[HTML][HTML] A review of Pakistani shales for shale gas exploration and comparison to North American shale plays

GM Sohail, AE Radwan, M Mahmoud - Energy Reports, 2022 - Elsevier
Recent advancements in technologies to produce natural gas from shales at economic rates
has revealed new horizons for hydrocarbon exploration and development worldwide. The …

Tight and Shale Oil Exploration: A Review of the Global Experience and a Case of West Siberia

DB Dorhjie, E Mukhina, A Kasyanenko, A Cheremisin - Energies, 2023 - mdpi.com
Shale and tight oil reservoirs, with horizontal wells and hydraulic fractures, typically have a
recovery ratio of around 10%. The exploration of tight oil and shale in North America has …

Seismic driven reservoir classification using advanced machine learning algorithms: A case study from the lower Ranikot/Khadro sandstone gas reservoir, Kirthar fold …

U Manzoor, M Ehsan, AE Radwan, M Hussain… - Geoenergy Science and …, 2023 - Elsevier
Reservoir characterization of thin sand bed reservoirs has been a challenge for petroleum
explorers across the globe. In this study, we have studied the heterogeneous Paleocene …

Machine learning accelerated approach to infer nuclear magnetic resonance porosity for a middle eastern carbonate reservoir

A Mustafa, Z Tariq, M Mahmoud, A Abdulraheem - Scientific Reports, 2023 - nature.com
Carbonate rocks present a complicated pore system owing to the existence of intra-particle
and interparticle porosities. Therefore, characterization of carbonate rocks using …

An integrated geochemical analysis, basin modeling, and palynofacies analysis for characterizing mixed organic-rich carbonate and shale rocks in Mesopotamian …

AQ Mahdi, MI Abdel-Fattah, HA Hamdan - Journal of Petroleum Science …, 2022 - Elsevier
Shales and carbonate-rich sediments are crucial in characterizing the geological history of
petroleum as source rocks. This emphasizes the global significance of carbonate source …

A novel ensemble machine learning model to predict mine blasting–induced rock fragmentation

M Yari, B He, DJ Armaghani, P Abbasi… - Bulletin of Engineering …, 2023 - Springer
In production blasting, the primary goal is to produce an appropriate fragmentation, whereas
an improper fragmentation is one of the most common side effects induced by these events …

Application of Machine Learning for Mineralogy Prediction from Well Logs in the Bakken Petroleum System

A Laalam, A Boualam, H Ouadi, S Djezzar… - SPE Annual Technical …, 2022 - onepetro.org
One of the significant unconventional oil reserves in the USA is the Bakken Petroleum
System located in the Williston Basin. It is known for its complex lithology, composed of three …

An advanced long short-term memory (LSTM) neural network method for predicting rate of penetration (ROP)

H Ji, Y Lou, S Cheng, Z Xie, L Zhu - ACS omega, 2022 - ACS Publications
Rate of penetration (ROP) is an essential factor in drilling optimization and reducing the
drilling cycle. Most of the traditional ROP prediction methods are based on building physical …

Implications of machine learning on geomechanical characterization and sand management: a case study from Hilal field, Gulf of Suez, Egypt

WK Abdelghany, MS Hammed, AE Radwan - Journal of Petroleum …, 2023 - Springer
Sand production is one of the major challenges in the oil and gas industry, so a
comprehensive geomechanical analysis is necessary to mitigate sand production in mature …

Experimental study on mechanical properties and fracture characteristics of shale layered samples with different mineral components under cyclic loading

G Li, Z Jin, X Li, K Liu, W Yang, M Qiao, T Zhou… - Marine and Petroleum …, 2023 - Elsevier
In shale plays, the in-situ effective stress is continuously being perturbed because of the
production which impacts field operations. Therefore, mechanical properties of the formation …