Results 1 to 10 of about 5,928 (182)

A Semi-Analytical Model for Production Prediction of Deep CBM Wells Considering Gas-Water Two-Phase Flow

Processes, 2023
The productivity prediction of deep coalbed methane (CBM) wells is significantly influenced by gas-water two-phase flow characteristics and seepage parameters of the fracture network. While numerical simulations offer a comprehensive approach, analytical models are favored for their faster and broader applicability.
Suran Wang, Wang Suran
exaly   +3 more sources

Critical technologies and geology-engineering integration practices for deep CBM production in the Yanchuannan CBM field [PDF]

Meitian dizhi yu kantan
Objective and Methods This study introduces the adjustments for coalbed methane (CBM) production in the Yanchuannan CBM field‒the first deep CBM field in China.
Zhenlong CHEN, Yunhai WANG, Xiao LIU, Bin CUI, Song YANG, Xin LI, Qilong FANG   +6 more
doaj   +3 more sources

Deep coalbed methane resource and its exploration and development prospect in East China [PDF]

Youqicang pingjia yu kaifa, 2023
Deep coalbed methane（CBM） development in East China is of great significance to ensure regional energy demand, optimize regional energy structure and realize the dual carbon goal.
SANG Shuxun,HAN Sijie,ZHOU Xiaozhi,LIU Shiqi,WANG Yuejiang
doaj   +4 more sources

Quantitative Analysis of Gas Occurrence States and Its Controlling Factors in Deep CBM Reservoirs: An Integrated Model With Application in Linxing Block

Geofluids
Deep coalbed methane (CBM) is a crucial resource for ensuring energy security. Despite some successful localized deep CBM developments, the unclear understanding of gas content and gas occurrence state remains a key obstacle to the comprehensive ...
Jian Wu, Songhang Zhang, Weiwei Chao, Tengfei Jia, Wenchun Peng, Zizhen Liu, Shilong Li   +6 more
doaj   +3 more sources

Deep Learning Based Impact Parameter Determination for the CBM Experiment

Particles, 2021
In this talk we presented a novel technique, based on Deep Learning, to determine the impact parameter of nuclear collisions at the CBM experiment. PointNet based Deep Learning models are trained on UrQMD followed by CBMRoot simulations of Au+Au collisions at 10 AGeV to reconstruct the impact parameter of collisions from raw experimental data such as ...
Manjunath Omana Kuttan, Jan Steinheimer, Kai Zhou, Andreas Redelbach, Horst Stoecker   +4 more
openaire   +4 more sources

A Parametric Study and Economic Evaluation of Drilling Patterns in Deep, Thick CBM Reservoirs

SPE Eastern Regional Meeting, 2011
Abstract Over the past decade, production from unconventional reservoirs such as coalbed methane has increased dramatically. The focal driving force for this growth in coalbed methane production was the development and promulgation of reservoir engineering and completion technology.
Ali Omran Nasar, Shahab D. Mohaghegh, Vida Gholami   +2 more
core   +5 more sources

NMR investigation on gas desorption characteristics in CBM recovery during dewatering in deep and shallow coals

Journal of Geophysics and Engineering, 2023
Abstract Coalbed methane (CBM) development requires dewatering until the reservoir pressure is less than the critical desorption pressure. Significant quantities of CBM in China are buried >1000 m deep. Therefore, the desorption characteristics of deep CBM reservoirs must be investigated for the further development of deep CBM. In
Yingfeng Sun, Qingxia Lin, Yixin Zhao
exaly   +2 more sources

The Health Index Prediction Model and Application of PCP in CBM Wells Based on Deep Learning

Geofluids, 2021
Aiming at the problems of the current production and operation status of the progressive cavity pump (PCP) in coalbed methane (CBM) wells which cannot be timely monitored, quantitatively evaluated, and accurately predicted, a five-step method for evaluating and predicting the health status of PCP wells is proposed: data preprocessing, principal ...
Chaodong Tan, Song Wang, Hanwen Deng, Guoqing Han, Guanghao Du, Wenrong Song, Xiongying Zhang   +6 more
openaire   +3 more sources

A Poly-Aromatic Hydrocarbon-Grafted Silicon-Quantum-Dot-Based Desorption Agent with High Salt Resistance and Its Influence on the Adsorption/Desorption Behavior of CBM in Deep Coal Rock. [PDF]

Polymers (Basel)
Coal-bed gas well production is too low to realize a highly efficient exploitation of the #8 coal seam in the Shanxi formation in the Nalin region. Based on the reservoir characteristics, the designed poly-aromatic-grafted silicon-quantum-dot-based desorption agent (PQS) has been developed.
Li H, Yue L, Xu H, Li Y, Zhou Y, Zhang R, Wang K, Zhang H, Luo S, Ren B, Chen F, Liu Y.   +11 more
europepmc   +2 more sources

Geological adaptability of deep CBM fractured horizontal well in SLN block

Frontiers in Earth Science, 2023
The buried depth of the main coal beds in SLN Block is more than 1,500 m, and the gas content of the coal beds is high. However, the coal beds are generally in a high geostress environment, the permeability of the coal beds is generally low, and the development effect of conventional fractured straight wells is poor.
Yutong Fu, Weilin Yuan, Zhidan Xu, Ruosi Zhao, Yue Wu, Haibo Zheng, Xianqing Wang, Xudong Guo, Shiyong Gou, Chunlin Ma   +9 more
openaire   +2 more sources