Abstract The Marcellus Shale and Energy Environmental Laboratory (MSEEL) provides a
comprehensive dataset and field tests that can be used to study the significance of …

This study proposes the application of geostatistically generated well-log data to predict well
productivity in Marcellus shale reservoirs using ensemble machine learning (ESM). ESM …

Limiting the injection rate to restrict the pressure below a threshold at a critical location can
be an important goal of simulations that model the subsurface pressure between injection …

To obtain a reliable production forecast, one has to establish a geological model with well
logs and seismic data. The geological model usually has to be upscaled using certain …

Optimizing the development of unconventional resources is a complex process, with
significant uncertainty in reservoir characterization, completion effectiveness, and drainage …

Modelling of oil well systems is important for a wide range of petroleum scientific and oil
industrial processes. Considering the uncertainty of the measurements and the demand for …

Based on a genetic algorithm and field production data, this paper reasonably optimizes the
fracture parameters of multistage fractured horizontal wells (MFHWs). First, a mathematical …

A reservoir-scale numerical conceptual model was established according to the actual
geological characteristics of a carbonate fractured-vuggy reservoir. Considering the …

随着基础理论和硬件计算能力的飞速发展, 深度学**技术在众多领域取得了令人瞩目的成绩.
作为描述客观物理世界的重要工具, 长期以来微分方程是各领域研究人员关心的重点. **年来 …

This research introduces a novel approach to overcoming key challenges in applying
machine learning (ML) for production forecasting and performance evaluation in …