201 research outputs found
ProLanGO: Protein Function Prediction Using Neural~Machine Translation Based on a Recurrent Neural Network
With the development of next generation sequencing techniques, it is fast and
cheap to determine protein sequences but relatively slow and expensive to
extract useful information from protein sequences because of limitations of
traditional biological experimental techniques. Protein function prediction has
been a long standing challenge to fill the gap between the huge amount of
protein sequences and the known function. In this paper, we propose a novel
method to convert the protein function problem into a language translation
problem by the new proposed protein sequence language "ProLan" to the protein
function language "GOLan", and build a neural machine translation model based
on recurrent neural networks to translate "ProLan" language to "GOLan"
language. We blindly tested our method by attending the latest third Critical
Assessment of Function Annotation (CAFA 3) in 2016, and also evaluate the
performance of our methods on selected proteins whose function was released
after CAFA competition. The good performance on the training and testing
datasets demonstrates that our new proposed method is a promising direction for
protein function prediction. In summary, we first time propose a method which
converts the protein function prediction problem to a language translation
problem and applies a neural machine translation model for protein function
prediction.Comment: 13 pages, 5 figure
A simulation-based method to determine the coefficient of hyperbolic decline curve for tight oil production
Tight oil reservoirs are characterized by the ultra low porosity and permeability, making it a great challenge to enhance oil production. Owing to the fast development in hydraulic fracturing technology of horizontal wells, tight oil has been widely explored in North America. Individual wells have a long term of low production after a rapid production decline. This causes low cumulative production in tight oil reservoirs. A rate decline curve is the most common method to forecast their production rates. The forecast can provide useful information during decision making on future development of production wells. In this paper, a relationship is developed between the parameters of a hyperbolic decline curve and the reservoir/fracture properties when a reservoir simulation model is used based on the data from a real field. Understanding of this relationship improves the application of the hyperbolic decline curve and provides a useful reference to forecast production performance in a more convenient and efficient way.Cited as: Yu, Y., Chen, Z., Xu, J. A simulation-based method to determine the coefficient of hyperbolic decline curve for tight oil production. Advances in Geo-Energy Research, 2019, 3(4): 375-380, doi: 10.26804/ager.2019.04.0
Hydraulic fracturing-induced seismicity characterization through coupled modeling of stress and fracture-fault systems
This work summarizes our recent findings on hydraulic fracturing-induced seismicity nucleated in the Duvernay shale reservoirs within the Western Canada Sedimentary Basin. A coupled model of in-situ stress and fracture-fault systems was built to quantify four-dimensional stress and pressure changes and spatiotemporal seismicity nucleation during hydraulic fracturing. Five triggering mechanisms were successfully recognized in seismicity-frequent areas, including a direct hydraulic connection between impermeable faults and hydraulic fractures, fault slip owing to downward pressure diffusion, fault reactivation due to upward poroelastic stress perturbation, aftershocks of mainshock events, and reactivation of natural fractures surrounding the faults. This work shed light on how fracturing operations triggered the induced seismicity, providing a solid foundation for the investigation of controlling factors and mitigation strategies for hydraulic fracturing-induced seismicity.Cited as: Hui, G., Chen, Z., Chen, S., Gu, F. Hydraulic fracturing-induced seismicity characterization through coupled modeling of stress and fracture-fault systems. Advances in Geo-Energy Research, 2022, 6(3): 269-270. https://doi.org/10.46690/ager.2022.03.1
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