scholarly journals Constructing dense grid-free linear 3-graphs

2021 ◽  
pp. 1
Author(s):  
Lior Gishboliner ◽  
Asaf Shapira
Keyword(s):  
Dense Grid

Acquire Ocean Bottom Seismic Data and Time-Lapse Geochemistry Data Simultaneously to Identify Compartmentalization and Map Hydrocarbon Movement

2021 ◽  
Author(s):  
Rick Schrynemeeckers
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Time Lapse ◽  
Field Trials ◽  
Detection Methods ◽  
Ocean Bottom ◽  
Field Development ◽  
Dense Grid ◽  
Hydrocarbon Charge ◽  
Sweet Spots

Abstract Current offshore hydrocarbon detection methods employ vessels to collect cores along transects over structures defined by seismic imaging which are then analyzed by standard geochemical methods. Due to the cost of core collection, the sample density over these structures is often insufficient to map hydrocarbon accumulation boundaries. Traditional offshore geochemical methods cannot define reservoir sweet spots (i.e. areas of enhanced porosity, pressure, or net pay thickness) or measure light oil or gas condensate in the C7 – C15 carbon range. Thus, conventional geochemical methods are limited in their ability to help optimize offshore field development production. The capability to attach ultrasensitive geochemical modules to Ocean Bottom Seismic (OBS) nodes provides a new capability to the industry which allows these modules to be deployed in very dense grid patterns that provide extensive coverage both on structure and off structure. Thus, both high resolution seismic data and high-resolution hydrocarbon data can be captured simultaneously. Field trials were performed in offshore Ghana. The trial was not intended to duplicate normal field operations, but rather provide a pilot study to assess the viability of passive hydrocarbon modules to function properly in real world conditions in deep waters at elevated pressures. Water depth for the pilot survey ranged from 1500 – 1700 meters. Positive thermogenic signatures were detected in the Gabon samples. A baseline (i.e. non-thermogenic) signature was also detected. The results indicated the positive signatures were thermogenic and could easily be differentiated from baseline or non-thermogenic signatures. The ability to deploy geochemical modules with OBS nodes for reoccurring surveys in repetitive locations provides the ability to map the movement of hydrocarbons over time as well as discern depletion affects (i.e. time lapse geochemistry). The combined technologies will also be able to: Identify compartmentalization, maximize production and profitability by mapping reservoir sweet spots (i.e. areas of higher porosity, pressure, & hydrocarbon richness), rank prospects, reduce risk by identifying poor prospectivity areas, accurately map hydrocarbon charge in pre-salt sequences, augment seismic data in highly thrusted and faulted areas.

An Algorithm to Slice 3-D Shapes for Reconstruction in Prototyping Systems

1991 ◽  
Author(s):  
K. L. Chalasani ◽  
B. Grogan ◽  
A. Bagchi ◽  
C. C. Jara-Almonte ◽  
A. A. Ogale ◽  
...  
Keyword(s):  
Data Structure ◽  
Rapid Prototyping ◽  
Surface Finish ◽  
Cyclic Order ◽  
Contour Tracing ◽  
Building Process ◽  
Dense Grid ◽  
A Chain ◽  
Definition Of

Abstract Rapid Prototyping (RP) processes reduce the time consumed in the manufacture of a prototype by producing parts directly from a CAD representation, without tooling. The StereoLithography Apparatus (SLA), and most other recent RP processes build a 3-D object from 2.5-D layers. Slicing is the process of defining layers to be built by the system. In this paper a framework is proposed for the development of algorithms for the representation and definition of layers for use in the SLA, with a view to determine if the slicing algorithms will affect surface finish in any significant manner. Currently, it is not possible to automatically vary slice thicknesses within the same object, using the existent algorithm. Also, it would be useful to use a dense grid for hatching or skin filling any given layer, or to change the hatch-pattern if desired. In addition, simulation of the layered building process would be helpful, so that the user can prespecify parameters that need to be varied during the process. The proposed framework incorporates these and other features. Two approaches for determining contours on each slice are suggested and their implementation is discussed. In the first, the layers are defined by the intersections of a plane with the surfaces defining the object. The plane is moved up from the base of the object as it is being built in increments. All intersections found are stored in a data structure, and sorted in head to tail fashion to define a contour for all closed areas on a layer. The second approach uses a scanline-type search to look for an intersection that will trigger a contour-tracing procedure. The contour-tracer is invoked whenever an unused edge is found in the search. This saves storage and sorting times, because the contour is determined as a chain of edges, in cyclic order. It is envisaged that results of this work on the SLA can be applied to other RP processes entailing layered building.

Study of Scale-Down Method for Dense Grid Points

2013 ◽  
Vol 734-737 ◽  
pp. 3011-3015
Author(s):  
Sheng Yun Yu ◽  
Chang He Song ◽  
Hai Ying Xu
Keyword(s):  
Numerical Simulation ◽  
Geological Model ◽  
Three Dimension ◽  
Reservoir Heterogeneity ◽  
Geological Models ◽  
Scale Down ◽  
Dense Grid ◽  
Grid Points ◽  
Renormalization Method

The data of three-dimension geological models are very large, this kind of three -dimension geological model can not be directly used for numerical simulation and must be scaled down. The reservoir parameters, especially permeability, are scaled down by the simple renormalization method. The interbeds and parts of strong heterogeneity are filled back. The simple renormalization method is good through evaluation , not only it reduces the number of grid points, but also retains reservoir heterogeneity.

Visualization of microbial biofilms in case of digestive disorders in lambs

2021 ◽  
Vol 1 (1) ◽  
pp. 59-67
Author(s):  
E. M. Lenchenko ◽  
N. P. Sachivkina ◽  
D. A. Blumenkrants ◽  
A. Yu. Arsenyuk
Keyword(s):  
Biofilm Formation ◽  
Three Dimensional ◽  
Density Measurement ◽  
Yeast Cells ◽  
Active Growth ◽  
Microbial Structures ◽  
Microbial Biofilms ◽  
Dense Grid ◽  
Digestive Disorders ◽  
Biofilm Structure

The paper demonstrates morphometric and densitometric parameters of microbial biofilms recovered from lambs with digestive disorders. Changes of quantitative and species composition of the intestinal microbiocenoses in the lambs with digestive disorders were compared with the ones of the clinically healthy lambs. Light microscopy results demonstrated formation of three-dimensional biofilm structure in the form of dense grid consisting of gram-negative and gram-positive bacteria, yeast cells, hyphas and pseudohyphas surrounded with intracellular polymer matrix. Presence of blastospores aided to the increased number of cells attached to the substrate, and biofilm was formed, which consisted of rod and round cells attached to the microfungi cells. In the process of dispersion that occurred during the destruction of the intercellular matrix and bacterial and yeast cell detachment, branched structures separated from the microcolonies and colonized microorganism- free regions of the substrate. The intensity of biofilm formation by the microorganisms under study was evaluated by optic density measurement in 48 hours of cultivation. Fluorescence microscopy results demonstrated that the dynamics of changes of the viable microbial structures was specified by intermittent periods of increased or decreased biofilm formation intensity. Cells characterized by active growth and replication and forming alternating subpopulations were detected in the examined microbial cultures. When determining the viability of the microorganisms in the biofilms, the viable (green fluorescence) and non-viable (red fluorescence) cells were differentiated.

scholarly journals Lab Non Destructive Test to Analyze the Effect of Corrosion on Ground Penetrating Radar Scans

2019 ◽  
Vol 11 (23) ◽  
pp. 2814 ◽  
Author(s):  
Sossa ◽  
Pérez-Gracia ◽  
González-Drigo ◽  
Rasol
Keyword(s):  
Ground Penetrating Radar ◽  
Wave Amplitude ◽  
Metallic Surface ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Accurate Analysis ◽  
Reflected Wave ◽  
Dense Grid ◽  
Ground Penetrating ◽  
Non Destructive

Corrosion is a significant damage in many reinforced concrete structures, mainly in coastal areas. The oxidation of embedded iron or steel elements degrades rebar, producing a porous layer not adhered to the metallic surface. This process could completely destroy rebar. In addition, the concrete around the metallic targets is also damaged, and a dense grid of fissures appears around the oxidized elements. The evaluation of corrosion is difficult in early stages, because damage is usually hidden. Non-destructive testing measurements, based on non-destructive testing (NDT) electric and magnetic surveys, could detect damage as consequence of corrosion. The work presented in this paper is based in several laboratory tests, which are centered in defining the effect of different corrosion stage on ground penetrating radar (GPR) signals. The analysis focuses on the evaluation of the reflected wave amplitude and its behavior. The results indicated that an accurate analysis of amplitude decay and intensity could most likely reveal an approach to the state of degradation of the embedded metallic targets because GPR images exhibit characteristics that depend on the effects of the oxidized rebar and the damaged concrete. These characteristics could be detected and measured in some cases. One important feature is referred to as the reflected wave amplitude. In the case of corroded targets, this amplitude is lower than in the case of reflection on non-oxidized surfaces. Additionally, in some cases, a blurred image appears related to high corrosion. The results of the tests highlight the higher amplitude decay of the cases of specimens with corroded elements.

Gridded Statistical Downscaling Based on Interpolation of Parameters and Predictor Locations for Summer Daily Precipitation in North China

2019 ◽  
Vol 58 (10) ◽  
pp. 2295-2311
Author(s):  
Yonghe Liu ◽  
Jinming Feng ◽  
Zongliang Yang ◽  
Yonghong Hu ◽  
Jianlin Li
Keyword(s):  
Distance Function ◽  
Statistical Downscaling ◽  
Spatial Dependence ◽  
Large Scale ◽  
North China ◽  
Dynamical Downscaling ◽  
Daily Precipitation ◽  
Summer Precipitation ◽  
Single Station ◽  
Dense Grid

AbstractFew statistical downscaling applications have provided gridded products that can provide downscaled values for a no-gauge area as is done by dynamical downscaling. In this study, a gridded statistical downscaling scheme is presented to downscale summer precipitation to a dense grid that covers North China. The main innovation of this scheme is interpolating the parameters of single-station models to this dense grid and assigning optimal predictor values according to an interpolated predictand–predictor distance function. This method can produce spatial dependence (spatial autocorrelation) and transmit the spatial heterogeneity of predictor values from the large-scale predictors to the downscaled outputs. Such gridded output at no-gauge stations shows performances comparable to that at the gauged stations. The area mean precipitation of the downscaled results is comparable to other products. The main value of the downscaling scheme is that it can obtain reasonable outputs for no-gauge stations.

scholarly journals Field Proximal Soil Sensor Fusion for Improving High-Resolution Soil Property Maps

Soil Systems ◽  
2020 ◽  
Vol 4 (3) ◽  
pp. 52
Author(s):  
Gustavo M. Vasques ◽  
Hugo M. Rodrigues ◽  
Maurício R. Coelho ◽  
Jesus F. M. Baca ◽  
Ricardo O. Dart ◽  
...  
Keyword(s):  
Soil Properties ◽  
Ordinary Kriging ◽  
Soil Property ◽  
Clay Content ◽  
Exchange Capacity ◽  
Organic C ◽  
Covariate Data ◽  
Independent Validation ◽  
Soil Sensors ◽  
Dense Grid

Mapping soil properties, using geostatistical methods in support of precision agriculture and related activities, requires a large number of samples. To reduce soil sampling and measurement time and cost, a combination of field proximal soil sensors was used to predict and map laboratory-measured soil properties in a 3.4-ha pasture field in southeastern Brazil. Sensor soil properties were measured in situ on a 10 × 10-m dense grid (377 samples) using apparent electrical conductivity meters, apparent magnetic susceptibility meter, gamma-ray spectrometer, water content reflectometer, cone penetrometer, and portable X-ray fluorescence spectrometer (pXRF). Soil samples were collected on a 20 × 20-m thin grid (105 samples) and analyzed in the laboratory for organic C, sum of bases, cation exchange capacity, clay content, soil volumetric moisture, and bulk density. Another 25 samples collected throughout the area were also analyzed for the same soil properties and used for independent validation of models and maps. To test whether the combination of sensors enhances soil property predictions, stepwise multiple linear regression (MLR) models of the laboratory soil properties were derived using individual sensor covariate data versus combined sensor data—except for the pXRF data, which were evaluated separately. Then, to test whether a denser grid sample boosted by sensor-based soil property predictions enhances soil property maps, ordinary kriging of the laboratory-measured soil properties from the thin grid was compared to ordinary kriging of the sensor-based predictions from the dense grid, and ordinary cokriging of the laboratory properties aided by sensor covariate data. The combination of multiple soil sensors improved the MLR predictions for all soil properties relative to single sensors. The pXRF data produced the best MLR predictions for organic C content, clay content, and bulk density, standing out as the best single sensor for soil property prediction, whereas the other sensors combined outperformed the pXRF sensor for the sum of bases, cation exchange capacity, and soil volumetric moisture, based on independent validation. Ordinary kriging of sensor-based predictions outperformed the other interpolation approaches for all soil properties, except organic C content, based on validation results. Thus, combining soil sensors, and using sensor-based soil property predictions to increase the sample size and spatial coverage, leads to more detailed and accurate soil property maps.

scholarly journals Analysis of GPR Wave Propagation Using CUDA-Implemented Conformal Symplectic Partitioned Runge-Kutta Method

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Hongyuan Fang ◽  
Jianwei Lei ◽  
Man Yang ◽  
Ziwei Li
Keyword(s):  
Wave Propagation ◽  
Forward Modeling ◽  
Electromagnetic Response ◽  
Acceleration Technique ◽  
Efficient Calculation ◽  
Dense Grid ◽  
Runge Kutta ◽  
Processor Unit ◽  
The Stability ◽  
Ground Penetrating

Accurate forward modeling is of great significance for improving the accuracy and speed of inversion. For forward modeling of large sizes and fine structures, numerical accuracy and computational efficiency are not high, due to the stability conditions and the dense grid number. In this paper, the symplectic partitioned Runge-Kutta (SPRK) method, surface conformal technique, and graphics processor unit (GPU) acceleration technique are combined to establish a precise and efficient numerical model of electromagnetic wave propagation in complex geoelectric structures, with the goal of realizing a refined and efficient calculation of the electromagnetic response of an arbitrarily shaped underground target. The results show that the accuracy and efficiency of ground-penetrating radar (GPR) forward modeling are greatly improved when using our algorithm. This provides a theoretical basis for accurately interpreting GPR detection data and accurate and efficient forward modeling for the next step of inversion imaging.

Detailed motion analysis of the left ventricular myocardium using an MR tagging method with a dense grid

2000 ◽  
Vol 44 (1) ◽  
pp. 73-82 ◽  
Author(s):  
Shin-ichi Urayama ◽  
Tetsuya Matsuda ◽  
Naozo Sugimoto ◽  
Shinobu Mizuta ◽  
Naoaki Yamada ◽  
...  
Keyword(s):  
Motion Analysis ◽  
Ventricular Myocardium ◽  
Left Ventricular ◽  
Left Ventricular Myocardium ◽  
Dense Grid
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