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.

scholarly journals Seismic pre-stack AVA inversion scheme based on lithology constraints

2020 ◽  
Vol 17 (3) ◽  
pp. 411-428
Author(s):  
Shuang Xiao ◽  
Jing Ba ◽  
Qiang Guo ◽  
J M Carcione ◽  
Lin Zhang ◽  
...  
Keyword(s):  
Model Updating ◽  
Optimal Solution ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Good Resolution ◽  
S Wave ◽  
Elastic Parameters ◽  
Multivariate Gaussian Distribution ◽  
Stability Performance ◽  
The Stability

Abstract Seismic pre-stack AVA inversion using the Zoeppritz equation and its approximations as a forward engine yields P- and S-wave velocities and density. Due to the presence of seismic noise and other factors, the solution to seismic inversion is generally ill-posed and it is necessary to add constraints to regularize the algorithm. Moreover, since pre-stack inversion is a nonlinear problem, linearized optimization algorithms may fall into false local minima. The simulated annealing (SA) algorithm, on the other hand, is capable of finding the global optimal solution regardless of the initial model. However, when applied to multi-parameter pre-stack inversion, standard SA suffers from instability. Thus, a nonlinear pre-stack inversion method is proposed based on lithology constraints. Specifically, correlations among the elastic parameters are introduced to establish constraints based on a Bayesian framework, with special intention of mitigating the ill-posedness of the inversion problem as well as addressing the lithological characteristics of the formations. In particular, to improve the stability, a multivariate Gaussian distribution of elastic parameters is incorporated into the model updating the SA algorithm. We apply the algorithm to synthetic and field seismic data, indicating that the proposed method has a good resolution and stability performance.

Seismic simultaneous inversion using a multidamped subspace method

Geophysics ◽  
2019 ◽  
Vol 85 (1) ◽  
pp. R1-R10 ◽  
Author(s):  
Jinyue Liu ◽  
Yanghua Wang
Keyword(s):  
Fourier Coefficients ◽  
Hessian Matrix ◽  
Wave Impedance ◽  
Seismic Inversion ◽  
P Wave ◽  
Inversion Method ◽  
Subspace Method ◽  
S Wave ◽  
Elastic Parameters ◽  
Simultaneous Inversion

Seismic inversion of amplitude variation with offset (AVO) plays a key role in seismic interpretation and reservoir characterization. The AVO inversion should be a simultaneous inversion that inverts for three elastic parameters simultaneously: the P-wave impedance, S-wave impedance, and density. Using only seismic P-wave reflection data with a limited source-receiver offset range, the AVO simultaneous inversion can obtain two elastic parameters reliably, but it is difficult to invert for the third parameter, usually the density term. To address this difficulty in the AVO simultaneous inversion, we used a subspace inversion method in which we partitioned the elastic parameters into different subspaces. We parameterized each single elastic parameter with a truncated Fourier series and inverted for the Fourier coefficients. Because the Fourier coefficients of different wavenumber components have different sensitivities, we grouped the Fourier coefficients of low-, medium-, and high-wavenumber components into different subspaces. We further assigned different damping factors to the Hessian matrix corresponding to different wavenumber components within each subspace. This inversion scheme is referred to as a multidamped subspace method. Synthetic and field seismic data examples confirmed that the AVO simultaneous inversion with this multidamped subspace method is capable of producing reliable estimation of the three elastic parameters simultaneously.

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.

Reciprocal velocity-porosity general linear form provides consistent and systematic industry-wide applications

2019 ◽  
Vol 7 (4) ◽  
pp. T751-T759
Author(s):  
Killian Ikwuakor
Keyword(s):  
Linear Form ◽  
Oil And Gas ◽  
Rock Physics ◽  
Time Lapse ◽  
General Linear ◽  
S Wave ◽  
Rock Property ◽  
Formation Evaluation ◽  
Clastic Rocks ◽  
Universal Applicability

Velocity is an important rock property that is required and used in different applications in petrophysics, rock physics, and seismic. The published literature shows a plethora of equations and models that relate velocity and porosity, a critical reservoir property. Attempts to account for the presence of shale in the formation invariably lead to more complicated relations. The inability of the industry to streamline these relations handicaps advancements in rock physics and formation evaluation, complicates the application of best practices in time-lapse seismic and fluid substitutions, and jeopardizes the integration of petrophysical, geologic, and seismic characteristics of oil and gas reservoirs. I have considered the following criteria to grade some of the different velocity-porosity relations in use today: (1) the significance of effective stress, (2) usefulness for interpreting geology, (3) predictive capability, and (4) universal applicability. Judging by these criteria, the general linear form, first prescribed by the late George R. Pickett, is the clear winner. The general linear form is a linear relationship between the reciprocal velocity and porosity. It passes theoretical and empirical justification. It is also valid for P- and S-wave velocities, yields easily to mathematical manipulation, and satisfies carbonate as well as clastic rocks for porosities encountered in everyday subsurface investigations. I evaluate practical examples in which the general linear form is the basis for multiple rock-typing criteria, comparative formation evaluation, and interpretive use of the [Formula: see text] ratio. Appropriate integration of the general linear form with other rock property relations provides avenues to redefine the [Formula: see text] ratio and acoustic impedance, and it expands the understanding and applications of reservoir elastic properties, as well as it constrains and streamlines rock physics models and applications.

Accuracy Comparison of Elastic Impedance Formula

2012 ◽  
Vol 466-467 ◽  
pp. 400-404
Author(s):  
Jin Zhang ◽  
Huai Shan Liu ◽  
Si You Tong ◽  
Lin Fei Wang ◽  
Bing Xu
Keyword(s):  
Seismic Data ◽  
Poisson Ratio ◽  
Seismic Inversion ◽  
P Wave ◽  
S Wave ◽  
Elastic Parameters ◽  
Accuracy Comparison ◽  
Elastic Impedance ◽  
Prestack Seismic Inversion ◽  
Lamé Coefficients

Elastic impedance (EI) inversion is one of the prestack seismic inversion methods, which can obtain P-wave and S-wave velocity, density, Poisson ratio, Lame coefficients and other elastic parameters. But there have been many EI formulas nowadays, so which formula should be used in inversion is an urgent problem. This paper divides these formulas into two categories, and use several forward modeling to test the accuracy of these EI formulas. It shows that using the first kind of EI formulas in near offset seismic data can get high precision results.

scholarly journals A Multi-Point Geostatistical Seismic Inversion Method Based on Local Probability Updating of Lithofacies

Energies ◽  
2022 ◽  
Vol 15 (1) ◽  
pp. 299
Author(s):  
Zhihong Wang ◽  
Tiansheng Chen ◽  
Xun Hu ◽  
Lixin Wang ◽  
Yanshu Yin
Keyword(s):  
Seismic Inversion ◽  
Western China ◽  
Inversion Method ◽  
Seismic Record ◽  
Elastic Parameters ◽  
Probability Updating ◽  
Geostatistical Inversion ◽  
Local Probability ◽  
Seismic Records ◽  
The Given

In order to solve the problem that elastic parameter constraints are not taken into account in local lithofacies updating in multi-point geostatistical inversion, a new multi-point geostatistical inversion method with local facies updating under seismic elastic constraints is proposed. The main improvement of the method is that the probability of multi-point facies modeling is combined with the facies probability reflected by the optimal elastic parameters retained from the previous inversion to predict and update the current lithofacies model. Constrained by the current lithofacies model, the elastic parameters were obtained via direct sampling based on the statistical relationship between the lithofacies and the elastic parameters. Forward simulation records were generated via convolution and were compared with the actual seismic records to obtain the optimal lithofacies and elastic parameters. The inversion method adopts the internal and external double cycle iteration mechanism, and the internal cycle updates and inverts the local lithofacies. The outer cycle determines whether the correlation between the entire seismic record and the actual seismic record meets the given conditions, and the cycle iterates until the given conditions are met in order to achieve seismic inversion prediction. The theoretical model of the Stanford Center for Reservoir Forecasting and the practical model of the Xinchang gas field in western China were used to test the new method. The results show that the correlation between the synthetic seismic records and the actual seismic records is the best, and the lithofacies matching degree of the inversion is the highest. The results of the conventional multi-point geostatistical inversion are the next best, and the results of the two-point geostatistical inversion are the worst. The results show that the reservoir parameters obtained using the local probability updating of lithofacies method are closer to the actual reservoir parameters. This method is worth popularizing in practical exploration and development.

SIMULTANEOUS INVERSION FOR S-WAVE VELOCITY DENSITY FROM THE SV-SV WAVE

Geophysics ◽  
2020 ◽  
pp. 1-50
Author(s):  
Feng Zhang
Keyword(s):  
Wave Velocity ◽  
Oil And Gas ◽  
Incident Angle ◽  
Inversion Method ◽  
S Wave ◽  
Simultaneous Inversion ◽  
Pp Wave ◽  
Velocity Information ◽  
Using Data ◽  
Two Parameters

Knowledge of shear-wave velocity ( Vs) and density ( ρ) is essential for oil and gas reservoir detection and characterization. However, reliable recovery of both parameters, especially density, from the reflected PP-wave data is a difficult issue, because this inverse problem is highly illconditioned. The reflected SV-SV wave is easier to process than the PS-wave, and can provide better estimates of Vs and ρ than the PP-wave, because it is more sensitive to these parameters than the PP-wave. I present a simultaneous inversion for Vs and ρ based on a modified approximation of the SV-SV wave reflection coefficient. The modified equation includes only two parameters (natural logarithms of Vs and ρ) to be inverted, and it has high accuracy even at large incident angles and for strong impedance contrasts. I show that simultaneous inversion based on the modified approximation is well-posed when using data of small-to-moderate incident angle (20°-30°), and the misfit function can be easily regularized. The new simultaneous inversion method is applied to a SV-SV wave prestack dataset acquired from a 2D ninecomponent survey. The field data example demonstrates that the proposed method can recover stable and high-resolution density and S-wave velocity information, which can be used to investigate rock mineral composition, porosity and fluid content.

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 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 Exploring Reservoir within Hugin Formation in Theta Vest Structure using 4-D Seismic and Machine Learning Approach

2021 ◽  
Vol 873 (1) ◽  
pp. 012042
Author(s):  
Lilik T. Hardanto ◽  
Mirzam Abdurrachman ◽  
Dwiharso Nugroho
Keyword(s):  
Machine Learning ◽  
Fluid Flow ◽  
Seismic Analysis ◽  
Time Lapse ◽  
Seismic Inversion ◽  
Seismic Survey ◽  
Inversion Method ◽  
Oil Distribution ◽  
Flow Processes ◽  
The Right

Abstract This paper aims to identify the oil distribution using 4-D seismic below a complex 3-D surface in Hugin Formation using machine learning and geobody detection. The exploration well 15/9-19-SR, drilled to the Theta Vest structure, was based on the interpretation of reprocessed ST8215R 3-D seismic survey data from 1991 in the Sleipner area, encountered oil in the Jurassic Hugin Formation. The drills stem test showed outstanding production capacities through time, with low water cut and low GOR. 4-D seismic has all the traditional benefits of 3-D seismic. A significant additional potential benefit is that fluid-flow processes can be directly imaged. The 4-D seismic analysis was conducted in 2012 to repeat the 3-D seismic surveys and analyze images in time-lapse mode to monitor time-varying fluid-flow processes during reservoir production. A comprehensive study of the structure and the discovery has been performed and is reported. The DNN method to predict facies far away from existing production wells by using facies log well to supervise seismic inversion created by the Seismic Color Inversion method. It can detect some oil pockets distribution and risk the well planning and the right candidate for new proposed wells.

Sign in / Sign up

Export Citation Format

Share Document