scholarly journals Analytical Model for Predicting Productivity of Radial-Lateral Wells

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6386
Author(s):  
Boyun Guo ◽  
Rashid Shaibu ◽  
Xu Yang
Keyword(s):  
Analytical Model ◽  
Sensitivity Analyses ◽  
Oil Viscosity ◽  
Acceptable Error ◽  
Skin Factor ◽  
Well Production ◽  
Drilling Technology ◽  
Increase Productivity ◽  
Horizontal Permeability ◽  
Parameter Values

An analytical model for predicting the productivity of Radial-lateral wells (RLW) drilled using radial jet drilling technology was developed in this work. The model assumes uniformly distributed equal-geometry laterals draining oil or gas under pseudo-steady state flow conditions within the lateral-reached drainage area. A numerical simulation and production data from three field cases of RLW were used to compare and validate the model. The result indicates that the model overestimates the well production rates for wells by 7.7%, 3.25%, and 8.8%, respectively. The error is attributed to several sources including, lack of data for well skin factor, uncertainty of horizontal permeability (kH) in the well area, uncertainty of permeability anisotropy (Iani), and uncertainty in bottom hole pressure (pw). Error analysis of uncertainties in kH, Iani, and pw showed that the model could predict productivity well with an acceptable error (10%) over practical ranges of these parameter values. Parameter sensitivity analyses showed that an increasing number of laterals, lateral length, and horizontal permeability would almost proportionally increase productivity. Well productivity is sensitive to well skin factor and oil viscosity, but not sensitive to the radius of the lateral.

Automated structural assessment of existing reinforced concrete underpasses

2021 ◽  
Author(s):  
Danny Jilissen ◽  
Rob Vergoossen ◽  
Yuguang Yang ◽  
Eva Lantsoght
Keyword(s):  
Reinforced Concrete ◽  
The Netherlands ◽  
Analytical Model ◽  
Load Distribution ◽  
Traffic Load ◽  
Sensitivity Analyses ◽  
Fem Model ◽  
Structural Assessment ◽  
Model Code ◽  
Model Code 2010

<p>Due to the large number of underpasses in the Netherlands that have to be assessed, a project at the Delft University of Technology in cooperation with Royal HaskoningDHV was started. Research was conducted into the automation of the structural assessment of existing reinforced concrete underpasses in the Netherlands. The developed Automated Structural Assessment Tool (ASA Tool) consists of an analytical model and a 2.5D FEM model. The analytical model uses traffic load distribution following the Guyon-Massonnet-Bares method for bending and a method based on <i>fib </i>Model Code 2010 for shear. The script-based 2.5D FEM model uses 2D shell elements and performs a linear elastic analysis. The input and output can be linked to a database for assessment of large batches. Sensitivity analyses showed that in-plane load distribution following <i>fib </i>Model Code 2010 combined with vertical load distribution according to EN 1991-2:2003 results in underestimated shear forces.</p>

Visuotactile Representation of Peripersonal Space: A Neural Network Study

2010 ◽  
Vol 22 (1) ◽  
pp. 190-243 ◽  
Author(s):  
Elisa Magosso ◽  
Melissa Zavaglia ◽  
Andrea Serino ◽  
Giuseppe di Pellegrino ◽  
Mauro Ursino
Keyword(s):  
Neural Network ◽  
Peripersonal Space ◽  
Sensitivity Analyses ◽  
Neurological Deficits ◽  
Inhibitory Synapses ◽  
Space Representation ◽  
Emergent Properties ◽  
Bilateral Stimulation ◽  
The Right ◽  
Parameter Values

Neurophysiological and behavioral studies suggest that the peripersonal space is represented in a multisensory fashion by integrating stimuli of different modalities. We developed a neural network to simulate the visual-tactile representation of the peripersonal space around the right and left hands. The model is composed of two networks (one per hemisphere), each with three areas of neurons: two are unimodal (visual and tactile) and communicate by synaptic connections with a third downstream multimodal (visual-tactile) area. The hemispheres are interconnected by inhibitory synapses. We applied a combination of analytic and computer simulation techniques. The analytic approach requires some simplifying assumptions and approximations (linearization and a reduced number of neurons) and is used to investigate network stability as a function of parameter values, providing some emergent properties. These are then tested and extended by computer simulations of a more complex nonlinear network that does not rely on the previous simplifications. With basal parameter values, the extended network reproduces several in vivo phenomena: multisensory coding of peripersonal space, reinforcement of unisensory perception by multimodal stimulation, and coexistence of simultaneous right- and left-hand representations in bilateral stimulation. By reducing the strength of the synapses from the right tactile neurons, the network is able to mimic the responses characteristic of right-brain-damaged patients with left tactile extinction: perception of unilateral left tactile stimulation, cross-modal extinction and cross-modal facilitation in bilateral stimulation. Finally, a variety of sensitivity analyses on some key parameters was performed to shed light on the contribution of single-model components in network behaviour. The model may help us understand the neural circuitry underlying peripersonal space representation and identify its alterations explaining neurological deficits. In perspective, it could help in interpreting results of psychophysical and behavioral trials and clarifying the neural correlates of multisensory-based rehabilitation procedures.

A Case Study in Oil-Gas Transportation through Subsea Pipeline in Liaohe Tanhai Oilfield

2011 ◽  
Vol 317-319 ◽  
pp. 2239-2243
Author(s):  
Yang Liu ◽  
Zhi Hua Wang ◽  
Li Xin Wei ◽  
Ren Shan Pang
Keyword(s):  
Freezing Point ◽  
Self Control ◽  
Outlet Temperature ◽  
Oil Viscosity ◽  
Long Distance ◽  
Pump System ◽  
Public Projects ◽  
Well Production ◽  
Water Cut ◽  
Oil Gas

The crude oil in Kuidong region of Liaohe Tanhai Oilfield is characterized by high oil viscosity, high density, high content of colloid asphalt, low content of wax and low freezing point. In the shallow region, the large current, high content of silt, long-distance subsea buried pipeline and drift ice in winter have brought great challenge to offshore construction and oil-gas transportation. In this paper, the investigations of offshore construction project and platform process are shown. Based on the well production rate, gas-oil ratio, water cut, wellhead back pressure and outlet temperature, the range of daily transportation volume was acquired, as well as the maximum inlet pressure and pressure difference of the pump. The paper also selected technically and economically feasible pumps, then designed the public projects, corresponding electric power and self-control facilities. The selected skidded twin screw multiphase pump system can smoothly transport produced liquid to the terminal systems onshore without any effect on the daily output.

Thermally Active Polymer To Improve Sweep Efficiency of Waterfloods: Simulation and Pilot Design Approaches

2012 ◽  
Vol 15 (01) ◽  
pp. 86-97 ◽  
Author(s):  
R.. Garmeh ◽  
M.. Izadi ◽  
M.. Salehi ◽  
J.L.. L. Romero ◽  
C.P.. P. Thomas ◽  
...  
Keyword(s):  
Oil Recovery ◽  
Pilot Project ◽  
Oil Reservoirs ◽  
Reservoir Rock ◽  
Sensitivity Analyses ◽  
Chemical Components ◽  
Chemical Adsorption ◽  
Oil Viscosity ◽  
Sweep Efficiency ◽  
Thief Zone

Summary A common problem in many waterflooded oil reservoirs is early water breakthrough with high water cut through highly conductive thief zones. Thermally active polymer (TAP), which is an expandable submicron particulate of low viscosity, has been successfully used as an in-depth conformance to improve sweep efficiency of waterfloods. This paper describes the workflow to evaluate technical feasibility of this conformance technology for proper pilot-project designs supported with detailed simulation studies. Two simulation approaches have been developed to model properties of this polymer and its interaction with reservoir rock. Both methods include temperature-triggered viscosification and adsorption/retention effects. Temperature profile in the reservoir is modeled by energy balance to accurately place this polymer at the optimum location in the thief zone. The first method considers a single chemical component in the water phase. The second method is based on chemical reactions of multiple chemical components. Both simulation approaches are compared and discussed. Results show that temperature-triggered polymers can increase oil recovery by viscosification and chemical adsorption/retention, which reduces thief-zone permeability and diverts flow into unswept zones. Sensitivity analyses suggest that ultimate oil recovery and conformance control depend on the thief-zone temperature, vertical-to the horizontal-permeability ratio (Kv/Kh), thief-zone vertical location, injection concentration and slug size, oil viscosity, and chemical adsorption and its reversibility, among other factors. For high-flow-capacity thief zones and mobility ratios higher than 10, oil recoveries can be improved by increasing chemical concentration or slug size of treatments, or both. Reservoirs with low Kv/Kh (&lt; 0.1) and high permeability contrast generally shows faster incremental recoveries than reservoirs with high Kv/Kh and strong water segregation. The presented workflow is currently used to perform in-depth conformance treatment designs in onshore and offshore fields and can be used as a reference tool to evaluate benefits of the TAP in waterflooded oil reservoirs.

scholarly journals The effect of control measures on COVID-19 transmission in Italy: Comparison with Guangdong province in China

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Pei-Yu Liu ◽  
Sha He ◽  
Li-Bin Rong ◽  
San-Yi Tang
Keyword(s):  
Media Coverage ◽  
Early Stage ◽  
Guangdong Province ◽  
Individual Behavior ◽  
Control Measures ◽  
Disease Spread ◽  
Sensitivity Analyses ◽  
And Control ◽  
Parameter Values ◽  
The Impact

Abstract Background COVID-19 has spread all around the world. Italy is one of the worst affected countries in Europe. Although there is a trend of relief, the epidemic situation hasn’t stabilized yet. This study aims to investigate the dynamics of the disease spread in Italy and provide some suggestions on containing the epidemic. Methods We compared Italy’s status at the outbreak stage and control measures with Guangdong Province in China by data observation and analysis. A modified autonomous SEIR model was used to study the COVID-19 epidemic and transmission potential during the early stage of the outbreak in Italy. We also utilized a time-dependent dynamic model to study the future disease dynamics in Italy. The impact of various non-pharmaceutical control measures on epidemic was investigated through uncertainty and sensitivity analyses. Results The comparison of specific measures implemented in the two places and the time when the measures were initiated shows that the initial prevention and control actions in Italy were not sufficiently timely and effective. We estimated parameter values based on available cumulative data and calculated the basic reproduction number to be 4.32 before the national lockdown in Italy. Based on the estimated parameter values, we performed numerical simulations to predict the epidemic trend and evaluate the impact of contact limitation, detection and diagnosis, and individual behavior change due to media coverage on the epidemic. Conclusions Italy was in a severe epidemic status and the control measures were not sufficiently timely and effective in the beginning. Non-pharmaceutical interventions, including contact restrictions and improvement of case recognition, play an important role in containing the COVID-19 epidemic. The effect of individual behavior changes due to media update of the outbreak cannot be ignored. For policy-makers, early and strict blockade measures, fast detection and improving media publicity are key to containing the epidemic.

A New Mathematical Model to Understand the Convective Heat Transfer Mechanism in Steam-Assisted Gravity Drainage Process

2017 ◽  
Vol 10 (1) ◽  
Author(s):  
Zhaoxiang Zhang ◽  
Huiqing Liu ◽  
Xiaohu Dong ◽  
Huanli Jiang
Keyword(s):  
Heat Transfer ◽  
Convective Heat Transfer ◽  
Analytical Model ◽  
Convective Heat ◽  
Transfer Mechanism ◽  
Gravity Drainage ◽  
Heat Transfer Mechanism ◽  
Oil Viscosity ◽  
Steam Chamber ◽  
Steam Assisted Gravity Drainage

Steam-assisted gravity drainage (SAGD) process has been an optimized method to explore heavy oil reservoirs in the world. The oil viscosity reduction and gravity force near the interface of steam–chamber are the main development mechanisms. In classical models, conductive heat transfer plays the only or dominant role in the heat transmission from high-temperature steam to low-temperature oil sands. Although some mathematical studies have paid attention to the convective heat transfer, the role of heat transfer by flowable oil normal to the steam–chamber interface has been given little attention. In SAGD, the viscosity of bitumen can be reduced by several orders of magnitude by the release of latent heat from injected steam. In this study, an analytical model is developed for the heat transfer process induced by flowable oil. Also, in order to accurately simulate the oil viscosity characteristics in steam–chamber, a correlation between oil viscosity and pressure is proposed. Results indicate that the oil mobility plays an important role on the flow normal to interface when the distance is smaller than 6 m. Even under the most extreme circumstances (μw = 0.1127 cp), the flowing of oil normal to steam–chamber interface also cannot be ignored. Comparing to Irani and Ghannadi model, it can be easy to draw the conclusion that the new model consists with the underground test facility (UTF) field data much better. This new analytical model will benefit to understanding the convective heat transfer mechanism in SAGD process.

scholarly journals The effect of control measures on COVID-19 transmission in Italy: Comparison with Guangdong province in China

2020 ◽  
Author(s):  
Pei-Yu Liu ◽  
Sha He ◽  
Li-Bin Rong ◽  
San-Yi Tang
Keyword(s):  
Media Coverage ◽  
Early Stage ◽  
Guangdong Province ◽  
Individual Behavior ◽  
Control Measures ◽  
Disease Spread ◽  
Sensitivity Analyses ◽  
And Control ◽  
Parameter Values ◽  
The Impact

Abstract Background: COVID-19 has spread all around the world. Italy is one of the worst affected countries in Europe. Although there is a trend of relief, the epidemic situation hasn’t stabilized yet. This study aims to investigate the dynamics of the disease spread in Italy and provide some suggestions on containing the epidemic. Methods: We compared Italy’s status at the outbreak stage and control measures with Guangdong Province in China by data observation and analysis. A modified autonomous SEIR model was used to study the COVID-19 epidemic and transmission potential during the early stage of the outbreak in Italy. We also utilized a time-dependent dynamic model to study the future disease dynamics in Italy. The impact of various non-pharmaceutical control measures on epidemic was investigated through uncertainty and sensitivity analyses. Results: The comparison of specific measures implemented in the two places and the time when the measures were initiated shows that the initial prevention and control actions in Italy were not sufficiently timely and effective. We estimated parameter values based on available cumulative data and calculated the basic reproduction number to be 4.32 before the national lockdown in Italy. Based on the estimated parameter values, we performed numerical simulations to predict the epidemic trend and evaluate the impact of contact limitation, detection and diagnosis, and individual behavior change due to media coverage on the epidemic. Conclusions: Italy was in a severe epidemic status and the control measures were not sufficiently timely and effective in the beginning. Non-pharmaceutical interventions, including contact restrictions and improvement of case recognition, play an important role in containing the COVID-19 epidemic. The effect of individual behavior changes due to media update of the outbreak cannot be ignored. For policy-makers, early and strict blockade measures, fast detection and improving media publicity are key to containing the epidemic.

scholarly journals A mathematical investigation of different growth rates in simultaneous tumors at two distant sites

2021 ◽  
Author(s):  
Farjana Aktar
Keyword(s):  
Mathematical Model ◽  
Growth Rate ◽  
Simulated Annealing Algorithm ◽  
The Other ◽  
Sensitivity Analyses ◽  
Small Tumour ◽  
System A ◽  
Set Up ◽  
Parameter Values ◽  
The Mathematical Model

Experimental data demonstrates that simultaneous injection of cancer cells at two distinct sites often results in one large and one small tumour. Unbalanced tumour-stimulating inflammation is hypothesized to be the cause of this growth rate separation, causing one tumour to grow faster than the other. Here, a mathematical model for immune recruitment and competition between two cancer sites is developed to explore the role of tumour-promoting inflammation in the observed growth rate separation. Due to the experimental set-up, immune predation may be neglected, focusing the model on tumour-promoting immune actions. A new mathematical model with localized immune recruitment and competition between the two cancer sites is developed using a multi-compartment ODE system. A simulated annealing algorithm is used to fit the model to control data (one tumour burden). Stability and parameter sensitivity analyses are used to explore the mathematical model and parameter space. Next, the two-tumour scenario is predicted by testing parameter values tied to possible biological mechanisms of action. The model predicts that indeed inflammation may be a contributor to growth rate separation observed in simultaneous tumour growth, if one site is pre-inflamed compared to the other.

scholarly journals Expert Agreement in Prior Elicitation and its Effects on Bayesian Inference

2021 ◽  
Author(s):  
Angelika Stefan ◽  
Dimitris Katsimpokis ◽  
Quentin Frederik Gronau ◽  
Eric-Jan Wagenmakers
Keyword(s):  
Bayesian Inference ◽  
Bayes Factor ◽  
Hypothesis Test ◽  
Data Uncertainty ◽  
Sensitivity Analyses ◽  
Prior Distributions ◽  
Prior Elicitation ◽  
Measures Of Concordance ◽  
Multiple Experts ◽  
Parameter Values

Bayesian inference requires the specification of prior distributions that quantify the pre-data uncertainty about parameter values. One way to specify prior distributions is through prior elicitation, an interview method guiding field experts through the process of expressing their knowledge in the form of a probability distribution. However, prior distributions elicited from experts can be subject to idiosyncrasies of experts and elicitation procedures, raising the spectre of subjectivity and prejudice. Here, we investigate the effect of interpersonal variation in elicited prior distributions on the Bayes factor hypothesis test. We elicited prior distributions from six academic experts with a background in different fields of psychology and applied the elicited prior distributions as well as commonly used default priors in a re-analysis of 1710 studies in psychology. The degree to which the Bayes factors vary as a function of the different prior distributions is quantified by three measures of concordance of evidence: We assess whether the prior distributions change the Bayes factor direction, whether they cause a switch in the category of evidence strength, and how much influence they have on the value of the Bayes factor. Our results show that although the Bayes factor is sensitive to changes in the prior distribution, these changes rarely affect the qualitative conclusions of a hypothesis test. We hope that these results help researchers gauge the influence of interpersonal variation in elicited prior distributions in future psychological studies. Additionally, our sensitivity analyses can be used as a template for Bayesian robustness analyses that involves prior elicitation from multiple experts.

A Formal Framework for Patch Management

2013 ◽  
Vol 5 (2) ◽  
pp. 18-31 ◽  
Author(s):  
Guillermo A. Francia ◽  
Kihyun Kim ◽  
Byungoh Ahn ◽  
Sen Xin Zhou
Keyword(s):  
Markov Chain Model ◽  
Sensitivity Analyses ◽  
Future Research ◽  
Chain Model ◽  
Research Directions ◽  
Proposed Model ◽  
Formal Framework ◽  
Future Research Directions ◽  
And Behavior ◽  
Parameter Values

A patch management model provides a framework with which a system’s parameters and behavior can be tested and validated. The authors propose a formal framework that is based on the Continuous Time Markov Chain Model and validate the model using the SHARPE modeling tool. Furthermore, they perform sensitivity analyses to study the dynamic behavior of the proposed model with varying parameter values. A discussion on the results of our study and future research directions concludes the paper.

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