scholarly journals Geostatistical modeling of porosity and evaluating the local and global distribution

2021 ◽  
Author(s):  
MohammadHossein GhojehBeyglou
Keyword(s):  
Reservoir Characterization ◽  
Correlation Coefficients ◽  
Global Distribution ◽  
Geostatistical Simulation ◽  
Sequential Gaussian Simulation ◽  
Estimation Methods ◽  
Data Sets ◽  
Cross Sectional ◽  
Simple Kriging ◽  
The Cross

AbstractPorosity is one of the main variables needed for reservoir characterization. For this volumetric variable, there are many methods to simulate the spatial distribution. In this article, porosity was analyzed and modeled in the local and global distribution. For simulation, Sequential Gaussian simulation (SGS) and Gaussian Random Function (GRFS) were applied. Also, kriging was used to estimate the porosity at specific locations. The main purpose of this work was to investigate the porosity to compare geostatistical simulation and estimation methods in a sandstone reservoir as a real case study. First, the data sets were normalized by the Normal Scores Transformation (NST) and stratigraphic coordinate. The model of experimental variograms was fitted in the vertical and horizontal directions. For the simulation methods, 10 realizations were generated by each method. The Q-Q plots were calculated, and both sets of quintiles (Target Porosity Distribution versus Porosity realization) came from normal distributions with the following correlation coefficients: 0.93, 0.94 and 0.97 related to GRFS, SGS and Kriging, respectively. The extracted variograms from realizations showed that the kriging couldn’t reproduce the variograms with global distribution. For local validation, the cross-validation was evaluated and three wells were omitted. The re-estimation of porosity was considered at located well logs through the well sections window where the kriging had a better performance with minimum error to estimate porosity locally. Finally, the cross-sectional models were generated by each algorithm which showed that the simple kriging tries to produce smoother distribution, whereas conditional simulations (SGS and GRFS) try to represent more global-detailed sections.

Estimation of carcass composition by computer image analysis in the cross sections of cross-bred steers

1996 ◽  
Vol 76 (4) ◽  
pp. 497-506 ◽  
Author(s):  
A. B. Karnuah ◽  
K. Moriya ◽  
Y. Sasaki ◽  
K. Mitani ◽  
T. Yamazaki
Keyword(s):  
Image Analysis ◽  
Cross Section ◽  
Computer Image ◽  
Correlation Coefficients ◽  
Carcass Composition ◽  
Data Sets ◽  
Computer Image Analysis ◽  
Data Set ◽  
Stepwise Procedure ◽  
The Cross

Estimation equations for carcass composition were obtained using the information extracted from the carcass cross section by Computer Image Analysis (CIA). The total kilograms of lean, fat, and bone, and their percentages, were measured on the left side of the carcasses of F1 (cross-bred between Japanese Black and Holstein) steers by physical dissection. Traced data of the cross section between the 5th and 6th ribs (Data set I) and pictures of carcass cross section between the 7th and 8th ribs (Data set II) were subjected to image analysis. Various information on both the individual muscles and the overall outline of the cross section was extracted by the CIA technique. Maximum R2 improvement method of the stepwise procedure was used to choose the best regression equation to estimate carcass composition as total kilograms and percentages of lean, fat, and bone. The data sets were also adjusted for age and the stepwise procedure was also conducted. Coefficients of determination, adjusted for the degrees of freedom (adjusted R2) of the regression equations for estimating carcass composition, were high, i.e., 0.779 to 0.959 for kilograms of lean, fat, and bone, whereas for the percentages of lean, fat, and bone were high, i.e., 0.788 to 0.952, respectively. For the adjusted data, the adjusted R2 for estimating kilograms of lean, fat, and bone with Data sets I and II were 0.729, 0.633, and 0.598, and 0.813, 0.806, and 0.878, respectively, while for the percentages of lean, fat, and bone were 0.793, 0.623, and 0.378, and 0.953, 0.989, and 0.467, respectively. When the estimation equation obtained from the unadjusted Data set I was fitted with the information extracted from Data set II, the correlation coefficients between the values estimated by the equation and the values obtained by physical dissection on carcass composition were high, ranging from 0.70 to 0.92. On the other hand, the correlation coefficients obtained from the adjusted data sets were low. Key words: Estimation equation, computer image analysis, carcass composition, carcass cross section, F1 steers

scholarly journals Estimating long-run effects and the exponent of cross-sectional dependence: An update to xtdcce2

2021 ◽  
Vol 21 (3) ◽  
pp. 687-707
Author(s):  
Jan Ditzen
Keyword(s):  
Error Correction ◽  
Error Correction Model ◽  
Estimation Methods ◽  
Cross Sectional ◽  
Correction Model ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Long Run ◽  
Cross Sectional Dependence ◽  
The Cross

In this article, I describe several updates to xtdcce2 (Ditzen, 2018, Stata Journal 18: 585–617). First, I explain how to estimate long-run effects in models with cross-sectional dependence. I review three methods to estimate the long-run effects and discuss their implementation into Stata using xtdcce2. Two of the estimation methods build on Chudik et al. (2016, Advances in Econometrics: Vol. 36—Essays in Honor of Aman Ullah, 85–135): the cross-sectionally augmented distributed lag and the cross-sectionally augmented autoregressive distributed lag estimator. As a third alternative, I review an error-correction model in the presence of cross-sectional dependence. Second, I explain how to estimate the exponent of cross-sectional dependence using xtcse2 following Bailey, Kapetanios, and Pesaran (2016, Journal of Applied Econometrics 31: 929–960; 2019, Sankhyā 81: 46–102).

Ultrasound-Based Mechanical Adaptation of Achilles Tendon After 12-Week Running with Minimalist Shoes

2020 ◽  
Vol 10 (5) ◽  
pp. 1205-1209
Author(s):  
Xini Zhang ◽  
Zhen Luo ◽  
Junqing Wang ◽  
Yang Yang ◽  
Weijie Fu
Keyword(s):  
Achilles Tendon ◽  
Isometric Contraction ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Cross Sectional Area ◽  
Sectional Area ◽  
Cross Sectional ◽  
Mechanical Adaptation ◽  
Intraclass Correlation Coefficients ◽  
The Cross

This study aimed to investigate the effect of a 12-week running program using minimalist shoes on ultrasoundbased mechanical adaptation of Achilles tendon (AT). Fifteen male recreational runners accustomed to run in standard cushioned shoes with rearfoot strike pattern were recruited. They were required to wear minimalist shoes without a compulsory transition in foot strike pattern, and be involved in a 12-week running program. Before and after the intervention, the cross-sectional area of AT was collected in the prone position via an ultrasound device. The ankle plantarflexion moment, recorded on an isokinetic dynamometer, was synchronized to the image changes in vivo AT length. Intraclass correlation coefficient was determined to evaluate the intraand interobserver variabilities. Paired t-test was used to quantify the effects of training program (pre- and posttraining) on each variable of the cross-sectional area, AT force, AT stress, and AT strain during an isometric contraction. Seven participants dropped out after the intervention. The results showed that the intraclass correlation coefficients for the intra- and interobserver reliabilities were good to excellent (intraclass correlation coefficients = 0.895–0.996) for the cross-sectional area and elongation. After 12-week running with minimalist shoes, plantarflexion moment, AT force, AT stress, and AT strain significantly increased during an isometric contraction (P < 0.05). The mechanical adaptation of AT improved after 12-week running with minimalist shoes by more efficient energy storage and release, which could prevent or reduce the risk of injury potentially.

Impacts of size and competition on tree form and distribution of aboveground biomass in Scots pine

1998 ◽  
Vol 28 (2) ◽  
pp. 216-227 ◽  
Author(s):  
Annikki Mäkelä ◽  
Petteri Vanninen
Keyword(s):  
Scots Pine ◽  
Data Sets ◽  
Allometric Relationships ◽  
Cross Sectional ◽  
Tree Form ◽  
Pipe Model ◽  
Crown Volume ◽  
Crown Structure ◽  
The Cross ◽  
Age Series

Studies on tree allometry have often focused on the average tree of a representative stand across an age gradient. Another dimension of change in tree form is the variation caused by differences in competitive status, evident between trees of one stand or between stands of comparable age but different stocking densities. This study compares the structural relationships of dominant Scots pine (Pinus sylvestris L.) trees over a wide age range with those in young trees of similar age but different competitive status. Allometric relationships are developed between biomass components and diameter, and crown structure is analysed in terms of crown allometry, pipe model relationships, and foliage density. The differences in allometry seem to be largely due to the rise of the crown base, which is positively correlated with size in the age series and negatively correlated with size in the cross-sectional data. The allometric relationships of the crown are less variable, but differences are found in the crown size to foliage biomass ratios between the two data sets. In the age series, foliage biomass is proportional to crown surface area, while in the cross-sectional data, it is proportional to crown volume. It is concluded that the reaction to competition for light is twofold: (1) to allocate new foliage higher up and, consequently, to lift the crown base, and (2) to grow sparser crowns.

On the cross-sectional shape of the cellulose crystallites in the tunicate Halocynthia papillosa

1990 ◽  
Vol 48 (3) ◽  
pp. 566-567
Author(s):  
J.-F. Revol ◽  
Y. Van Daele ◽  
F. Gaill
Keyword(s):  
Contrast Imaging ◽  
Animal Kingdom ◽  
Bright Field ◽  
Field Mode ◽  
Cross Sectional ◽  
Ultrathin Sections ◽  
The Cross ◽  
Sectional Shape ◽  
Valonia Ventricosa ◽  
C Nmr

The only form of cellulose which could unequivocally be ascribed to the animal kingdom is the tunicin that occurs in the tests of the tunicates. Recently, high-resolution solid-state l3C NMR revealed that tunicin belongs to the Iβ form of cellulose as opposed to the Iα form found in Valonia and bacterial celluloses. The high perfection of the tunicin crystallites led us to study its crosssectional shape and to compare it with the shape of those in Valonia ventricosa (V.v.), the goal being to relate the cross-section of cellulose crystallites with the two allomorphs Iα and Iβ.In the present work the source of tunicin was the test of the ascidian Halocvnthia papillosa (H.p.). Diffraction contrast imaging in the bright field mode was applied on ultrathin sections of the V.v. cell wall and H.p. test with cellulose crystallites perpendicular to the plane of the sections. The electron microscope, a Philips 400T, was operated at 120 kV in a low intensity beam condition.

Leader-Member Exchange (LMX) Impact on Work-Home Interference in a South African Commuter Transport Engineering Company

2019 ◽  
Vol 43 ◽  
Author(s):  
Jan Christoff Visagie ◽  
Michael M. Jones ◽  
Herman L. Linde
Keyword(s):  
South African ◽  
Structural Equation ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Leader Member Exchange ◽  
Negative Consequences ◽  
Dyadic Relationship ◽  
Cross Sectional ◽  
Engineering Company ◽  
Member Exchange

The South African workplace is confronted with many leadership challenges, specifically those relating to the employment relationship between subordinates and their supervisors. A high-quality relationship is essential, considering the work-family spillovers employees experience. Limited research has been conducted on the potential positive and negative consequences of the leader-member exchange (LMX) dyadic relationship. In this study, we used a cross-sectional research design, and drew an employee sample (N = 120) from a commuter transport engineering company. A five-point Likert scale was employed and statistical analyses were carried out using the SAS statistical program. We calculated Pearson correlation coefficients and used structural equation modelling to test the proposed conceptual model to indicate possible correlations between the different variables. The main finding of the study was that the nature of the LMX relationship quality in the relevant company appeared to be high and positively related to work-home enrichment but negatively related to work-home conflict and role overload. The article concludes by making a number of suggestions to respond to challenges.

A Technique for Measuring the Cross-Sectional Axes of the Longissimus Dorsi Muscle and Fat Depth in Lambs1,2

1960 ◽  
Vol 19 (3) ◽  
pp. 803-809
Author(s):  
D. J. Matthews ◽  
R. A. Merkel ◽  
J. D. Wheat ◽  
R. F. Cox
Keyword(s):  
Longissimus Dorsi ◽  
Cross Sectional ◽  
Longissimus Dorsi Muscle ◽  
Dorsi Muscle ◽  
The Cross

Automated Diagonal Slice and View Solution for 3D Device Structure Analysis

2018 ◽  
Author(s):  
Sang Hoon Lee ◽  
Jeff Blackwood ◽  
Stacey Stone ◽  
Michael Schmidt ◽  
Mark Williamson ◽  
...  
Keyword(s):  
Cross Section ◽  
Focused Ion Beam ◽  
Ion Beam ◽  
Image Data ◽  
Planar Surface ◽  
Device Structure ◽  
Cross Sectional ◽  
Device Structures ◽  
The Cross ◽  
Planar Analysis

Abstract The cross-sectional and planar analysis of current generation 3D device structures can be analyzed using a single Focused Ion Beam (FIB) mill. This is achieved using a diagonal milling technique that exposes a multilayer planar surface as well as the cross-section. this provides image data allowing for an efficient method to monitor the fabrication process and find device design errors. This process saves tremendous sample-to-data time, decreasing it from days to hours while still providing precise defect and structure data.

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