VR visualization of large fluid-flow data sets

1999 ◽  
Author(s):  
Marco O. Lanzagorta ◽  
Robert O. Rosenberg ◽  
Alexei Khokhlov ◽  
Almadena Chtchelkanova ◽  
Eddy Kuo
Keyword(s):  
Fluid Flow ◽  
Data Sets ◽  
Flow Data

Representation and display of vector field topology in fluid flow data sets

Computer ◽  
1989 ◽  
Vol 22 (8) ◽  
pp. 27-36 ◽  
Author(s):  
J. Helman ◽  
L. Hesselink
Keyword(s):  
Fluid Flow ◽  
Vector Field ◽  
Data Sets ◽  
Flow Data ◽  
Vector Field Topology

A New Concept in Generalizing Non-Newtonian Fluid Flow Data

1965 ◽  
Vol 8 (2) ◽  
pp. 184-190 ◽  
Author(s):  
W. A. Wright ◽  
W. W. Crouse
Keyword(s):  
Fluid Flow ◽  
Newtonian Fluid ◽  
Flow Data

Modeling Traffic Flows with Fluid Flow Model

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Paulus Setiawan Suryadjaja ◽  
◽  
Maclaurin Hutagalung ◽  
Herman Yoseph Sutarto ◽  
◽  
...  
Keyword(s):  
Fluid Flow ◽  
Traffic Flow ◽  
Flow Model ◽  
Intelligent Transportation System ◽  
Macroscopic Model ◽  
Chain Process ◽  
Data Traffic ◽  
Flow Data ◽  
Order Markov Chain ◽  
Parameter Values

This Research presents a macroscopic model of traffic flow as the basis for making Intelligent Transportation System (ITS). The data used for modeling is The number of passing vehicles per three minutes. The traffic flow model created in The form of Fluid Flow Model (FFM). The parameters in The model are obtained by mixture Gaussian distribution approach. The distribution consists of two Gaussian distributions, each representing the mode of traffic flow. In The distribution, intermode shifting process is illustrated by the first-order Markov chain process. The parameters values are estimated using The Expectation-maximization (EM) algorithm. After The required parameter values are obtained, traffic flow is estimated using the Observation and transition-basedmost likely estimates Tracking Particle Filter (OTPF). To Examine the accuracy of the model has been made, the model estimation results are compared with the actual traffic flow data. Traffic flow data is collected on Monday 20 September 2017 at 06.00 to 10.00 on DipatiukurRoad, Bandung. The proposed model has accuracy with MAPE value below 10%, or falls into highly accurate categories

Evaluation of Fractured Reservoirs

1969 ◽  
Vol 9 (01) ◽  
pp. 28-38 ◽  
Author(s):  
G.R. Pickett ◽  
E.B. Reynolds
Keyword(s):  
Fluid Flow ◽  
Fractured Reservoirs ◽  
Fractured Reservoir ◽  
Flow Data ◽  
Fracture Detection ◽  
Transient Pressure ◽  
Variable Intensity ◽  
Reservoir Volume ◽  
Fracture Systems ◽  
Different Sources

Abstract Efforts were made to find improved means for locating fractures penetrated by a wellbore and for estimating fracture reservoir volume. The four approaches to the problem utilized acoustic logs, porosity estimates from different sources, transient pressure and fluid flow data, and resistivity logs. Acoustic amplitude attenuation and acoustic variable-intensity interference patterns have been used to locate fractures. Although amplitude logs have often proved useful for fracture detection, they are frequently inconclusive when used alone. This is due partially to variations in amplitude caused by factors other than fracturing. The variable-intensity interference patterns produced by borehole discontinuities in casing and in open-hole fractured sections were found to be quite useful in detecting fractures; but, like amplitude logs, they are not definitive by themselves. A technique has been developed that uses porosity estimate comparisons to evaluate fractured reservoirs. If this technique is used with acoustic variable-intensity interference patterns, it may be helpful for delineating fractured zones and for estimating fracture porosity. Transient pressure behavior observed for a fractured reservoir was found to be in agreement with that theoretically predicted for linear flow systems. Since this behavior is markedly different from that of a homogeneous reservoir, interpretation of transient pressures may provide a means of recognizing fractures. Other helpful techniques employing pressure and fluid flow data are comparison of calculated kh's for injection and withdrawal of fluids, comparison of calculated kh's for different rates of injection, and calculation of k/phi's from pressure and log data, where k is permeability, h is producing thickness, and phi is porosity. Some of these techniques also present possibilities for calculation of reservoir volumes. The fourth approach to fracture detection showed that, under certain conditions, an induction log can be used to detect a resistivity anomaly opposite a fractured zone. Although some of the techniques discussed show promise of being helpful, further study will be required before evaluations of fractured reservoirs become as satisfactory as evaluations of "normal" porosity reservoirs. Introduction Experience has shown that the presence of a fractured system can improve the productivity of hydrocarbon reservoirs. In some cases, fracture void space also supplies a significant portion of the total porosity. However, quantitative determination of the contribution of fracture systems to production from petroleum reservoirs has proven difficult. This is due in part to lack of consistently successful techniques for locating and usefully describing fracture systems penetrated by a wellbore. This paper presents the initial results of a research program on the use of borehole measurements for evaluation of fractured reservoirs. The objectives of this research are to find improved means forlocating fractures penetrated by a wellbore, andestimating in-situ reservoir volume contained within fracture systems in communication with the wellbore. This progress report will describe our attempts to date to use four types of data for fractured reservoir evaluation:acoustic logs,porosity estimates from different sources,transient pressure and fluid flow data, andresistivity logs. ACOUSTIC LOGS Amplitude Logs The acoustic amplitude log is one of the most widely used measurements in attempts to detect fractures. SPEJ P. 28ˆ

High-Performance Computing for Fluid Flow and Heat Transfer

2002 ◽  
Author(s):  
Darrell W. Pepper ◽  
Joseph M. Lombardo
Keyword(s):  
Heat Transfer ◽  
Fluid Flow ◽  
High Performance ◽  
Daily Basis ◽  
Data Sets ◽  
Graphical Displays ◽  
Levels Of Detail ◽  
Flow And Heat Transfer ◽  
Micro Level ◽  
Performance Computing

The use of computers in heat transfer and fluid flow has become so commonplace today that no one would consider working in either field without some knowledge of computing. Problems are now being solved on a daily basis that even a few years ago were considered intractable. While we once thought that a problem with a few million nodes was huge a few years ago, researchers are now addressing problems with over 100 million nodes. At such levels of detail, one can begin to model processes at the micro level of physics. When researchers are able to quickly analyze these gigantic data sets and can generate insightful graphical displays, the understanding of fundamental processes and governing relations will escalate tremendously.

scholarly journals Focused fluid seepage related to variations in accretionary wedge structure, Hikurangi margin, New Zealand

Geology ◽  
2019 ◽  
Vol 48 (1) ◽  
pp. 56-61 ◽  
Author(s):  
Sally J. Watson ◽  
Joshu J. Mountjoy ◽  
Philip M. Barnes ◽  
Gareth J. Crutchley ◽  
Geoffroy Lamarche ◽  
...  
Keyword(s):  
Fluid Flow ◽  
New Zealand ◽  
Fluid Pressure ◽  
Data Sets ◽  
Accretionary Wedge ◽  
Fault Mechanics ◽  
Spatial Coverage ◽  
Fluid Seepage ◽  
Pressure Regime ◽  
Subduction Setting

Abstract Hydrogeological processes influence the morphology, mechanical behavior, and evolution of subduction margins. Fluid supply, release, migration, and drainage control fluid pressure and collectively govern the stress state, which varies between accretionary and nonaccretionary systems. We compiled over a decade of published and unpublished acoustic data sets and seafloor observations to analyze the distribution of focused fluid expulsion along the Hikurangi margin, New Zealand. The spatial coverage and quality of our data are exceptional for subduction margins globally. We found that focused fluid seepage is widespread and varies south to north with changes in subduction setting, including: wedge morphology, convergence rate, seafloor roughness, and sediment thickness on the incoming Pacific plate. Overall, focused seepage manifests most commonly above the deforming backstop, is common on thrust ridges, and is largely absent from the frontal wedge despite ubiquitous hydrate occurrences. Focused seepage distribution may reflect spatial differences in shallow permeability architecture, while diffusive fluid flow and seepage at scales below detection limits are also likely. From the spatial coincidence of fluids with major thrust faults that disrupt gas hydrate stability, we surmise that focused seepage distribution may also reflect deeper drainage of the forearc, with implications for pore-pressure regime, fault mechanics, and critical wedge stability and morphology. Because a range of subduction styles is represented by 800 km of along-strike variability, our results may have implications for understanding subduction fluid flow and seepage globally.

Estimation of constraint parameters in optimal power flow data sets

2015 ◽  
Author(s):  
Daniel K. Molzahn ◽  
Zev B. Friedman ◽  
Bernard C. Lesieutre ◽  
Christopher L. DeMarco ◽  
Michael C. Ferris
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Data Sets ◽  
Flow Data ◽  
Optimal Power

Computational framework for discontinuity network characterization

2020 ◽  
Author(s):  
Thomas Poulet ◽  
Ulrich Kelka ◽  
Stefan Westerlund ◽  
Luk Peeters
Keyword(s):  
Fluid Flow ◽  
Large Scale ◽  
Spatial Arrangement ◽  
Data Sets ◽  
Two Dimensional ◽  
Fracture Networks ◽  
Underlying Distribution ◽  
Network Characterization ◽  
Discontinuity Network ◽  
The Impact

<p>The topological and geometrical description of fault and fracture networks is an essential first step in any investigation of fractured or faulted media. The spatial arrangement, density, connectivity, and geometry of the discontinuities strongly impact the physical properties of the media such as resilience and permeability. Obtaining reliable metrics for characterizing fault and fracture networks is of interest for mining engineering, reservoir characterization, groundwater management, and studies on the regional fluid flow history. During large-scale studies, we mostly rely on two-dimensional lineaments obtained through structural mapping, outcrop analysis, or remote sensing. An efficient and widely applicable framework for discontinuity network characterization should therefore be based on the analysis of the frequently available two-dimensional data sets.</p><p>Here, we present an automated framework for efficient and robust characterization of the geometric and topologic parameters of discontinuity networks. The geometry of the lineaments is characterised based on orientation, length, and sinuosity. The underlying distribution of these parameters are determined, and representative probability density functions are reported. The connection between the geometric parameters is validated, e.g. correlation between orientation and length. The spatial arrangement is determined by classical line- and window-sampling, by assessing the fractal dimension, and via graph-based topology analysis.</p><p>In addition to the statistical analysis of lineament networks, we show how the graph data structure can be utilized for further characterization by linking it to raster data such as magnetic, gravimetric, or elevation. This procedure not only yields an additional means for lineament characterization but also allows users to assess dominant pathways based, for instance, on hydraulic gradients. We demonstrate the applicability of our algorithm on synthetic data sets and real-world case studies on mapped fault and fracture networks.</p><p>We finally show how our framework can also be utilized to design detailed numerical studies on the fluid flow properties of analysed networks by conditioning mesh refinement on the type and number of intersections. In addition, due to known scaling relationships our framework can help to determine appropriate parameters for the simulations. We provide examples of statistically parametrized fluid flow simulations in natural discontinuity networks and show the impact of conceptualizing the lineaments as conduits, barriers or conduit-barrier systems.</p>

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