12999638
Descripción
Test por Aiman Zamri, actualizado hace más de 1 año
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Creado por Aiman Zamri
hace alrededor de 6 años
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Pregunta 1
Pregunta
Which of the following are valid guidelines, or rules of thumb, for constructing variograms?
Respuesta
-
a. it is best to start with isotropic variograms before proceeding to investigation of anisotropic variograms
-
b. estimation of variograms should begin with large tolerances, and should be decreased as needed to achieve a clearly defined structure
-
c. use half the maximum possible distance within a region of interest as the maximum lag distance at the which the variogram is calculated
-
d. at least 15 to 20 data pairs are needed for a reliable estimate of the variogram for a given lag distance
Pregunta 2
Pregunta
Which of the following are true statements about variogram models?
Respuesta
-
a. the spherical model is probably the most commonly used model
-
b. any linear combination of nugget, exponential, spherical and Gaussian models is a valid variogram model
-
c. the simplest model is the exponential model
-
d. the Gaussian model is more robust than the exponential model
Pregunta 3
Pregunta
To model the condition of geometric anisotropy, we have to use the same combination of linear models in both directions except with different sills.
Respuesta
- True
- False
Pregunta 4
Pregunta
Which of the following are reasons why we restrict the number of samples to a smaller neighborhood for estimation using kriging?
Respuesta
-
a. Because kriging requires inverting a matrix, using a large number of data points can require an excessive amount of memory and computation time requirements
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b. If too many sample points are used, there is a possibility the matrix will become close to singular
-
c. If we use data points at large distances, we may have to extrapolate beyond the available data in the variogram model
-
d. Restricting the search to closer samples results in a more representative estimate, because of local variations due to a lack of stationarity in practice
-
e. Use of sample points farther away tend to screen sample points that are closer, reducing the accuracy of the estimation
Pregunta 5
Pregunta
The maximum size of the search neighborhood for kriging should be based on the range of the variogram model.
Respuesta
- True
- False
Pregunta 6
Pregunta
Which of the following are true statements about kriging cross validation?
Respuesta
-
a. Cross validation involves the estimation of values at unsampled locations so they can be compared with values at sampled locations
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b. Cross validation can identify glaring errors in estimation, but it does not guarantee a successful kriging operation
-
c. "Jackknifing" is the most common version of cross validation
-
d. Heteroscedasticity of error variance is a desirable outcome of a cross validation exercise
Pregunta 7
Pregunta
Which of the following are true statements about kriging?
Respuesta
-
a. The maximum kriging error variance is the data variance
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b. Simple kriging is the most popular kriging procedure
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c. Kriging is a weighted average of values at sampled locations
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d. Kriging weights assigned to sample values are directly proportional to the covariances among the sample points
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e. Kriging weights assigned to sample values are directly proportional to the covariances between sample points and the unsampled location
Pregunta 8
Pregunta
Ordinary kriging overcomes which of the following problems that can occur with simple kriging?
Respuesta
-
a. the true global mean is rarely known
-
b. all of the other choices
-
c. the local mean within the search neighborhood may vary over the region of interest
-
d. the assumption of first-order stationarity may not be strictly valid
Pregunta 9
Pregunta
In ordinary kriging, the sum of the weights is forced to be zero.
Respuesta
- True
- False
Pregunta 10
Pregunta
Because λ0 is forced to be zero in ordinary kriging, there are only n unknowns to solve for instead of n+1 unknowns as for simple kriging.
Respuesta
- True
- False
Pregunta 11
Pregunta
Weights can be negative in ordinary kriging.
Respuesta
- True
- False
Pregunta 12
Pregunta
The presence of a high nugget effect reduces spatial information, which results in higher error variance.
Respuesta
- True
- False
Pregunta 13
Pregunta
One common application of cross variograms is using high-density seismic data to help estimate permeability at undrilled well locations.
Respuesta
- True
- False
Pregunta 14
Pregunta
Which of the following are true statements about cross variograms?
Respuesta
-
a. the cross covariance is symmetric.
-
b. the cross variogram is symmetric.
-
c. the cross variogram is always non-negative.
-
d. estimation of the cross variogram requires that both variable values be available at locations ui and ui+L.
Pregunta 15
Pregunta
In variogram modeling for two variables, the x variogram, y variogram, and x-y cross variogram must all have the same linear combination of structures and must all have the same sill.
Respuesta
- True
- False
Pregunta 16
Pregunta
In variogram modeling with multiple variables and anisotropy, if all the variograms cannot be modeled well, it is critical to model the cross variograms well while the other models can be sacrificed somewhat.
Respuesta
- True
- False
Pregunta 17
Pregunta
The cross variogram provides a quantitative measure of the spatial relationship between two variables.
Respuesta
- True
- False
Pregunta 18
Pregunta
Additional information from the covariable in cokriging should reduce the error variance as compared to just kriging of the primary variable.
Respuesta
- True
- False
Pregunta 19
Pregunta
Simple cokriging with one secondary variable requires the inversion of a (n+m+2)-size matrix, where n is the number of samples of the primary variable and m is the number of samples of the covariable.
Respuesta
- True
- False
Pregunta 20
Pregunta
Collocated cokriging requires the covariable sample to be available at every location where the primary variable is to be estimated, which increases the matrix size compared to regular (non-collocated) cokriging.
Respuesta
- True
- False
Pregunta 21
Pregunta
Which of the following factors, if favorable, support use of cokriging?
Respuesta
-
a. there is a physical basis for the relationship between the primary variable and covariable
-
b. the primary variable is considerably undersampled
-
c. the relationship between the primary variable and covariable is strong
-
d. the covariable has been used successfully in the past for estimation of the primary variable
-
e. the primary variable and covariable are linearly related
Pregunta 22
Pregunta
The kriging error variance is a good measure of the local uncertainty at the unsampled location.
Respuesta
- True
- False
Pregunta 23
Pregunta
The estimated value from kriging is dependent on the values of the surrounding samples, while the error variance is independent.
Respuesta
- True
- False
Pregunta 24
Pregunta
Estimation by kriging does not reproduce extreme values observed in the sample data because the weights associated with individual samples are nearly always less than one, thus reducing the effects of extreme values.
Respuesta
- True
- False
Pregunta 25
Pregunta
Which of the following characterize the differences between conventional estimation and conditional simulation techniques?
Respuesta
-
a. Conventional estimation does not reproduce extreme values in the sample data, while conditional simulation is able to.
-
b. Conventional estimation does not provide a good estimation of local uncertainty, while conditional simulation is able to.
-
c. Conventional estimation preserves the spatial relationship among the estimated values while conditional simulation does not.
Pregunta 26
Pregunta
A variogram based on estimated values from kriging will have higher sill than the variogram based on sample data.
Respuesta
- True
- False
Pregunta 27
Pregunta
One of the advantages of conditional simulation is that if we create multiple equiprobable realizations and these realizations correctly represent the multivariate distribution, they will bound the true realization.
Respuesta
- True
- False
Pregunta 28
Pregunta
A major disadvantage of grid-based simulation methods is that they do not honor the spatial relationships of reservoir properties.
Respuesta
- True
- False
Pregunta 29
Pregunta
A major disadvantage of object-based simulation methods is that it is difficult to condition data at individual well locations.
Respuesta
- True
- False
Pregunta 30
Pregunta
Estimation using conventional kriging techniques is dependent on the order in which unsampled locations are visited, while simulation using sequential conditional simulation methods is independent of the order in which unsampled locations are visited.
Respuesta
- True
- False
Pregunta 31
Pregunta
In the sequential simulation technique, in addition to selecting the sampled points within the search neighborhood, previously simulated points within the search neighborhood are also selected.
Respuesta
- True
- False
Pregunta 32
Pregunta
The ability to closely reproduce the basic univariate statistics of the conditioning data is one of the best properties of sequential Gaussian simulation.
Respuesta
- True
- False
Pregunta 33
Pregunta
The five-step sequential simulation process is as follows: (1) model variograms, (2) transform the original data into a new domain, (3) determine a random path to visit all the unsampled locations, (4) sequentially estimate values at the unsampled locations, and (5) back-transform the values to the original domain.
Respuesta
- True
- False
Pregunta 34
Pregunta
Grid-based conditional simulation methods employ kriging as part of the simulation process.
Respuesta
- True
- False
Pregunta 35
Pregunta
If full cokriging is used in sequential cosimulation, the following variograms are required for modeling:
Respuesta
-
a. cross-variograms for all pairs of attributes in the original domain
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b. variograms for each attribute in the transformed domain
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c. cross-variograms for all pairs of attributes in the transformed domain
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d. cross-variograms for all pairs of attributes for which there are dependencies in the original domain
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e. cross-variograms for all pairs of attributes for which there are dependencies in the transformed domain
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f. variograms for each attribute in the original domain
Pregunta 36
Pregunta
In a typical reservoir characterization involving cosimulation, geological facies are dependent on porosity and permeability while seismic attributes are dependent on facies and porosity.
Respuesta
- True
- False
Pregunta 37
Pregunta
The primary advantage of sequential cosimulation is its ability to honor the local relationships between multiple attributes, as well as the individual spatial relationships of the multiple attributes.
Respuesta
- True
- False
Pregunta 38
Pregunta
In sequential cosimulation of multiple attributes, at each unsampled location, all the unknown attributes are simulated in sequential order from least independent to most independent to preserve their relationships.
Respuesta
- True
- False
Pregunta 39
Pregunta
If cokriging is used in cosimulation, then the local relationships among the attributes must be linear in the transformed domain.
Respuesta
- True
- False
Pregunta 40
Pregunta
Geostatistical estimation, or kriging, is based on minimizing the variance between the estimation point and the available samples.
Respuesta
- True
- False
Pregunta 41
Pregunta
The variability of a regionalized variable is always zero for distance zero.
Respuesta
- True
- False
Pregunta 42
Pregunta
Estimating the values at unsampled points requires knowledge about the relationship between sampled and unsampled locations.
Respuesta
- True
- False
Pregunta 43
Pregunta
Geological features are randomly distributed in a spatial context.
Respuesta
- True
- False
Pregunta 44
Pregunta
Reservoirs are heterogeneous and have directions of continuity because of their specific depositional, structural, and digenetic histories.
Respuesta
- True
- False
Pregunta 45
Pregunta
Two different reservoir models with similar statistics can be very different in geological features.
Respuesta
- True
- False
Pregunta 46
Pregunta
For a given direction, spatial covariance depends only on the distance and not location.
Respuesta
- True
- False
Pregunta 47
Pregunta
By assuming stationarity, we can use observations from one part of the reservoir to construct variograms for other parts.
Respuesta
- True
- False
Pregunta 48
Pregunta
A Variogram is a measure of similarity between two random variables.
Respuesta
- True
- False
Pregunta 49
Pregunta
The range in variogram is the distance at which the variogram value becomes constant with respect to lag.
Respuesta
- True
- False
Pregunta 50
Pregunta
Kriging allows for production uncertainty analysis.
Respuesta
- True
- False
Pregunta 51
Pregunta
Both Kriging and simulation methods can honor hard data.
Respuesta
- True
- False
Pregunta 52
Pregunta
Both Kriging and simulation methods can honor the local variogram model.
Respuesta
- True
- False
Pregunta 53
Pregunta
Relative to Kriging, the sequential Gaussian simulation is locally accurate.
Respuesta
- True
- False
Pregunta 54
Pregunta
If the random path in sequential Gaussian simulation is not changed, the generated realizations will be identical.
Respuesta
- True
- False
Pregunta 55
Pregunta
Similar to variance, covariance is defined in units that depend on the units of x and y but the correlation coefficient is dimensionless, and its value always falls between the limits of 1 and -1.
Respuesta
- True
- False
Pregunta 56
Pregunta
When the square of the correlation coefficient is used to describe the relationship between two variables, whether the two variables are negatively or positively related cannot be exhibited, but it is a common way in describing the "goodness of fit" in a linear regression between two variables.
Respuesta
- True
- False
Pregunta 57
Pregunta
A Q-Q plot is a scattered plot based on ranked pair data, so two samples with equal size are always required.
Respuesta
- True
- False
Pregunta 58
Pregunta
SGEMS Objects are files with numerical information and there are two types, Data and Grid, both of which specify the location in the file.
Respuesta
- True
- False
Pregunta 59
Pregunta
Geostatistics represents a set of mathematical tools which have deterministic or stochastic components, may represent different types of data at different scales, but cannot fill the interwell space properly.
Respuesta
- True
- False
Pregunta 60
Pregunta
The SGEMS grid(s) has to be specified before attempting any processing that will result in the generation of a grid variable such as Kriging.
Respuesta
- True
- False
Pregunta 61
Pregunta
In SGEMS, grids can only be displayed in graphical form and grid values are stored in binary form.
Respuesta
- True
- False
Pregunta 62
Pregunta
The semivariogram is related to the covariance by the difference between the variance and the spatial covariance regardless of the stationarity of the mean.
Respuesta
- True
- False
Pregunta 63
Pregunta
The spatial covariance always starts with a zero value and increases as the lag distance between the two values increases.
Respuesta
- True
- False
Pregunta 64
Pregunta
Kriging is a form of linear regression and works best for estimation inside a convex hull of the data.
Respuesta
- True
- False
Pregunta 65
Pregunta
The most frequently used types of semi-variogram models are Gaussian, Spherical, and Exponential models.
Respuesta
- True
- False
Pregunta 66
Pregunta
A semivariogram model is:
Respuesta
-
A polynomial expression representing sample variance
-
A mathematical approximation of sample variability
-
A determinate trend in sample values
-
None of the above
Pregunta 67
Pregunta
Assume we have two porosity models generated with the same parameters using Gaussian and exponential models. Identify the variogram model for porosity map given in Figure (1).
Image:
1 (binary/octet-stream)
Respuesta
-
Gaussian Model
-
Exponential Model
Pregunta 68
Pregunta
Assume we have two porosity models generated with the same parameters using Gaussian and exponential models. Identify the variogram model for porosity map given in Figure (2).
Image:
1 (binary/octet-stream)
Respuesta
-
Gaussian Model
-
Exponential Model
Pregunta 69
Pregunta
For the following three basic variogram models, which one has the highest growth at the origin? (i.e. the biggest slope at origin)
Image:
2 (binary/octet-stream)
Respuesta
-
1
-
2
-
3
Pregunta 70
Pregunta
For the following three basic variogram models, which one has the lowest growth at the origin? (i.e. the smallest slope at origin)
Image:
2 (binary/octet-stream)
Respuesta
-
1
-
2
-
3
Pregunta 71
Pregunta
Conditional simulation reproduces the value and location of observations.
Respuesta
- True
- False
Pregunta 72
Pregunta
Kriging method accounts for local variations.
Respuesta
- True
- False
Pregunta 73
Pregunta
Kriging estimation method is appropriate for flow simulation.
Respuesta
- True
- False
Pregunta 74
Pregunta
Sequential Gaussian simulation requires transformation of data to normal scores.
Respuesta
- True
- False
Pregunta 75
Pregunta
Geo-statistical simulation method cannot use secondary data.
Respuesta
- True
- False
Pregunta 76
Pregunta
For collocated cokriging method, the secondary data points have to be at the same locations as the primary data points.
Respuesta
- True
- False
Pregunta 77
Respuesta
-
5.87
-
3.14
-
2.73
-
None of the above
Pregunta 78
Respuesta
-
3.64
-
2.07
-
2.23
-
3.78
Pregunta 79
Pregunta
In the following drawing, we know the attributes at S1, S2, and S3. What is Z(S0)?
As shown, we know the distances in between, e.g. the distance between S1 and S2 is 20. We also know the variogram model.
Image:
5 (binary/octet-stream)
Respuesta
-
21.69
-
21.83
-
22.83
-
23.34
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