A Commentary on the Applications of Python in Resolving Issues Concerning Energy and the Ecosystems
DOI:
https://doi.org/10.18034/apjee.v8i2.655Keywords:
Python, Gas Problems, Energy, Artificial intelligence, Internet of things, Machine learningAbstract
The energy industry is just getting started with applying it to problems with energy and ecosystems so they can find solutions. Python's popularity has increased across a variety of sectors, including businesses, academic institutions, government agencies, and research organizations. The true potential it possesses to automate a variety of processes while simultaneously increasing the capabilities of various industries to predict outcomes has been observed. Because of the digital transformation, such as sensors and high-performance computing services, which enable artificial intelligence (AI), machine learning (ML), big data acquisition, and storage in digital oilfields, its popularity has been on the rise in the industry that deals with energy and ecosystems. This is one of the primary reasons why. This can be easily verified by conducting a quick search for the number of publications that have been produced in the field of energy and ecosystems by the Society of Petroleum Engineers over the past few years. Without having to invest in pricey software, the production and reservoir engineers will be able to better manage the production operation thanks to this development. In addition to this, it will lead to a decrease in the overall operating costs and an increase in revenue. As a result, it has been demonstrated to be a promising application that has the potential to bring about a revolutionary change in the industry of energy and ecosystems and to transform the features that are already in place for the purpose of resolving issues related to energy and ecosystems.
Downloads
References
Abbas H, Mustapha H. An Efficient Method to Control Oilfield Wells Through Advanced Field Management Ensemble-Based Optimization Capabilities. Presented at the Abu Dhabi International Petroleum Exhibition and Conference. 2019; SPE-197730-MS. Available: https://doi.org/10.2118/197730-MS
Achar, S. (2015). Requirement of Cloud Analytics and Distributed Cloud Computing: An Initial Overview. International Journal of Reciprocal Symmetry and Physical Sciences, pp. 2, 12–18. Retrieved from https://upright.pub/index.php/ijrsps/article/view/70
Achar, S. (2016). Software as a Service (SaaS) as Cloud Computing: Security and Risk vs. Technological Complexity. Engineering International, 4(2), 79–88. https://doi.org/10.18034/ei.v4i2.633
Achar, S. (2018a). Data Privacy-Preservation: A Method of Machine Learning. ABC Journal of Advanced Research, 7(2), 123–129. https://doi.org/10.18034/abcjar.v7i2.654
Achar, S. (2018b). Security of Accounting Data in Cloud Computing: A Conceptual Review. Asian Accounting and Auditing Advancement, 9(1), 60–72. https://4ajournal.com/article/view/70
Achar, S. (2019). Early Consequences Regarding the Impact of Artificial Intelligence on International Trade. American Journal of Trade and Policy, 6(3), 119–126. https://doi.org/10.18034/ajtp.v6i3.634
Akter, N., Rahman, M. M., & Akter, S. (2013). Introducing a Phenomenon of Single Junction Multiple Band-gap Solar Cell Compared to Single Junction or Multi Junction Solar Cell to Achieve High Efficiency. ABC Journal of Advanced Research, 2(1), 30-35. https://doi.org/10.18034/abcjar.v2i1.16
Al Mahmud, T. (2012). A Survey on How Dynamically Changes Topology in Wireless Sensor Network. ABC Journal of Advanced Research, 1(1), 28-34. https://doi.org/10.18034/abcjar.v1i1.3
Amin, R. (2019). Innovations in Information Systems for Business Functionality and Operations Management. ABC Research Alert, 7(3), 148–158. https://doi.org/10.18034/abcra.v7i3.546
Asala HI, Chebeir J, Zhu WI, Gupta A, Taleghani D, Romagnoli J. A Machine Learning Approach to Optimize Shale Gas Supply Chain Networks. Presented at the SPE Annual Technical Conference and Exhibition. 2017; SPE-187361-MS. Available: https://doi.org/10.2118/187361-MS
Atikol, U., Enayatollahi, R., & Madani, S. S. (2013). Performance of a Solar Humidification Dehumidification Desalination System on December 27th and 28th in North Cyprus. ABC Journal of Advanced Research, 2(1), 20-29. https://doi.org/10.18034/abcjar.v2i1.15
Awan, A. G. (2015). Environmental Challenges to South Asian Countries. Asian Accounting and Auditing Advancement, 6(1), 83–102. https://doi.org/10.18034/4ajournal.v6i1.38
Choi Jung C, Skurtveit E, Lars Grande. Deep Neural Network Based Prediction of Leak-Off Pressure in Offshore Norway. Presented at the Offshore Technology Conference. 2019; OTC-29454-MS. Available: https://doi.org/10.4043/29454-MS.
Diakonova E, Bonnet G. Yann Brouard. Innovative Design Methodology Supporting Concept EngineeringThrough to Project Cost Optimization. Presented at the Offshore Technology Conference. 2019;OTC-29529-MS. Available: https://doi.org/10.4043/29529-MS
Dipa, D. D., Abedin, K., Khan, M. M., & Hasan, M. M. (2015). Impacts of Energy Subsidy in Bangladesh: An Analysis. ABC Journal of Advanced Research, 4(1), 39-56. https://doi.org/10.18034/abcjar.v4i1.44
Ejimuda CC, Ejimuda CM. Using Deep Learning and Computer Vision Techniques to Improve Facility Corrosion Risk Management Systems. Presented at the SPE Nigeria Annual International Conference and xhibition. 2018; SPE-190036-MS. Available: https://doi.org/10.2118/198863-MS
Graziatti, L. V. (2017). The Treaty of Rome EEC and EURATOM 1957. ABC Research Alert, 5(3), Peru. https://doi.org/10.18034/abcra.v5i3.316
Hesar M, TziPiau C, Qingjing M, Leonardo G, Carlos C. Seismic Design of Large Scale Integrated Subsea Facilities. presented at the 28th International Ocean and Polar Engineering Conference. 2018;10–15:ISOPE-I-18-681.
Hossain, S., Mrida, M. I. A., Das, P. C., Sayed, A., Rahman, N., & Rashid, M. M. (2015). Mimo Channel and Performance Analysis using OFDM System for Reduced Bit Error Rate. ABC Research Alert, 3(3), Bangladesh. https://doi.org/10.18034/abcra.v3i3.299
Hossain, S., Rahman, M. S., & Yeasmin, S. (2019). Environmental Radioactivity Monitoring and Assessment of Excess Lifetime Cancer Risk to People in Demra Thana, Dhaka, Bangladesh. ABC Research Alert, 7(3), Bangladesh. https://doi.org/10.18034/abcra.v7i3.269
Hosseinimotlagh, S. N. (2014). Computation of time energy gain in D-3He mixture: Energy deposited through deuterium ignition beam. Asia Pacific Journal of Energy and Environment, 1(2), 153-168. https://doi.org/10.18034/apjee.v1i2.217
Kushkumbayeva G, Zhumabayev B, Daniyar G, Ruslan B, Justus A, Tamer S, Giovanni B, Alberto B. Evaluating Effectiveness of Stimulation Treatment in Karachaganak Multistage Wells. Presented at the SPE Annual Caspian Technical Conference and Exhibition. 2018; 2:SPE-192569-S. https://doi.org/10.2118/192569-MS
Maiorano S, Selvaggio P, Distaso RE, Rossi R, Stano E. Innovative Water Salinity Management Through Integrated Asset Model Applied to Mexico Area-1. Presented at the SPE Reservoir Characterization and Simulation Conference and Exhibition. 2019; 17– 19.SPE-196622-MS. Available: https://doi.org/10.2118/196622-MS
Mohammadmoradi P, Moradi, Hessam M, Kantzas A. Data-Driven Production Forecasting of Unconventional Wells with Apache Spark. Presented at the SPE Western Regional Meeting. 2018; SPE-190098-MS. Available: https://doi.org/10.2118/190098-MS
Nasreen, H., & Hassan, M. (2019). Nitazoxanide – A New Option in Biliary Ascariasis. ABC Research Alert, 7(1), Bangladesh. https://doi.org/10.18034/abcra.v7i1.236
Noshi C, Noynaert S. Jerome Schubert. Data Mining Approaches for Casing Failure Prediction and Prevention. presented at the International Petroleum Technology Conference. 2019; IPTC-19311-MS. Available: https://doi.org/10.2523/IPTC-19311-MS
Noshi CI, Noynaert SF, Schubert JJ. Failure Predictive Analytics Using Data Mining: How to Predict Unforeseen Casing Failures? Presented at the Abu Dhabi International Petroleum Exhibition & Conference. 2018;SPE-193194-MS. Available: https://doi.org/10.2118/193194-MS
Ojah M, Emumena E, Collins O, Oduh P, Steve A. Determination of Optimal Well Location in Bounded Reservoirs Using the Dimensionless Pressure Derivative. SPE-203627-MS. presented at the SPE Nigeria Annual International Conference and Exhibition; 2020. Available: https://doi.org/10.2118/203627-MS
Ojha, A., & Bairagi, S. (2013). Corporate Restructuring. ABC Research Alert, 1(1), India. https://doi.org/10.18034/abcra.v1i1.243
Olusola Bukola K, Orozco D, Aguilera R. Optimization of Recovery by Huff and Puff Gas Injection in Shale Oil Reservoirs Using the Climbing Swarm Derivative Free Algorithm. Presented at the SPE Latin American and Caribbean Petroleum Engineering Conference. 2020; SPE-199028-MS. Available: https://doi.org/10.2118/199028-MS
Rodger I, Andrew, Garnett. Lost Time Analysis of Queensland Coal Seam Gas Drilling Data and Where Next for Improvement? Presented at the SPE Asia Pacific Oil and Gas Conference and Exhibition. 2018; SPE-192034-MS. Available: https://doi.org/10.2118/192034-MS
Saadallah N, Jan Einar Gravdal, Robert Ewald, Sonja Moi, Adrian Ambrus, and Benoit Daireaux, Norce; Stian Sivertsen and Kristian Hellang, Miles; Roman Shor, Dan Sui; Stefan Ioan Sandor, Aker BP; Marek Chojnacki, Jacob Odgaard. OpenLab: Design and Applications of a Modern Drilling Digitalization Infrastructure. Presented at the SPE Norway One Day Seminar. 2019; SPE-195629-MS. Available: https://doi.org/10.2118/195629-MS
Saini G, Chan H, Ashok PE, Van, Oort MR. Isbell. Automated Large Data Processing: A Storyboarding Process to Quickly Extract Knowledge from Large Drilling Datasets. Presented at the IADC/SPE Drilling Conference and Exhibition. 2018; IADC/SPE-189605-MS. Available: https://doi.org/10.2118/189605-MS
Sarkar, M. S. K., Sadeka, S., Sikdar, M. M. H., & Badiuzzaman. (2018). Energy Consumption and CO2 Emission in Bangladesh: Trends and Policy Implications. Asia Pacific Journal of Energy and Environment, 5(1), 41-48. https://doi.org/10.18034/apjee.v5i1.249
Shoaib M, Selvaggio P, Cominelli A, Rossi R, Thompson A, Amoudruz P. Flexible Integrated Asset Models for Deep Water Developments Presented at the Offshore Mediterranean Conference and Exhibition. 2019; OMC-2019-0996.
Velmurugan, C., & Radhakrishnan, N. (2018). Visualizing Energy and Environment Research Productivity in Australia: A Scientometric Profile. Asia Pacific Journal of Energy and Environment, 5(1), 11–26. https://doi.org/10.18034/apjee.v5i1.246
Yahaya, I., & Mato, U. (2017). Workforce Diversity and Organizational Effectiveness in 21st Century Business Arena. Asian Accounting and Auditing Advancement, 8(1), 24–29. https://doi.org/10.18034/4ajournal.v8i1.46
Zhou W, Samad Ali, Shripad B. Openness in Reservoir Simulation: Empowering Flexible Field Management. Presented at the SPE Asia Pacific Oil & Gas Conference and Exhibition. 2020; SPE-202303-MS. Available: https://doi.org/10.2118/202303-MS
--0--
Downloads
Published
Issue
Section
License
How to Cite
