scholarly journals Predictive assessment for the potential pollution of underground hydrosphere due to extraction of unconventional hydrocarbons (using remote sensing data)

Author(s):  
Vadim Lyalko ◽  
Oleksandr Azimov ◽  
Yevgen Yakovlev

The article considers the relevance of the application of modern remote aerospace and hydrogeological methods in the problems of the ecological safety for the hydrosphere in Ukraine during unconventional hydrocarbons extraction, especially shale gas is considered. Case studies of pilot implementation of these methods are present for the Bilyaivska area adjacent to the Yuzivka licensed site within the Dnieper-Donets Depression as the biggest artesian basin within Ukraine. A number of the hydrogeological filtration parameters of multilayers' system (water aquifers, aquitard and aquiclude regional layers) enable to obtain the rough estimate of the temporal indices for the areal upward pollutant migration from the fracturing zone to the groundwater aquifers in the potential process of shale gas production (as an example the 400-Bilyaivska well). It is found that the possible variety of the rock double permeability in the complete rock continuum is responsible for the passage time of diffusive convective pollutant migration from the fracturing zone to the groundwater aquifers, and this time interval consists of 170 ÷70 years. Considering the balance ratio between the water volume for the dilution of pollutants to the safe concentrations and the volume of porous solutions, which is over the fracturing zone the conclusion is drawn that remains of technological solutions in the fracturing zone in some cases can continuously contaminate the underground water within the zones of slow and active water exchange.

2014 ◽  
Vol 522-524 ◽  
pp. 1039-1044
Author(s):  
Qiu Lei Guo ◽  
Shu Heng Tang ◽  
Yi Wan ◽  
Er Ping Fan

When energy crisis is somewhat relieved by the shale gas production, serious negative impacts are simultaneously created to the environment e.g. the regional underground water system will be seriously damaged. Currently, the shale gas production, which is blossoming in China at present, centralizes primarily in the South-west area, where the hydrological environment is quite complicated and pretty weak. In this paper, three threatens caused during the shale gas exploitation is summarized and the crisis source is also outlined. Furthermore, the probable solutions aiming at these problems are discussed, thereby the concept of ‘Water resources tolerance ability evaluation model in SouthWest China’ being proposed. This paper emphasizes that the further enhancement of environment monitoring, improvement of legislation in the related areas as well as domestic adjustment of production technologies are critical to balance the industrializing production and sustainable development.


Fuels ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 286-303
Author(s):  
Vuong Van Pham ◽  
Ebrahim Fathi ◽  
Fatemeh Belyadi

The success of machine learning (ML) techniques implemented in different industries heavily rely on operator expertise and domain knowledge, which is used in manually choosing an algorithm and setting up the specific algorithm parameters for a problem. Due to the manual nature of model selection and parameter tuning, it is impossible to quantify or evaluate the quality of this manual process, which in turn limits the ability to perform comparison studies between different algorithms. In this study, we propose a new hybrid approach for developing machine learning workflows to help automated algorithm selection and hyperparameter optimization. The proposed approach provides a robust, reproducible, and unbiased workflow that can be quantified and validated using different scoring metrics. We have used the most common workflows implemented in the application of artificial intelligence (AI) and ML in engineering problems including grid/random search, Bayesian search and optimization, genetic programming, and compared that with our new hybrid approach that includes the integration of Tree-based Pipeline Optimization Tool (TPOT) and Bayesian optimization. The performance of each workflow is quantified using different scoring metrics such as Pearson correlation (i.e., R2 correlation) and Mean Square Error (i.e., MSE). For this purpose, actual field data obtained from 1567 gas wells in Marcellus Shale, with 121 features from reservoir, drilling, completion, stimulation, and operation is tested using different proposed workflows. A proposed new hybrid workflow is then used to evaluate the type well used for evaluation of Marcellus shale gas production. In conclusion, our automated hybrid approach showed significant improvement in comparison to other proposed workflows using both scoring matrices. The new hybrid approach provides a practical tool that supports the automated model and hyperparameter selection, which is tested using real field data that can be implemented in solving different engineering problems using artificial intelligence and machine learning. The new hybrid model is tested in a real field and compared with conventional type wells developed by field engineers. It is found that the type well of the field is very close to P50 predictions of the field, which shows great success in the completion design of the field performed by field engineers. It also shows that the field average production could have been improved by 8% if shorter cluster spacing and higher proppant loading per cluster were used during the frac jobs.


2021 ◽  
pp. 1-49
Author(s):  
Boling Pu ◽  
Dazhong Dong ◽  
Ning Xin-jun ◽  
Shufang Wang ◽  
Yuman Wang ◽  
...  

Producers have always been eager to know the reasons for the difference in the production of different shale gas wells. The Southern Sichuan Basin in China is one of the main production zones of Longmaxi shale gas, while the shale gas production is quite different in different shale gas wells. The Longmaxi formation was deposited in a deep water shelf that had poor circulation with the open ocean, and is composed of a variety of facies that are dominated by fine-grained (clay- to silt-size) particles with a varied organic matter distribution, causing heterogeneity of the shale gas concentration. According to the different mother debris and sedimentary environment, we recognized three general sedimentary subfacies and seven lithofacies on the basis of mineralogy, sedimentary texture and structures, biota and the logging response: (1) there are graptolite-rich shale facies, siliceous shale facies, calcareous shale facies, and a small amount of argillaceous limestone facies in the deep - water shelf in the Weiyuan area and graptolite-rich shale facies and carbonaceous shale facies in the Changning area; (2) there are argillaceous shale facies and argillaceous limestone facies in the semi - deep - water continental shelf of the Weiyuan area and silty shale facies in the Changning area; (3) argillaceous shale facies are mainly developed in the shallow muddy continental shelf in the Weiyuan area, while silty shale facies mainly developed in the shallow shelf in the Changning area. Judging from the biostratigraphy of graptolite, the sedimentary environment was different in different stages.


2021 ◽  
pp. 1-25
Author(s):  
Huijie Zhang ◽  
Shuhai Liu

Abstract The tribological properties of proppant particle sliding on shale rock determine the shale gas production. This work focuses on investigating the impacts of sliding speed on the coefficient of friction (COF) and wear of the silica ball-shale rock contact, which was lubricated by water or different types of polyacrylamide (PAM) aqueous or brine solution. The experimental results show that both boundary and mixed lubrication occur under specific speed and normal load. COF and wear depth of shale rock under water are higher than those under PAM solution due to superior lubrication of PAM. COF of shale rock under PAM brine solution increases and the wear of the rock is more serious, attributed to the corrosion of shale rock and adverse effect on lubrication of PAM by brine.


2018 ◽  
Vol 41 (11) ◽  
Author(s):  
Natalia Kovalchuk ◽  
Constantinos Hadjistassou

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