[HTML][HTML] A review of the application of data-driven technology in shale gas production evaluation

W Niu, J Lu, Y Sun, H Liu, X Cao, H Zhan, J Zhang - Energy Reports, 2023 - Elsevier
Shale gas, as an important unconventional natural gas resource, is the main force to
increase natural gas reserves and production in the future. For shale gas with huge …

An ensemble transfer learning strategy for production prediction of shale gas wells

W Niu, Y Sun, X Zhang, J Lu, H Liu, Q Li, Y Mu - Energy, 2023 - Elsevier
In order to overcome the training data insufficient problem of model for shale gas wells
production prediction in new block, this study proposes a transfer learning strategy of …

Toward production forecasting for shale gas wells using transfer learning

W Niu, Y Sun, X Yang, J Lu, S Zhao, R Yu… - Energy & …, 2023 - ACS Publications
Accurate prediction of shale gas well production and estimated ultimate recovery (EUR) is
always a difficult and hot spot in shale gas development. In particular, the production and …

A Review of Predictive Analytics Models in the Oil and Gas Industries

PA R Azmi, M Yusoff, MT Mohd Sallehud-din - Sensors, 2024 - mdpi.com
Enhancing the management and monitoring of oil and gas processes demands the
development of precise predictive analytic techniques. Over the past two years, oil and its …

Development of a Software Tool for Visualizing a Mine (Wellbore) in the Industrial Drilling of Oil Wells

F Abu-Abed, K Pivovarov, V Zhironkin, S Zhironkin - Processes, 2023 - mdpi.com
The purpose of the software development presented in the article is to obtain detailed
information about the surface of the walls in wells necessary for more efficient and safe …

[HTML][HTML] Waterflooding interwell connectivity characterization and productivity forecast with physical knowledge fusion and model structure transfer

Y Jiang, H Zhang, K Zhang, J Wang, J Han, S Cui… - Water, 2023 - mdpi.com
Waterflooding reservoir interwell connectivity characterization is the fundamental work in oil
development, aiming to inverse the vital connecting channels between injectors and …

A subsurface machine learning approach at hydrocarbon production recovery & resource estimates for unconventional reservoir systems: Making subsurface …

SJ Prochnow, NS Raterman, M Swenberg… - Journal of Petroleum …, 2022 - Elsevier
An innovative, practical, and successful subsurface machine learning workflow was
introduced that utilizes any structured reservoir, geologic, engineering and production data …

Self-supervised similarity models based on well-logging data

S Egorov, N Gevorgyan, A Zaytsev - arXiv preprint arXiv:2209.12444, 2022 - arxiv.org
Adopting data-based approaches leads to model improvement in numerous Oil&Gas
logging data processing problems. These improvements become even more sound due to …

A transfer learning framework for the assessment of unconventional resources opportunities in the Middle East

C Ashayeri, B Jha - Geoenergy Science and Engineering, 2025 - Elsevier
An inadequate understanding of fluid transport processes in ultra-low permeability rocks has
propelled data-driven modeling as an alternative and complementary tool to create recovery …

Application of gas spark switch: A plasma-based improvement technology for unconventional reservoir

S Zheng, Z Kang, Z Shao, X Fu, C Gao, K Li… - Journal of Natural Gas …, 2022 - Elsevier
Plasma pulse technology is one of the method to create fractures in the reservoir. This
technology is inexpensive and environmentally friendly as compared to other reservoir …