scholarly journals THE IMPORTANCE OF LOCALLY CONVERTED WAVES ON THE ELASTIC INVERSION OF COMPRESSIONAL DATA

2014 ◽  
Vol 32 (2) ◽  
pp. 323 ◽  
Author(s):  
Jorge Nicolás Hounie ◽  
Sérgio Adriano Moura Oliveira
Keyword(s):  
Elastic Properties ◽  
Seismic Waves ◽  
Oil And Gas ◽  
Seismic Inversion ◽  
Stratified Medium ◽  
Inversion Method ◽  
Elastic Media ◽  
Nonlinear Inversion ◽  
Converted Waves ◽  
Elastic Inversion

ABSTRACT. Seismic inversion is routinely used in oil and gas exploration to estimate the elastic properties of the subsurface. However, most of the inversion methodsused in the industry disregard an inherent phenomenon of wave propagation in elastic media: the conversion of compressional waves into shear waves and vice versa.In this paper we analyze the importance of the locally converted seismic waves in the results of compressional wave based elastic inversion. For this, the reflectivitymethod is used to model the seismic response of a layered elastic media and also as the base of a nonlinear inversion method. We show that the compressional wavesgenerated by local conversion can hardly be identified and eliminated by moveout filters once their transit time are very close to that of primary reflections. To assess theimpact of the locally converted waves, two versions of the inversion method were implemented: in the first one, all seismic events generated in a stratified medium weretaken into account, including the effects of transmission, internal multiples and converted waves. In the second version, the converted waves were ignored. A series ofsynthetic data were generated using full reflectivity modeling and submitted to the two versions of the inversion methods, what allow us to evaluate the error made whenthese waves are ignored. We conclude that this error is proportional to the degree of contrast in elastic properties between layers and is greatly affected by the presenceof thin layers.Keywords: waveform inversion, reflectivity, seismic. RESUMO. A inversão de dados sísmicos é utilizada rotineiramente na exploração de hidrocarbonetos e na caracterização de reservatórios, com o objetivo de estimaras propriedades elásticas do interior da terra. No entanto, a maioria dos algoritmos de inversão elástica desconsidera um fenômeno inerente à propagação de ondas emmeios elásticos: a conversão de ondas compressionais em cisalhantes e vice-versa. Neste artigo analisamos o impacto das ondas convertidas localmente nos resultadosde inversão elástica de dados compressionais. O método da refletividade é utilizado de duas maneiras na análise das ondas convertidas: como método de modelagem ecomo base para algoritmos de inversão. A modelagem mostra que as ondas convertidas localmente são de difícil identificação em um sismograma, confundindo-se comeventos de origem puramente compressional, o que torna inviável sua filtragem com os métodos de processamento baseados na diferença de tempo de trânsito entreeventos compressionais e convertidos. Para avaliar a influência das ondas convertidas nos resultados da inversão elástica de dados compressionais foram desenvolvidasduas estratégias de inversão baseadas no método da refletividade: na primeira, foram considerados todos os efeitos de propagação em meios elásticos estratificados,enquanto na segunda foram desconsideradas as conversões de modo que ocorrem entre as camadas. As estratégias foram testadas em dados sintéticos, e os resultadospermitiram avaliar a influência das ondas convertidas na inversão elástica de dados compressionais. De uma maneira geral, a inversão de forma de onda considerandotodos os efeitos de propagação apresentou resultados superiores aos da inversão que desconsideram as conversões de modo. Entretanto, em situações onde não ocorram camadas delgadas com grandes contrastes nas propriedades em relação às camadas adjacentes, as duas estratégias apresentaram resultados similares.Palavras-chave: inversão de forma de onda, refletividade, sísmica.

scholarly journals Bayesian Time-lapse Difference Inversion Based on the exact Zoeppritz Equations with Blockiness Constraint

2020 ◽  
Vol 25 (1) ◽  
pp. 89-100
Author(s):  
Lin Zhou ◽  
Jianping Liao ◽  
Jingye Li ◽  
Xiaohong Chen ◽  
Tianchun Yang ◽  
...  
Keyword(s):  
Wave Equations ◽  
Oil And Gas ◽  
Time Lapse ◽  
Seismic Inversion ◽  
Field Application ◽  
Inversion Method ◽  
S Wave ◽  
Elastic Parameters ◽  
Zoeppritz Equations ◽  
Approximate Formulas

Accurately inverting changes in the reservoir elastic parameters that are caused by oil and gas exploitation is of great importance in accurately describing reservoir dynamics and enhancing recovery. Previously numerous time-lapse seismic inversion methods based on the approximate formulas of exact Zoeppritz equations or wave equations have been used to estimate these changes. However the low accuracy of calculations using approximate formulas and the significant calculation effort for the wave equations seriously limits the field application of these methods. However, these limitations can be overcome by using exact Zoeppritz equations. Therefore, we study the time-lapse seismic difference inversion method using the exact Zoeppritz equations. Firstly, the forward equation of time-lapse seismic difference data is derived based on the exact Zoeppritz equations. Secondly, the objective function based on Bayesian inversion theory is constructed using this equation, with the changes in elastic parameters assumed to obey a Gaussian distribution. In order to capture the sharp time-lapse changes of elastic parameters and further enhance the resolution of the inversion results, the blockiness constraint, which follows the differentiable Laplace distribution, is added to the prior Gaussian background model. All examples of its application show that the proposed method can obtain stable and reasonable P- and S-wave velocities and density changes from the difference data. The accuracy of estimation is higher than for existing methods, which verifies the effectiveness and feasibility of the new method. It can provide high-quality seismic inversion results for dynamic detailed reservoir description and well location during development.

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

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

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

Direct nonlinear inversion of multiparameter 1D elastic media using the inverse scattering series

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. WCD15-WCD27 ◽  
Author(s):  
Haiyan Zhang ◽  
Arthur B. Weglein
Keyword(s):  
Wave Velocity ◽  
Material Properties ◽  
Value Added ◽  
P Wave ◽  
Added Value ◽  
Inversion Method ◽  
Elastic Media ◽  
Nonlinear Inversion ◽  
Model Matching ◽  
S Wave

In the direct nonlinear inversion method and in algorithms for 1D elastic media, P-wave velocity, S-wave velocity, and density are depth dependent. “Direct nonlinear” means that the method uses explicit formulas that (1) input data and directly output changes in material properties without the need for indirect procedures such as model matching, searching, optimization, or other assumed aligned objectives or proxies and that (2) the algorithms recognize and directly invert the intrinsic nonlinear relationship between changes in material properties and the recorded reflection wavefields. To achieve full elastic inversion, all components of data (such as PP, SP, and SS data) are needed. The method assumes that only data and reference medium propertiesare input, and terms in the inverse series for moving mislocated reflectors resulting from the linear inverse term are separated from amplitude correction terms. Although in principle this direct inversion approach requires all components of elastic data, synthetic tests indicate that a consistent value-added result may be achieved given only PP data measurements, as long as the PP data are used to approximately synthesize the PS and SP components. Further value would be derived from measuring all components of the data as the method requires. If all components of data are available, one consistent method can solve for all of the second terms (the first terms beyond linear). The explicit nonlinear inversion formulas provide an unambiguous data requirement message as well as conceptual and practical added value beyond both linear approaches and all indirect methods.

scholarly journals Simultaneous Seismic Inversion for Reservoir Characterization at Poseidon Field, Browse Basin, Australia

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Suleman Mauritz Sihotang ◽  
Ida Herawati
Keyword(s):  
Oil And Gas ◽  
Reservoir Characterization ◽  
Research Area ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Well Log ◽  
Gas Field ◽  
Simultaneous Inversion ◽  
Fluid Saturation ◽  
Oil And Gas Field

Seismic inversion method has been widely used to obtain reservoir property in an oil and gas field. In this research, one of inversion methods known as simultaneous inversion is used to analyze reservoir characterization at Poseidon Field, Browse Basin. Simultaneous inversion is applied to partial angle stack data and result in volume of Acoustic Impedance (AI), Shear Impedance (SI) and Lame parameter (LMR). The objective of this study is to determine distribution of sandstone lithology with gas saturated in Plover reservoir formation. Sensitivity analysis is done by cross-plotting elastic and Lame parameter from five well log data and analyzing lithology type and fluid saturation. Based on those cross-plots, lithological type can be identified from AI, λρ, µρ and λ/µ parameters. Meanwhile, the presence of gas can be discriminated using SI, λρ, and λ/µ parameters. Gas-saturated sandstone presence is characterized by Lambda-Rho value less than 50 GPa g cc-1 and Lambda over Mu value less than 0.8 GPa g cc-1. Maps of each parameter are generated at reservoir interval. Based on those maps, it can be concluded that gas sand spread out in the eastern and western areas of research area.

scholarly journals Poisson impedance for lithology characterization

2021 ◽  
Vol 6 (1) ◽  
pp. 23-28
Author(s):  
A. V. Khitrenko ◽  
K. A. Groman ◽  
A. V. Lobusev
Keyword(s):  
Elastic Properties ◽  
Seismic Data ◽  
Western Siberia ◽  
Oil And Gas ◽  
Seismic Attributes ◽  
Seismic Inversion ◽  
Seismic Survey ◽  
Lateral Heterogeneity ◽  
Main Method

Tyumen formation is a formation with very considerably lateral heterogeneity. It influences on process of exploration oil and gas traps. No one can deny that seismic survey is a main method for prediction lateral heterogeneity. Nowadays, geoscientists can model different useful seismic attributes, apart from structural maps. Seismic inversion is most effective tool for transformation amplitude seismic data into elastic properties. However, sometimes result of seismic inversion is very hard to understand and analyze. In this work, authors will show additional methods for better understanding results of seismic inversion using Impedance Poisson. Area of research is located in the Western Siberia.

Geostatistical inversion of prestack seismic data for the joint estimation of facies and impedances using stochastic sampling from Gaussian mixture posterior distributions

Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. M55-M65 ◽  
Author(s):  
Xiaozheng Lang ◽  
Dario Grana
Keyword(s):  
Elastic Properties ◽  
Posterior Distribution ◽  
Seismic Data ◽  
Gaussian Mixture ◽  
Seismic Inversion ◽  
Joint Estimation ◽  
Inversion Method ◽  
Inversion Algorithm ◽  
Data Set ◽  
Geostatistical Approach

We have developed a seismic inversion method for the joint estimation of facies and elastic properties from prestack seismic data based on a geostatistical approach. The objectives of our inversion methodology are to sample from the posterior distribution of seismic properties and to simultaneously classify the lithology conditioned by seismic data. The inversion algorithm is a sequential Gaussian mixture inversion based on Bayesian linearized amplitude variation with offset inverse theory and sequential geostatistical simulations. The stochastic approach to the inversion allows generating multiple elastic models that match the seismic data. To mathematically represent the multimodal behavior of elastic properties due to their variations within different lithologies, we adopt a Gaussian mixture distribution for the prior model of the elastic properties and we use the prior probability of the facies as weights of the Gaussian components of the mixture. The solution of the inverse problem is achieved by deriving the explicit analytical expression of the posterior distribution of the elastic properties and facies and by sampling from this distribution according to a spatial correlation model. The inversion methodology has been validated using well logs and synthetic seismic data with different noise levels, and it is then applied to a real 3D seismic data set in North Sea.

Nonlinear amplitude-variation-with-offset inversion for Lamé parameters using a direct inversion method

2017 ◽  
Vol 5 (3) ◽  
pp. SL57-SL67 ◽  
Author(s):  
Guangsen Cheng ◽  
Xingyao Yin ◽  
Zhaoyun Zong
Keyword(s):  
Nonlinear Equation ◽  
Real Data ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Nonlinear Inversion ◽  
Reservoir Prediction ◽  
Amplitude Variation ◽  
Linear Inversion ◽  
Amplitude Variation With Offset ◽  
Avo Inversion

Prestack seismic inversion is widely used in fluid indication and reservoir prediction. Compared with linear inversion, nonlinear inversion is more precise and can be applied to high-contrast situations. The inversion results can be affected by the parameters’ sensitivity, so the parameterization of nonlinear equations is very significant. Considering the poor nonlinear amplitude-variation-with-offset (AVO) inversion results of impedance and velocity parameters, we adjust the parameters of the nonlinear equation, avoid the inaccuracy caused by parameters sensitivity and get the ideal nonlinear AVO inversion results of the Lamé parameters. The feasibility and stability of the nonlinear equation based on the Lamé parameters and method are verified by the model and the real data examples. The resolution and the lateral continuity of nonlinear inversion results are better compared with the linear inversion results.

scholarly journals Prestack Seismic Inversion via Nonconvex L1-2 Regularization

2021 ◽  
Vol 11 (24) ◽  
pp. 12015
Author(s):  
Wenliang Nie ◽  
Fei Xiang ◽  
Bo Li ◽  
Xiaotao Wen ◽  
Xiangfei Nie
Keyword(s):  
Objective Function ◽  
Regularization Method ◽  
Oil And Gas ◽  
A Priori ◽  
Low Frequency ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Data Logging ◽  
Elastic Parameters ◽  
Geological Interpretation

Using seismic data, logging information, geological interpretation data, and petrophysical data, it is possible to estimate the stratigraphic texture and elastic parameters of a study area via a seismic inversion. As such, a seismic inversion is an indispensable tool in the field of oil and gas exploration and development. However, due to unknown natural factors, seismic inversions are often ill-conditioned problems. One way to work around this unknowable information is to determine the solution to the seismic inversion using regularization methods after adding further a priori constraints. In this study, the nonconvex L1−2 regularization method is innovatively applied to the three-parameter prestack amplitude variation angle (AVA) inversion. A forward model is first derived based on the Fatti approximate formula and then low-frequency models for P impedance, S impedance, and density are established using logging and horizon data. In the Bayesian inversion framework, we derive the objective function of the prestack AVA inversion. To further improve the accuracy and stability of the inversion results, we remove the correlations between the elastic parameters that act as initial constraints in the inversion. Then, the objective function is solved by the nonconvex L1−2 regularization method. Finally, we validate our inversion method by applying it to synthetic and observational data sets. The results show that our nonconvex L1−2 regularization seismic inversion method yields results that are highly accurate, laterally continuous, and can be used to identify and locate reservoir formation boundaries. Overall, our method will be a useful tool in future work focused on predicting the location of reservoirs.

Basaltic mantle reservoirs from seismic inversion of reflection data 

2021 ◽  
Author(s):  
Benoit Tauzin ◽  
Lauren Waszek ◽  
Jun Yan ◽  
Maxim Ballmer ◽  
Nick Schmerr ◽  
...  
Keyword(s):  
Seismic Waves ◽  
Thermal State ◽  
Global Scale ◽  
Seismic Inversion ◽  
Planetary Science ◽  
Compressional Waves ◽  
Reflection Data ◽  
Chemical Segregation ◽  
Geodynamic Models ◽  
Plate Subduction

<p>Convective stirring of chemical heterogeneities introduced through oceanic plate subduction results in the marble cake model of mantle composition. A convenient description invokes a chemically unequilibrated mixture of oceanic basaltic crust and harzburgitic lithosphere. Such a composition is required to explain joint observations of shear and compressional waves reflected underneath transition zone (TZ) discontinuities<sup>1</sup>. The formation of basaltic reservoirs at TZ depth results from complex interaction between phase-change induced chemical segregation, subducted slab downward entrainment, and plume upward advection. However, the dominant mechanism to create and maintain the reservoirs is debated, because both present-day reservoir location and the amount of basalt in these reservoirs are unconstrained. Here, Bayesian inversion of SS- and PP-precursors reflection data indicates that the TZ comprises a global average basalt fraction f = 0.32 ± 0.11. We find the most enriched basaltic reservoirs (f = 0.5-0.6) are associated with recent subduction in the circum-Pacific region. We investigate the efficiency of plate subduction to maintain such reservoirs using global-scale thermochemical  convection models<sup>2</sup>.</p><p>[1] Waszek, L., Tauzin, B., Schmerr, N.C., Ballmer, M., & Afonso, J.C. (in review). A poorly mixed mantle and its thermal state inferred from seismic waves.</p><p>[2] Yan, J., Ballmer, M. D., & Tackley, P. J. (2020). The evolution and distribution of recycled oceanic crust in the Earth's mantle: Insight from geodynamic models. <em>Earth and Planetary Science Letters</em>, <em>537</em>, 116171.</p>

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