Controlling Factors of Shale Gas Production: What can Artificial Intelligence Tell Us?

2019 ◽  
Author(s):  
Qin He ◽  
Jonathan Bruno ◽  
Zhi Zhong
Keyword(s):  
Artificial Intelligence ◽  
Shale Gas ◽  
Gas Production ◽  
Controlling Factors

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.

scholarly journals The Genetic Mechanism and Evolution Process of Overpressure in the Upper Ordovician–Lower Silurian Black Shale Formation in the Southern Sichuan Basin

Minerals ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 238
Author(s):  
Xiaoqi Wang ◽  
Yanming Zhu
Keyword(s):  
Shale Gas ◽  
Southern China ◽  
Pressure Coefficient ◽  
Fluid Pressure ◽  
Initial Pressure ◽  
Gas Production ◽  
Controlling Factors ◽  
Formation Mechanisms ◽  
Hydrocarbon Generation ◽  
Upper Ordovician

The overpressure phenomenon is a widespread occurrence in unconventional shale gas reservoirs. Multiple overpressure shale gas fields were discovered in southern China, and there is no doubt that the gas production per well increases with increasing pressure coefficient (the ratio of the reservoir fluid pressure to the corresponding normal hydrostatic pressure). Thus, successful evaluation and production strategies of organic-rich shale deposits require an understanding of the evolution of the pressure coefficient and its controlling factors in these deposits. In this paper, drilling engineering data of a typical well were collected, and clay mineral tests and overburden diffusion coefficient experiments were conducted. Based on multiphysics simulations, this paper analyzes the overpressure characteristics and formation mechanisms of overpressure in the Longmaxi Formation shale, as well as its geological evolution and controlling factors. The results show that the large amount of shale gas is the cause of overpressure formation rather than disequilibrium compaction. The simulation results show that pressure coefficients of the typical well range from 0.84 to 1.49. The current pressure coefficient increases with increasing pressure coefficient after the last hydrocarbon generation. A large initial pressure coefficient (>1.9), short lifting time (<100 Ma) and small lifting amplitude (<4000 m) are favorable for the preservation of shale gas.

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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