Amplitude analysis with an optimal model-based linear AVO approximation: Part II — Field data example

Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. C71-C79 ◽  
Author(s):  
E. Causse ◽  
M. Riede ◽  
A. J. van Wijngaarden ◽  
A. Buland ◽  
J. F. Dutzer ◽  
...  
Keyword(s):  
Field Data ◽  
Vertical Section ◽  
Seismic Facies ◽  
Amplitude Analysis ◽  
Seismic Parameters ◽  
Amplitude Variation With Offset ◽  
Model Based ◽  
Optimized Model ◽  
Zero Offset ◽  
Avo Attributes

AVO analysis can be conducted by estimating amplitude variation with offset (AVO) attributes from seismic prestack data and by characterizing the measured amplitude responses by the position of their projection in the attribute space. The most common AVO attributes are the intercept (zero-offset reflectivity) and AVO gradient. We have constructed an optimized, model-based linear AVO equation that is more accurate than usual AVO approximations. The parameters of this equation represent new AVO attributes that are more directly related to the information contained in seismic reflection amplitudes. We use these new AVO attributes to classify reflector responses from field data. Five seismic facies are defined that are characterized by differentdistributions of seismic parameters. Nine reflector classes are formed by associating appropriate pairs of facies. The expected locations of the different reflector classes in the space of optimized attributes are found by modeling and are used to derive a classification scheme. This scheme is applied to sections of optimized attributes calculated from the prestack data, leading to a vertical section showing the distribution of most probable facies in an area containing a sand reservoir. We compare the new approach to classification with intercept and gradient. The new method is more robust and less sensitive to the number of attributes (two or three) used for classification. It offers an optimal, flexible, and robust way of extracting the information contained in reflection amplitudes by simple linear AVO equations.

Amplitude analysis with an optimal model-based linear AVO approximation: Part I — Theory

Geophysics ◽  
2007 ◽  
Vol 72 (3) ◽  
pp. C59-C69 ◽  
Author(s):  
E. Causse ◽  
M. Riede ◽  
A. J. van Wijngaarden ◽  
A. Buland ◽  
J. F. Dutzer ◽  
...  
Keyword(s):  
Linear Equations ◽  
Basis Functions ◽  
Optimal Model ◽  
Amplitude Analysis ◽  
Avo Analysis ◽  
Model Based ◽  
Proper Number ◽  
Validity Range ◽  
Avo Attributes ◽  
Value Decomposition

Linear equations used to approximate reflection coefficient-versus-angle curves are usually valid only for small seismic parameter changes across reflectors, and they are rather inaccurate close to the critical angle. These inaccuracies affect the quality of AVO analysis and cause systematic errors when estimating relative seismic-parameter variations at reflectors, especially for density. We present an optimal model-based approach to build more accurate linear AVO approximations. Their basis functions are calculated by applying singular value decomposition to realistic modeled AVO curves. By extending the validity range of linear approximations to larger angles, this approach helps when using information contained at near-critical offsets. It alsooffers several advantages in other situations. The basis functions of the new approximations are orthogonal. Their coefficients represent new AVO attributes that can be used either to classify AVO responses directly, or to obtain more accurate estimates of usual AVO attributes (intercept, gradient, and possibly a third coefficient). This leads to a better estimation of seismic-parameter contrasts at reflecting interfaces. These coefficients are naturally sorted in decreasing order of importance. Therefore, the proper number of terms in the proposed equations can be chosen easily to offer an optimal compromise between noise and the information carried by each coefficient. Synthetic tests confirm the robustness of the method. This flexible and robust approach will be particularly well adapted for three-parameter AVO analysis.

Improvement of METANET Model Based on Critical Density Modeling for Traffic Control

2021 ◽  
Author(s):  
Lina Fu ◽  
Jie Fang ◽  
Yunjie Lyu ◽  
Huahui Xie
Keyword(s):  
Traffic Safety ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Field Data ◽  
Critical Density ◽  
Predictive Performance ◽  
Density Model ◽  
Model Based ◽  
Freeway Control ◽  
Density Modeling

Freeway control has been increasingly used as an innovative approach to ease traffic congestion, improve traffic safety and reduce exhaust emissions. As an important predictive model involved in freeway control, the predictive performance of METANET greatly influences the effect of freeway control. This paper focuses on modifying the METANET model by modeling the critical density. Firstly, the critical density model is deduced based on the catastrophe theory. Then, the perturbation wave and traveling wave that are obtained using the macro and micro data, respectively, have been developed to modify the above proposed critical density model. Finally, the numerical simulation is established to evaluate the effectiveness of the modified METANET model based on the field data from the realistic motorway network. The results show that overall, the predicted data from the modified METANET model are closer to the field data than those obtained from the original model.

WEATHER AND THE ECOLOGY OF APANTELES FUMIFERANAE VIER. (HYMENOPTERA: BRACONIDAE)

1988 ◽  
Vol 120 (S146) ◽  
pp. 57-70 ◽  
Author(s):  
Vincent G. Nealis
Keyword(s):  
Field Data ◽  
Historical Data ◽  
Spruce Budworm ◽  
Temperature Dependent ◽  
Maturation Period ◽  
Phenological Model ◽  
Model Based ◽  
Egg Maturation ◽  
Adult Parasitoid ◽  
Specific Mortality

AbstractThe effects of weather on the spruce budworm parasitoid, Apanteles fumiferanae Vier., are examined. A phenological model based on temperature-dependent rates of development and longevity is developed and validated with field data. The model is then used to explore the effects of age-specific mortality on phenological behaviour of the parasitoid and the seasonal synchrony between the parasitoid and its host over several years. The results show that the parasitoid adult ecloses well before the host reaches an age susceptible to parasitism but that the egg maturation period and the longevity of the parasitoid diminish the consequences of the apparent asynchrony. The historical data reveal that the relative phenological characteristics of A. fumiferanae and its host vary little from year to year. In the second part of the study, temperature is shown to have a strong effect on adult parasitoid activity and on the rate of oviposition.

Signal leakage in f-x deconvolution algorithms

Geophysics ◽  
2017 ◽  
Vol 82 (5) ◽  
pp. W31-W45 ◽  
Author(s):  
Necati Gülünay
Keyword(s):  
Field Data ◽  
New Technologies ◽  
Filter Design ◽  
Synthetic Data ◽  
Data Sets ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
Backward Design ◽  
Use Of Data ◽  
Domain Prediction

The old technology [Formula: see text]-[Formula: see text] deconvolution stands for [Formula: see text]-[Formula: see text] domain prediction filtering. Early versions of it are known to create signal leakage during their application. There have been recent papers in geophysical publications comparing [Formula: see text]-[Formula: see text] deconvolution results with the new technologies being proposed. These comparisons will be most effective if the best existing [Formula: see text]-[Formula: see text] deconvolution algorithms are used. This paper describes common [Formula: see text]-[Formula: see text] deconvolution algorithms and studies signal leakage occurring during their application on simple models, which will hopefully provide a benchmark for the readers in choosing [Formula: see text]-[Formula: see text] algorithms for comparison. The [Formula: see text]-[Formula: see text] deconvolution algorithms can be classified by their use of data which lead to transient or transient-free matrices and hence windowed or nonwindowed autocorrelations, respectively. They can also be classified by the direction they are predicting: forward design and apply; forward design and apply followed by backward design and apply; forward design and apply followed by application of a conjugated forward filter in the backward direction; and simultaneously forward and backward design and apply, which is known as noncausal filter design. All of the algorithm types mentioned above are tested, and the results of their analysis are provided in this paper on noise free and noisy synthetic data sets: a single dipping event, a single dipping event with a simple amplitude variation with offset, and three dipping events. Finally, the results of applying the selected algorithms on field data are provided.

scholarly journals Generalized Hierarchical Model-Based Estimation for Aboveground Biomass Assessment Using GEDI and Landsat Data

2018 ◽  
Vol 10 (11) ◽  
pp. 1832 ◽  
Author(s):  
Svetlana Saarela ◽  
Sören Holm ◽  
Sean Healey ◽  
Hans-Erik Andersen ◽  
Hans Petersson ◽  
...  
Keyword(s):  
Hierarchical Model ◽  
Aboveground Biomass ◽  
Field Data ◽  
Airborne Lidar ◽  
Ecosystem Dynamics ◽  
Alternative Methods ◽  
Optical Data ◽  
Strongly Correlated ◽  
Landsat Data ◽  
Model Based

Recent developments in remote sensing (RS) technology have made several sources of auxiliary data available to support forest inventories. Thus, a pertinent question is how different sources of RS data should be combined with field data to make inventories cost-efficient. Hierarchical model-based estimation has been proposed as a promising way of combining: (i) wall-to-wall optical data that are only weakly correlated with forest structure; (ii) a discontinuous sample of active RS data that are more strongly correlated with structure; and (iii) a sparse sample of field data. Model predictions based on the strongly correlated RS data source are used for estimating a model linking the target quantity with weakly correlated wall-to-wall RS data. Basing the inference on the latter model, uncertainties due to both modeling steps must be accounted for to obtain reliable variance estimates of estimated population parameters, such as totals or means. Here, we generalize previously existing estimators for hierarchical model-based estimation to cases with non-homogeneous error variance and cases with correlated errors, for example due to clustered sample data. This is an important generalization to take into account data from practical surveys. We apply the new estimation framework to case studies that mimic the data that will be available from the Global Ecosystem Dynamics Investigation (GEDI) mission and compare the proposed estimation framework with alternative methods. Aboveground biomass was the variable of interest, Landsat data were available wall-to-wall, and sample RS data were obtained from an airborne LiDAR campaign that produced simulated GEDI waveforms. The results show that generalized hierarchical model-based estimation has potential to yield more precise estimates than approaches utilizing only one source of RS data, such as conventional model-based and hybrid inferential approaches.

AVA analysis after velocity-independent DMO and imaging

Geophysics ◽  
1998 ◽  
Vol 63 (2) ◽  
pp. 686-691 ◽  
Author(s):  
Gerald H. F. Gardner ◽  
Anat Canning
Keyword(s):  
Reflection Coefficient ◽  
Peak Amplitude ◽  
Angle Of Incidence ◽  
Amplitude Variation ◽  
Amplitude Variation With Offset ◽  
The Past ◽  
Reflectivity Function ◽  
Velocity Of Propagation ◽  
Zero Offset ◽  
Amplitude Versus

A common midpoint (CMP) gather usually provides amplitude variation with offset (AVO) information by displaying the reflectivity as the peak amplitude of symmetrical deconvolved wavelets. This puts a reflection coefficient R at every offset h, giving a function R(h). But how do we link h with the angle of incidence, θ, to get the reflectivity function, R(θ)? This is necessary for amplitude versus angle-of-incidence (AVA) analysis. One purpose of this paper is to derive formulas for this linkage after velocity-independent dip-moveout (DMO), done by migrating radial sections, and prestack zero-offset migration. Related studies of amplitude-preserving DMO in the past have dealt with constant-offset DMO but have not given the connection between offset and angle of incidence after processing. The results in the present paper show that the same reflectivity function can be extracted from the imaged volume whether it is produced using radial-trace DMO plus zero-offset migration, constant-offset DMO plus zero-offset migration, or directly by prestack, common-offset migration. The data acquisition geometry for this study consists of parallel, regularly spaced, multifold lines, and the velocity of propagation is constant. Events in the data are caused by an arbitrarily oriented 3-D plane reflector with any reflectivity function. The DMO operation transforms each line of data (m, h, t), i.e., midpoint, half-offset, and time, into an (m1, k, t1) space by Stolt-migrating each radial-plane section of the data, 2h = Ut, with constant velocity U/2. Merging the (m1, k, t1) spaces for all the lines forms an (x, y, k, t1) space, where the first two coordinates are the midpoint location, the third is the new half-offset, and the fourth is the time. Normal moveout (NMO) plus 3-D zero-offset migration of the subspace (x, y, t1) for each k creates a true-amplitude imaged volume (X, Y, k, T). Each peak amplitude in the volume is a reflection coefficient linked to an angle of incidence.

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