude data, well logs, geologic information, and spatial variability to produce models of the subsurface. Amplitude variation with angle (AVA) deterministic, stochastic, and wave-equation-based amplitude variation with offset (WEB-AVO) inversion algorithms are used to describe Intra-Triassic Mungaroo gas reservoirs located in the Carnarvon Basin, Western Australia. The interpretation of inverted elastic properties in terms of lithology- and fluid-sensitive attributes from AVA deterministic inversion provides quantitative information about the geomorphology of fluvio-deltaic sediments as well as the delineation of gas reservoirs. AVA stochastic inversion delivers higher resolution realizations than those obtained from standard deterministic methods and allows for uncertainty analysis. Additionally, the cosimulation of petrophysical parameters from elastic properties provides precise 3D models of reservoir properties, such as volume of shale and water saturation, which can be used as part of the static model building process. Internal multiple scattering, transmission effects, and mode conversion (considered as noise in conventional linear inversion) become useful signals in WEB-AVO inversion. WEB-AVO compressibility shows increased sensitivity to residual/live gas discrimination compared to fluid-sensitive attributes obtained with conventional inversions.

A stable and effective strategy for angle gather extraction from reverse time migration using traveltime gradient

ABSTRACTThe generation of angle-domain common imaging gathers (ADCIGs) from reverse time migration (RTM) is essential for velocity updates, migration quality control and amplitude variation with angle (AVA) inversion. However, computational stability and efficiency challenges remain with ADCIGs extracted from RTM. Here, we develop a stable and effective strategy to produce ADCIGs during RTM based on the traveltime gradient. The first arrival traveltime is calculated efficiently using the dynamic programming scheme, and the source-side propagating direction of the local plane-wave can be obtained using the traveltime field gradient. Compared with propagation directions calculated using the local slowness analysis method, the traveltime gradient can also provide stable and accurate source-side directions. Benefitting from the migrated images, we can collect normal direction information for the reflector from the stacked images effectively using the omnidirectional plane-wave destruction (OPWD) method. Construction of subsurface scattering angles is straightforward via combination of the source-side propagation and reflector normal directions. Subsequently, we apply an effective imaging condition based on the excitation criterion in the angle domain to generate ADCIGs. Thanks to conversion from a wavefield-based to a traveltime-based calculation, the proposed method provides more stable and reliable wave propagation directions in complicated areas compared with the Poynting vector (PV) method which is based on the full wavefield. Because traveltime can be calculated efficiently beforehand, the proposed method can be adapted economically to the conventional RTM imaging frame, which reveals significant implementation potential for practical seismic exploration. We demonstrate the stability and effectiveness of this approach for both synthetic and field data.

Imperialist competitive algorithm optimization method for nonlinear amplitude variation with angle inversion

Amplitude variation with angle (AVA) inversion is one of the most effective techniques in hydrocarbon exploration and estimating subsurface petrophysical properties. The inversion problem as a nonlinear, multiparameter, and multimodal optimization problem is conventionally solved through linearized optimization methods, but with the cost of smoothing important geologic interfaces. In addition, the results obtained by these methods are more possible to be trapped in a local minimum, while global-optimization methods can produce more accurate results and preserve the interfaces of geologic structures. A Bayesian framework is used to formulate the AVA inversion problem, which incorporates a novel prior constraint included by two regularization functions, one for sparsity of the coefficients as well as recovering discontinuities and another one for enhancing the lateral continuity. The imperialist competitive algorithm as an efficient evolutionary algorithm is then used to optimize the resulted objective function, to invert the P-and S-wave velocities as well as the density. We compare our algorithm with a commonly used Bayesian linearized inversion method by applying both methods on synthetic data and real seismic data from Gulf of Mexico. Our results reveal the practicability and stability of the presented method for the AVA inversion problem.

Pre-stack AVA Inversion by Using Propagator Matrix Forward Modeling

Most existing amplitude variation with angle (AVA) inversions are based on the exact Zoeppritz equation or its approximations. These modeling methods, which are ray-tracing-based and describe P-wave primary reflections only, lead to exacting requirements for pre-processing of the input data. Current processing is inadequate to satisfy these demands, especially for removing the effects of transmission losses, P-wave multiples and various converted-wave modes. By using input data with processing errors, inversion results of primary-only methods are predictably not accurate enough. The propagator matrix (PM), like the reflectivity method, uses an analytical solution to the wave equation and considers full-wave propagation effects in horizontal or nearly horizontal multilayered earth models. The numerical examples verify that a PM can effectively estimate transmission losses, multi-reflections and the comprehensive responses of thin interbedded layers, and also has higher reflection sensitivities to P-wave and S-wave velocity and density, as compared with ray-tracing-based AVA modelling. A pre-stack AVA three-parameter inversion by using a PM as the forward engine is proposed. Following a Bayesian approach, the inversion is stabilized by including the correlation of P-wave velocity, S-wave velocity and density. For inversion accuracy, the limited-memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) optimization method is used to solve the augmented function, and the generalized cross-validation (GCV) criterion (Huang et al. in J Geophys Eng 14(1):100–112, 2017) is introduced to adaptively acquire the regularization parameter. Theoretical model inversion analysis shows that the proposed inversion can make use of transmission losses, P-wave multiples and converted wave modes, which not only cost-effectively simplifies the pre-processing, but also generates reasonable inverted results for multilayered conditions. The proposed inversion is then applied to a set of real data, and a comparison with Zoeppritz equation-based inversion demonstrates that PM inversion is clearly superior to Zoeppritz equation-based inversion in terms of stability and accuracy.

Active seismic studies in valley glacier settings: strategies and limitations

ABSTRACTSubglacial tills play an important role in glacier dynamics but are difficult to characterize in situ. Amplitude Variation with Angle (AVA) analysis of seismic reflection data can distinguish between stiff tills and deformable tills. However, AVA analysis in mountain glacier environments can be problematic: reflections can be obscured by Rayleigh wave energy scattered from crevasses, and complex basal topography can impede the location of reflection points in 2-D acquisitions. We use a forward model to produce challenging synthetic seismic records in order to test the efficacy of AVA in crevassed and geometrically complex environments. We find that we can distinguish subglacial till types in moderately crevassed environments, where ‘moderate’ depends on crevasse spacing and orientation. The forward model serves as a planning tool, as it can predict AVA success or failure based on characteristics of the study glacier. Applying lessons from the forward model, we perform AVA on a seismic dataset collected from Taku Glacier in Southeast Alaska in March 2016. Taku Glacier is a valley glacier thought to overlay thick sediment deposits. A near-offset polarity reversal confirms that the tills are deformable.

Two-stage and single-stage seismic-petrophysical inversions applied in the Nile Delta

We discuss two Bayesian seismic-petrophysical inversion techniques, the two-stage and single-stage approach, which estimate petrophysical properties from prestack seismic data. Both approaches are developed considering linear approximations and are applied for reservoir appraisal studies in the Nile Delta. The two-stage approach first uses an amplitude-variation-with-angle (AVA) inversion to infer P-wave velocity, S-wave velocity, and density. Then, a linear empirical rock-physics model, properly calibrated for the investigated area, is used to transform the estimated elastic parameters into the petrophysical properties of interest under the assumption of Gaussian mixture distributed petrophysical properties. The single-stage approach uses the linear rock-physics model to rewrite the time-continuous P-wave reflectivity equation as a function of the petrophysical contrasts instead of the elastic constants. This reformulation, together with the assumption of a Gaussian prior model, allows us to directly derive (in a single-stage inversion) the petrophysical properties from AVA data. Despite the differences in the forward-model parameterization and in the assumed a priori distribution for the petrophysical properties, the two inversion methods yield comparable predictions that are consistent with borehole data. For the investigated zone, this work demonstrates that, although neglecting the facies-dependent behavior of petrophysical properties, the a priori Gaussian assumption for the petrophysical properties can provide reliable predictions with a very limited computational effort. In addition, the good match between predicted and logged properties proves the suitability of the linear rock-physics model for reservoir characterization in the Nile Delta.

Reservoir fluid determination from angle stacked seismic volumes in ‘Jay’ field, Niger Delta, Nigeria

The study was carried out to investigate the dissimilar seismic amplitude responses observed in sandstone reservoirs with the same fluid saturation. This challenge now informed the analysis of different amplitude responses from the ‘Jay’ Field in order to verify the reservoirs fluids around and away from well location based on the integration of Amplitude Variation with Angle (AVA) and seismic inversions. The well log data provided were used to identify hydrocarbon bearing zones and Poisson Ratio analysis. Anomalies from the AVA analysis were investigated using the elastic impedance inversion of the near and far volumes. Crossplots of Lambda-Mu-Rho inversion were produced to relate reservoir incompressibility and rigidity modulus for lithology and fluid determination. Sand E exhibited amplitude increase with angles at well point and also away from well location (red triangle). The approximate elastic impedances of the inverted seismics are almost similar to the log estimates, an indication of good correlation. Integration of incompressibility (Lambda-Rho) and rigidity (Mu-Rho) modulus analyses reveals the presence of gas saturation in reservoir Sand G because low Lambda-Rho coincides with high Mu-Rho from both log estimates and inverted seismics. In the case of Sand D, high Lambda-Rho coincides with high Mu-Rho because it is oil saturated. This study has helped to differentiate the fluids in Sands D and G despite having similar AVA responses. The methods adopted in this work can be useful in hydrocarbon detection from seismic data in fields with similar geological setting.Keywords: Amplitude Variation with Angles; Elastic Impedance; Near and Far offsets; Full stack seismic volume

Identification of morphologies of gas hydrate distribution based on amplitude variation with angle analysis

There are two basic distribution morphologies of gas hydrates in nature: pore filling and fracture filling. Identification of gas hydrate morphologies is essential for improved resource evaluation and exploitation. Improper exploitation may cause seafloor instability, lead to atmospheric venting, and exacerbate the greenhouse effect. To identify gas hydrate morphologies, we combine rock-physics modeling and amplitude variation with angle (AVA) analysis to study the theoretical AVA patterns of the bottom simulating reflector (BSR) beneath the pore-filling and fracture-filling gas hydrate bearing sediments (GHBS), respectively. The theoretical results indicate completely different AVA patterns between these two morphologies. The AVA of the BSR beneath the pore-filling GHBS shows a class III anomaly with negative intercept and gradient. However, the AVA of the BSR beneath the fracture-filling GHBS exhibits a class IV anomaly with a negative intercept and positive gradient. In addition, the theoretical AVA intercept and gradient are affected by the fracture orientation, manifesting an anisotropic signature varying with the fracture dip and azimuth. The processed prestack data at well sites 08 and 16 in the northern South China Sea are selected for testing our method. The AVA analysis of the actual BSRs beneath the pore-filling and fracture-filling GHBS at these sites shows class III and IV responses, respectively, in agreement with our theoretical results. The gas hydrate saturations are also estimated by comparing the theoretical AVA with the actual AVA patterns. The estimations at site 08 are close to those estimated from the pore-water freshening.

PP- and Split PS-Wave AVA Responses of Fractured Shale

With seismic exploration advancing to the deep Earth, the seismic response of fractured strata has currently become a hot research topic. However, characteristics of the amplitude variation with angle (AVA) of saturated fractured shale still remain unclear. Furthermore, the direct relationships between the AVA response and fracture system parameters have not received much attention. This study is aimed at analyzing the effect of fracture density on AVA responses of fractured shale. For this purpose, we propose a method for modeling saturated fractured shale and analyzing AVA responses of PP- and split PS-waves. First, we introduce Gurevich’s fluid theory into the fractured-shale modeling and establish the relationship between Thomsen’s weak anisotropy parameters and fracture density and fluid properties. Second, we perform forward simulation considering an isotropic overburden and a fractured stratum. The results show that differences in AVA responses of the fractured-shale model and the isotropic model increase with increasing fracture densities. At small to intermediate incidence angles, the reflection coefficients of split PS-waves increase, whereas those of PP-wave decrease. The reflection coefficients of the two models differ dramatically at incidence angles larger than 55°. Furthermore, when the fracture density is large, polarity reversal occurs only in PS2-wave AVA gathers.