Simultaneous inversion of prestack seismic data for rock properties using simulated annealing

Geophysics ◽  
2002 ◽  
Vol 67 (6) ◽  
pp. 1877-1885 ◽  
Author(s):  
Xin‐Quan Ma
Keyword(s):  
Simulated Annealing ◽  
Seismic Data ◽  
Low Frequency ◽  
Optimization Procedure ◽  
P Wave ◽  
Rock Properties ◽  
Inversion Method ◽  
Inversion Algorithm ◽  
Simultaneous Inversion ◽  
Reflection Seismic

A new prestack inversion algorithm has been developed to simultaneously estimate acoustic and shear impedances from P‐wave reflection seismic data. The algorithm uses a global optimization procedure in the form of simulated annealing. The goal of optimization is to find a global minimum of the objective function, which includes the misfit between synthetic and observed prestack seismic data. During the iterative inversion process, the acoustic and shear impedance models are randomly perturbed, and the synthetic seismic data are calculated and compared with the observed seismic data. To increase stability, constraints have been built into the inversion algorithm, using the low‐frequency impedance and background Vs/Vp models. The inversion method has been successfully applied to synthetic and field data examples to produce acoustic and shear impedances comparable to log data of similar bandwidth. The estimated acoustic and shear impedances can be combined to derive other elastic parameters, which may be used for identifying of lithology and fluid content of reservoirs.

Simultaneous inversion of PP and PS seismic data

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. R1-R10 ◽  
Author(s):  
Helene Hafslund Veire ◽  
Martin Landrø
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Model Building ◽  
Joint Inversion ◽  
P Wave ◽  
Inversion Method ◽  
System Of Equations ◽  
S Wave ◽  
Data Set ◽  
Simultaneous Inversion

Elastic parameters derived from seismic data are valuable input for reservoir characterization because they can be related to lithology and fluid content of the reservoir through empirical relationships. The relationship between physical properties of rocks and fluids and P-wave seismic data is nonunique. This leads to large uncertainties in reservoir models derived from P-wave seismic data. Because S- waves do not propagate through fluids, the combined use of P-and S-wave seismic data might increase our ability to derive fluid and lithology effects from seismic data, reducing the uncertainty in reservoir characterization and thereby improving 3D reservoir model-building. We present a joint inversion method for PP and PS seismic data by solving approximated linear expressions of PP and PS reflection coefficients simultaneously using a least-squares estimation algorithm. The resulting system of equations is solved by singular-value decomposition (SVD). By combining the two independent measurements (PP and PS seismic data), we stabilize the system of equations for PP and PS seismic data separately, leading to more robust parameter estimation. The method does not require any knowledge of PP and PS wavelets. We tested the stability of this joint inversion method on a 1D synthetic data set. We also applied the methodology to North Sea multicomponent field data to identify sand layers in a shallow formation. The identified sand layers from our inverted sections are consistent with observations from nearby well logs.

scholarly journals Using Very Fast Simulated Annealing in the Weighted AB Semblance method

2019 ◽  
Vol 37 (4) ◽  
Author(s):  
Marcelo Souza ◽  
Milton Porsani
Keyword(s):  
Simulated Annealing ◽  
Seismic Data ◽  
Real Data ◽  
Velocity Spectrum ◽  
Velocity Analysis ◽  
Inversion Algorithm ◽  
Coherence Measure ◽  
Reflection Seismic ◽  
Very Fast Simulated Annealing ◽  
Velocity Spectra

ABSTRACTThe conventional velocity analysis does not consider AVO effects in reflection seismic data. These conditions lead to obtaining of inadequate velocity fields, making it difficult to execute other steps in seismic processing. To overcome this problem, researchers developed the Weighted AB semblance method, a coherence measure which deals with AVO effects in velocity spectra. It is based on the application of two sigmoid weighting functions to AB semblance, which depend on four coefficients. The values of these coefficients directly influence the resolution of the resulting velocity spectrum. In this work, we apply the inversion algorithm Very Fast Simulated Annealing (VFSA) to obtain these values. Numerical experiments show that VFSA is a quite effective method, obtaining correct coefficient values and allowing the generation of the velocity spectrum with an excellent resolution for both synthetic and real data. Results also proved that Weighted AB semblance is an optimal coherence measure to be used in velocity spectrum, because it is insensitive to AVO effects and reversal polarity and presents considerably a better resolution than conventional semblance.Keywords: velocity analysis, AVO, high-resolution velocity spectra RESUMOA análise de velocidades convencional não considera efeitos de AVO em dados sísmicos de reflexão. Essas condições levam à obtenção de campos de velocidades inadequados, dificultando a execução de outras etapas do processamento sísmico. Para superar esse problema, pesquisadores desenvolveram o método AB semblance Ponderado, uma medida de coerência que lida com efeitos de AVO em espectros de velocidades. Ela ´e baseada na aplicação de duas funções sigmoides à AB semblance, que depende de quatro coeficientes. Os valores desses coeficientes influenciam diretamente a resolução do espectro de velocidade resultante. Nesse trabalho, n´os aplicamos o algoritmo de inversão Very Fast Simulated Annealing (VFSA) para obter esses valores. Experimentos numéricos mostram que VFSA é um método bastante eficaz, obtendo valores corretos dos coeficientes e permitindo a geração do espectro de velocidade com uma excelente resolução tanto para dados sintéticos quanto para dados reais. Resultados também provam que o AB semblance Ponderado ´e uma medida de coerência ótima para ser usada no espectro de velocidade, porque ela é insensível aos efeitos de AVO e apresenta resolução consideravelmente melhor do que a semblance convencional.Palavras-chave: análise de velocidades, AVO, espectro de velocidades de alta resolução.

An Adaptive Stratified Joint PP and PS AVA Inversion Using Accurate Jacobian Matrix

Geophysics ◽  
2021 ◽  
pp. 1-145
Author(s):  
Xiaobo Liu ◽  
Jingyi Chen ◽  
Jing Zeng ◽  
Fuping Liu ◽  
Handong Huang ◽  
...  
Keyword(s):  
Seismic Data ◽  
Jacobian Matrix ◽  
Incidence Angle ◽  
P Wave ◽  
Rock Properties ◽  
Inversion Method ◽  
S Wave ◽  
Zoeppritz Equations ◽  
Wave Velocities ◽  
Strong Contrast

Amplitude variation with incidence angle (AVA) analysis is an essential tool for discriminating lithology in the hydrocarbon reservoirs. Compared with the traditional AVA inversion using only P-wave information, joint AVA inversion using PP and PS seismic data provides better estimation of rock properties (e.g., density, P- and S-wave velocities). At present, the most used AVA inversions depend on the approximations of Zoeppritz equations (e.g., Shuey and Aki-Richards approximations), which are not suitable for formations with strong contrast interfaces and seismic data with large incidence angles. Based on the previous derivation of accurate Jacobian matrix, we find that the sign of each partial derivative of reflection coefficient with respect to P-, S-wave velocities and density changes across the interface, represents good indicator for the reflection interfaces. Accordingly, we propose an adaptive stratified joint PP and PS AVA inversion using the accurate Jacobian matrix that can automatically obtain the layer information and can be further used as a constraint in the inversion of in-layer rock properties (density, P- and S-wave velocities). Due to the use of the exact Zoeppritz equations and accurate Jacobian matrix, this proposed inversion method is more accurate than traditional AVA inversion methods, has higher computational efficiency and can be applied to seismic wide-angle reflection data or seismic data acquired for formations with strong contrast interfaces. The model study shows that this proposed inversion method works better than the classical Shuey and Aki-Richards approximations at estimating reflection interfaces and in-layer rock properties. It also works well in handling a part of the complex Marmousi 2 model and real seismic data.

Automatic traveltime inversion via sparse decomposition of seismic data

Geophysics ◽  
2018 ◽  
Vol 83 (6) ◽  
pp. R659-R668 ◽  
Author(s):  
Bo Feng ◽  
Huazhong Wang ◽  
Ru-Shan Wu
Keyword(s):  
Seismic Data ◽  
Low Frequency ◽  
Velocity Model ◽  
Inversion Method ◽  
Traveltime Inversion ◽  
Sparse Decomposition ◽  
Reflection Seismic ◽  
New Strategy ◽  
Gradient Based ◽  
Intersection Criterion

We have developed an automatic traveltime inversion (ATI) method to estimate the macrovelocity model from reflection seismic data. First, we extract the kinematic information (i.e., source/receiver ray parameters, traveltime, and source/receiver coordinates) of locally coherent events using a sparse-decomposition method. And then we evaluate a new strategy to calculate the reflection traveltime residual based on a ray-intersection criterion, eliminating the influence of seismic amplitude to the estimation of the traveltime residual. The velocity model can be updated iteratively by minimizing the traveltime residual functional with a gradient-based method. To obtain a smooth gradient free of artifacts, we first estimate the high-wavenumber components of the functional gradient with a total variation (TV) regularization method and then subtract it from the full gradient. Because the reflection traveltime residual calculation and velocity update are fully automated procedures, the proposed traveltime inversion method is referred to as ATI. We determine with 2D synthetic and field examples that ATI does not need a good starting model. Furthermore, it requires neither low-frequency seismic data nor long-offset acquisition. Nevertheless, the proposed traveltime residual calculation strategy is only valid for the 2D case, which limits its 3D applicability. We explore a possible solution for 3D extension.

A New Inversion Method Using a Modified Bat Algorithm for Analysis of Seismic Refraction Data in Dam Site Investigation

2019 ◽  
Vol 24 (2) ◽  
pp. 201-214
Author(s):  
Rashed Poormirzaee ◽  
Siamak Sarmady ◽  
Yusuf Sharghi
Keyword(s):  
Seismic Data ◽  
Seismic Refraction ◽  
Bat Algorithm ◽  
Inversion Method ◽  
Model Parameters ◽  
Inversion Algorithm ◽  
Dam Site ◽  
Seismic Refraction Data ◽  
Modified Bat Algorithm ◽  
Refraction Data

Similar to any other geophysical method, seismic refraction method faces non-uniqueness in the estimation of model parameters. Recently, different nonlinear seismic processing techniques have been introduced, particularly for seismic inversion. One of the recently developed metaheuristic algorithms is bat optimization algorithm (BA). Standard BA is usually quick at the exploitation of the solution, while its exploration ability is relatively poor. In order to improve exploration ability of BA, in the current study, a hybrid metaheuristic algorithm by inclusion a mutation operator into BA, so-called mutation based bat algorithm (MBA), is introduced to inversion of seismic refraction data. The efficiency and stability of the proposed inversion algorithm were tested on different synthetic cases. Finally, the MBA inversion algorithm was applied to a real dataset acquired from Leylanchay dam site at East-Azerbaijan province, Iran, to determine alluvium depth. Then, the performance of MBA on both synthetic and real datasets was compared with standard BA. Moreover, the dataset was further processed following a tomographic approach and the results were compared to the results of the proposed MBA inversion method. In general, the MBA inversion results were superior to standard BA inversion and results of MBA were in good agreement with available boreholes data and geological sections at the dam site. The analysis of the seismic data showed that the studied site comprises three distinct layers: a saturated alluvial, an unsaturated alluvial, and a dolomite bedrock. The measured seismic velocity across the dam site has a range of 400 to 3,500 m/s, with alluvium thickness ranging from 5 to 19 m. Findings showed that the proposed metaheuristic inversion framework is a simple, fast, and powerful tool for seismic data processing.

scholarly journals Variational Bayesian inversion of seismic attributes jointly for geologic facies and petrophysical rock properties

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. MR213-MR233 ◽  
Author(s):  
Muhammad Atif Nawaz ◽  
Andrew Curtis ◽  
Mohammad Sadegh Shahraeeni ◽  
Constantin Gerea
Keyword(s):  
Gaussian Mixture ◽  
Seismic Attributes ◽  
Joint Estimation ◽  
Training Data ◽  
P Wave ◽  
Rock Properties ◽  
Inversion Method ◽  
Computationally Efficient ◽  
S Wave ◽  
Well Data

Seismic attributes (derived quantities) such as P-wave and S-wave impedances and P-wave to S-wave velocity ratios may be used to classify subsurface volume of rock into geologic facies (distinct lithology-fluid classes) using pattern recognition methods. Seismic attributes may also be used to estimate subsurface petrophysical rock properties such as porosity, mineral composition, and pore-fluid saturations. Both of these estimation processes are conventionally carried out independent of each other and involve considerable uncertainties, which may be reduced significantly by a joint estimation process. We have developed an efficient probabilistic inversion method for joint estimation of geologic facies and petrophysical rock properties. Seismic attributes and petrophysical properties are jointly modeled using a Gaussian mixture distribution whose parameters are initialized by unsupervised learning using well-log data. Rock-physics models may be used in our method to augment the training data if the existing well data are limited; however, this is not required if sufficient well data are available. The inverse problem is solved using the Bayesian paradigm that models uncertainties in the form of probability distributions. Probabilistic inference is performed using variational optimization, which is a computationally efficient deterministic alternative to the commonly used sampling-based stochastic inference methods. With the help of a real data application from the North Sea, we find that our method is computationally efficient, honors expected spatial correlations of geologic facies, allows reliable detection of convergence, and provides full probabilistic results without stochastic sampling of the posterior distribution.

Investigating the velocity‐depth ambiguity of reflection traveltimes

Geophysics ◽  
1994 ◽  
Vol 59 (11) ◽  
pp. 1763-1773 ◽  
Author(s):  
Hans J. Tieman
Keyword(s):  
Velocity Field ◽  
Seismic Data ◽  
Effective Width ◽  
Entire Space ◽  
Inversion Algorithm ◽  
Long Wavelength ◽  
Velocity Anomaly ◽  
Reflection Seismic ◽  
Frequency Components ◽  
The Difference

Reflection seismic data contain a long wavelength ambiguity making it difficult to separate traveltime information into velocity and reflector depth components. The existence of this velocity‐depth ambiguity is a feature of the geometry of the subsurface and is not caused by the particular inversion algorithm being used. Factors that control the occurrence of velocity‐depth ambiguities include the effective width of a potential velocity anomaly; i.e., its spatial wavelength, its height above a reflector, and its thickness. Factors that do not affect velocity‐depth ambiguities are the magnitude of the anomaly (the difference in velocity between it and the background) and the cable length with which data were recorded. A thin velocity anomaly induces an ambiguity at a wavelength approximately equal to 4.44 times the height of the anomaly above the reflector. A thick anomaly that spans the entire space from surface to reflector induces an ambiguity at a wavelength approximately equal to 2.57 the depth to the reflector. These are wavelengths that are significant in size, and therefore are of exploration interest. Through Fourier analysis, any subsurface velocity field can be decomposed into spatial frequency components. Thus the wavelength dependent velocity‐depth ambiguity adversely affects all velocity distributions.

Nonlinear waveform inversion of plane‐wave seismograms in stratified elastic media

Geophysics ◽  
1991 ◽  
Vol 56 (5) ◽  
pp. 664-674 ◽  
Author(s):  
F. Kormendi ◽  
M. Dietrich
Keyword(s):  
Plane Wave ◽  
Least Squares ◽  
Wave Velocity ◽  
Generalized Least Squares ◽  
P Wave ◽  
Gradient Algorithm ◽  
Stratified Medium ◽  
Inversion Method ◽  
Inversion Algorithm ◽  
Frequency Wave

We present a method for determining the elastic parameters of a horizontally stratified medium from its plane‐wave reflectivity. The nonlinear inverse problem is iteratively solved by using a generalized least‐squares formalism. The proposed method uses the (relatively) fast convergence properties of the conjugate gradient algorithm and achieves computational efficiency through analytical solutions for calculating the reference and perturbational wavefields. The solution method is implemented in the frequency‐wave slowness domain and can be readily adapted to various source‐receiver configurations. The behavior of the algorithm conforms to the predictions of generalized least‐squares inverse theory: the inversion scheme yields satisfactory results as long as the correct velocity trends are introduced in the starting model. In practice, the inversion algorithm should be applied first in the precritical region because of the strong nonlinear behavior of postcritical data with respect to velocity perturbations. The suggested inversion strategy consists of first inverting for the density and P‐wave velocity (or P‐wave impedance) by considering plane waves in the low slowness region (near‐normal angles of incidence), then in optimizing for the S‐wave velocity by progressively including contributions from the high slowness region (steep angles of incidence). Numerical experiments performed with noise‐free synthetic data prove that the proposed inversion method satisfactorialy reconstructs the elastic properties of a stratified medium from a limited set of plane‐wave components, at a reasonable computing cost.

Reservoir Prediction Under Control of Sedimentary Facies

2017 ◽  
Vol 25 (03) ◽  
pp. 1750022
Author(s):  
Xiuwei Yang ◽  
Peimin Zhu
Keyword(s):  
Seismic Data ◽  
Low Frequency ◽  
Prediction Method ◽  
Rock Physics ◽  
Real Data ◽  
Sedimentary Facies ◽  
Seismic Inversion ◽  
Rock Properties ◽  
Reservoir Prediction ◽  
Frequency Model

Acoustic impedance (AI) from seismic inversion can indicate rock properties and can be used, when combined with rock physics, to predict reservoir parameters, such as porosity. Solutions to seismic inversion problem are almost nonunique due to the limited bandwidth of seismic data. Additional constraints from well log data and geology are needed to arrive at a reasonable solution. In this paper, sedimentary facies is used to reduce the uncertainty in inversion and rock physics modeling; the results not only agree with seismic data, but also conform to geology. A reservoir prediction method, which incorporates seismic data, well logs, rock physics and sedimentary facies, is proposed. AI was first derived by constrained sparse spike inversion (CSSI) using a sedimentary facies dependent low-frequency model, and then was transformed to reservoir parameters by sequential simulation, statistical rock physics and [Formula: see text]-model. Two numerical experiments using synthetic model and real data indicated that the sedimentary facies information may help to obtain a more reasonable prediction.

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