Water Use for Shale-Gas Production in Texas, U.S.

2012 ◽  
Vol 46 (6) ◽  
pp. 3580-3586 ◽  
Author(s):  
Jean-Philippe Nicot ◽  
Bridget R. Scanlon
Keyword(s):  
Water Use ◽  
Shale Gas ◽  
Gas Production

scholarly journals Water Availability Assessment of Shale Gas Production in the Weiyuan Play, China

2019 ◽  
Author(s):  
Xia Wu ◽  
Xia Jun ◽  
Baoshan Guan ◽  
Xinming Yan ◽  
Lei Zou ◽  
...  
Keyword(s):  
Water Use ◽  
Shale Gas ◽  
Water Availability ◽  
Water Footprint ◽  
Management Strategies ◽  
Gas Production ◽  
Water Withdrawal ◽  
Gas Industry ◽  
Streamflow Statistics ◽  
Availability Assessment

Innovations and improvements in hydraulic fracturing and horizontal well technologies have contributed to the success of the shale gas industry; however, the industry is also challenged by freshwater use and environmental health issues. Increasing water impact makes precise quantification of water consumption important. The objective in this study was to better understand water sustainability and availability of the projected shale gas from 2018 to 2030 in the Weiyuan play, China. The water footprint framework was used to quantify the potential water use and environmental impacts on different time scales. The results showed that the water use per well ranged from 11351.3 to 60664.73 m3, with a median of 36013.94 m3, totaling ~3.44 Mm3 for 97 wells. Yearly evaluation results showed that the gray water footprint was the main contributor and accounted for 83.82% to 96.76%, which was dependent on different scenarios of treatment percentages. The monthly environmental impact results indicated that the annual streamflow statistics were more likely to prevent water withdrawal. Water quality issues may be alleviated through recycling and retreatment measures that improve current waste water management strategies. Resource regulators should manage their water resources by matching water demand to water availability or replenishment.

scholarly journals Water Availability Assessment of Shale Gas Production in the Weiyuan Play, China

2019 ◽  
Vol 11 (3) ◽  
pp. 940 ◽  
Author(s):  
Xia Wu ◽  
Jun Xia ◽  
Baoshan Guan ◽  
Xinming Yan ◽  
Lei Zou ◽  
...  
Keyword(s):  
Water Use ◽  
Shale Gas ◽  
Water Availability ◽  
Water Footprint ◽  
Management Strategies ◽  
Gas Production ◽  
Water Withdrawal ◽  
Gas Industry ◽  
Streamflow Statistics ◽  
Availability Assessment

Innovations and improvements in hydraulic fracturing and horizontal well technologies have contributed to the success of the shale gas industry; however, the industry is also challenged by freshwater use and environmental health issues, and this makes precise quantification of water consumption important. The objective of this study was to better understand water sustainability and availability of the projected shale gas from 2018 to 2030 in the Weiyuan play, China. The water footprint framework was used to quantify the potential water use and environmental impacts on different time scales. The results showed that the water use per well ranged from 11,300 to 60,660 m3, with a median of 36,014 m3, totaling ~ 3.44 Mm3 for 97 wells. Yearly evaluation results showed that the gray water footprint was the main contributor and accounted for 83.82% to 96.76%, which was dependent on the different treatment percentage scenario. The monthly environmental impact results indicated that the annual streamflow statistics were more likely to prevent water withdrawal. Water quality issues may be alleviated through recycling and retreatment measures that improve current waste water management strategies. Resource regulators should manage their water resources by matching water demand to water availability or replenishment.

scholarly journals New Hybrid Approach for Developing Automated Machine Learning Workflows: A Real Case Application in Evaluation of Marcellus Shale Gas Production

Fuels ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 286-303
Author(s):  
Vuong Van Pham ◽  
Ebrahim Fathi ◽  
Fatemeh Belyadi
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Shale Gas ◽  
Field Data ◽  
Marcellus Shale ◽  
Hybrid Approach ◽  
Gas Production ◽  
Bayesian Optimization ◽  
Real Field ◽  
Engineering Problems

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.

Lithology and sedimentary heterogeneity of the Longmaxi Shale in the southern Sichuan Basin, China

2021 ◽  
pp. 1-49
Author(s):  
Boling Pu ◽  
Dazhong Dong ◽  
Ning Xin-jun ◽  
Shufang Wang ◽  
Yuman Wang ◽  
...  
Keyword(s):  
Continental Shelf ◽  
Deep Water ◽  
Shale Gas ◽  
Sichuan Basin ◽  
Sedimentary Environment ◽  
Gas Production ◽  
Carbonaceous Shale ◽  
Gas Wells ◽  
Longmaxi Shale ◽  
Siliceous Shale

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.

Sliding behavior of silica ball-shale rock contact under polyacrylamide aqueous solutions

2021 ◽  
pp. 1-25
Author(s):  
Huijie Zhang ◽  
Shuhai Liu
Keyword(s):  
Adverse Effect ◽  
Shale Gas ◽  
Normal Load ◽  
Gas Production ◽  
Wear Depth ◽  
Brine Solution ◽  
Shale Rock ◽  
Different Types ◽  
The Coefficient Of Friction ◽  
Specific Speed

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.

New insights from shale gas production at the microscopic scale

2018 ◽  
Vol 41 (11) ◽  
Author(s):  
Natalia Kovalchuk ◽  
Constantinos Hadjistassou
Keyword(s):  
Shale Gas ◽  
Gas Production ◽  
Microscopic Scale
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