scholarly journals Stochastic Assessment of Groundwater Contamination Risks From Onshore Gas Development Using Computationally Efficient Analytical and Numerical Transport Models

2022 ◽  
Vol 3 ◽  
Author(s):  
David Rassam ◽  
J. Sreekanth ◽  
Dirk Mallants ◽  
Dennis Gonzalez ◽  
Rebecca Doble ◽  
...  

Regulators require the gas industry to assess the risks of unintentional release of chemicals to the environment and implement measures to mitigate it. Industry standard models for contaminant transport in aquifers do not explicitly model processes in the unsaturated zone and groundwater models often require long run times to complete simulation of complex processes. We propose a stochastic numerical-analytical hybrid model to overcome these two shortcomings and demonstrate its application to assess the risks associated with onshore gas drilling in the Otway Basin, South Australia. The novel approach couples HYDRUS-1D to an analytical solution to model contaminant transport in the aquifer. Groundwater velocities and chemical trajectories were derived from a particle tracking analysis. The most influential parameters controlling solute delivery to the aquifer were the soil chemical degradation constant and the hydraulic conductivity of a throttle soil horizon. Only 18% of the flow paths intercepted environmental receptors within a 1-km radius from the source, 87% of which had concentrations of <1% of the source. The proposed methodology assesses the risk to environmental assets and informs regulators to implement measures that mitigate risk down to an acceptable level.

2021 ◽  
pp. 1-25
Author(s):  
Franz X. Hof ◽  
Klaus Prettner

Abstract We employ a novel approach for analyzing the effects of relative consumption and relative wealth preferences on economic growth. In the pertinent literature, these effects are usually assessed by examining the dependence of the growth rate on the two parameters of the utility function that seem to measure the strength of the relative consumption and the relative wealth motives. Applying our fundamental factor approach, we identify specifications in which the traditional approach yields incorrect qualitative conclusions. The problematic specifications have the common unpleasant property that the parameter that seems to determine the strength of the relative consumption motive actually also affects the elasticity of intertemporal substitution of absolute consumption (and the strength of the relative wealth motive). Since the standard approach is unaware of the additional effect(s), it attributes the total change in the growth rate incorrectly to the change in the strength of the relative consumption motive.


Author(s):  
Ramin Bighamian ◽  
Hamid Reza Mirdamadi ◽  
Jin-Oh Hahn

This paper presents a novel approach to damage identification in a class of collocated multi-input multi-output structural systems. In the proposed approach, damage is identified via the structural Markov parameters obtained from a system identification procedure, which is in turn exploited to localize and quantify damage by evaluating relative changes occurring in the mass and stiffness matrices associated with the structural system. To this aim, an explicit relationship between structural Markov parameters versus mass and stiffness matrices is developed. The main strengths of the proposed approach are that it is capable of quantitatively identifying the occurrence of multiple damages associated with both mass and stiffness characteristics in the structural system, and it is computationally efficient in that it is solely based on the structural Markov parameters but does not necessitate costly calculations related to natural frequencies and mode shapes, making it highly attractive for structural damage detection and health monitoring applications. Numerical examples are provided to demonstrate the validity and effectiveness of the proposed approach.


2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
M. M. Potsane ◽  
R. J. Moitsheki

The transport of chemicals through soils to the groundwater or precipitation at the soils surfaces leads to degradation of these resources. Serious consequences may be suffered in the long run. In this paper, we consider macroscopic deterministic models describing contaminant transport in saturated soils under uniform radial water flow backgrounds. The arising convection-dispersion equation given in terms of the stream functions is analyzed using classical Lie point symmetries. A number of exotic Lie point symmetries are admitted. Group invariant solutions are classified according to the elements of the one-dimensional optimal systems. We analyzed the group invariant solutions which satisfy the physical boundary conditions.


2020 ◽  
Author(s):  
Ronald van der A ◽  
Jos de Laat ◽  
Henk Eskes ◽  
Jieying Ding

<p><span><span>New TROPOMI (Sentinel 5P) high quality satellite measurements of nitrogen dioxide (NO<sub>2</sub>) over snow-covered regions of Siberia reveal previously undocumented but significant nitrogen oxides (NO<sub>x</sub> = NO + NO<sub>2</sub>) emissions associated with the natural gas industry in Western Siberia. Besides gas drilling and natural gas power plants, also gas compressor stations for the transport of natural gas are sources of high amounts of NO<sub>x</sub> emissions, which are emitted in otherwise pristine regions. The emissions from these remote gas compressor stations are at least an order of magnitude larger than those reported for North American gas compressor stations, possibly related to less stringent environmental regulations in Siberia compared to the United States. This discovery was made possible thanks to a newly developed technique for discriminating snow covered surfaces from clouds, which for the first time allows for satellite measurements of tropospheric NO<sub>2</sub> columns over large boreal snow-covered areas. This results in 23% more TROPOMI observations on an annual basis. Furthermore, these observations have a precision four times better than nearly any TROPOMI observation over other areas and surfaces around the world. These new results highlight the potential of TROPOMI on Sentinel 5P as well as future satellite missions for monitoring small-scale emissions</span></span></p>


2015 ◽  
Vol 12 (01) ◽  
pp. 1350107 ◽  
Author(s):  
Fatih Selimefendigil ◽  
Hakan F. Öztop

In the present study, a novel approach based on Proper Orthogonal Decomposition (POD) and fuzzy clustering method is utilized to predict the flow field and heat transfer for the unsteady mixed convection in a square enclosure with two ventilation ports. An adiabatic thin fin is placed on the bottom wall of the cavity and all walls of the enclosure are kept at constant temperature. An oscillating velocity is imposed at the inlet port for a range of Strouhal numbers between 0.1 and 1. Reduced order models of the system are obtained with fuzzy-POD approach for Richardson number of 1 and 100. The estimation data set is obtained for Strouhal numbers 0.1 and 0.5, and the validation data set is obtained for Strouhal number of 0.25. A comparison of the modal coefficients obtained from the proposed approach compares well with the modal coefficients obtained by projecting the CFD data at Strouhal number of 0.25 onto the POD modes. The proposed approach is computationally efficient and the problem of numerical instability in the computation with the conventional Galerkin-POD approach can be circumvented.


F1000Research ◽  
2022 ◽  
Vol 9 ◽  
pp. 1159
Author(s):  
Qian (Vicky) Wu ◽  
Wei Sun ◽  
Li Hsu

Gene expression data have been used to infer gene-gene networks (GGN) where an edge between two genes implies the conditional dependence of these two genes given all the other genes. Such gene-gene networks are of-ten referred to as gene regulatory networks since it may reveal expression regulation. Most of existing methods for identifying GGN employ penalized regression with L1 (lasso), L2 (ridge), or elastic net penalty, which spans the range of L1 to L2 penalty. However, for high dimensional gene expression data, a penalty that spans the range of L0 and L1 penalty, such as the log penalty, is often needed for variable selection consistency. Thus, we develop a novel method that em-ploys log penalty within the framework of an earlier network identification method space (Sparse PArtial Correlation Estimation), and implement it into a R package space-log. We show that the space-log is computationally efficient (source code implemented in C), and has good performance comparing with other methods, particularly for networks with hubs.Space-log is open source and available at GitHub, https://github.com/wuqian77/SpaceLog


Author(s):  
Sofia KAFKA

The article deals with the key issues concerning the system of security of fixed assets at the enterprises of the oil and gas industry. The purpose of the article is to investigate the fixed assets features and composition at the the enterprises of oil and gas industry, to determine the approaches to their assessment at the stage of their receipt by the enterprise. The state, dynamics of value and the degree of depreciation of fixed assets in Ukraine for the year 2017 have been analyzed, their features have been distinguished at the enterprises of different branches of the economy. To ensure the effective operation of the enterprises of the oil and gas industry, significant assets are required, and the results of their activities to a large extent depend on the availability and condition of fixed assets that ensure economic sustainability of economic entities. Oil and gas companies include pipelines and related equipment in fixed assets, oil and gas assets, machinery and equipment, buildings, buffer gas, drilling and reconnaissance equipment and other fixed assets. Among the assets of NJSC "NAFTOGAZ OF UKRAINE" for the year 2017, non-current assets occupied 86% of the total assets of the company, of which 94% were fixed assets, what determines the reliability of their accounting as an important element of effective management of enterprises. The dynamics of value and composition of fixed assets of enterprises of the oil and gas industry of Ukraine for 2016-2017 have been determined according to separate economic segments. The cost of fixed assets of NJSC "NAFTOGAZ OF UKRAINE" as of December 31, 2017 amounted to UAH 491 482 million, respectively, according to economic segments, it is structured in such a way that their largest share is concentrated in the system of transportation and distribution of natural gas - almost 48%, for storage of natural gas - 34%, production and sale of natural gas - 12%, and the rest belongs to the economic activities related to oil: the production of crude oil and gas condensate, transportation of crude oil. The composition of fixed assets of extractive enterprises differs from their composition in refineries. Industrial features of mining industry with significant volumes of work related to the disclosure of layers of minerals are characteristic to chemical production with a significant cost of equipment. The main approaches to the evaluation of fixed assets objects at the stage of their entrance to the enterprise have been investigated. The reliability of the accounting information on fixed assets depends on their assessment. When they are received, they are valued at their original cost, that is, by the amount of cash paid or their equivalents or fair value, another form of indemnity granted to obtain the asset at the time of its acquisition or creation, or, if accepted, the amount that is distributed to that asset in the original recognized in accordance with the specific requirements of other IFRSs. After recognition, the entity should choose either a cost model or a revaluation model in its accounting policies and should apply this policy to the entire group of fixed assets. A cessation of recognition occurs after the release of an object or when it does not expect future economic benefits from its use or disposal. In this case, it is recognized as profit or loss.


Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2795
Author(s):  
Łukasz Januszkiewicz ◽  
Paolo Di Barba ◽  
Sławomir Hausman

In the paper, we present a novel approach to the optimum design of wearable antenna arrays intended for off-body links of wireless body area networks. Specifically, we investigate a four-element array that has a switchable radiation pattern able to direct its higher gain towards a signal source and a lower gain towards an interference. The aim is to increase the signal to interference ratio. We apply a genetic algorithm to optimize both the spatial placement and the feed phasing of the elementary on-body antennas. We propose a simplified, computationally efficient model for the simulation of the array radiation pattern. The model is based on full-wave simulations obtained with a simplified cylindrical model of the human body. We also propose, implement, and evaluate four objective functions based on signal to interference ratio, i.e., min-max, nadir point distance maximization, utopia point distance minimization, and full Pareto-like. Our optimized design obtained with this approach exhibits a significant performance improvement in comparison to the initial heuristic design.


2021 ◽  
Author(s):  
Peace Bello

Abstract As the Oil & Gas industry journeys towards net zero carbon emissions, a lot needs to be done, one of which is the adoption of digital transformation across companies. Decarbonization requires a transformational shift in the way companies operate, how they source, use, consume and think about energy and feedstocks. If the Oil & Gas sector will continue to exist, it must carry out its activities in the safest possible way and digitalizing it will help in achieving this. A survey by Newsweek shows that areas where transformative technologies are having the biggest impact are production-related, operations and maintenance, enhanced recovery, fracking/tight reservoirs, and exploitation at greater depths. Luis Abril of Minsait opined that digital technology enables companies to extract more value from data, using new platforms to share data with the entire organization, suppliers, contractors, and partners. The real-time visualization of data helps optimize decision making. Big data can be analyzed to find answers to questions such as: What piece of equipment is showing signs of wear and should be replaced? What sort of predictive maintenance can be leveraged? What is the most effective fracking approach for this well? AI helps to reduce routine flaring, employ methane capture, optimize production and reservoir management using digital tools such as IoT sensors, digital twins, and virtual reality to model scenarios, monitor operations, track emissions, energy usage and proactively maintain equipment, produce lower-emission products by moving from one hydrocarbon to another (e.g., from coal to natural gas) or creating another product (such as biofuels or syngas). Transformative technologies, particularly IoT, mobility and cloud applications are going to have a profound effect on the future of the oil and gas sector. Investment in these technologies cost a lot which might be difficult for private companies, but it is worth the money in the long run.


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