Explicit calculation of nuclear magnetic resonance relaxation rates in small pores to elucidate molecular scale fluid dynamics [PDF]
Phys. Rev. E 95, 033117 (2017), 2016 A model linking the molecular-scale dynamics of fluids confined to nano-pores to nuclear magnetic resonance (NMR) relaxation rates is proposed. The model is fit to experimental NMR dispersions for water and oil in an oil shale assuming that each fluid is characterised by three time constants and L\'{e}vy statistics.
arxiv +1 more source
The influence of pyrolysis type on shale oil generation and its composition (Upper layer of Aleksinac oil shale, Serbia) [PDF]
, 2017 The influence of pyrolysis type on shale oil generation and its composition was studied. Different methods such as Rock-Eval pyrolysis, thermogravimetric analysis (TGA) and pyrolysis in the open and closed systems were applied.
Aleksic, Nikoleta +5 more
core +5 more sources
Loopless non-trapping invasion percolation model for fracking [PDF]
Phys. Rev. E 02/2014; 89(2):022119, 2014 Recent developments in hydraulic fracturing (fracking) have enabled the recovery of large quantities of natural gas and oil from old, low permeability shales. These developments include a change from low-volume, high-viscosity fluid injection to high-volume, low-viscosity injection.
arxiv +1 more source
Granulation of oil shale ash with sodium alginate for the removal of phenols from shale oil wastewater [PDF]
, 2018 Granulated oil shale ash is used for removal of phenols from shale oil waste waterGranulation of oil shale ash with sodium alginate for the removal of phenols from shale oil wastewaterOil shale ash (OSA) from the circulating fluidized bed (CFB) boiler ...
Heinmaa, Ivo +3 more
core +1 more source
Oil Shale and Its Potential Utilization [PDF]
, 1974 The large deposits of oil shale in the Green River Formation in Colorado, Utah, and Wyoming offer a potential source of significant quantities of liquid fuels.
Dineen, G. U.
core +1 more source
Managing Data Lineage of O&G Machine Learning Models: The Sweet Spot for Shale Use Case [PDF]
2020 European Association of Geoscientists and Engineers (EAGE)
Digitalization Conference and Exhibition, 2020 Machine Learning (ML) has increased its role, becoming essential in several industries. However, questions around training data lineage, such as "where has the dataset used to train this model come from?"; the introduction of several new data protection legislation; and, the need for data governance requirements, have hindered the adoption of ML models
arxiv
Optimising the Use of Spent Oil Shale [PDF]
, 2014 Worldwide deposits of oil shales are thought to represent ~3 trillion barrels of oil. Jordanian oil shale deposits are extensive and high quality, and could represent 100 billion barrels of oil, leading to much interest in the development of deposits ...
FOSTER, HELEN,JANE
core
The Price Responsiveness of Shale Producers: Evidence from Micro Data [PDF]
, 2022 We show that shale oil producers respond positively to favourable oil price signals, and that this response is mainly associated with the timing of production decisions through well completion and refracturing, consistent with the Hotelling theory of ...
Aastveit, Knut Are +2 more
core
Examining Rail Transportation Route of Crude Oil in the United States Using Crowdsourced Social Media Data [PDF]
Transportation Research Record, 2678(1), 218-228 (2024)Safety issues associated with transporting crude oil by rail have been a concern since the boom of US domestic shale oil production in 2012. During the last decade, over 300 crude oil by rail incidents have occurred in the US. Some of them have caused adverse consequences including fire and hazardous materials leakage. However, only limited information
arxiv +1 more source
Probabilistic Heat Transfer in Variably Random Oil Shale Kerogen Deposit [PDF]
, 2014 Oil shale is one of most potential unconventional oil sources to replace the conventional crude oil in future. It is a fine sedimentary rock which rich in organic substances called kerogen.
Hoe, Wong Leh
core