Fully connected deep network: An improved method to predict TOC of shale reservoirs from well logs

An improved neural network for TOC, S1 and S2 estimation based on conventional well logs

(2019) Huijun Wang et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

An improved method for evaluating the TOC content of a shale formation using the dual-difference ΔlogR method

(2019) Linqi Zhu et al.   MARINE AND PETROLEUM GEOLOGY

Applicability of deep neural networks on production forecasting in Bakken shale reservoirs

(2019) Shuhua Wang et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Total organic carbon content prediction based on support-vector-regression machine with particle swarm optimization

(2019) Jianwen Rui et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

An improved model for estimating the TOC in shale formations

(2017) Peiqiang Zhao et al.   MARINE AND PETROLEUM GEOLOGY

Revised models for determining TOC in shale play: Example from Devonian Duvernay Shale, Western Canada Sedimentary Basin

(2016) Pengwei Wang et al.   MARINE AND PETROLEUM GEOLOGY

Application of extreme learning machine and neural networks in total organic carbon content prediction in organic shale with wire line logs

(2016) Xian Shi et al.   Journal of Natural Gas Science and Engineering

The characteristics and significance of conventional and unconventional Sinian–Silurian gas systems in the Sichuan Basin, central China

(2015) Caineng Zou et al.   MARINE AND PETROLEUM GEOLOGY

Support-vector-regression machine technology for total organic carbon content prediction from wireline logs in organic shale: A comparative study

(2015) Maojin Tan et al.   Journal of Natural Gas Science and Engineering

Continuous hydrocarbon accumulation over a large area as a distinguishing characteristic of unconventional petroleum: The Ordos Basin, North-Central China

(2013) C.N. Zou et al.   EARTH-SCIENCE REVIEWS