A novel domain adaptation method with physical constraints for shale gas production forecasting
L Gou, Z Yang, C Min, D Yi, X Li, B Kong - Applied Energy, 2024 - Elsevier
Effective forecasting of shale gas production is essential for optimizing exploration strategies
and guiding subsequent fracturing. However, in the new development of shale gas blocks …
and guiding subsequent fracturing. However, in the new development of shale gas blocks …
Domain adaption and physical constrains transfer learning for shale gas production
Z Yang, L Gou, C Min, D Yi, X Li, G Wen - arXiv preprint arXiv:2312.10920, 2023 - arxiv.org
Effective prediction of shale gas production is crucial for strategic reservoir development.
However, in new shale gas blocks, two main challenges are encountered:(1) the occurrence …
However, in new shale gas blocks, two main challenges are encountered:(1) the occurrence …
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 …
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 …
always a difficult and hot spot in shale gas development. In particular, the production and …
Machine-learning-based well production prediction under geological and hydraulic fracture parameters uncertainty for unconventional shale gas reservoirs
C Xiao, G Wang, Y Zhang, Y Deng - Journal of Natural Gas Science and …, 2022 - Elsevier
Shale gas production prediction under history-matching-based geomodel is crucial to
achieve reliable assessment and economic management of unconventional shale …
achieve reliable assessment and economic management of unconventional shale …
Identifying the controlling geological and engineering factors of shale gas production using deep learning models: a case study from Weiyuan, China
Y Dong, Y Hao, D Lu - Petroleum Science and Technology, 2023 - Taylor & Francis
Predicting shale gas production is challenging due to varying and unclear influencing
factors. In this work, we explore the average daily production rate (ADPR) and its …
factors. In this work, we explore the average daily production rate (ADPR) and its …
[HTML][HTML] A novel framework for predicting non-stationary production time series of shale gas based on BiLSTM-RF-MPA deep fusion model
Shale gas, as an environmentally friendly fossil energy resource, has gained significant
commercial development and shows immense potential. However, accurately predicting …
commercial development and shows immense potential. However, accurately predicting …
A machine-learning inverse model framework for rapid forecasting and history matching in unconventional reservoirs
Model-based optimization for real-time forecasting in unconventional reser-voirs requires
novel methods and work? ows since the strategies and work? ows used in conventional …
novel methods and work? ows since the strategies and work? ows used in conventional …
Unsupervised Adversarial Domain Adaptation Regression for Rate of Penetration Prediction
J Jiang, Z Guo - SPE Journal, 2023 - onepetro.org
The rate of penetration (ROP) refers to the speed at which a drill bit breaks through rock and
deepens the drill hole. ROP is of great significance for drilling optimization and drilling cost …
deepens the drill hole. ROP is of great significance for drilling optimization and drilling cost …
A Combined Neural Network Forecasting Approach for CO2-Enhanced Shale Gas Recovery
Intensive growth of geological carbon sequestration has motivated the energy sector to
diversify its storage portfolios, given the background of climate change mitigation. As an …
diversify its storage portfolios, given the background of climate change mitigation. As an …