Sedimentary Process Simulation: A New Approach for Describing Petrophysical Properties in Three Dimensions for Subsurface Flow Simulations

1996 ◽  
pp. 1-25 ◽  
Author(s):  
Johannes Wendebourg ◽  
John W. Harbaugh
Keyword(s):  
Process Simulation ◽  
Subsurface Flow ◽  
Three Dimensions ◽  
Petrophysical Properties ◽  
Sedimentary Process ◽  
New Approach ◽  
Flow Simulations

Measurement of cortical plate volume based on CBCT of frontal teeth in studies with retrusion and normality

2021 ◽  
pp. 17-21
Author(s):  
N. G. Meskhiya ◽  
I. S. Kopetskiy ◽  
I. A. Nikolskaya ◽  
D. A. Eremin ◽  
O. N. Kovaleva
Keyword(s):  
Orthodontic Treatment ◽  
Soft Tissues ◽  
Three Dimensions ◽  
Cone Beam ◽  
Cortical Plate ◽  
Imaging Method ◽  
New Approach ◽  
Accuracy Of Measurements ◽  
Bone Structures

Cone Beam Computed Tomography (CBCT) is the preferred imaging method for a comprehensive orthodontic examination. Thanks to the development of this technique, clinicians today can make most accurate measurements without fear of errors associated with projection distortion or localization of landmarks on radiographs. The quality of CBCT images gives to orthodontists the ability to analyze bone structures, teeth (even impacted teeth), and soft tissue in three dimensions. The accuracy of measurements of hard and soft tissues from CBCT images determines the accuracy of diagnosis and treatment planning. A fundamentally new approach has been proposed, which makes it possible to thoroughly study the bone tissue surrounding the tooth at the stages of planning orthodontic treatment. Аnalysis of radiation studies of patients with dentoalveolar anomalies was carried out to select the optimal treatment tactics and to control its effectiveness.

Novel Performance Prediction of a Transonic 4.5 Stage Compressor

2012 ◽  
Author(s):  
Andreas Schmitz ◽  
Marcel Aulich ◽  
Dirk Schönweitz ◽  
Eberhard Nicke
Keyword(s):  
Performance Prediction ◽  
Three Dimensions ◽  
Navier Stokes ◽  
3D Flow ◽  
3D Design ◽  
New Approach ◽  
Multi Stage ◽  
Compressor Design ◽  
Basic Parameters ◽  
Flow Effects

Computing capacities have grown exponentially in recent years and 3D-Navier-Stokes methods were developed widely. However it is still not feasible to design a multi-stage compressor directly in three dimensions. Instead, compressor design starts with 1D-design. In accordance with this approach, basic parameters such as the number of stages and stage pressure ratios are determined. In the following 2D-design, the geometry of the flow channel and the main parameters of the blade geometries can be determined. Afterwards in the 3D-design, unsteady and 3D-flow-effects are considered and the design optimized accordingly. Therefore, it is virtually impossible to correct conceptual faults in the 3D-design phase. Thus a robust and reliable 2D-Throughflow-solver including a performance prediction for modern airfoil geometries is necessary. So far there is no efficient methodology known which predicts the performance for all kinds of airfoil geometries, as it would be necessary in a 2D-Throughflow optimization process. In [1, 2] a novel methodology was presented, which is able to predict the performance for a large number of airfoil geometries accurately. This method is based on a large airfoil database which is used to train a surrogate model for airfoil performance prediction. The scope of this work is to validate and to document the progress of this new approach. In Schmitz et al. [1] it was validated on rotor 1 of the 4.5 stage transonic test compressor DLR-RIG250 of the Institute of Propulsion Technology. In this work all 4.5 stages were calculated at different speedlines and different vane positions. The results of the S2-solver are compared to experimental data and 3D-CFD calculations, obtained using the DLR in-house solver TRACE.

A one-step Bayesian inversion framework for three-dimensional reservoir characterization based on a Gaussian mixture model – A Norwegian Sea demonstration

Geophysics ◽  
2020 ◽  
pp. 1-68
Author(s):  
Torstein Fjeldstad ◽  
Per Avseth ◽  
Henning Omre
Keyword(s):  
Random Field ◽  
Markov Random Field ◽  
Gaussian Mixture ◽  
Three Dimensions ◽  
Monte Carlo Algorithm ◽  
Petrophysical Properties ◽  
Norwegian Sea ◽  
Spatial Coupling ◽  
Markov Random ◽  
One Step

A one-step approach for Bayesian prediction and uncertainty quantification of lithology/fluid classes, petrophysical properties and elastic attributes conditional on prestack 3D seismic amplitude-versus-offset data is presented. A 3D Markov random field prior model is assumed for the lithology/fluid classes to ensure spatially coupled lithology/fluid class predictions in both the lateral and vertical directions. Conditional on the lithology/fluid classes, we consider Gauss-linear petrophysical and rock physics models including depth trends. Then, the marginal prior models for the petrophysical properties and elastic attributes are multivariate Gaussian mixture models. The likelihood model is assumed to be Gauss-linear to allow for analytic computation. A recursive algorithm that translates the Gibbs formulation of the Markov random field into a set of vertical Markov chains is proposed. This algorithm provides a proposal density in a Markov chain Monte Carlo algorithm such that efficient simulation from the posterior model of interest in three dimensions is feasible. The model is demonstrated on real data from a Norwegian Sea gas reservoir. We evaluate the model at the location of a blind well, and we compare results from the proposed model with results from a set of 1D models where each vertical trace is inverted independently. At the blind well location, we obtain at most a 60 % reduction in the root mean square error for the proposed 3D model compared to the model without lateral spatial coupling.

scholarly journals Modified Sonine approximation for granular binary mixtures

2009 ◽  
Vol 623 ◽  
pp. 387-411 ◽  
Author(s):  
VICENTE GARZÓ ◽  
FRANCISCO VEGA REYES ◽  
JOSÉ MARÍA MONTANERO
Keyword(s):  
Transport Coefficients ◽  
Direct Simulation Monte Carlo ◽  
Boltzmann Distribution ◽  
Three Dimensions ◽  
Navier Stokes ◽  
State Distribution ◽  
New Approach ◽  
Viscosity Coefficients ◽  
Stokes Transport ◽  
Simulation Monte Carlo

We evaluate in this work the hydrodynamic transport coefficients of a granular binary mixture in d dimensions. In order to eliminate the observed disagreement (for strong dissipation) between computer simulations and previously calculated theoretical transport coefficients for a monocomponent gas, we obtain explicit expressions of the seven Navier–Stokes transport coefficients by the use of a new Sonine approach in the Chapman–Enskog (CE) theory. This new approach consists of replacing, where appropriate in the CE procedure, the Maxwell–Boltzmann distribution weight function (used in the standard first Sonine approximation) by the homogeneous cooling state distribution for each species. The rationale for doing this lies in the well-known fact that the non-Maxwellian contributions to the distribution function of the granular mixture are more important in the range of strong dissipation we are interested in. The form of the transport coefficients is quite common in both standard and modified Sonine approximations, the distinction appearing in the explicit form of the different collision frequencies associated with the transport coefficients. Additionally, we numerically solve by the direct simulation Monte Carlo method the inelastic Boltzmann equation to get the diffusion and the shear viscosity coefficients for two and three dimensions. As in the case of a monocomponent gas, the modified Sonine approximation improves the estimates of the standard one, showing again the reliability of this method at strong values of dissipation.

scholarly journals Continuous-Time Perfect Control Algorithm—A State Feedback Approach

2021 ◽  
Vol 11 (16) ◽  
pp. 7466
Author(s):  
Marek Krok ◽  
Wojciech P. Hunek ◽  
Paweł Majewski
Keyword(s):  
Design Process ◽  
Process Simulation ◽  
Continuous Time ◽  
Control Algorithm ◽  
State Feedback ◽  
Closed Loop ◽  
Control Design ◽  
Control Law ◽  
New Approach

In this paper, a new approach to the continuous-time perfect control algorithm is given. Focusing on the output derivative, it is shown that the discussed control law can effectively be implemented in terms of state-feedback scenarios. Moreover, the application of nonunique matrix inverses is also taken into consideration during the perfect control design process. Simulation examples given within this work allow us to showcase the main properties obtained for continuous-time perfect control closed-loop plants.

A Novel Workflow for Optimizing Well Placement Under Geomechanical Constraints: A Case Study

2020 ◽  
Vol 143 (3) ◽  
Author(s):  
Cheng An ◽  
Peng Zhang ◽  
Amanveer Wesley ◽  
Gaetan Bardy ◽  
Kevin Hall ◽  
...  
Keyword(s):  
Stress Field ◽  
Three Dimensional ◽  
Production Performance ◽  
Natural Fracture ◽  
Petrophysical Properties ◽  
Reservoir Model ◽  
Differential Stress ◽  
Well Placement ◽  
Flow Simulations

Abstract A novel workflow to optimize well placement using geomechanical constraints is introduced to maximize production performance, reduce excessive simulation runs, and minimize drilling constraints by considering the local stress field and the petrophysical properties in a given reservoir. A case study is presented for optimization of horizontal well placement in the Monterey Formation of Miocene Age in California. First, a three-dimensional reservoir model of formation pressure, in situ stresses, petrophysical and rock properties were built from available petrophysical and well log data. Second, numerical modeling using material point method (MPM) was applied to generate the differential stress field, taking into consideration a three-dimensional natural fracture network in the reservoir model. Third, an optimization algorithm which incorporates petrophysical properties, natural fracture distribution, differential stresses, and mechanical stability was used to identify the best candidate locations for well placement. Finally, flow simulations were conducted to segregate each candidate location where both natural and hydraulic fractures were considered. Statistical methods identify optimal well positions in areas with low differential stress, high porosity, and high permeability. Several candidate locations for well placement were selected and flow simulations were conducted. A comparison of the production performance between the best candidates and other randomly selected well configurations indicates that the workflow can effectively recognize scenarios of optimum well placement. The proposed workflow provides practical insight on well placement optimization by reducing the number of required reservoir simulation runs and maximizing the hydrocarbon recovery.

A new approach to the degree of greyness

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rafał Mierzwiak ◽  
Marcin Nowak ◽  
Naiming Xie
Keyword(s):  
Three Dimensions ◽  
New Approach ◽  
Content Type ◽  
Reference Base ◽  
The Third ◽  
Grey Systems Theory ◽  
Three Stages ◽  
Sets Theory ◽  
Modelling Methods ◽  
Space Concept

PurposeThe degree of greyness may be regarded as a measure of cognitive uncertainty. Therefore, it is a part of the epistemological core of the grey systems theory. The theoretical importance of the degree of greyness concept is also due to its application in a range of uncertainty modelling methods: predictive, relational and decision-making methods. Greyness, being a result of cognitive uncertainty, was recently subjected to axiomatization in the form of grey space with the use of the classical sets theory. The purpose of this article is to develop a new approach to the degree of greyness, being consistent with the grey space concept.Design/methodology/approachIn order to realise the article’s goals, the research is divided into three stages described in particular sections. The first section of the article presents a theoretical framework of the degree of greyness and the grey space. The second part includes the assumptions of the new degree of greyness concept, along with the mathematical models for the first, the second and the third degree of greyness. The third section contains numerical examples for each degree of greyness.FindingsAs a result of the research, a concept of a degree of greyness was created and it was linked with a concept of grey space. This new approach to the issue of the degree of greyness has allowed the analysing of this category in three dimensions dependent on an accepted reference base. As a result, a concept of concrete and abstractive grey numbers was introduced and relationships between these categories of numbers and the degree of greyness were determined.Originality/valueThe proposed approach to the issue of the degree of greyness is a theoretical unification of the previous considerations in this area. The proposed three dimensions of greyness degree will be derived from the grey space, so they will also be a function of quantity. Thus, the degree of greyness was linked with a classical set theory. An original input in this article is also a differentiation of concrete and abstractive grey numbers, which give a basis for deliberations connected with interpretation of grey numbers in the context of real applications.

A FAST-MANIFOLD APPROACH TO MELNIKOV FUNCTIONS FOR SLOWLY VARYING OSCILLATORS

1996 ◽  
Vol 06 (08) ◽  
pp. 1575-1578 ◽  
Author(s):  
SHYH-LEH CHEN ◽  
STEVEN W. SHAW
Keyword(s):  
Present Method ◽  
Homoclinic Orbits ◽  
Melnikov Function ◽  
Three Dimensions ◽  
Distance Functions ◽  
New Approach ◽  
Alternative Derivation ◽  
Melnikov Functions ◽  
Melnikov Analysis ◽  
Insight Into

A new approach to obtaining the Melnikov function for homoclinic orbits in slowly varying oscillators is proposed. The present method applies the usual two-dimensional Melnikov analysis to the “fast” dynamics of the system which lie on an invariant manifold. It is shown that the resultant Melnikov function is the same as that obtained in the usual way involving distance functions in three dimensions [Wiggins and Holmes, 1987]. This alternative derivation provides some useful insight into the structure of the dynamical system.

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