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Fracture prediction method for narrow-azimuth seismic data of offshore streamer acquisition
Considering the constraints in the costs and efficiency of seismic exploration acquisition, marine hydrocarbon exploration mainly relies on...
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Analysis of actual evapotranspiration changes in China based on multi-source data and assessment of the contribution of driving factors using an extended Budyko framework
Quantifying actual evapotranspiration (ETa) changes and the drivers is important for both water and energy cycles. However, these issues are commonly...
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Prediction of Minimum Mud Weight for Prevention of Breakout Using New 3D Failure Criterion to Maintain Wellbore Stability
Oil and gas extraction is difficult without understanding the subsurface formation up to the desired depth. Wellbore instability, such as lost...
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Prediction and predictability of boreal winter MJO using a multi-member subseasonal to seasonal forecast system of NUIST (NUIST CFS 1.1)
The Madden–Julian Oscillation (MJO) provides an important source of global subseasonal-to-seasonal (S2S) predictability, while its prediction remains...
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Precise prediction of polar motion using sliding multilayer perceptron method combining singular spectrum analysis and autoregressive moving average model
The precise prediction of polar motion parameters is needed for the astrogeodynamics, navigation and positioning of the deep space probe. However,...
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Subsurface structure identification at the blind prediction site of ESG6 based on the earthquake-to-microtremor ratio method and diffuse field concept for earthquakes
We participated in the blind prediction exercise organized by the committee of the blind prediction experiment during the 6th International Symposium...
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Groundwater Quality Analysis and Drinkability Prediction using Artificial Intelligence
Water quality strongly influences sustainable growth of a healthy society and green environment. According to the International Initiative on Water...
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Climate-induced deterioration prediction for bridges: an evolutionary computing-based framework
Bridge deterioration is attributed to inadequate maintenance budgets, ineffective restoration strategies, and rapidly changing climatic conditions....
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Probability prediction method for rockburst intensity based on rough set and multidimensional cloud model uncertainty reasoning
Rockburst is a serious disaster caused by the sudden release of rock energy during underground construction in high-stress environments, resulting in...
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A novel prediction method for coalbed methane production capacity combined extreme gradient boosting with bayesian optimization
Coalbed methane plays a significant role for the sustainable utilizing of resources and ecological environment. Production capacity forecasting of...
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Prediction of Filtering Efficiency of an Air Filter Using Light Shading Rate
There have been some studies on the theoretical formula for predicting the filtering efficiency of an air filter. However, accurate predictions...
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A new decomposition model of sea level variability for the sea level anomaly time series prediction
Rising sea level is of great significance to coastal societies; predicting sea level extent in coastal regions is critical. When carrying out...
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Typhoon Track, Intensity, and Structure: From Theory to Prediction
To improve understanding of essential aspects that influence forecasting of tropical cyclones (TCs), the National Key Research and Development...
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Soil–Water Retention Curve Prediction for Compacted London Clay Subjected to Moisture Cycles
The evolution of the hydraulic properties of London Clay when compacted at a range of initial conditions (density and water content) was...
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Stochastic Simulation and Development of the Ground Motion Prediction Equation for the Baikal Rift Zone
Abstract —To obtain realistic and correct estimates of seismic effects in the Baikal Rift Zone (BRZ), a ground motion prediction equation has been...
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Short-term rainfall prediction using MLA based on commercial microwave links of mobile telecommunication networks
Rainfall prediction is a major problem with considerable socio-economic, industrial, and environmental impacts. The expansion of mobile...
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Reservoir production capacity prediction of Zananor field based on LSTM neural network
This paper aims to explore the application of artificial intelligence in the petroleum industry, with a specific focus on oil well production...
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Model-based prediction of water levels for the Great Lakes: a comparative analysis
This comprehensive study addresses the correlation between water levels and meteorological features, including air temperature, evaporation, and...
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Porosity prediction using ensemble machine learning approaches: A case study from Upper Assam basin
Porosity is an important petrophysical parameter that determines the amount of fluid, including oil, water, and gas contained within the rock. In...
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Prediction of Fluid–Brine Event Zones by Artificial Intelligence Methods Based on New Generation RTH Seismic Attributes and Drilling Data at the Kovykta Gas Condensate Field
AbstractA new method for predicting lithofacies, gas, fluid and brine zones, and zones with abnormally high reservoir pressure, as well as the...
