A stochastic approach for integrating market and technical uncertainties in economic evaluations of petroleum development

The paper presents a stochastic and economic analysis for petroleum development under uncertain market and technical environments. Mean-reversion with jumps for price forecasting is used to consider market uncertainty, while various scenarios for the reservoir properties and cost are employed to consider technical uncertainty. Monte Carlo simulation is carried out to obtain the feasible range of net present values and internal rates of return. The influence of stochastic parameters is examined through correlation coefficients. The stochastic approach yields more reliable evaluation and effectively investigates the characteristics of development. The integration of uncertainties and contractual terms results in an irregular tendency in the future cash flow and reveals that a larger reserve does not guarantee a greater profit. The reserve and the well rate affect the economic values whereas the parameters for price prediction don＇t. The research confirms the necessity of qualifying uncertainties for realistic decision-making at the initial stage of development.

Structure-Preserving Dynamics of Stochastic Epidemic Model with the Saturated Incidence Rate

The structure-preserving features of the nonlinear stochastic models are positivity,dynamical consistency and boundedness.These features have a significant role in different fields of computational biology and many more.Unfortunately,the existing stochastic approaches in literature do not restore aforesaid structure-preserving features,particularly for the stochastic models.Therefore,these gaps should be occupied up in literature,by constructing the structure-preserving features preserving numerical approach.This writing aims to describe the structure-preserving dynamics of the stochastic model.We have analysed the effect of reproduction number in stochastic modelling the same as described in the literature for deterministic modelling.The usual explicit stochastic numerical approaches are time-dependent.We have developed the implicitly driven explicit approach for the stochastic epidemic model.We have proved that the newly developed approach is preserving the structural,dynamical properties as positivity,boundedness and dynamical consistency.Finally,convergence analysis of a newly developed approach and graphically illustration is also presented.

Optimal paths planning in dynamic transportation networks with random link travel times

A theoretical study was conducted on finding optimal paths in transportation networks where link travel times were stochastic and time-dependent(STD). The methodology of relative robust optimization was applied as measures for comparing time-varying, random path travel times for a priori optimization. In accordance with the situation in real world, a stochastic consistent condition was provided for the STD networks and under this condition, a mathematical proof was given that the STD robust optimal path problem can be simplified into a minimum problem in specific time-dependent networks. A label setting algorithm was designed and tested to find travelers' robust optimal path in a sampled STD network with computation complexity of O(n2+n·m). The validity of the robust approach and the designed algorithm were confirmed in the computational tests. Compared with conventional probability approach, the proposed approach is simple and efficient, and also has a good application prospect in navigation system.

Earthquake motion input and its dissemination via the Internet

Objectives of this task are to conduct research on seismic hazards,and to provide relevant input on the expected levels of these hazards to other tasks.Other tasks requiring this input include those dealing with inventory,fragility curves, rehabilitation strategies and demonstration projects.The corresponding input is provided in various formats depending on the intended use:as peak ground motion parameters and/or response spectral values for a given magnitude,epicentral distance and site conditions;or as time histories for scenario earthquakes that are selected based on the disaggregated seismic hazard mapped by the U.S.Geological Survey and are incorporated in building codes.The user community for this research is both academic researchers and practicing engineers who may use the seismic input generated by the synthesis techniques that are developed under this task for a variety of applications.These include ground motions for scenario earthquakes,for developing fragility curves and in specifying ground motion input for critical facilities (such as hospitals) located in the eastern U.S.

Common Fixed Point Theorems and Q-property for Quasi-contractive Mappings under c-distance on TVS-valued Cone Metric Spaces without the Normality

In this paper, we derive the stochastic maximum principle for optimal control problems of the forward-backward Markovian regime-switching system. The control system is described by an anticipated forward-backward stochastic pantograph equation and modulated by a continuous-time finite-state Markov chain. By virtue of classical variational approach, duality method, and convex analysis, we obtain a stochastic maximum principle for the optimal control.

Numerical Simulation of the Porous Structure of Biomaterials

Porous biomaterials are widely used as bone replacement materials because of thers high biocompatibility and osteoconductivity property. Understanding of their porous structure (i.e. geometrical and topological characteristic) and studying how to the body fluid flow through them are essential to investigate the degradation behaviour at the surface-liquid interface. This research develops a numerical model to simulate the porous structure of biomaterials based on the stochastic approach in pore size distribution and interconnectivity.

A Stochastic Model Approach for Optimisation of Lowland River Restoration Works

Over the course of centuries, river systems have been heavily trained for the purpose of safe discharge of water, sediment and ice, and improves navigation. Traditionally, dikes are used to be reinforced and heightened to protect countries from ever higher flood levels. Other types of solutions than technical engineering solutions, such as measures to increase the flood conveyance capacity（e.g., lowering of groynes and floodplains, setting back dikes） become more popular. These solutions may however increase the river bed dynamics and thus impact negatively navigation, maintenance dredging and flood safety. A variety of numerical models are available to predict the impact of river restoration works on river processes. Often little attention is paid to the assessment of uncertainties. In this paper, we show how we can make uncertainty explicit using a stochastic approach. This approach helps identifying uncertainty sources and assessing their contribution to the overall uncertainty in river processes. The approach gives engineers a better understanding of system behaviour and enables them to intervene with the river system, so as to avoid undesired situations. We illustrate the merits of this stochastic approach for optimising lowland river restoration works in the Rhine in the Netherlands.

Jinzhai County Household Technical Change and Efficiency Change Analysis: Stochastic Frontier Production Function Approach

Stochastic frontier production function approach is adopted, 93 farmer samples have been collected, pure efficiency, technical efficiency, technical change and scale efficiency and the institutional contribution have been calculated. The results indicated that increasing productivity is the sole measurement to reduce poverty, institution and technical change are the two key factors. Therefore, stable institution, improving technical changes are required. At present, it is urgent to make technical progre...

Karhunen-Loeve expansions for the m-th order detrended Brownian motion

The m-th order detrended Brownian motion is defined as the orthogonal component of projection of the standard Brownian motion onto the subspace spanned by polynomials of degree up to m. We obtain the Karhunen-Loeve expansion for the process and establish a connection with the generalized （m-th order） Brownian bridge developed by MacNeill （1978） in the study of distributions of polynomial regression. The resulting distribution identity is also verified by a stochastic Fubini approach. As applications, large and small deviation asymptotic behaviors for the L2 norm are given.

Does oil price affect the value of firms？ Evidence from Tunisian listed firms

A new debate on the potential impact of oil price changes on the value of firms was initiated in this paper. Using a stochastic frontier approach, an attempt was made to derive the optimal value Q＊ of firms and calculate the Q value observed. Then the shortfall （Q＊-Q） which represents the inefficiency term was explained. Starting from 19 industrial Tunisian firms listed on the Tunis Stock Exchange between 2007 and 2011, the fact that variation of oil prices can largely explain distortions in the value of firms was empirically demonstrated.