可解释机器学习在油气领域人工智能中的研究进展与应用展望.

闵超, 文国权, 李小刚, 赵大志… - Natural Gas …, 2024 - search.ebscohost.com
人工智能作为战略性新兴产业及新质生产力正迅速地渗透入油气领域, 并有望成为行业发展的新
引擎和制高点.“黑盒” 的机器学习模型缺乏透明度和可解释性, 导致现有机器学习方法在油气领域 …

Machine learning for open-pit mining: a systematic review

SQ Liu, L Liu, E Kozan, P Corry, M Masoud… - … Journal of Mining …, 2024 - Taylor & Francis
Nowadays, open-pit mining is the large-scale extraction of valuable ore materials from the
surface with the use of modern mining equipment. If not operated properly, various …

[HTML][HTML] Multi-horizon well performance forecasting with temporal fusion transformers

E Maldonado-Cruz, MJ Pyrcz - Results in Engineering, 2024 - Elsevier
Forecasting fluid flow in subsurface resources such as groundwater, geothermal, and oil and
gas is essential to maximize project economics and maximize resource recovery. We …

[HTML][HTML] Low-cycle fatigue design for reinforced high-strength concrete under high compressive stress

DS Yang, D Xue, H Xu, W Duan - Case Studies in Construction Materials, 2024 - Elsevier
As engineering endeavors push the boundaries of material and design capabilities, the
significance of understanding and mitigating fatigue in construction materials becomes …

Stop Using Black-Box Models: Application of Explainable Artificial Intelligence for Rate of Penetration Prediction

H Meng, B Lin, Y Jin - SPE Journal, 2024 - onepetro.org
Rate of penetration (ROP) prediction plays a crucial role in optimizing drilling efficiency and
reducing overall costs in the petroleum industry. Although modern artificial intelligence (AI) …

[HTML][HTML] Oil and gas flow anomaly detection on offshore naturally flowing wells using deep neural networks

G Bayazitova, M Anastasiadou… - Geoenergy Science and …, 2024 - Elsevier
The oil and gas industry is changing. The drive towards cleaner and safer operations is
becoming increasingly important. Researchers are looking for more efficient and accurate …

Geomechanical Rock Properties from Surface Drilling Telemetry

A Olkhovikov, D Koroteev, K Antipova - SPE Journal, 2023 - onepetro.org
We present a novel approach for real-time estimation of the mechanical properties of rock
with drilling data. We demonstrate that surface drilling telemetry (also known as mud …

[HTML][HTML] Разработка алгоритмов раннего прогнозирования нестандартных ситуаций при бурении скважин (Development of algorithms for predictive alarming on …

ЕВ Гурина - 2024 - dissercat.com
A significant proportion of the investment and capital expenditures of oil and gas companies
falls on the drilling of wells during the development of fields [29], as well as during the …

Machine learning-based uncertainty models for reservoir property prediction and forecasting

E Maldonado Cruz - 2023 - repositories.lib.utexas.edu
In subsurface data analytics and machine learning, advances enable new methods and
workflows for spatio-temporal, geoscience, and engineering property estimation and …

[PDF][PDF] Анализ опыта применения методов машинного обучения при бурении нефтяных и газовых скважин

ВА Старцев, ГВ Буслаев… - … нефтяных и газовых …, 2023 - researchgate.net
В данной работе приведен анализ мирового опыта использования различных методов
машинного обучения в нефтегазовой отрасли для оптимизации процесса бурения …