Elastic Impedance Research Articles

Seismic transmission operator reciprocity – I: a direct derivation showing the role of elastic impedance operator symmetry

Seismic transmission operator reciprocity – I: a direct derivation showing the role of elastic impedance operator symmetry

Sea Lion Field, North Falkland Basin: seismic inversion and quantitative interpretation

Extensive use has been made of seismic-derived quantitative interpretation for mapping and predicting reservoir properties in the Sea Lion Field, North Falkland Basin. The Sea Lion sands are acoustically hard compared to the encasing shales, with fairly constant rock properties. The fans are typically 20–60 m in thickness and are predominantly seismically tuned events. Detection of hydrocarbon fluid effects from seismic data has proved elusive to date. Extended elastic impedance (EEI) was selected as the appropriate seismic analysis tool. Almost all sands are visible on the full-stack seismic data. Coloured inversion of an EEI volume with a rotation angle ( χ ) of −70° (henceforth shown as EEI(−70)) was found to be an optimal sand predictor and is primarily sensitive to the shale volume of the sands. This EEI χ angle also allows detection of sand that is not observed on the full-stack seismic. The EEI(−70) coloured inversion data were also used to estimate net sand thickness and the net-to-gross maps of the fans. Subsequently, a new algorithm termed DT-AMP was used to apply seismic amplitude detuning to the full three-dimensional (3D) seismic volume. This has proved useful in the evaluation of new exploration targets beyond the Sea Lion Field area. A sand classification was performed using multiple EEI attributes, including lithology and fluid cubes. This indicates that there are differences in the amplitude v. offset (AVO) response across the main Sea Lion fan complex. Pre-stack simultaneous inversion was also performed using both deterministic and stochastic schemes. A three-term inversion was tested but density estimation was considered to be unreliable. Seismic data were tested at several stages to constrain the static reservoir model, using coloured, deterministic and stochastic inversion methods. The final static model incorporated a set of scenarios using net-to-gross maps inferred from the quantitative analysis of the EEI(−70) data.

Exact elastic impedance tensor for isotropic media

The existing expressions of elastic impedance, as the generalized form of acoustic impedance, represent the resistance of subsurface media to seismic waves of non-normal incidence, and thus include information on the shear-wave velocity. In this sense, conventional elastic impedance is an attribute of the seismic reflection and not an intrinsic physical property of the subsurface media. The derivation of these expressions shares the approximations made for reflectivity, such as weak impedance contrast andisotropic or weakly anisotropic media, which limits the accuracy of reflectivity reconstruction and seismic inversion. In this paper, we derive exact elastic impedance tensors of seismic P- and S-waves for isotropic media based on the stress-velocity law. Each componentof the impedance tensor represents a unique mechanical property of the medium. Approximations of P-wave elastic impedance tensor components are discussed for seismic inversion and interpretation. Application to synthetic data and real data shows the accuracy and robust interpretation capability of the derived elastic impedance in lithology characterizations.

확장 탄성 임피던스 역산을 이용한 저류층 물성 예측

확장 탄성 임피던스(extended elastic impedance, EEI)는 입사각에 따른 음향 임피던스(acoustic impedance, AI) 를 일반화한 탄성 임피던스(elastic impedance, EI)를 확장한 개념으로서 다양한 저류암 물성과 대비가 가능한 것으로 알려져 있다. 하지만 EEI 역산을 적용하여 예측한 저류암적 물성이 실제 물성을 얼마나 정확히 예측하는지를 검증한 사례는 거의 없다. 본 연구에서는 EEI 역산 기법을 이용하여 미국 와이오밍주 Teapot Dome 유전의 주요 저류층 중 하나인 Second Wall Creek 사암층의 P파속도(<TEX>$V_p$</TEX>), S파속도(<TEX>$V_s$</TEX>), P파속도-S파속도 비(<TEX>$V_p/V_s$</TEX>), 포아송비(Poisson's ratio)와 같은 속도 물성들을 유추하고 실제 물리검층 자료와 비교하여 EEI 역산 기법의 정확도를 검증했다. 사용된 자료는 Teapot Dome 유전 남부의 3차원 공심점 모음 자료(CDP gather)와 많은 시추공에서 선택된 4개의 시추공 자료이다. <TEX>$V_s$</TEX> 검층자료는 경험식을 통해 <TEX>$V_p$</TEX> 검층자료로부터 계산되었다. 4개의 속도 물성 EEI 예측 %에러는 한 시추공에서의 포아송비를 제외하면 약 5%를 넘지 않는다. 그러나 속도로부터 직접적으로 계산되지 않는 공극률, 감마선 검층값, 밀도와 같은 물성들은 시추공에서의 EEI 역산 분석 결과가 만족스럽지 못하여 전체 자료에 EEI 역산을 적용할 수 없었다. 따라서 속도 물성의 경우 EEI 역산을 적용할 수 있지만 속도로부터 직접 계산이 되지 않는 물성의 경우는 EEI 역산 적용에 신중해야 할 것으로 판단된다. Extended elastic impedance (EEI) is an extension of elastic impedance (EI) which is a generalization of acoustic impedance (AI) for nonzero angles of incidence and can be tuned to be proportional to reservoir properties. In this study, we evaluated EEI inversion by estimating the P-(<TEX>$V_p$</TEX>) and S-wave velocities (<TEX>$V_s$</TEX>), P-wave to S-wave velocity ratio (<TEX>$V_p/V_s$</TEX>), and Poisson's ratio of the Second Wall Creek Sand of the Teapot Dome field, Wyoming, USA. We also applied the EEI inversion technique to estimate porosity, gamma-ray values, and density of the Second Wall Creek Sand. Data used in the study include 3-D pre-stack seismic data from the southern part of the field and four wells, selected from a large well database. The <TEX>$V_s$</TEX> logs at the wells were constructed from the <TEX>$V_p$</TEX> logs using the empirical relationships. The percent prediction errors for the four velocity properties are less than about 5% except for Poisson's ratio at one well, supporting that the EEI inversion can be used in the prediction of rock properties. However, the results from the EEI inversion analysis of porosity, gamma-ray values, and density at the wells were unsatisfactory and thus these properties, which are not directly computed from velocities, may not be suitable for EEI inversion.

Phoxonic Hybrid Superlattice.

We studied experimentally and theoretically the direction-dependent elastic and electromagnetic wave propagation in a supported film of hybrid PMMA (poly[methyl-methacrylate])-TiO2 superlattice (SL). In the direction normal to the layers, this one-dimensional periodic structure opens propagation band gaps for both hypersonic (GHz) phonons and near-UV photons. The high mismatch of elastic and optical impedance results in a large dual phoxonic band gap. The presence of defects inherent to the spin-coating fabrication technique is sensitively manifested in the band gap region. Utilizing Brillouin light scattering, phonon propagation along the layers was observed to be distinctly different from propagation normal to them and can, under certain conditions (SL thickness and substrate elasticity), reveal the nanomechanical properties of the constituent layers. Besides the first realization of unidirectional phoxonic behavior, hybrid (soft-hard) periodic materials are a promising simple platform for opto-acoustic interactions and applications such as filters and Bragg mirrors.

Quantitative seismic interpretations to detect biogenic gas accumulations: a case study from Qaidam Basin, China

Abstract Quantitative seismic interpretation can be used to identify lithology and detect petroleum accumulations by integrating rock properties and attributes derived from advanced seismic inversion methods with existing petrophysical data and geological knowledge. We use quantitative seismic interpretations for detection of shallow biogenic gas accumulations in the Qaidam Basin, China, employing an integrated workflow that incorporates petrophysical data, seismic attribute analysis, Constrained Simultaneous Inversion (C-SI) and Bayesian-based Support Vector Machine (B-SVM) inference. Previous petrophysical studies have shown that it is challenging to effectively identify gas-bearing intervals using parameters such as impedance, Poisson’s ratio and porosity, because the reservoir sediments are unconsolidated and at shallow depths. The resistivity well-log response remains as an effective tool for estimating gas saturation and identifying gas-bearing intervals. In this study, we propose the use of the petroleum pore-volume, which is defined as the product of reservoir porosity and gas saturation, to detect biogenic gas accumulations seismically. Rock properties inferred from seismic inversion, such as compressional velocity (Vp), shear velocity (Vs) and density, cannot be used directly for petroleum pore-volume estimation. Therefore, we employ a Bayesian-based support vector machine approach to cross-link well-log properties, seismic AVO attributes and seismic rock properties to quantitatively predict petroleum pore-volume in 2D and 3D seismic dataset. Because seismic information is crucial to statistical inference, we propose C-SI to infer the Vp, Vs and density from seismic elastic impedance gathers, which can be generated from seismic gathers using a traditional recursive seismic inversion method. The C-SI procedures use the Interior-Point algorithm to optimize and solve elastic impedance equations. The Interior-Point method is a popular method for handling constrained non-convex, non-linear optimization problems that involve simultaneously inverting the seismic properties with thousands of seismic samples. This case study indicates that the integrated study workflow is useful for quantitatively predicting petroleum pore-volume, especially in the depth-domain, and that it is an excellent potential indicator for biogenic gas accumulations in complicated geological settings.

Application of elastic impedance: A case study from Mahanadi Basin, India

Over the last decade, seismic inversion has acquired the status of being a routine interpretation step during exploration as well as development of fields. For detailed reservoir characterization, prestack inversion is desirable; however, poststack inversion is a reasonably effective tool. The inversion starts with calibration of the well with seismic data. The synthetic seismogram is tied with stacked seismic data on the basic premise that the seismic data (full stack) mimics the zero-offset data and therefore should match with the zero-offset synthetic seismogram. Generally, a good match is obtained. However, during the course of many inversion exercises, it is observed that the synthetic-to-seismic match is not good in parts of the drilled interval. There could be many reasons for this partial mismatch. One of the important reasons is that the well data represent one-dimensional data, whereas the seismic data are stacked over an angle range. In other words, the well data are equivalent to zero-offset data, whereas seismic is not. The poor calibration at the well location leads to lack of confidence in inversion results. The possible solution, such as simultaneous or full-waveform inversion, involves a lot of computation time and hardware requirements. An alternative approach is introduced which uses elastic impedance instead of normal P-impedance for synthetic match and inversion of stacked data. The synthetic seismic generated from elastic impedance shows an improved match with seismic data. The approach is quick, reliable, easy, and not heavy on computational resources. The result is inverted volumes with better hydrocarbon delineation and characterization ability.

Prediction of deep-buried gas carbonate reservoir by combining prestack seismic-driven elastic properties with rock physics in Sichuan Basin, southwestern China

The prediction of seismic reservoirs in marine carbonate areas in the Sichuan Basin, southwestern China, is very challenging because the target zone is deeply buried (more than 6 km), with multiphase tectonic movements, complex diagenesis, and low porosity, and the incident angle of the seismic data is finite. We developed reliable hydrocarbon indicators of a marine carbonate deposit based on prestack elastic impedance (EI) and well observations. Although the hydrocarbon indicators can be calculated from elastic parameters, the inversion for EI-driven elastic attributes is usually unstable. To constrain the inversion process, we discovered a new strategy to recover the elastic properties from EIs within a Bayesian framework (called Bayesian elastic parameter inversion from elastic impedance). We applied the strategy to a carbonate reef identified at the center of a study line based on the geologic context and the seismic reflection patterns. We then used rock-physics analyses to classify the lithologies and the reservoir at a well location. Rock-physics modeling quantified the hydrocarbon sensitivity of the elastic attributes. Fluid substitution was used to investigate the effects of pore fluids on the elastic properties. A comparison of two synthetic amplitude-versus-angle responses (for gas and brine saturation) with real seismic data showed that the reservoir was gas charged. Using well-based crossplot analyses, reliable direct hydrocarbon indicators can be constructed for a deeply buried gas reservoir and were effective for interpretation in an area of marine carbonates in the Sichuan Basin.

Deepwater reservoir heterogeneity delineation using rock physics and extended elastic impedance inversion: Nile Delta case study

Deepwater channel reservoirs in the Nile Delta are delineated using extended elastic impedance inversion (EEI). We used the following workflow: seismic spectral blueing, rock physics and amplitude variation with offset modeling, seismic EEI and interpretation of the inverted cubes in terms of geologic facies, net-to-gross ratio, and static connectivity among depositional geobodies. Three subenvironments within the targeted reservoir interval were recognized using a combination of shale volume and [Formula: see text]-inverted cubes. These were used to generate 3D geobodies and a net-pay thickness map that were used in turn to calculate reservoir volumetrics. The results from the workflow matched well logs and could thus be used to investigate the potential of nearby prospects that have the same geologic settings.

Fracture filling fluids identification using azimuthally elastic impedance based on rock physics

Abstract Fracture filling fluids identification is an important aspect of fractured reservoirs description. It is well known that fracture weaknesses parameters (the normal and tangential weaknesses) are closely related to fracture parameters (fracture density, fracture aspect ratio and fracture fillings). Hence, the fracture filling fluids can be identified after the fracture weaknesses parameters being obtained. The efficient method, which is presented to estimate the fracture weaknesses parameters in this paper, is azimuthally elastic impedance (EI) inversion. We first derive a new azimuthal EI equation which contains fracture weaknesses parameters. Using the formula, we propose a method of seismic inversion for elastic parameters (P-wave and S-wave impedances) and fracture weaknesses parameters. The fluid factor, which is introduced to identify the fluids in fractures, can be estimated after the calculation of elastic and fracture weaknesses parameters. Tests on real data show that the method is more stable and reasonable by reducing the uncertainty for the estimation of elastic parameters and fracture weaknesses parameters. The inverted results are in good agreement with the results of well log data.

Prestack seismic amplitude analysis: An integrated overview

In this tutorial, I present an overview of the techniques that are in use for prestack seismic amplitude analysis, current and historical. I show that these techniques can be classified as being based on the computation and analysis of either some type of seismic reflection coefficient series or seismic impedance. Those techniques that are based on the seismic reflection coefficient series, or seismic reflectivity for short, are called amplitude variation with offset methods, and those that are based on the seismic impedance are referred to as prestack amplitude inversion methods. Seismic reflectivity methods include: near and far trace stacking, intercept versus gradient analysis, and the fluid factor analysis. Seismic impedance methods include: independent and simultaneous P and S-impedance inversion, lambda-mu-rho analysis, Poisson impedance inversion, elastic impedance, and extended elastic impedance inversion. The objective of this tutorial is thus to make sense of all of these methods and show how they are interrelated. The techniques will be illustrated using a 2D seismic example over a gas sand reservoir from Alberta. Although I will largely focus on isotropic methods, the last part of the tutorial will extend the analysis to anisotropic reservoirs.

From ocean-bottom cable seismic to porosity volume: A prestack PP and PS analysis of a turbidite reservoir, deepwater Campos Basin, Brazil

The Campos Basin is the best known and most productive of the Brazilian coastal basins. Turbidites are, by far, the main hydrocarbon-bearing reservoirs in the Campos Basin. Using a 4C ocean-bottom cable seismic survey, we set out to improve the reservoir characterization in a deepwater turbidite field in the Campos Basin. To achieve our goal, prestack angle gathers were derived and PP and PS inversion were performed. The inversion was used as an input to predict the petrophysical properties of the reservoir. Converting seismic reflection amplitudes into impedance profiles not only maximizes vertical resolution but also minimizes tuning effects. Mapping the porosity is extremely important in the development of hydrocarbon reservoirs. Combining seismic attributes derived from the PP and PS multicomponent data and porosity logs, we used linear multiregression and neural networking to predict porosity between the seismic attributes and porosity logs at the well locations. After estimating porosity in the well locations, those relationships were applied to the seismic attributes to generate a 3D porosity volume. The porosity volume highlighted the best reservoir facies in the reservoir. The integration of elastic impedance, shear impedance, and porosity improved the reservoir characterization.

Estimation of gas hydrate saturation in the Ulleung basin using seismic attributes and a neural network

Among the unconventional natural resources, gas hydrates have recently received much attention as a promising potential energy source. To develop gas hydrates, their distribution and saturation should be estimated, preferentially at the initial stage of development. In most cases, the distribution of gas hydrates can be identified by using seismic indicators including a bottom simulating reflector (BSR) and chimney/column structures, which indirectly determine the presence of gas hydrate. However, these indicators can be used only when they appear on a seismic image. Because the saturation of gas hydrate is generally calculated by using well logs, the information is limited to the well location. To overcome these limitations, seismic impedance inversion and neural network methods can be used. Seismic inversion enables the identification of a gas hydrate reservoir even if seismic indicators do not exist, and a neural network makes it possible to predict the gas hydrate saturation in a region of interest away from the wells by combining well logging data and other attributes extracted from the seismic data . In this study, to estimate the distribution and saturation of gas hydrates that are broadly distributed in the Ulleung basin of the East Sea, seismic inversions such as acoustic impedance (AI), shear impedance (SI), and elastic impedance (EI) were calculated, and then the seismic attributes (ratio of compressional wave velocity to shear wave velocity, Vp/Vs, and combinations of Lamé parameters, λρ and μρ) that have unique features in hydrated sediments were extracted. Gas-hydrate-bearing sediments displayed high AI, high SI, high EI (22.5°), low Vp/Vs ratio, high λρ, and high μρ compared the surrounding sediments. The sediments containing free gas displayed low AI, low SI, low EI (22.5°), high Vp/Vs ratio, low λρ, and low μρ due to the phase transition from gas hydrate to gas. By combining these findings, the distribution of gas hydrates was estimated even if seismic indicators were not present in the seismic profile. Using the extracted seismic attributes, as well as standard seismic attributes and three-phase Biot-type equation (TPBE)-derived saturation logs of gas hydrates at the wells which had a high correlation to the seismic attributes, the saturation of gas hydrates away from the wells could be estimated based on probabilistic neural network (PNN) predictions. To validate the predicted saturation, cross-validation of wells was undertaken. The average correlation coefficient between the predicted saturation and actual saturation logs at the UBGH-09 and UBGH2-10 wells was 82.6%. In addition, for the estimation of the saturation section of gas hydrate, a relatively high saturation region of gas hydrate corresponded well to the gas hydrate occurrence zone of each well. • Gas hydrate saturation is estimated in the Ulleung basin, East Sea, Korea. • Impedance inversion enables the distribution of a gas hydrate reservoir. • Saturation is predicted in a target region away from the wells by using PNN.

Seismic screening for hydrocarbon prospects using rock-physics attributes

Rock-physics templates (RPT), in combination with seismic AVO inversion data, can be used to screen for hydrocarbon prospects during exploration. With the improved quality and increased use of elastic seismic inversion, there has recently been a paradigm change in prospect mapping in the oil industry, and quantitative interpretation has become a widely used jargon. Rock-physics models are essential in that they help in converting elastic parameters from inversion data to reservoir parameters. In the screening phase of inversion data, rock-physics models also can reveal hydrocarbon-associated anomalies. Two new rock-physics attributes help in detecting hydrocarbons from seismic—the curved pseudo-elastic impedance and the trend angle. The first of these is similar to the extended elastic impedance or the fluid factor in that it represents a deviation from a wet-background trend in a rock-physics template. However, it honors the nonlinear nature of a compaction trend. The trend angle is a measure of slope angle between two adjacent data points in the AI-versus-VP/VS crossplot, and this attribute will highlight fluid trends in the data. Those two attributes can be used complementarily to detect and highlight hydrocarbon accumulations, as demonstrated on data from the Norwegian shelf.

Multidimensional scaling for the evaluation of a geostatistical seismic elastic inversion methodology

Due to the nature of seismic inversion problems, there are multiple possible solutions that can equally fit the observed seismic data while diverging from the real subsurface model. Consequently, it is important to assess how inverse-impedance models are converging toward the real subsurface model. For this purpose, we evaluated a new methodology to combine the multidimensional scaling (MDS) technique with an iterative geostatistical elastic seismic inversion algorithm. The geostatistical inversion algorithm inverted partial angle stacks directly for acoustic and elastic impedance (AI and EI) models. It was based on a genetic algorithm in which the model perturbation at each iteration was performed recurring to stochastic sequential simulation. To assess the reliability and convergence of the inverted models at each step, the simulated models can be projected in a metric space computed by MDS. This projection allowed distinguishing similar from variable models and assessing the convergence of inverted models toward the real impedance ones. The geostatistical inversion results of a synthetic data set, in which the real AI and EI models are known, were plotted in this metric space along with the known impedance models. We applied the same principle to a real data set using a cross-validation technique. These examples revealed that the MDS is a valuable tool to evaluate the convergence of the inverse methodology and the impedance model variability among each iteration of the inversion process. Particularly for the geostatistical inversion algorithm we evaluated, it retrieves reliable impedance models while still producing a set of simulated models with considerable variability.

Measurement of Elastic Parameters of Lithium Hydroxylammonium Sulphate Single Crystal, by Ultrasonic Pulse Echo Overlap Technique

Ultrasonics is the most established and precise technique to determine the elastic parameters of materials. Elastic constants are important parameters of a crystal which provide valuable infor-mation about the bonding characteristic between adjacent atomic planes and the anisotropic cha-racter of the bonding and structural ability. Second order elastic constants can be measured by measuring the velocity of the ultrasonic pulses of different polarization along different symmetry directions. Elastic Constants of Lithium Hydroxylammonium Sulphate [LHAS] single crystal by ul-trasonic Pulse Echo Overlap [PEO] technique are reported for the first time. Large single crystals of LHAS of size [26×26×10] mm3 have been grown from supersaturated aqueous solution of the salt by slow evaporation technique over a period of 40 - 45 days at 305 K. Absolute velocities at room temperature (303 K) have been measured for the selected direction and modes with McSkimin criterion. The anisotropy in the elastic properties of LHAS is well studied by measuring ultrasonic velocity in the crystal in certain specified crystallographic directions. The elastic stiffness constants C11, C33, C44, C55, and C66, and Acoustic impedance constants and Rao’s constants in specified directions are evaluated.

ガボン共和国沖合Nguma鉱区へのExtended Elastic Impedanceの適用例

Since farming in to an offshore exploration block of Elf Gabon (presently Total Gabon) in 1974, MPDC Gabon Co., Ltd. (subsidiary of Mitsubishi Corporation) has been acting E&P business in Gabon. The Nguma permit is located in northern offshore Gabon approximately 65 km southwest from Port Gentil city and covers an area of 1,199 km2 (presently reduced to 600 km2).The turbidite sandstone in several geological periods is expected as possible reservoir in this area, and the main target is the Batanga sandstones in the Maastricht period. This facies is missing in the some wells and possibly to be distributed unevenly, and grasping Batanga sandstone distribution is one key point of this exploration.The distribution of reservoir sandstone was predicted using Extended Elastic Impedance (hereafter referred as EEI). EEI can approximate reflectivity or impedance to several elastic parameters (such as bulk modulus, Lamé parameter, rigidity modulus, and poison ratio) by a projection of acoustic impedance (AI) and gradient impedance (GI) data (AVO attributes). Gamma ray (GR) is the most suitable well log item to indicate sandstone reservoir and this prediction is first target for this study. However it is not tied to elastic modulus directly like as water saturation. Therefore it may not be necessarily derived from AVO attributes, and then the feasibility evaluation for applying EEI in this area was applied by taking empirical correlation.In data processing, EEI inversion with its proper (AVO friendly) pre-conditioning was applied on 3D seismic bin gather after pre-stack time migration. This EEI inversion derived pseudo GR and it has fine consistency with real GR at not only control well but also new well. In interpretation, turbidite sandstone distribution was predicted and delineated using EEI data.

Improved unconventional reservoir characterization using multi-azimuth stratigraphic inversion, case study on the Fort Worth Basin

The development of the exploration and exploitation of unconventional hydrocarbons requires innovative skills to allow a better characterization of natural fracture networks and fracability of the rocks at depth. Within this context, we bring into focus a multi-azimuth inversion methodology to give clues about the sweet spots characterization through the Barnett Shales formation. To achieve our goal we used an isotropic model-based stratigraphic seismic inversion, considering a series of azimuthal sectors to build partial seismic stacks required as input of the workflow. The initial seismic survey was recorded over a surface of approximately 100 square miles to image the Barnett Shales formation, of about 150 ft thickness only and localized in a transition zone between the oil and gas window. A preliminary processing task was to define limits of azimuthal and incidence angle sectors to build several multi-azimuth post-stack and pre-stack seismic datasets. Two exploration wells with a set of log data are available in the interest area helping in the model a priori building and in the well-to-seismic calibration, both crucial steps to apply the inversion workflow. We first perform full post-stack and pre-stack usual inversion to help in finding sets of best inversion parameters, then we do the multi-azimuth post-stack and pre-stack inversion workflow using the same previous sets of parameters for each azimuthal sector. Consequently a series of acoustic impedance, P- and S-wave elastic impedance cubes are computed for each azimuthal sector. Another aspect of the study is the quantification of azimuthal variations using an ellipse fitting algorithm giving, for each bin of the interest volume, the ratio (between major and minor axes) and tilt (i.e. azimuth from the East) of the ellipse. Results showed up to 10% of anisotropy for impedances in the Barnett Shales. We go a step further computing geomechanical features like Poisson's ratio and brittleness coefficient within the Barnett Shales and we quantified their azimuthal variations. Some areas present lower Poisson's ratio and higher brittleness than other parts. It may suggest that the latter are sweet spots that could be more easily stimulated by induced fracturing.

The application of high-resolution 3D seismic data to model the distribution of mechanical and hydrogeological properties of a potential host rock for the deep storage of radioactive waste in France

In the context of a deep geological repository of high-level radioactive wastes, the French National Radioactive Waste Management Agency (Andra) has conducted an extensive characterization of the Callovo-Oxfordian argillaceous rock and surrounding formations in the Eastern Paris Basin. As part of this project, an accurate 3D seismic derived geological model is needed. The paper shows the procedure used for building the 3D seismic constrained geological model in depth by combining time-to-depth conversion of seismic horizons, consistent seismic velocity model and elastic impedance in time. It also shows how the 3D model is used for mechanical and hydrogeological studies. The 3D seismic field data example illustrates the potential of the proposed depth conversion procedure for estimating density and velocity distributions, which are consistent with the depth conversion of seismic horizons using the Bayesian Kriging method. The geological model shows good agreement with well log data obtained from a reference well, located closest to the 3D seismic survey area.Modeling of the mechanical parameters such as shear modulus, Young modulus, bulk modulus indicates low variability of parameters confirming the homogeneity of the target formation (Callovo-Oxfordian claystone). 3D modeling of a permeability index (Ik-Seis) computed from seismic attributes (instantaneous frequency, envelope, elastic impedance) and validated at the reference well shows promising potential for supporting hydrogeological simulation and decision making related to safety issues.

Elastic impedance parameterization and inversion with Young’s modulus and Poisson’s ratio

Young’s modulus and Poisson’s ratio are related to quantitative reservoir properties such as porosity, rock strength, mineral and total organic carbon content, and they can be used to infer preferential drilling locations or sweet spots. Conventionally, they are computed and estimated with a rock physics law in terms of P-wave, S-wave impedances/velocities, and density which may be directly inverted with prestack seismic data. However, the density term imbedded in Young’s modulus is difficult to estimate because it is less sensitive to seismic-amplitude variations, and the indirect way can create more uncertainty for the estimation of Young’s modulus and Poisson’s ratio. This study combines the elastic impedance equation in terms of Young’s modulus and Poisson’s ratio and elastic impedance variation with incident angle inversion to produce a stable and direct way to estimate the Young’s modulus and Poisson’s ratio, with no need for density information from prestack seismic data. We initially derive a novel elastic impedance equation in terms of Young’s modulus and Poisson’s ratio. And then, to enhance the estimation stability, we develop the elastic impedance varying with incident angle inversion with damping singular value decomposition (EVA-DSVD) method to estimate the Young’s modulus and Poisson’s ratio. This method is implemented in a two-step inversion: Elastic impedance inversion and parameter estimation. The introduction of a model constraint and DSVD algorithm in parameter estimation renders the EVA-DSVD inversion more stable. Tests on synthetic data show that the Young’s modulus and Poisson’s ratio are still estimated reasonable with moderate noise. A test on a real data set shows that the estimated results are in good agreement with the results of well interpretation.